higher education; long range planning; mathematical models ...popular types of forecasting for...

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Morrison, James L.; And OthersFutures Research and the Strategic Planning ProcessImplications for Higher Education. ASHE-ERIC HigherEducation Research Report No. 9, 1984.Association of American Colleges, Washington, D.C.;ERIC Clearinghouse on Higher Education, Washington,D.C.National Inst. of Education (ED), Washington, DC.ISBN-0-913317-18-784400-82-0011141p.Association fcr the Study of Higher Education, OneDupont Circle, Suite 630, Department PR-9,Washington, DC 20036 ($7.50, nonmembers; S6.00,members).Information Analyses ERIC Information AnalysisProducts (071)

EDRS PRICE MF01/PC06 Plus Postage.DESCRIPTORS *Change Strategies; *College Planning; Delphi

Technique; Educational Policy; *Futures (of Society);Higher Education; Long Range Planning; MathematicalModels; Prediction; *Predictive Measurement;Statistical Analysis; *Trend Analysis

I7ENTIFIERS *Environmental Scanning; Futures Research; *StrategicPlanning

ABSTRACTThe use of futures research to improve a college's

ability to deal with changes brough4. about by social, economic,political, and technological developments is discussed, withattention to new planning strategies and forecasting methods. Whiletraditional long-range planning tracks and forecasts theinstitution's internal development, strategic planning considers arange of possible societal conditions that may influence education,as well as the potential effects of different policies. The techniqueof environmental scanning, which is derived from futures research, isan integral part of strategic planning. The environmental scanningprocess and the following evaluation and forecasting methods areexplained, with examples and charts/illustrations: impact network;probability-impact chart; individual judgmental forecasting;mathematical trend extrapolation (e.g., regression, time series);group '.orecastrig (e.g., the Delphi technique); cross-impact models;scenarioq; and policy impact analysis. Key stages in the developmentof public issues, and lessons learned in the corporate world are alsoconsidered, along with suggestions for developing a strategicplanning process within an existing organization. (SW)

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2 BEST COME.AILABL

Futures Research and the Strategic Planning Process:Implications for Higher Education

by James L. Morrison, William L. Renfro, and Wayne I. Boucher

ASHE -ERIC Higher Education Research Report No. 9, 1984

Prepared by

ERIC

Published by

e Clearinghouse on Higher EducationThe George Washington University

ASH*Association for the Study of Higher Education

Jonathan D. Fife,Series Editor

Cite as:

Morrison, James L.; Renfro, William L.; and Boucher, Wayne 1.

Futures Research and the Strategic Planning Process: Implica-tions Pr Higher Education. ASHE-ERIC Higher EducationResearch Report No. 9. Washington. D.C.: Association for theStudy of Higher Education, 1984.

The ERIC Clearinghouse on Higher Education invites individualsto submit proposals for writing monographs for the HigherEducation Research Report series. Proposals must include:1. A detailed manuscript proposal of not more than five pages.2. A 75-word summary to be used by several review committees

for the initial screening and rating of each proposal.3. A vita.4. A writing sample.

Library of Congress Catalog Card Number: 85.61908ISSN 0737.1292ISBN 0-913317-18.7

raw7c1 Clearinghouse on Higher EducationThe George Washington UniversityOne Dupont Circle, Suite 630Washington, D.C. 20036

ASHk Associativn for the Study of Higher EducationOne Dupont Circle. Suite 630Washington, D.C. 20036

This publication was partially prepared with funding from theNational Institute of Education, U.S. Department of Education.under contract no. 400-82-0011. The opinions expressed in thisreport do not necessarily reflect the positions or policies of NIEor the Department.

EXECUTIVE SUMMARY

America's colleges and universities are undergoing changesas profound as those that transformed the nineteenth cen-tury world of small religious colleges into universities.These changes are part of a larger transition in Americansocietythe transition into an "information age." Rapidtechnological developments in computers and telecommu-nications are revolutionizing instruction and management.Rapid changes in the workplace are causing adults,to reen-!ter postsecondary educationto enhance their quality oflife and to obtain essential retraining. Many colleges anduniversities are faced with retrenchment and budget cuts,constricting finances, increased competition, changes inthe demographics and vdues of the student body, someoverflowing degree programs and others half full, and anincreased uncertainty among the public about the worth ofa college education. It is becoming more evident that tradi-tional methods of long-range planning, with their inwardfocus on budgets and staff, are inadequate for our educa-tional institutions. Faced wit much the same challenges,the business sector over the past two decades has devel-oped a body of concepts and ;echniques known as "strate-gic planning." This volume explains how and why institu-tions of higher education can exploit futures research instrategic planning.

What Is Strategic Planning?When augmented by futures research, contemporary stra-tegic planning differs from traditional long-range planningin that it adds a special emphasis on discerning and under-standing potential changes in the external environment,competitive conditions, threats, and opportunities. It at-tempts to develop a greater sensitivity ;o the changingexternal world and assist the organization to thrive by cap-italizing on existing strengths (Cyert 1983, p. vii). It is anapproach that gets key administrators "thinking inno-vatively and acting strategically, with a future in mind"(Keller 1983). Modern strategic planning recognizes thatorganizations are shaped by outside forces at least as muchas by internal ones. In particular, it represents an effort to"make this year's decisions more intelligent by lookingtoward the probable future in coupling the decisions to anoverall institutional strategy" (Keller 1983, p. 182).

Clearly, success in this endeavor depends upon having an

J

adequate and effective means of identifying and forecastingwhat is likely to happen in the external environment andhow these events may affect the institution.

How Is Environmental Scanning Useful forHigher Education?A planning model that has emerged from futures researchcan serve to enhance planning in higher education. Thismodel, the "environmental scanning model," begins withscanning the external environment for emerging issues thatmay pose threats or opportunities to the organization. Es-tablishing the capability for environmental scanning re-quires the naming of an in-house, interdisciplinary scan-ning committee whose purpose is to develop a taxonomy ofissues that disciplines the search for important possibledevelopments in the social, economic, legislative/regulatory, and technological environments. (Within thesebroad categories, more specific categories relating to theimmediate concerns of the institution may be developed.)it also requires the identification of sources of informationand their assignment to individual members of the commit-tee. It is important that high-level administrators be on thisscanning committee, as their broad perspective on theinstitution's current operations and likely future directionswill be essential in evaluating the potential significance ofissues identified during scanning.

Even an elementary environmental scanning system canquickly identify a plethora of emerging issues. These issuesmust be limited to some manageable number to ensure theorganization's effecti% eness. To limit the issues, the plan-ning committee must address certain questions: (1) What isthe probability that an issue will actually emerge? (2) As-suming that it does actually emerge, to what ,xtent will itaffect current strategic assumptions and plans? (3) Whatstrategies ere available to the institution to manage its re-sources in anticipation of the issue, and how effectivecould each of them he?

How Can Environmental Scanning Be Used inForecasting the Institution's Future?Several methods are available to respond to these ques-tions and thereby enable the institution to order the issues

and then probe them in greater detail according to theirrelative importance. For example, if the "issue" takes theform of a series of eventsfor example, the elimination oftenurethe results of the first two questions can be plottedon probability-impact charts. That is, the planning commit-tee's ollective judgments on the events' probability overtime and their impact can be determined through simplequestionnaires or a meeting in which the group's opinionsare quantified using various scales. These estimates canthen be cross-plotted, which immediately reveals whichevents have high probability but low impact or low proba-bility but high impact.

The next step is to forecast in detail the trends or eventsthat make up the issues identified earlier. One of the mostpopular types of forecasting for harnessing the insights,experience, and judgment of knowledgeable people is theDelphi technique, which can be used to develop forecastsfrom a group of "experts," a process in which individualsforecast each trend and event privately, the results aresynthesized by an intermediary, and the resulting summaryis fed back to each member of the group with a request toreestimate the forecast in light of the results obtained. Thisprocess continues until the group's consensus is closeenough for practical purposes or the reasons why such aconsensus cannot be achieved have been documented.

Other forecasting techniques include mathematical trendextrapolation (such as regression analysis), time-seriesmodels (such as the Box-Jenkins technique), and probabi-listic forecasts, which are distinguished by including theestimated probabilities and impacts of possible future sur-prise developments to adjust the extrapolative forecasts ofa trend. Cross-impact analysis is an especially interestingtype of probabilistic forecasting technique, for it enablesthe user to produce comprehensive forecasts by takingsystematic account of the effects of the occurrence of aparticular future event on each of the other events in theset being considered, as well as the event's effects on eachtrend in the set. Policy impact analysis is cross-impactanalysis plus the ability to test candidate actions within themodelthat is, to simulate their consequences. By repeat-ing these simulations it is possible to develop a number ofalternative futures, which can then be described by multi-ple scenarios.

These methods serve to enhance our vision of what liesin the future so that we can examine the practicality of ourplans vis-a-vis these possible futures. Such forecastingmethods, then, provide administrators with a much richerinformation base on which to establish goals, develop andevaluate alternative policies, outline programs to imple-ment these policies, and design systems to monitor theeffectiveness of the policies.

The field of futures research has always been contrip :r-sial, and many academics doubt its legitimacy, particulaiiythose who have been led to believe that futures researchseeks to predict the future (which it does not), that it is ascience (which it is not), or that it will somehow replaceestablished research methods and concepts (whict, it can-not). This volume attempts to make clear that the ap-proaches, the techniques, and the very philosophy of fu-tures research have been developed to augment thecapability of individuals and institutions to deal intelli-gently with uncertainty, change, and complex interrelation-ships. The theme of this volume therefore is that mergingthe environmental scanning model with conventional plan-ning approaches will enhance planning in higher education.This argument rests in large part on experience with suc-cessful strategic forecasting and planning in other organiza-tions: the military, private business, trade and professionalassociations, and the volunteer sector. Arguing from anal-ogy is always dangerous, of course, but there is no reasonwhy many of the lessons painfully learned in other sectorscannot be adapted to the administration of colleges anduniversities.

Indeed, many higher education administrators realizethat the need for new approaches is growing. When theyrecognize that they already have a wealth of informationabout their institutions and about society and that tech-niques used in futures research can provide models forstructuring and improving the quality of this information,they will be ready to adopt new methods to build theirfuture.

If we are to respond creatively, ve must begin to lookbeyond our own organizational boundaries and antici-pate internal changes brought on by changing externalconditions. We must Mkt, our early warning .signals,

combine them with our existing internal data and fore-casting techniques, and ensure that we tap the wealth ofcreativity and resourcefulness higher education has tooffer (Heydinger 1983, p. 98).

9

ASHE-ERIC HIGHER EDUCATION RESEARCHREPORT SERIES

ADVISORY BOARD

Roger BaldwinAssistant Professor of EducationCollege of William and Mary

Susan W. CameronAssistant Professor and ChairHigher/Postsecondary Education'Syracuse University

Clifton F. ConradProfessor of Higher EducationUniversity of Arizona

George D. KuhProfessor and ChairEducational Leadership and Policy StudiesIndiana University

Yvonna S. LincolnAssociate Professor of Higher EducationThe University of Kansas

Robert A. ScottDirector of Academic AffairsState of Indiana Commission for Higher Education

Joan S. StarkProfessor of EducationUniversity of Michigan

I`

.\SHE -ERIC HIGHER EDUCATION RESEARCHREPORT SERIES

CONSULTING EDITORS

Robert CopeProfessor of Higher EducationUniversity of Washington

Robert L. CraigVice President, Government AffairsAmerican Society for Training and Development, Inc.

John W. CreswellAssociate ProfessorDepartment of Educational AdministrationUniversity of Nebraska

David KaserProfessorSchool of Library and Information ScienceIndiana University

George KellerSenior Vice PresidentBarton-Gillet Company

David W. LabeProfessor and ChairDepartment of Educational LeadershipThe Florida State University

Linda Koch LorimerAssociate General CounselYale University

Ernest A. LyntonCommonwealth ProfessorCenter for the Study of Policy and the Public InterestUniversity of Massachusetts

Gerald W. McLaughlinInstitutional Research and Planning AnalysisVirginia Polytechnic Institute and State University

Theodore J. MarcheseVice PresidentAmerican, Association for Higher Education

11

Virginia B. NordbyDirectorAffirmative Action ProgramsUniversity of Michigan

Harold OrlansOffice of Programs and PolicyUnited States Civil Rights Commission

Lois S. PetersCenter for Science and Technology PolicyNew York University

John M. PetersonDirector, Technology PlanningThe B. F. Goodrich Company

Marianne PhelpsAssistant Provost for Affirmative ActionThe George Washington University

Richard H. QuaySocial Science LibrarianMiami University

John E. SteckleinProfessor of Educational PsychologyUniversity of Minnesota

Donald WilliamsProfessor of Higher EducafonUniversity of Washington

12

CONTENTS

Foreword'Acknowledgments

The Rationale 'for Futures Research

The Strategic Planning Process 5

Evolution of the Concept S

Strategic Planning 8

The Stages of the Strategic Planning Process 15

Environmental Scanning 15

Evaluating the Issues 30

Forecasting 40

Goal Setting 77

Implementation 84

Monitoring 85

Developing a Strategic Planning Capability 95

Early Stages 95

Link to Long-Range Planning 99

The Relevance of Environmental Scanning andForecasting to Higher Education 103

Appendices 107

References 111

13

FOREWORD

If anything, the problems now facing higher educationshluld have taught us the need for sound long-range plan-ning. Many of today's conditionsthe decrease in the pop-ulation of traditional 18 to 24-year-old students, the deteri-orating infrastruct_fe of higher education institutions, theobsolescence of research equipment, and the stagnation offacultycould all have been predicted five or ten yearsahead of their impact. For many colleges and universities,even those with a long -range planning strategy, it was notthe case, however. The reason is that much of the planningin higher education is based on the assumption that whathas happened in the past will happen in the future; institu-tions v.ould do better to try to anticipate events that mightdiffer from the economic, sucial, and political conditions ofthe present.

The processes of planning over the past decade shouldalso have taught that, for changes to occur within the insti-tution to meet the changes of the external environment, theentire institution must in some fashion be involved in plan-ning. Sudden institutional change is unlikely to be success-fully or harmoniously accepted without the involvement ofboth administrators and faculty.

This report by James L. Morrison, Professor of Educa-tion, The University of North Carolina at Chapel Hill,William L. Renfro, President, Policy Analysis Company,Inc., and Wayne 1. Boucher, Executive Vice President,ICS Group, Inc., addresses both issues: the developmentof a strategy to assist the inAitution in anticipating a chang-ing environment, and a process that will ensure a smoothintegration of the needed changes.

Morrison, Renfro, and Boucher propose the technique ofenvironmental scanning as an integral part of strategicplanning. They develop numerous techniques that, whenused with an institutionwide planning commioce, can helppredict both threats and orportunities to the organization.Some techniques, such as the Delphi technique, are cur-rently being used. Other forecasting techniques, such asmathematical trend extrapolation, time-series models, andprobabilistic forecasts, are less familiar to higher educationadministrators, although they have been used for manyyears in the business sector. In many ways. this reportdetails a revolutionary new aspect in long-range planning.But success will be determined by the institution's commit-

XV

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ment to develop a planning process that ensures the in-volvement of the entire institution and includes a system-atic reevaluation of its plans in light of unanticipatedevents.

Jonathan D. FifeSeries EditorProfessor and DirectorERIC Clearinghouse on Higher EducationThe George Washington University

xvi

15

ACKNOWLEDGMENTS

A host of colleagues who willingly gave large amounts oftime and energy to provide feedback and criticize earlydrafts assisted the authors in*this enterprise. We would liketo thank George Keller (Barton-Gillet Company), Ted Mar-chese (AAHE), Robert Cope (Washi .gton), RichardHeydinger and Jim Hearn (Minnesota), !Arvin Kornblum(Congressional Research Service), Guy Siebold, DougMacPherson, and Bill Haythorn (Army Research Institute),Paul Fendt, Bruce Sigmon, John Goode, CurtisMcLaughlin, Tim Sanford, Pat Sanford, Warren Bannuch,and Sherry Morrison (UNCChapel Hill), Karen Peterson(North Carolina State University), Michael Marian (WorldFuture Society), Lewis Perelman (consultant), DebrisBurke and John Rider (Duke), Jim Pierce and Linda Pratt(North Carolina Central University), Dan Ruff (MidlandsTechnical College), Phil Winstead (Furman), and TomMecca (Piedmont Technical College). The authors, ofcourse, assume responsibility for the final product.

James L. Morrison, Chapel Hill, North CarolinaWilliam L. Renfro, Washington, D.C.Wayne 1. Boucher, Harbor City, California

xvii

1 6

THE RATIONALE FOR FUTURES RESEARCH

A sense of the .future is behind all good policies.Unless wee hove it. wee can give nothing eitherwise or decent to the world.

C.P. Snow

A sense of the future not only pervades all good policies; italso underlies every decision of human beings. We eatexpecting to be satisfied and nourishedin the future. Wesleep assuming that in the future we will feel rested. Weinvest our energy, our money, and our time because webelieve that our efforts will be rewarded in the future. Webuild highways assuming that automobiles and trucks willneed them in the future. We educate our children on thebasis of forecasts that they wilt need certain skills, atti-tudes, and knowledge when they grow up. In short, we allmake assumptions about the future or implicit forecaststhroughout our daily lives.

The question, then, is not whether we should forecastbut rather whether we should articulate, discuss, analyze,and try to improve our forecasts. The premise of explicitforecasting is that by moving beyond our ordinarily unar-ticulated assumptions about the future, we can better guideour current decisions to achieve a more desirable futurestate of affairs. It is a matter of whether we will go into thefuture with our eyes and our minds open or stumble into itwith them closed.

The process of forecasting and developing informationabout the future raises several fundamental problems. Weknow that we can know nothing with absolute certaintyabout the future. But we can know, in a weaker sense, agreat many useful things about the future: when a contractis scheduled to expire, when an election is expected to beheld, when a machine is likely to be replaced, when a newtechnology is likely to come on line, when the life of every-one who is over 40 today is likely to have ended, how pur-chasing patterns are likely to change if present social andeconomic trends continue, and so on. Knowledge in thisweaker sense implies a possibilitysometimes high, some-times lowthat something may come along to upset ourotherwise secure understanding of the future. When wegrant the presence of uncertainty, however slight, then weare in the realm of forecasting. Forecasting is valuable andimportant even when we have less confidence. Indeed, it is

The question. . . is notwhether weshouldforecaat butrather whetherwe . . .shouldtry to improveour forecasts.

Futures Research and the Strategic Planning Process

often far more important and/or valuable to focus on thoseareas where our confidence is low and where uncertaintyand the likelihood of upsetare high.

Highly likely and highly unlikely events are not usuallyvery interesting, unless, of course, they fail to turn out asexpected. The "interesting future" includes such possibili-ties, but it also (and more importantly) includes develop-ments of middling probability whose occurrence or nonoc-currence will surely ;:1(.! decided within the period ofinterest as a result of decisions and policies implementedbetween now and then. In a society and a culture based onthe scientific process of experimenting to develop andprove what is or can be known about nature. the process ofthinking about the future and making forecasts standsalone in its vulnerability. Yet in spite of these risks and theunpredictability of the future, we all constantly make as-sumptions about the future in guiding our everyday deci-sions. Occasionally, of course, our assumptions are wrong__and we-are surprised by sudden opportunities or develop-ments that create both pain and loss. Nevertheless, as longas the future remains unpredictable, we have no choice butto go on making the best, most reliable assumptions andforecasts about the future we can.

Forecasting and the study of the future raise anothermajor problem. Individual reputations, especially in theacademic world, are built or' research that follows es-tablished rules and procedures, research that should leadto the same results, regardless of the individual conductingthe research. Information about the future, however, isbased on assumptions about which reasonable persons canand do differ. The information we generate about the fu-ture is fundamentally linked to our personal values, con-cepts, ideas, experience, outlook, and makeup. While fore-casting and futures research have to some extent borroweddetailed research methods and scientific concepts fromother disciplines, these procedures cannot change the fun-damental nature of information about the future. In theend, this information is based upon subjective judgment.As a result, for people whose lives, reputations, and ca-reers rest on successful adherence to the traditional es-tablished rules and procedurzs of research, making fore-casts is uncomfortable, even threatening. To speculateabout the unknown and the unknowable is to cliallen. one

of the keys to their successcareful use of "proper" re-search methods. By recognized standards of every profes-sional discipline, even the best information about the fu-ture is unacceptable, because its foundation is subjectivejudgment and thus it cannot meet traditional scientific stan-dardsof objectivity, experimental verification, reproduc-ibility, and so on. All information about the future may bejudged inadequate in this light, but information about thefutureany information about the futUreis better than noinformation about the future,

What is good information about the future? Simply put,it is information that helps us to improve our current per-formance so that we can achieve a better future than wouldotherwise occur. Thus, total accuracy in the forecast can-not be the goal. By the time we know that the informationabout the future is correct, it must be too late to do any-thing about it. For example, if an air traffic controller

__watching two planes- on-a-tadar screen develops-a-forecast-that the planes are likely to collide, we must ask, "Whatshould we do with this forecast?" We can wait, watchingthe radar screen to see whether the planes do in fact collideand thus confirm the accuracy of our forecast. But by thetime we know that our forecast was correct, we have acatastrophe. The forecast has value only if we use thatinformation to avoid the undesirabl future of the forecast

catastrophe-by -directing the aircraft to safer courses. Thisprinciple is just as valid for large complex social systems:What should we do now to avoid the catastrophe of bank-ruptcy for the social security system 25 or 40 years hence'?What should we do now to avoid the catastrophe of certainpresent trends in elementary and secondary education?

A forecast can be a failure even if it turns out to be accu-rate. The Paley Commission appointed by PresidentEisenhower in 1952 to study the long-term energy circum-stances of the United States generated such a forecast. Theforecast that it producedthat the country faced an energycrisis in the mid-1970sturned out to be quite accurate.The forecast was a failure because it was not used to avoidthat crisis. Thus, the key criterion must be that the forecastis usedused to create a better future. To be used, theforecast must he communicated to the relevant decisionmakers, and they must believe the forecast and have theresources to act on that information. Naturally, the nett-

Futures Research and the Strategic Planning Process 3

racy of previous forecasts derived from similar methods orproduced by similar forecasters or forecasting groupswould enhance credibility; that is, decision makers will bemore likely to assume a method (or forecast) is credible ifit has been accurate in the past.

Most of the forecasting we do is implicitunarticu-latedand can appropriately stay that way. Some of theforecasting, however, should be articulated, discussed,debated, evaluated, challenged, changed, modified, andused as we make decisions in an effort to achieve moredesirable futures. Forecasting may be both inadequate andbetter than ignorance of possible futures. The curse ofCassandra was to know the future but be powerless tochange it. Forecasting gives us our best information aboutthe future, but we will never know the future nor the curseof Cassandrafor we have the power to change the future.

4

THE STRATEGIC PLANNING PROCESS

Evolution of the ConceptIn preparing his famous history of the Mediterranean,Fernand Braude! discovered that he was writing three his-tories concurrently. His first work followed day-to-daydevelopments, recording the events and ongoing progressof the society. 14e discovered, however, that a second levelof ongoing developments was apparentthe level of struc-tural and institutional change. Braude! realized that muchof the surface history, or the indicators of surface change,depicted on the first level were driven by and dependent onthis second level. Today we would categorize unemploy-ment as a key surface indicator, and we would give it muchattention in our first history. Yet over the past decade wehave discovered that other forces shape unemployment,for example, the structural and institutional changes thatare occurring as we evolve from a manufacturing, indus-trial economy to a service economy. If we want to under-stand the shifting demand and mix of employment in thecountry, we must understand the dynamics of baby boomdemographic forces, the changing family, and emergingpersonal roles. Interest rates, economic growth, govern-ment policies, and other surface factors alone cannot ex-plain unemployment rates.

Finally, Braude! discovered a third level of history--onederived and focused on individual attitudes, values, andbeliefs. He argued that these forces bring institutional andstructural changes, which in turn bring the changes in thesurface indicators. These three levelssuperficial,structural/historical, and attitudinalcan be recursive; thatis, surface changes "cause" structural changes, whichcause changec. in values, which then cause changes on theother levels. Consider, for example, how reliable, inexpen-sive birth control affected society's sexual values and howthese value changes affected school enrollments.

These three levels of history can also serve as a meansfor viewing the future. Early forecasting and futures re-search methods focused on indicators and measures ofsurface change, such as unemployment, inflation, eco-nomic growth, sales of automobiles, and housing starts.Most of our discussions of the future still focus on thesesurface indicators, usually using implicit forecasts. Forexample, on the first page of the Wall Street Journal everyday is a historical chart of some surface indicator from

Earlyforecastingand futuresresearchmethodsfocused onindicators andmeasures ofsurfacechange.


2

which readers can derive their own forecast. This chartserves to establish the unarticulated, implicit forecast.

Given this view of the future, it is not surprising thatfutures research and forecasting developed and used a hostof extrapolative methods in support of long-range planningfocused on surface indicators. These methods included,among others, regression analysis, mathematical and judg-mental trend extrapolation, Box-Jenkins, and rolling aver-ages. The focus of this traditional long-range planning wasinternal, based on tracking and forecasting an organiza-tion's or a system's internal development.

As surprise developments continued to upset the fore-casts and long-range plans produced by these methods,forecasters modified them to take explicit account of unprecedented new developments and external "surprises."While many of them were surprises on the surface, futuresresearchers began to increasingly include changing struc-tural and institutional developments. Thus, trend extrapo-lation was modified to become trend-impact analysis, aprobabilistic forecasting technique in which an extrapola-tive trend is modified by the occurrence of hypothesizedexternal surprise events.

At the same time, modeis of large systems createdthrough the method known as systems dynamics weremodified to include similar external surprises: with thismodification, it became known as probabilistic systemsdynamics. Relationships among external surprise eventswere also explored through such methods as cross-impactanalysis. Most recently, in the mid-1970s, a method forguiding the development of responses to information aboutthe future on the first two levels was developedpolicyimpact analysis. While a small scan of the external envi-ronment usually was made to identify candidate surpriseevents. the focus remained on the trends and issues devel-oped from the traditional, internal perspective.

Today, methods are used that will take account of infor-mation from the third level of the futurechanging valuesand attitudes. But these methods are in their infancy in thissort of application, and their users frequently have no clearidea of what balance should be struck among potentialdevelopments on all three levels. Coping seriously withthisquestion is one of the frontiers of futures research.While we could of course approach this question through

opinion research, opinion research has been notoriouslyweak in forecasting for the simple reason that individualopinion about the future is much more unreliable thanopinion about the present. But the real difficulty with poll-ing is not that individuals are unreliable; it is that pollsterswho have tried forecasting have aimed at predictive accu-racy with "one-shot" estimates. That is, .'hey failed toprovide respondents feedback on the original judgment,thereby prohibiting their using that informetion to reflecton the initial judgments or the arguments behind them.Consequently, the polling technique is limitt.d in obtainingthat information useful for managing change and increasingour options.. As futures research and forecasting method:; became lessquantitative and more qualitative, the process t)fexploringand responding to changing social structure ano values (thesecond and third levels of the future) was becoming moreand more important. The traditional "fire fightini" modeof public relations was modified to include a planting orforecasting role in what became known as public affairs.This role was extended to include policy planning. Thus, itis not unusual to find on a contemporary corporate ,)rgani-zational chart a director of public policy planning, a DOSi-tion stationed philosophically somewhere between tintraditional public relations/government relations/publr:affairs function and the corporate planning function. Irsome organizations, the policy planning function has bten'extended to include a director of public issues, who is re-sponsible for anticipating and helping the organization torespond to emerging issues in the external environment.The new field of issues management emerged as publicrelations and public affairs officers recognized the need toexpand the use of forecasting and futures research in theirplanning and analysis of policy. The merger of futures re-search concepts and techniques into public policy planningholds the prospect that administrators will eventually paymuch closer attention to detailed information about thefuture on all three levels discussed earlier.

Currently the most common technique used for includingmore information about the external world from moth thesecond and third levels (structural/institutional change andattitudinal change) is environmental scanning. As withearlier forecasting, environmental scanning focuses first on


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the surface indicatorsderived from newspapers, litera-ture, and periodicalsas signals of underlying change inthe more difficult-to-understand structural and attitudinallevels. Although refinements in environmental scanningwill have to be developed, this approach to long-rangeplanning moves us into the strategic planning process.

Strategic PlanningThe word "strategy" comes from the Greek strategos,referring to a military general and combining stratos (thearmy) and ago (to lead). The primary tasks of strategicmanagement are to understand the environment, defineorganizational goals, identify options, make and implementdecisions, and evaluate actual performance. Thus, strate-gic planning aims to exploit the new and different oppor-tunities of tomorrow, in contrast to long-range planning,which tries to optimize for tomorrow the trends of today(Drucker 1980, p. 61).

Most colleges and universities currently engage in long-range planning, but they can fruitfully augment that workby using the concepts of strategic planning and therebyenhance their ability to steer a course in a changing exter-nal environment. This section briefly describes the tradi-tional models for long-range planning and environmentalscanning and then shows how these two models can bemerged to provide the basis of a strategic planning process.

Traditional long-range planning in its most elementaryform is based on the concept that planning consists of.atleast four key steps--monitoring, forecasting, goal setting,and implementingwhich are intended to answer thesequestions: (1) Where is the organization now? (2) Where isit going? (3) Where does it want to go? and (4) What does ithave to do to change where it is going to get to where itwants to go? (Renfro 1980b, 1980c; see figure I). Perform-ing these activities is a continuing process that, for exam-ple, produces a one-year operating plan and a five- or ten-year long-range plan every year. The long-range planning,cycle begins by monitoring selected trends of interest tothe organization, forecasting the expected future of thosetrends (usually based upon extrapolation from historicaldata using regression analysis or a similar technique), de-fining the desired future by setting organizational goals inthe context of the expected future, developing and

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FIGURE 1LONG-RANGE PLANNING

I

FORECASTING

MONITORING

GOAL SETTING

iIMPLEMENTING

2 5

implementing specific policies and actions designed to re-duce the difference between the expected future and thedesired future, and monitoring the effects of these actionsand policies on the selected trends.

The environmental scanning model (figure 2) begins withscanning the external environment for emerging issues thatpose threats or opportunities to the organization. As partof this step, trends are specified that describe the issuesand can be used to measure changes in their nature or sig-nificance. Each potential issue or trend is then analyzed(evaluation/ranking) as to the likelihood that it will emergeand the nature and degree of its impact on the organizationif it should actually materialize. This stage produces a rankordering of the issues and trends according to their impor-tance to current or planned operations. The next stage,forecasting, focuses on developing an understanding of theexpected future for the most important issues and trends.In this stage, any of the modern forecasting techniquesmay be used. Once the forecasts are made, each issue and

trend is then monitored to track its continued relevanceand to detect any major departures from the forecastsmade in the preceding stage. Monitoring, in effect. identi-fies areas for additional and continued scanning. For exam-ple. subsequent monitoring may begin to suggest that anoriginal forecast of the employee turnover rate is no longercredible, which would imply the need for more focusedscanning, forecasting, and analysis to develop a more cred-ible projection (see Renfro and Morrison 1984).

As noted earlier, one of the major limitations of thetraditional long-range planning model is that informationabout the changing external environment is usually nottaken into account systematically or comprehensively.When this omission occurs because of an assumption that"we cannot predict external changes," long-range planningdestines itself to surprise and failure, if only because itlocks itself to the information known from direct experi-ence in the past and immediate present.

Information from the external environment adds impor-tant components to long-range planning, however. First, itidentifies new and potentially crucial subjects that shouldhe added to those identified and tracked during monitoring.Second, it identities possible developments that must heused to adjust the forecasts of the internal issues derived

10

2t

FIGURE 2ENVIR')NMENTAL ScANNING

EVALUATION/RANKING FORECASTING

SCANNING/

MONITORING

27

from forecastingspecifically, the surprise events that arcused in policy impact analysis or techniques like probabi-listic systems dynamics and in other rigorous forecastingmethods used in traditional long-range planning.

These two models of planninglong-range planning andenvironmental scanningmay be merged. The interrelatedmodel, the strategic planning process, consists of six iden-tifiable stages: environmental scanning, evaluation of is-sues, forecasting, goal setting, implementation, and moni-toring (see figure 3). The merged model, then, allows infor-mation from the external environment in the form ofemerging developments to enter the traditionally in-wardly focused planning system, thereby enhancing theoverall effectiveness of an institution's planning. Morespecifically, it allows the identification of issues and trendsthat must be used to modify the internal issues derivedduring monitoring.

The argument for combining these two models becomesapparent when the future that happens to the institutionand the future that happens for the institution are con-trasted. In the future that happens to the institution (thetypical "planned" future), new developments arc not antic-ipated before they force their way to the top of the agenda,demanding crisis management and the latest fire-fightingtechniques. In this future, issues are usually defined byothers whose interests do not necessarily include those ofthe institution or its purpose. Not only are threats from theexternal environment not anticipated as early as possible;ke; opportunities wit; be missed or diminished in value.

In the future that happens fur the institution, in contrast(the "strategic" future), administras.x leadership is fo-cused more on fire prevention and less on fire fighting.Hence, it is able to exercise more careful judgment in theorderly and efficient allocation of resources. Certainlymanagement will still have to deal with unforeseen devel-opments, but they will probably be fewer and less trau-matic. Thus, institutions will be able to pursue their mis-sion with greater confidence and consistency becausethey will be interrupted by fewer and smaller fire-lightingexercises.

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FIGURE 3THE STRATEGIC PLANNING PROCESS

EVALUATION/RANKING

EXTERNAL PERSPECTIVE

(ENVIRONMENTAL SCANNING)

SCANNING

FORECASTING

INTERNAL PERSPECTIVE

(LONG-RANGE PLANNING)

GOAL SETTING

MONITORING IMPLEMENTING

Source: Renfro and Morrison 1984.

2 9

THE STAGES OF THE STRATEGICPLANNING PROCESS

Enrironmental ScanningDuring the 1960s and 1970s, planners and forecasters suc-ceeded in developing many useful methods based on an"inside-out" perspective; that is, it was implicitly assumedthat knowledge about issues internal to their organizationswas most important. At the same time, however, analystsincreasingly found that emerging external issues often hada greater impact on the future of their organizations thanany of the internal issues. In response, they began to mod-ify some of their techniques and concepts so that outsidedevelopments mild be formally included in their results.Initially, the emphasis on tracking the outside world fell onmonitoring developments that, from an inside perspective,had already been identified as potentially important (Ren-fro and Morrison 1982).

Eventually, even this so-called "monitoring" was foundinadequate as entirely new issues emerged that had majoreffects through mechanisms that had not previously beenrecognized. Thus, it became the responsibility of the fore-caster to scan more widely in the external environment foremerging issues, however remote. The search for the pos-sibility, rather than the probability, of major impact be-came common. The importance of scanning in the newsense was first recognized in the national security estab-lishment and later by the life insurance industry, when itdiscovered that its market was declining. From the inside-out perspective of the insurance industry, the decline couldnot be explained. The economy was growing. The popula-tion was growing. The baby boom was just entering thelabor market, adding millions of potential new customers.Yet the sales of life insurance failed to reflect this expectedgrowth. Somehow the industry had failed to perceive afundamental social changethe emergence of the wife as apermanent, second earner in the family. While manywomen in the past worked briefly before marriage or be-fore starting their families, many if not most left the laborforce when they began their families. In the late 1960s andthrough the 1970s, however, more and more women re-turned to work after starting their families. And thischange affected the demand for life insurance: The lifeinsurance needs of a family with one income are muchgreater than those of the family protected by two incomes.This development, coupled with a postponement of form-


3 0

ing families, a decline in the birthrate, and an increase inchildless couples, all reduced the traditional market for lifeinsurance. That so major an industry could have over-looked these social developments stimulated the develop-ment of environmental scanning methods, particularly asthe scope of scanning activities expanded to include tech-nological developments, economic developments, andlegislative and regulatory developments.

Developing the environmental scanning structure'INvo main barriers impede the introduction of environmen-tal scanning techniques in higher education: ( I) learningthe new process and (2) achieving the necessary organiza-tional acceptance and commitment to make the processwork and be worthwhile (Renfro and Morrison 1983a).These two barriers pose several questions: How can anenvironmental scanning function be developed in an al-ready existing organizational structure? How should en-vironmental scanning work within the organization?What resources are needed for the process to functionsuccessfully?

While the organizational structure of the scanning func-tion will vary according to a given institution's manage-ment style, the functions of the scanning process are uni-versal. Developing a scanning function within an existingorganizational structure is necessarily evolutionary be-cause sudden organizational change is disruptive andcostly. While the scanning function could be implementedin many ways, the most popular of the formal systems byfar is through an in-house, interdisciplinary, high-levelcommittee of four or five members (but no more than 12 orso). If assigned to a particular department or contractedout, the results of scanning can easily be ignored. And toachieve the widest appreciation of the potential interac-tions of emerging issues, the scanning function must beinterdisciplinary. Without several disciplines involved,cross-cutting impacts, such as the impact of a technologicaldevelopment (for example. the home computer) on socialissues (for example, the family), will most likely be missed.To facilitate the communication of the results of scanningthroughout the institution, it is easiest to work directlywith the various leaders of the institution rather than withtheir designated experts. Ideally, therefore, the chief exec-

31

utive officer of the institution should appoint the scanningcommittee, and to increase the likelihood that results willbe incorporated into the decision-making process, the chairof the committee should be one of the president's or chan-cellor's most trusted advisors.

Perhaps the essential issue for the suczessful operationof a scanning committee is the selection of the other mem-bers. Ideally, membership should include a broad cross-section of department heads, vice presidents, deans, theprovost, faculty members, trustees, and so forth. Certainlythe institutional research office should be represented, ifnot by the director, then by a senior assistant. The objec-tive is to ensure that all important positions of responsibil-ity in the institution are represented on the committee.

High-level administrators should participate in scanningfor several reasons. First, only those with a broad perspec-tive on an institution's current operations and future direc-.tions can make an informed evaluation of the potentialimportance or relevance of an item identified in scanning.Second, the problems of gaining the necessary communica-tion, recognition, and acceptance of change from the exter-nal environment are minimized. Hence, the time betweenrecognition of a new issue and communication to the insti-tutional leadership is reduced, if not eliminated. And whenan issue arises that requires immediate action, a top-levelscanning committee is ready to serve the institution's lead-ership, offering both experience and knowledge of the is-sue in the external world and within the institution. Third,one of the more subtle outcomes of being involved with ascanning system is that the participants begin to ask howeverything they read and hear bears on the work of thescanning committee: "What is its possible relevance formy institution?" Indeed, the development within top-levelexecutives of an active orientation to the external environ-ment and to the future may well be as beneficial to theorganization as any other outcome of the process.

A scanning committee does not need to have generalauthorization, for it serves only as an advisory board to thechief executive. In this sense it functions similarly to theplanning office in preparing information to support theinstitution's authorized leadership. The scanning commit-tee is, of course, available to be used as one of the institu-tion's resources to implement a particular policy in antici-

Futures Research and the Strategic Planning Process 17 .

32

pation of or response to an issue. But the basic purpose ofthe scanning committee is to identify important emergingissues that may constitute threats or opportunities, therebyfacilitating the orderly allocation of the institution's re-sources to anticipate and respond to its changing externalenvironment.

The environmental scanning processEnvironmental scanning begins with gathering informationabout the external environment. This information can beobtained from various sources, both internal and externalto the organization. Internal sources include key adminis-trators and faculty members; they could be interviewed toidentify emerging issues they believe will affect the institu-tion but are not currently receiving the attention they willeventually merit. Such interviews usually release a hood ofemerging issues, indicating that the organization's keyleaders are already aware of many important new develop-ments but rarely have the opportunity to deal with themsystematically because they are so overburdened withcrisis management.

Administrators and selected faculty members could iden-tify the sources they use for information about the externalworldthe newspapers, magazines trade publications,association journals, and other sources they, regularly useto keep in touch with developments in the external world.Typically, these surveys show that administrators readbasically the same publications but only selected sections.

Scanning includes a broad range of personal and organi-zational activities. It is a process of screening a large bodyof information for some particular bit or bits of informationthat meet certain screening criteria (Renfro and Morrison1983b). For example, some people scan headlines in anewspaper for particular kinds of ir ;les, and when theyfind that information, they stop scanning and read the arti-cle. Then they resume scanning. This process has severaldistinct steps:

1 searching for information resources2. selecting information resources to scan3. identifying criteria by which to scan4. scanning and5. determining special actions to take on the scanning

results.

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33

How these steps are taken determines the kind ofscanningpassive, active, or directed. (For an excellentdiscussion of scanning used-by business executives, seeAguilar 1967, pp. 9-30.)

Passive scanning. Everyone scans continually. Whatever aparticular individual's interests, goals, personal values, orprofessional objectives, it is an element of human nature torespond to incoming information that might be important.Ongoing scanning at an almost unconscious level is passivescanning. No effort is made to select a particular informa-tion resource to scan. The criteria of passive scanning areobscure, unspecified, and often continuously changing.Only ad hoc decisions are made on the results of this typeof scanning.

Passive scanning has traditionally been a major source ofinformation about the external world for most decisionmakers and hence forlheir organizations. The externalenvironment has historically been a subject of some inter-est to most people, requiring at least passive scanning atsome level for the maintenance of one's chosen level offluency in current or emerging issues. The pace of changein the external environment has moved this scanning froman element of good citizenship to a professional require-ment from a low-level personal interest satisfied by pas-sive scanning to a high-level professional responsibilityrequiring active scanningmore like the special scanningused for subjects of particular importance, such as careerdevelopment.

Active scanning. The components of active scanning arequite different from those of passive scanning. For exam-ple, the searching or screening process requires a muchhigher level of attention. The information resourcesscanned are specifically selected for their known or ex-pected richness in the desired information. These re-sources may include some, but usually not all, of the regu-larincoming resources of passive scanning. Thus, a ...

me giber of the scanning committee would not actively scanmagazines about sailing for emerging issues of potentialimportance to the university. This is not to say that suchissues will never appear in this literature but that passivescanning is sufficient to pick up any that do.

The basicpurpose of thescanningcommittee isto identifyimportantemergingissues thatmay constitutethreats oropportunities.


3

The criteria of screening for signals of emerging issuesmust be broad to ensure cempleteness, and they usuallyfocus on certain questions: Is this item presently or poten-tially relevant to the institution's current or planned opera-tions? Is the relationship between the likelihood and poten-tial impact of the item sufficient to justify notifying thescanning committee? For example, a major renewal ofcentral cities in the United States accompanied by highrates of inward migration might have tremendous impacton the educational system but just be too unlikely in theforeseeable future to warrant inclusion in the scanningprocess. It is not part of the institution's current "interest-ing future," which is a very small part of the whole future.

The interesting future is bounded by the human limita-tions of time, knowledge, and resources; it represents onlythat part of the future for which it is practical to plan ortake actions now or in the foreseeable future. For almostall issues, thisinteresting future is bounded in time by thenext three or four decades at the most, although most is-sues will fall in the period of the next 20 years. This timeframe is defined as that period in which the major timelyand practical policy options should, if planned or adoptednow, begin to have significant impact.

The issues-policy-response time frame depends on thecycle time of the issue. For the issue of funding social se-curity, the interesting future certainly runs from now for atleast 75 to 85 yearsthe life expectancy of children bornnow. Actually, as their lire expectancy will probably in-crease in the decades ahead, 90 to 100 years may be a morerealistic minimum. For financial issues, the interestingfuture may be the next several budget cyclesjust two orthree years. For a new federal regulatory requirement thatmay be imposed next year, the interesting future runs fromnow until then.

The interesting future is bounded by a measure of theuncertainty that a particular issue might actually material-ize. Developments that are virtually certain either to hap-pen or not happen ire of little interest in scanning, becausethey involve little uitcr!rtainty. If the institution has littleability to affect these more or less certain happenings, theyshould be referred to the appropriate department for inclu-sion in its planning assumptions. The aging of the babyboom, for example, is certain to happen and should be

3

factored into the current strategic planning process. Apotential new impact of the baby boom that may or maynot happensuch as growing competition within the medi-cal care system for federal resourcesshould be forwardedto the scanning committee for evaluation of both its proba-bility and its importance. Thus, the interesting future iscomprised primarily of those developments that are (1)highly uncertain, (2) important if they do or do not happen,and (3)'responsive to current policy options.

A second dimension of scanning concerns the time ele-ment of the information source being scanned. Informationsources are either already existing resources, such as "theliterature," or continuing resources, which continue tocome in, such as a magazine subscription. Passive scan-ning uses all continuing resourcesconversations at home,television and radio programs, conferences, meetings,memos, notes, and all other incoming information. l'assitrescanning rarely involves the use of existing resources.Active scanning involves the conscious selection of con-tinuous resources and, from time to time, supplementingthem with existing resources as needed. For example, anitem resulting from scanning continuing resources mayrequire the directed scanning of an existing resource todevelop the necessary background, context, or history tosupport the determination of an appropriate response.

Directed scanning. The active scanning of a selected existing resource for specific items is directed scanning. Usu-ally this scanning continues until the items are located, notnecessarily until the resources are exhausted. For exam-ple, if a member of the scanning committee knows that agood analysis of an issue was in a particular journal sometime last year, he could examine the table of contents of allvolumes of the journal to locate the article. As the specificdesired item is known and the resource can be specified,the scanning committee can delegate whatever directedscanning is necessary.

Scanning for the institution.To anticipate the changing conditions of its external envi-ronment, the institution needs both active and passivescanning of general and selected continuing informationresources. The results of this processin the form of clip-


3

pings or photocopies of articleswill be reported to thescanning committee for evaluation. The chair of the com-mittee (or its staff, if any) compiles the incoming clippingsto prepare for the discussion of new issues at the commit-tee's next regular meeting. In performing this task, thechair looks for reinforcing signals, for coincident items(each of which may have sufficient importance only if bothhappen), for items that may call for active or directedscans of new or different resources, and for informationabout the interesting future.

Developing a scanning taxonomy. Any number of taxono-mies and mechanisms have been used to structure thescanning process. All of them attempt to satisfy severalconflicting objectives. First, the taxonomy must be com-plete in that every possible development identified in thescanning has a logical place to be classified. Second, everysuch development should have only one place in the filesystem. Third, the total number of categories in the systemmust be small enough to be readily usable but detailedenough to separate different issues. The concepts devel-oped from technology assessment in the mid-I970s providean elementary taxonomy consisting of four categories:(1) social, (2) technological, (3) economic, and (4) legisla-tive/regulatory.

The taxonomy at the University of Minnesota, for exam-pie, includes five areas.* The political area includes thechanging composition and milieu of governmental bodies,with emphasis at the federal and state levels. The eco-nomic area identifies trends related to the national andregional economy, including projections of economichealth, inflation rates, money supply, and investment re-turns. The social/lifestyle area focuses on trends relating tochanging individual values and their impact on families, jobpreferences, consumer decisions, and educational choi,-es,and the relationship of changing career patterns and leisureactivities to educational choices. The technological areaincludes changing technologies that can influence the work-place, the home, leisure activities, and education. Thedemographic /manpower area includes the changing mix of

*Richard B. Heydinger 1984. personal communication.

22

population and resulting population momentum, includingage cohorts, racial and gender mix for the region, the re-gion's manpower needs, and the implications for curriculaand needed research.

To develop a more specialized taxonomy, the scanning-committee should focus on the issues of greatest concernto the institution. The committee can use any method itchooses to select these categoriesbrainstorming, ques-tionnaires, meetings, for example. Whatever method isteed, it should be thorough, democratic, and, to the extentpossible, anonymous (so that results are not judged on thebasis of personalities). One method that meets these crite-ria is to use a questionnaire based on an existing issuestaxonomy. Sears Roebuck, for example, has over 35 majorcategories in its scanning system, ALCOA uses a taxon-omy with over 150 categories, and the U.S. Congress orga-nizes its pending legislation into over 200 categories. Sucha list can be used as the basis of a questionnaire that asksrespondents to rate the relative importance of each cate-gory and expand categories that may be of particular im-portance to the institution. For example, under the cate-gory of higher education, the committee may want to addsubcategories concerning issues of tenure and the aca-demic marketplace, among others.

Alternatively, the committee may want to develop itsown taxonomy. Although using a detailed taxonomy likethe one Congress uses helps to ensure thoroughness andalthough an organized system can be adapted to new issuesus additional categories rue opened, the advantage of start-ing with oily tour categories is simplicity.

When the questionnaire is complete, the categoriesnamed most frequently should be selected for scanning.That number is determined by the size of the committee;experience indicazes that a 10- to /2-member committeecan handle no more than 25 to 40 assigned categories forscanning, with each member having responsibility for twoor three categories and the relevant sources to scan foreach of them. The list of categories then becomes the sub-ject index of the scanning files.

With this list of categories and a list of the publicationsand other resources already being scanned, the committeecan identify the categories for which assigned scanning isnecessary. At this point, the kind of resource takes on


3k

importance. For example, "alcoholism" may be an issueselected for scanning but one for which no current re-source can be identified. For this issue, generic andsec-ondary resources may he sufficient--newspapers, nationalweekly magazines, or other resources in the passive scan-ning network. Nevertheless, the resources designated for.this it:sue and their designated scanners should be identi-fied. Of course, a particular publication or resourWinaycover more than a single category, and it may take severalpublications to cover a single issue adequately.

What to scan. Determining which materials to scan is anextremely important and difficult task. This process in-volves deciding what "blinders" the committee will wear.It is obviously better to err on the side of inclusion ratherthan exclusion at this point, yet the amount of materialcommittee members can for will) scan is clearly limited.The decisions made at this point will determine for themost part the kind, content, and volume of informationpresented to the scanning committee and will ultimatelydetermine its value to the institution. This question de-serves substantial attention.

Bticause of the limitations of various resources, scanning-lust he limited to those resources reporting issues thathave a primary or major impact on an institution, whetherthe issues originate in the external world or not. A collegeor university must anticipate, respond to, and participatein public issuesissues for which it may not be the princi-pal organization affected but for which it nevertheless hasan important responsibility to anticipate. It is useful, then,to formally structure the discussion of issues and theirrelative position to each other. An example of such a chartis shown in figure 4. Such a chart creates an orderly struc-ture for the discussion of issues, ranging from an introspec-tive focus to a focus on the entire world. The levels shouldbe arranged so that all issues confronting the institutioncan be identified as having their focus at one of the levels.

The vertical dimensions of the chart are the areas ofconcern to the university. Although they will necessarilyvary from time to time, the issues include students, re-search, finances, technological change, legislative/regulatory change, social values, and more. The relative

24

3 9

FIGURE 4CHARTING THE ISSUES

ow %sr ir 0.0`" 1017"*SF-0

Finances

Faculty

Students

Curricula

Technological Change

Legislative /RegulatoryRegulations

Economic Condhions1

Alumni Support

SociopoliticalImplications


4 0

importance of each of the intercepts of the horizontal andvertical axes can be evaluated using the Delphi processdescribed in "Forecasting." For the most importantareasusually about 10-to I2the next step is to identifyspecific resources to be scanned. An area that is ranked asamong the most important but without acceptable scanningresources may require some additional research.

MI members of the scanning committee should becomemore aware of their ongoing passive scanning. The specialscreen of the scanning criteria should be added to the flowof each person's continuing resources; it is a level of sensitivity that has to be learned with experience. It must be arule of the committee that information in any form is ac-ceptable. The process of passing notes, clippings, or copiesfrom any resource must become second nature. The scan-ning coordinator or staff person will have the responsibilityto process the incoming flow for the committee's formalreview,

The committee must now address the question of theresources it will actively scan, and it must consider severalaspects of the available resources in making the decision.First, a survey of the committee will show the specificresources included in its passive scanning. Then the com-mittee must determine the kinds of resources it should bescanning, which involves the content and the kind ofresearchfor example, germane to all issues, germaneonly to special issues, emerging or first impression of is-sues, the spread of issues.

In the process of assigning resources to issues, the com-mittee should also address the question of the mix of themedia it is usingfrom periodical to annual publications,from print to electronic formsand it should review itsresources to determine a balance in the mix of the media.A list of journals focusing on the general field of highereducation or on specific aspects of the field is shown inAppendix A, and Appendix 13 includes publications focus-ing on external issues.

Popular scanning resources. Newspapers are a major scan-ning resource, and the members of the committee shouldcover four to six national newspapers to balance the news-paper !. .:!icular focuses and biases: the New York Timesfor on international affairs, the Washington Post

26

41

or Times for their focus on domestic political develop-ments, the Chicago Tribune for its focus on the Midwest,the Los Angeles Times for its West Coast perspective, andone of the major papers of the Sunbelt. USA Today and theWall Street Journal, with their emphasis on trends andforces for change, are perhaps the most popular newspa-pers of scanners. The national perspective should be sup-ported by a review of the relevant major state, regional,and local newspapers.

Magazines, periodicals, newsletters, and specializednewspapers in each of the four major areassocial, tech-nological, economic, and legislative /regulatory should beincluded. But it is also important to include publications ofspecial interest groups that are attempting to put their is-sues on the national agenda (Congresswatch, Fusion, theUnion of Concerned Scientists, the Sierra Club, the Na-tional Organization for Women, and Eagle Forum, for ex-ample) and journals reporting new developments, such asthe Swedish Journal of Social Change and PsychologyToday. Although the list of scanning resources may appearformidable, the number of new periodicals added to exist-ing resources may be quite small, for at most universities,some member of the faculty already sees one of the re-sources or it already is received in a campus library.

A special effort should be made to seek publications ofthe fringe literaturethe underground pressas exempli-fied by the Village Voice and other nonestablishment publi-cations. Depending upon the results of the survey of litera-ture already being covered by members of the scanningcommittee, a special effort could be made to include publi-cations like Ms.. Glamour, Working Woman, WorkingMother, Family Today, and Ladies Home Journal. Finally,the scanning literature should include a few wild cardsHigh Times, Heavy Metal, Mother Jones, for example.The scanning staffer should maintain a list of publicationsthat are being scanned and the committee members respon-sible for scanning them. Ideally, each member of the com-mittee should be responsible for three to four titles.

Additional resources for scanning include trade and pro-fessional publications, association newsletters, conferenceschedules showing topics being addressed and considered,and, in particular, publications of societies and associa-tions involved with education and training. For example,


4'

many instructional innovations are surfacing in corporatetraining programs and are being discussed at annual meet-ings of the American Society for Training and Developmentand in trade publications like Journal of Training and De-velopment and Training: The Magazine of Human Re-sources Development. As a further example, the forecast-ing movement and the concept of strategic planningdeveloped in the business sector years before most individ-uals in higher education were aware of them as potentiallyaffecting colleges and universities. Other industrieshealth care and social services, for examplemay experi-ence issues before higher education. Strategies for costcontainment in the health care sector, for example, maywell merit adaptation by higher education as funding sup-port lessens (Morgan 1983).

A number of associations and societies track or advocatesocial change. The World Future Society, for example,publishes The Futurist, The Futures Research Quarterly,and Future Survey, all of which are dedicated to the explo-ration and discussion of ideas about the future. The Ameri-can Council of Life Insurance in Washington, D.C., pub-lishes a newsletter, Straws in the Wind, and periodicreports on emerging issues called The ACLI Trend Report.In addition, major corporations use commercial services tosupplement their scanning functions: Yankelovitch's Cor-porate Priorities, the Policy Analysis Company's Con -gresScanTM and Issue Paks, the Naisbitt Group's TrendReport, SRI International's Scan, and the Institute forFuture Systera Research's Trend Digest. The more expen-sive outside resources are beyond the budgets of mostcolleges and universities and are not without their ownliabilities (many of them attempt to cover all issues from allperspectives, making their results too general to meet theneeds of specific organizations), and an overemphasis onoutside resources violates an organizational requirementthat the scantling function be developed within the existingstructure rather than added on from the outside.

The scanning committee should make a special effort toinclude within the scanning process whatever fugitive liter-ature it is able to obtain, that is, sources that are publishedprivately and are available only if their existence is knownand they are hunted down. Such literature would include,for example, the more than 25 articles, pamphlets, and

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43

other private publications now available on the new field ofissues management compiled by the issues ManagementAssociation in Washington, private publications on chang-ing social values such as the 1981 Connecticut Mutual LifeInsurance study, AT&T's Context of Legislation, and thepublications of research organizations like the Rand Corpo-ration, SRI International, or the Center for Futures Re-search at the University of Southern California. Fugitiveliterature often enters the established literature, but some-times years after its initial private publication. Thus, it isnecessary to develop personal and professional contactsthroughout the scanning network to gain access to thesematerials. Professional associations like The World FutureSociety, the Issues Management Association, or the NorthAmerican Society for Corporate Planning and their confer-ences can be major sources for fugitive literature.

Other resources. The scanning committee should tap theresources of its resident experts (Renfro and Morrison1983b), best accomplished by the publication of a weeklyor monthly scanning newsletter prepared by the commit-tee's staff. This brief newsletter might present two to fiveof the more significant items recently found by the scan-ning committee. Such newsletters continue to build a con-stituency for the scanning process and an informal networkfor the recognition and appreciation of the results of scan-ning. The newsletter might be sent, for example, to alldepartment chairs with an open invitation for their com-ments and for suggestions of new ideas they see in theirfields. Colleges and universities are in a unique position toconduct scanning: Many organizations do not have the in-house experience that is available on most faculties.

Internal scanning newsletters frequently use political andissue cartoons found in major newspapers and in nationalmagazines like The New Yorker. Such cartoons provide animportant signal that at least the editors believe the issuehas reached national standing and that some consensus onthe issue exists for the cartoonist to create the foil andhence the humor. These cartoons serve the additional func-tions of communicating a tremendous amount of informa-tion in a very small spacea picture is still worth a thou-sand words.


44

After operating for a year, the scanning committee needsto review the clippings and articles collected and eliminateoutdated materials. A staff person should have the respon-sibility of maintaining the files, opening and closing catego-ries only with the approval of the whole committee. Tokeep the scanning from becoming outdated, the list ofpublications scanned should be reviewed and those re-sources that yielded little information in the preceding yeardropped.

Operating an environmental scanning process requires acommitment of time and resources. It may be desirable forcolleges to form consortia to share resources, following theexample of the life insurance industry. Or they may de-velop cooperative arrangements with local corporationsthrough which they receive scanning information, particu-larly projections of the region's economy and emergingtechnology. It is imperative, however, to establish an effec-tive scanning system in this fast-changing world to identifyas early as possible those emerging trends and issues thatmay so dramatically affect the organization's future.

Evaluating the IssuesThe most elementary environmental scanning system canquickly identify more emerging issues than the largest insti-tution can address. Even Connecticut General Life Insur-ance Company (now part of CIGNA) limits itself to ad-dressing no more than its six most important issues. Theissues must be limited to some manageable number to en-sure the organization's effectiveness. This limiting processis achieved by a rigorous, objective evaluation of the is-sues. The goal is to create a process within which the is-sues compete with one another to determine their relativeand/or expected importance. The less important issues arethe focus of continued monitoring and analysis or are usedin the forecasting or other stages. The traditional methodsof research analysis and forecasting can be used at thisstage. Frequently, evaluation of the future impacts ofanemerging issue must rest on opinion, belief, and judgmentalforecasts. (Several techniques for gathering judgmentalopinion as they apply to forecasting are described in thenext section.) The methods described in this section forevaluating issues can also be used in forecasting.

30

Probability-impact chartsOne method of evaluating the issues, events, or trendsidentified during scanning involves addressing three sepa-rate questions: (1) What js the probability that the emerg-ing issue or event will actually happen during some futureperiod, usually the next decade? (2) Assuming it actuallyhappens, what will its impact be on the future of the insti-tution? (3) What is the ability of the institution to effec-tively anticipate, respond to, and manage the emergingissue, trend, or event? While these questions appear easyto answer, their use and interpretation in the evaluationprocess involve care and subtlety. The results for the firsttwo questions are frequently plotted on a simple chart toproduce a distribution of probability and impact. Manypossible interpretations of the results can easily be dis-played on such a chart.

The first question, that of the probability of the event'shappening, may be easy to understand but difficult to esti-mate. if the scanning process has identified a particularevent (that is, something that will happen or not happen insuch a way that it can be verified in retrospect), then esti-mating the probability can be relatively straightforward.Suppose, for example, the United States replaces the cur-rent income tax system with a flat tax. This sharp, clearlydefined, verifiable event is.one about which the questionbeing asked is clear (althotigh opinions may differ). lf, onthe other hand, the scanning process identifies a broaderissue that does not have this focus on a specific event, itmay be extremely difficult to define when an issue hasemerged and happened. In essence, the emergence of anissue is somewhat like news: It is the process of learningof something that makes it news. Thus, an issue emergeswhen it is recognized by a broader and broader spec-trum of the society and in particular by those whom itwill affect.

Collecting judgments on an event's probability, impact,and degree of control can be done by using simple ques-tionnaires or interviews and quantifying participants' opin-ions using various scales (for example, probability canrange from 0 to 100, impact from 0 to 10). When all partici-pants have made their forecasts, the next step is to calcu-late a group average or median score. Quantification isuseful because it is fast, and it tends to focus the attention

What is theability of theinstitution toeffectivelyanticipate,respond to,and managethe emergingissue, trend,or eve;. t?


t)

L 32

of the group on the subject rather than the source of theestimates.

The next question concerns evaluating the impact of theemerging issue or event, based on the assumption that itactually occurs. Frequently a scale of 0 to 10 is used toprovide a range for the answers to this question, where 0 isno impact, 5 is moderate impact, and 10 is catastrophic orsevere impact.. Usually plus or minus answers can be in-corporated. This question and the first question (an event'sprobability) can be combined in a single chart that displaysa probability impact space with positive and negative im-pacts on the vertical axis and probability from 0 to 100 onthe horizontal axis. This chart can be used as a question-naire in which respondents record their answer to the prob-ability and impact questions by placing a mark on the chartwith the coordinates of their opinion about the probabilityand the impact of the issue. When all of the participantshave expressed their opinions, all of the votes can be trans-ferred to a single chart to show the group's opinion. Asample chart with a group's opinions about an X-event andan 0-event is shown in figure 5. The X-event shows rea-sonably good consensus that the event will probably hap-pen and that it will have a positive impact; therefore, cal-culating an average for the group's response is useful andcredible. For the 0-event, however, the group shows rea-sonable agreement that the event has low probability ofoccurring but is split on its probable impact.

The X-event highlights one of the problems of this par-ticular method: Respondents tend to provide answerseither from different perspectives or with some inherentnet impact where positive impacts cancel or offset negativeimpacts. In reality, an emerging issue or event often hasboth positive and negative impacts. Thus, the questionshould be asked in two parts: What are the positive im-pacts of this event, and what are its negative impacts? Inrank ordering events, two ranks are preparedone forpositive and one for negative eventsto permit the devel-opment of detailed policies responses, and strategiesbased upon a recognition of the dual impacts of mostemerging issues.

Even with the recognition of an event's dual impact,consensus may be insufficient to identify the average groupresponse. in this case, it may be useful to return the

y

FIGURESPROBABILITY-IMPACT CHART SUMMARIZING SEVEN VOTES FOR TWO DIFFERENIT EVENTS

IMPACTIFEVENT DOESHAPPEN

REVOLUTIONARY(+IOW

STRONG( +75%)

MODERATE(+W)

LIGHT(+25%)

NONE

LIGHT(-25%)

MODERATE( -51%)

SEVERE

(-75%)

CATASTROPHIC(-IN%)

X

Mml

1% 591, 75% fae%

Average impact: 4.5 iAverage probability:" %Weighted impact:

POSITIVEIMPACT

Average impact: No consensusAverage probability: 30%Weighted impact: Unknown

NEGATIVEIMPACT

PROBABILITY THAT THE EVENT WILL HAPPEN

Note: Xs show consensus about a very probable event with high, positive impact,Os show an event with consensus on probability (low), but not on impact.

Source: Renfro and Morrison 1911Ja. 48

rI

group's opinion to the individual participants for furtherdiscussion and reevaluation of the issue. This process ofanonymous voting with structured feedback is -known asDelphi. Anonymity can be extremely useful. In one privatestudy, for example, all of the par Acipants in the projectpublicly supported the need to adopt a particular policy forthe organization. But when asked to evaluate the policyanonymously on the probability-impact chart, the respon-dents indicated that though they believed the policy waslikely to be adopted, they did not expect it to have anysignificant impact. This discovery allowed the decisionmakers to avoid the risks and costs of a new policy thatwas almost certain to fail. (The Delphi process is describedfurther in the next section.)

When repeated reevaluations and discussions do notproduce sufficient consensus, it may be necessary to rede-fine the question to evaluate the impact on particular sub-categories; subcategories of the institution, for example,would include the impact on personnel, on finances, oncurricula, or on faculty. As with all of today's judgmentalforecasting techniques, the purpose is to produce usefulsubstantive information about the future and to arrive at agreater understanding of the context, setting, and frame-work of the evolving future (De Jouvenel 1967, p. 67).

The most pop, method of interpreting the result of aprobability-impact chart is to calculate the weighted posi-tive and negative importancethat is, the product of theaverage probability and the average (positive and negative)importancefor each event. The events, issues, andtrends are then ranked according to this weighted impor-tance. Thus, the event ranked as nil- Lber one is that withthe highest combined probability ,.ad impact. The otherevents are listed in descending priority according to theirweighted importance.

Ranking the issues according to weights calculated inthis manner implicitly assumes that the item identified inthe scanning is indeed an emerging issuethat is, one thathas an element of surprise. If all of the items identified inscanning are new and emerging and portend this element ofsurprise (that is, they are unknown to the educational com-munity or at least to the community of the institution nowand will remain that way until they emerge with surpriseand the potential for upset), then the strategic planning

4 9

process would do well to focus on those that are mostlikely to do so and to have the greatest impact

lf, however, the issues are not surprises, then anothersystem of evaluating and ranking the events and issues willbe necessary. For example, if the entire community knowsof a particular event and expects that it will not happen,then this low probability will produce a low priority. Yet, ifthe event would in fact occur, then it would be of greatimportance. The surprise then is in the occurrence of theunexpected. The key in this case is the upset expectation.It may be just as much of an upset if an item that everyoneexpects to occur does not in fact happen. Thus, the evalua-tion of a probability-impact ch4rt depends on anotherdimensionthat is, one of expectation and awareness. Themost important events might be those of high impact andhigh uncertainty, that is, those centered around the 50percent probability line. These are the events that are aslikely as not to occur and portend an element of surprisefor some portion of the community when they happen ordo not happen.

Another aspect of emerging issues that is often evaluatedis their timing, that is, when they are most likely toemerge. If an issue or event is evaluated in several rounds,consensus about the probability is often achieved in theearly rounds. In the last rounds, timing can be substitutedfor probability by: changing the horizontal axis from 0 to100 to now to 10 years from now. Then the question be-comes, In which of the next 10 years is the event mostlikely to happen? If necessary, additional questions canexplore lead time for an issue's occurrence, year of lasteffective re'ponse opportunity, lag time to impact, and soon. All of t' iese factors have been used to evaluate therelative importance of emerging issues and events.

Emerging issues and events that are ranked according totheir weighted importance have a built-in assumption thatshould usually be challenged; that is, the ranking assumesthat the administrators and the institution will be equallyeffective in addressing all of the issues. This assumption isalmost certainly false and seldom of great importance.Suppose that the top priority issue is one on which theinstitution could have little influence and then only at greatcost but that a lower-level item is one on which the institu-tion could have a significant impact with a small invest-


5

mein of resources. It would clearly be foolish to squandergreat resources for little advantage, when great advantagecould be obtained for a much smaller investment. Thus, inaddition to the estimation of the weighted importance, theextent to which the event might respond to institutionalactions of various costs and difficulty must be evaluated.The cost-effectiveness ratio measures the relative effi-ciency of alternative institutional actionsactions that areexpressions of strategy. This outcome is especially evidentwhen the differences in ratio are small, but if the emergingissues are competing for the same resources, the cost-effectiveness ratios will be essential in guiding the effectiveuse of the institution's limited resources.

The top-ranked events may also be important to majoradministrative functions other than strategic planning.Many corporations. trade associations, and not-for-profitinstitutions have formed special "issues management com-mittees" to support the authorized leadership of the insti-tution in managing all of the resources they might haveavailable to address an emerging issue. While such systemsmay be more formal than is needed at most institutions ofhigher education, they may serve as a useful model.

Impact networksAnother simple evaluation methodthe impact networkwas derived from the concept of "relevance trees," whichare essentially a graphical presentation of an outline of acomplete analysis of an issue. Impact networks are a brain-storming technique designed to identify potential impactsof key events on future developments. An impact networkis generated by identifying the possible effects of a givenspecific event. SkA an event might be the abolishment oftenure, or the reduction of federally sponsored studentfinancial aid, or the requirement that all professors be cer-tified to teach in colleges and universities. When the issuehas been selected and sharpened into a brief, clear state-ment, the group is ready to begin to form the impactnetwork. The procedure is quite simple. Any impact that islikely to resin ft 9m the event, whether negative or posi-tive, is an "acceptable impUct." The question is one ofpossibility, not probability. With the initial event written inthe middle of the page, each first-order impact is linked tothe initial event by a single line (see figure 6).

36

51

FIGURE 6IMPACT NETWORK

SECOND -ORDERIMPACT

THIRD-ORDER

4 1

FIRSTORDERIMPACT

INITIALISSUE

r.

SECOND -ORDERIMPACT

FIRSTORDERIMPACT

FIRST -ORDERIMPACT


When five or six first-order impacts have been identifiedor when the space around the initial event is occupied, theprocess is repeated for each first-order impact. Again, thetask is to determine the possible impacts if this event wereto occur. The second-order impacts are linked to their first-order impacts by two lines. These steps are repeated forthird- and fourth-order impacts, or as far*as the groupwould like to go. Typically, third- and fourth-order impactsare sufficient to explore all of the significant impacts of theinitial event. Usually a group identifies sev,eral feedbackloops; for example, a fourth-order impact imight increase ordecrease a third- or a second-order impact. The value ofimpact networks lies in their simplicity and in their poten-tial to identify a wide range of impacts very quickly. ifmore impacts or higher-order impacts need to be consid-ered, the process is repeated.

A simple example of the use ofan impact network illus-trates the impact of the elimination of tenure ii higher edu-cation (Wagschall 1983). As shown in figure 7, the immedi-ate or first-order consequences of the event were perceivedto be (1) reduced personnel costs, (2) more frequent turn-over of faculty, and (3) an improvement in the academicquality of the faculty. Each consequence then becomes thecenter of an impact network, and the search for impactscontinues. For example, the improvement of the faculty'sacademic quality causes improved learning experiences,students' increased satisfaction with their education, andthe accomplishment of more research. The reduction inpersonnel costs produces stronger faculty unions, morefunds for nonpersonnel items, and decreased costs perstudent. Increased faculty turnover produces a decrease inaverage faculty salary, an increase in overall quality of thefaculty, and a decrease in the average age of the faculty.Each consequence in turn becomes the center of the third-order impact network, and so on.

A completed impact network is often very revealing. Inone sense, it serves as a Rorschach test of the authoringgroup or the organization because the members of thegroup are most likely to identify impacts highlighting areasof concern. In another sense, by trying to specify the rangeof second-order impacts, new insights into the total impactof a potential development can be identified.,For example,while an event may stimulate a majority of small, positive,

38

FIGURE 7AN IMPACT NETWORK:

THE CONSEQUENCES OF ELIMINATING TENURE

ih

LEARNINGEXPERIENCES

ACADEMICQUALITY

OF FACULTYIMPROVES

MORERESEARCH

ACCOMPLISH II

AVERAGE AGEOF FACULTYDECREASES

TENUREIS

ELIMINATED

PERSONNELCOOTS

REM CED

TURNOVER OFFACULTY

MOREFREQUENT

QUALITYOF

FACULTYIMPROVE/

FACULTYUNIONS

STRONGER

COSTSPER

STUDENTDECREASE

AVERAGEFACULTYSALARY

DECREASED

FUNDSFOR

NON-PERSONNEL

ITEMSINCREASE

Source: Wagschall 1983,

Futures Research and the Strategic Planning Process 39.

54

first-order impacts, these first-order impacts may stimulatea wide range of predominantly negative second-order im-pacts that in total would substantially reduce if not elimi-nate the positive value of the first-order impacts. Feedbackloops may promote the growth of an impact that would faroutweigh the original estimate of its importance.

ForecastingScanning typically leads to the identification of more issuesthan the organization can reasonably expect to explore indepth, given its limitations of time, money, and people.Simple evaluation techniques like those described in theprevious section can help reduce the set of candidates tomanageable size. The surviving issues can then be sub-jected to detailed forecasting, analysis, and policy evalua-tion. Many methods have been developed for forecasting.This section surveys the range of methods, beginning withseveral varieties of the simplest, most popular ty.-e of fore-casting, individual judgmental forecasting. It then brieflydescribes techniques of mathematical trend extrapolationand group forecasting, cross-impact models, and scenarios.

Implicit forecastingAccording to Yogi Berra, "You can observe a lot just bywatching." And much of what can be ob erved is the fu-ture. Despite the constant flood of assertions about theaccelerating pace of change, despite endless warningsabout impermanence and future shock, despite the vigor ofthe minor industry that produces one book or report afteranother that b. gins by telling us that we are on the verge ofa societal transformation every bit as profound as the in-dustrial revolution (all of which may actually be true), thepresent still foreshadows the future. If only we knew thepa..it and present well enough, far fewer "surprises" wouldcatch us unaware in the future. It pays to watch, and iteswcially pays to watch the largest systemsgovernment,education, transportation, primary metals, finance, healthcare, energyfor they usually change very slowly andonly after protracted debate and consensus building.

No one should have any difficulty with the notion thatmany of the developments causing turmoil and confusionin each of these systems today were being widelydiscussedeven passionately advocated or resisted at

40

least 10 or more years ago. Five or 10 years from now noone should find it hard to look back to today and discoverthat the same was true.

Administrators in large institutions know that very longlead times are often required before major decisions can beinitiated and fully implemented. They also know that theenvironment can change in peculiar, sometimes unpredict-able ways while these decisions are coursing through thesystem. The result can be that by the time the decisionsshould have been fully implemented, the world will havechanged so much that they musi be abandoned or radicallyaltered. To the extent, however, that the original expecta-tions were shattered by forces arising from large systems,why should administrators be surprised by the outcome?They may be exceedingly disappointed that they have per-seered in a losing battle, but they should not be surprised.

Real surprises usually come from failing to keep track ofsmall-scale developments in the external environment, notfrom excluding small-scale developments within one's ownsystem. By systematica4 following these external devel-opments it is possible not only to anticipate the directionsand potential,impacts of the slower, more pronounced,more profoundly influential changes but also to obtain theearly warning needed for timely adjustments of strategy.Emerging patterns of events, the ebb and flow of particularsets of issues that can be revealed by close monitoring,provide a basis for forecasts relevant to policy. These fore-casts are intuitive, to be sure, and perhaps seen only dimlyin outline, but they are nonetheless the best forecastsavailable.

Even when the output from scanning consists of fore-casts, we must still make our own judgments about thefuture, because we must decide what is relevant and wemust make judgments as to whether we agree with thegiven forecasts. The same process is at play when we readnewspapers, journals, reports, and government documentsor listen to a broadcast. We constantly make personal fore-casts on the basis of sparse and fragmented historical datain an attempt to distill the future that may be implied.

This process of trying to infer the future by mentallyextending current or historical data is sometimes called"implicit forecasting.- Such forecasting is obviously asuseful as it is unavoidable when it comes to obtaining an

It pays towatch . . . thelargest systems. . . for theyusuallychange veryslowly.

Futures Research and the Strategic Pla,?ning Process 41

5 6

appreciation of the broad outlines of possible futures. Byitself, however, implicit forecasting is not sufficient when itcomes to making today's decisions about our own mostimportant long-range issuesthe direction of a career, thedevelopment of a profession, the survival of an institution,department, or program, for example. In such cases, theneed is also for methods that deal much more formally,systematically, and comprehensively with the nature andlikely dynamics of future events, trends, and policychoices.

It is easy to see why our implicit forecasts of the generalcontext are progressively less trustworthy as the questionsat stake become more important. These forecasts are en-'!rely subjective, they are no doubt idiosyncratic, they areoften made on topics we are unqualified to assess becauseof a lack of relevant experience or knowledge, they restvery largely on unspoken arguments from historical prece-dent or analogy, and they are haphazard in that they aremade primarily in response to information we receivethat is itself usually developed haphazardly or opportu-nistically.

As futures research has developed since the mid-I960s,much work has gone into the invention and application oftechniques intended to overcome these and other limita-tions of widely practiced methods of forecasting. In gen-eral, the newer methods are alike in that they tend to dealas explicitly and s istematically as possible with the variouselements of alternative futures, the aim being to providethe %vherewithal for users to retrace the steps taken. Thefollowing paragraphs highlight some of these methods.

Genius forecastingApart from implicit forecasting, the most common ap-proach to forecasting throughout history has been for asingle individual simply to make explicit guesstimatesabout the future. In their weaker moments, many brightand otherwise well-informed peopleincluding even ru-tures researchersare sometimes cajoled into offeringsuch guesstimates, which typically take the form of one-line forecasts ("cancer will be cured," "no ship will everbe sunk by a bomb," or "the end is near"). But if they arepersuaded to reflect on the future in a widely ranging way,to try to articulate the underlying logic of affairs and its

42

likely evolution over time, to reason through the obviousalternatives and imagine the not so obvious ones, when inshort they offer a careful but creative image of the future inits richness and complexity, then a much different processis involved. It has no common name, but in futures re-search it is often lightly called "genius forecasting." It is apowerful and highly cost-effective way to obtain forecastsif the "genius" is indeed thoughtful, imaginative, and wellread in many areas.

The disadvantages of genius forecasting are clear enoughto require no enumeration here. "In the end, genius fore-cast g depends on more than the genius of the forecaster;it depends or. luck and insight. There may be many ge-niuses whose forecasts are made with full measure of both,but it is nearly impossible to recognize them a priori, andthis, of course, is the weakness of the method" (Gordon1972, p. 167).

If used properly, however, the strengths of the methodusually outweigh its weaknesses. The probability of theintegrated forecast produced by the "genius" is certain tobe virtually zero. Time will show that the forecast wasoversimplified, led astray by biases, and ignorant of criticalpossibilities. Yet the genius has the ability to identify un-precedented future events, to imagine current policies thatmight be abandoned, to assess the interplay of trends andfuture events in a far more meaningful way than any exist-ing model can, to trace.out the significance of this inter-play, to identify opportunities for action that no one elsemight ever see, and to explain assumptions and reasoning.Although the genius forecast will be both "wrong" andincomplete, it will nevertheless have provided somethingvery useful: an intelligent base case.

Occasionally, genius forecasts can serve as the onlyforecasts in a study. This approach makes excellent sensein studies being accomplished under severely constrainedtime and resources. Increasingly in futures research, how-ever, studies are begun by commissioning one or moregenius forecasts, which take the form of essays or sce-narios of one sort or another. With them in hand, the in-vestigators explore them carefully for omissions and incon-sistencies, and then the forecasts are carefully pulled apartto identify the specific trends, events, and policies thatappear to warrant detailed evaluation; that is, the most


56

uncertain, problematical, intractable, and potentially valu-able statements about the future can be selected. Beingable to launch a more sophisticated forecasting effort fromsuch a basis is much better than having random thoughtsand blank paper.

Extrapokstion of mathematical trendsMost forecasters and some practitioners of futures re-search use techniques of mathematical trend extrapolationthat are well understood, rest on a fairly adequate theoreti-cal foundation, convey the impression of being scientificand objective, and in skilled hands are usually quick andinexpensive to use. One of the most commonly used tech-niques is regression analysis, one purpose of which is toestimate the predicted values of a trend (the dependentvariable) from observed values of other trends (the inde-pendent variables). Hierarchical regression models aresometimes referred to as "causal" models if an obser edstatistical relationship exists between the independent anddependent variables, if the independent variables occurbefore the dependent variable, and if one can develop areasonable explanation for the causal relationship. A fore-cast of the independent variables makes possible a forecastof th% dependent ones to which they are statisticallylinked, whether the case is simple or complex. In eithercase, however, the purpose behind causal regressionmodels is always to explain complex dynamic trends (forexample, college and university enrollment patterns) interms of elementary stable trends (for example, demo-graphics or government spending).

When cause is not an essential factor, trends are oftenforecast using time as the independent variable. Much ofthe "trend extrapolation" in futures research takes thisform. Common methods of time-series forecasting beingused today are the smoothing, decomposition, andautoregression/moving average methods. Smoothingmethods are used to eliminate randomness from a dataseries to identify an underlying pattern, if one exists, butthey make no attempt to identify individual components ofthe underlying pattern. Decomposition methods can beused to identify those componentstypically, the trend,the cycle, and the seasonal factorswhich are then pre-dicted individually. The recombination of these predicted

a

patterns is the final forecast of the series. Like smoothingmethods, decomposition methods lack a fully developedtheoretical basis, but they are being used today because oftheir simplicity and short-term accuracy. Autoregression isessentially the same as the classical multivariate regres-sion, the only difference being that the independent (pre-dictor) variables are simply the time-lagged values of thedependent (predicted) variable. Because time-lagged valuestend to be highly correlated, coupling autoregression withthe moving average method produces a very general classof time-series models called autoregression/moving average(ARMA) models.

All regression and time-series methods rest on the as-sumption that the historical data can, by themselves, beused to forecast the future of a series. In other words, theyassume that the future of a trend is exclusively a functionof its past. This assumption, however, will always provefalse eventually because'of the influence of forces not mea-sured by the time series itself. That is to say, unprece-dented sorts of events always occur and affect the series,which is precisely why the historical data are so irregular.

These difficulties have not deterred many traditionalanalysts and long-range forecasters from using such .

methods and thereby generating dubious advice for theirsponsors. Within futures research, however, thesetechniqueswhen used wellare applied in a very distinc-tive way. The objective is not to foretell the future, whichis obviously impossible, but to provide purely extrapola-tive base-line projections to use as a point of referencewhen obtaining projections of the same trends by moreappropriate methods. What would the world look like ifpast and current forces for change were allowed to playthemselves out? What if nothing novel ever happenedagain? The only value of these mathematical forecastingtechniques in futures research is to provide answers tothese remarkably speculative questions. But once they areanswered, a reference %All have been established for get-ting on with more serious forecasting.

For example, in a study by Boucher and Neufeld (1981),a set of I l I trends was forecast 20 years hence boll, mathe-matically (using an ARMA technique) and judgmentally(using the Delphi technique). Analysis of the resultsshowed that the average difference between the two sets of


46

forecasts was over 15 percent. By the first forecasted year(which was less than a year from the date of the comple-tion of the Delphi), the divergence already averaged morethan 10 percent; by the 20th year, it had reached 20 per-cent. This result is interesting because even experiencedmanager: usually accept mathematical forecasts uncriti-cally. They like their apparent scientific objectivity, theyhave been trained in school to accept their plausibility, andacceptance has been reinforced by an endless stream ofsuch projections from government, academia, and otherorganizations. Seeing judgmental and mathematical resultsside-by-side can thus be most instructive. Moreover, assome futur 's researchers believe, if the difference betweensii,:h a pair of projections is 10 percent or more, it is proba-bly worth examining in depth.

The Delphi techniqueGiven the limitations of personal forecasting (implicit orgenius) and of mathematical projections, it is nowcommonand usually wiseto rely on systematicmethods for using a group of persons to prepare the fore-casts and assessments needed in strategic planning. Expe-rience suggests, however, that at least five conditions musthe present before the decision to use a group should bemade: (1) No "known" or "right" answers exist or can behad (that is, acceptable forecasts do not exist or are notavailable): (2) equally reputable persons disagree about thenature of the problem, the relative importance of variousissues, and the probable future; (3) the questions to beinvestigated cross disc.plinary, political, or jurisdictionallines. and no one individual is considered competentenough to cope with so many subjects; (4) cross-fertilization of ideas seems worthwhile and possible; and(5) a credible method exists for defining group consensusand evaluating group performance.

The fifth condition is especially importantand often~lighted. As a matter of fact, the emphasi., one places onthis consideration often determines the method of groupforecasting one chooses. If, for example, the person seek-ing the forecasts will be content with an oral summary ofthe results (or perhaps a memo for the record), then a con-ventional face-to-face meeting of some sort may he theappropriate method. If, at the other extreme, it is known

that the intended user will insist on having a detailed com-prehensive forecast and that the persons whose viewsshould be solicited would never speak openly or calmly toeach other at a face-to-face meeting, then a differentscheme for eliciting, integrating, and reporting the fore-casts would surely be required.

Considerations like these were responsible in large partfor the invention of what is no doubt the most famous andpopular of all forecasting methods associated with futuresresearch: the Delphi technique. Delphi was designed toobtain consensus forecasts from a group of "experts" onthe assumption that many heads are indeed often betterthan one, an assumption supported by the argument that agroup estimate is at least as reliable as that of a randomlychosen expert (Da !key 1969). But Delphi was developed todeal especially with the situation in which risks were inher-ent in bringing these experts together for a face-to-facemeetingfor example, possible reluctance of some partici-pants to revise previously expressed judgments, possibledomination of the meeting by a powe'rful individual orclique, possible bandwagon effects on some issues, andsimilar problems of group psychology. The Delphi methodwas intended to overcome or minimize such obstacles toeffective collaborative forecasting by four simple proce-dural rules, the first of which is desirable, the last three ofwhich are mandatory.

First, 9 participant is told the identity of the othermembers of the group. which is easily accomplished if, asis common, the forecasts are obtained by means of ques- .

tionnaires or individual interviews. When the Delphi isconducted in a workshop settingone of the more produc-tive ways to proceed in many casesthis rule cannot behonored, of course.

Second, no single opinion, forecast, or other key input isattributed to the individual who provided it or to anyoneelse. Delphi questionnaires, interviews, and computer con-ferences all easily provide this protection. In the workshopsetting, it is more difficult to ensure, but it can usually be ob-tained by using secret ballots or various electronic machinesthat permit anonymous voting with immediate display ofthe distribution of answers from the group as a whole.

Third, the results from the initial round offorecastingmust be collated and summarized by an intermediary (the


62

experimenter), vho freds these data hack to all partici-pants. and invites each to rethink his or her original an-swers in light of the responses from the group as a whole.If, for example, the participants have individually esti-mated an event's probability by nome :ature year, the in-termediary might compute the mean or median response,the interquartile range or upper and lower envelopes of theestimates, the standard deviation, and so forth, and passthese data back to the panelists for their consideration inmaking a new estimate. If the panelists provided qualita-tive information as wellfor example, reasons for estimat-ing the probabilities as they did or judgments as to the,consequences of the event if it were actually to occurtherole of the intermediary would be to edit these statements,eliminate the redundant ones and arrange them in somereasonable order before returning them for the group'sconsideration.

Fourth, the process of eliciting judgments and estimates(deriving the group response, feeding it back, and askingfor reestimates in light of the results obtained so far)should he continued until either of two thing.s happens: Theconsensus vithin the group is close nousth for practicalpurposes, or the reasons rhy such a consensus cannot heachieved have been docur!ented.

In sum, the defining characteristics of Delphi are ano-nymity of the estimates, controlled feedback, and iteration.The promise of Delphi was that if these characteristicswere preserved, consensus within the panel would sharpenand the opinions or forecaits derived by the process wouldbe closer to the "true" answer than forecasts derived byother judgmental approaches.

Thousands of Delphi studies of varying quality havebeen conducted throughout the world since 1964. when thefirst major report on the technique was published (Gordonand Helmer 1964). The subjects forecast have ranged fromthe future of absenteeism in the work force to the future ofwar and along the way have included topics as diverse asprospective educational technologies, the likely incidenceof breast cancer, the future of the rubber industry, thedesign of an ideal telephone switchboard, and the future ofDelphi itself. Some of these studies proved to be extremelyhelpful in strategic planning: a few virtually decided thefuture of the sponsoring organization. But most had little

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or no effect, apart from providing general background in-formation or satisfying a momentary curiosity about thisnovel method of forecasting.

Part of the problem in many cases is that practitionershave had false hopes. The literature conveys the impres-sion that Delphi is so powerfurand simple that anyone can"run one" on any subject. What the literature often fails tomention is that no established conventions yet exist for anyaspect of study design, execution, analysis, or reporting.Intermediaries, who are the key to useful and responsibleresults, are very much on their own. As novices theyshould examine studies by others, but because these stud-ies are all different, it may be very difficult to find or recog-nize good models. Even with an excellent model in hand,the newcomer cannot fully appreciate what it means to useit. Only through practice can one discover the significanceof four key facts about Delphi: (I) The amount of informa-tion and data garnered through the process can and willexplode from round to round; (2) good questions are diffi-cult.to devise, and the better the design of the questionsasked, the more likely it is that good participants will re-sign from the panel out of what has been called the B1Ffactorboredom, irritation, and fatiguebecause they willbe asked to answer the same challenging questions againand again for each trend or event in the set they are fore-casting; (3) the likelihood of such attrition within the panelmeans not that the questions should be cheapened but thatlarge panels must be established so that each participantwill have fewer questions to answer, which is very timeconsuming; (4) Delphi itself does not include proceduresfor synthesizing the entire set of specific forecasts andsupporting arguments it produces, so that when the studyis "completed," the work has usually just begun. And if, asone hopes, the intermediary and the panelists take theprocess and the questions seriously, the probability is highthat the schedule will slip, the budget will be overrun, andso on and on.

Another reason that success with Delphi is hard toachieve is that, despite .:0 years of serious applications,very little is known about how and why the consensus-buildivocess in Delphi works or what it actually pro-duce, wide-ranging research on the fundamentals ofthe rilithOd has been done for more than a decade. Accord-


ing to Olaf Helmer, one of the inventors of Delphi, "Delphistill lacks a completely sound theoretical basis. . . . Delphiexperience derives almost wholly either from studies car-ried out without proper experimental controls or from con-trolled experiments in which students are used as surrogateexperts" (Linstone and Turoff 1975, p. v). The same is truetoday. The practical implication is that most of what is"known" about Delphi consists of rules of thumb based onthe experience of individual practitioners.

For example, a goal of Delphi is to facilitate a sharpeningof consensus forecasts from round to round of interroga-tion. And, in fact, there probably has yet to be a Delphistudy in which the consensus among the participating ex-perts did not actually grow closer on almost all of the esti-mates requested (as measured by, say, a decline in the sizeof the interquartile range of estimates). Yet the limitedempirical evidence available on this phenomenon is repletewith suggestions that increased consensus is produced onlyin slight part by the panelists' deliberations on the groupfeedback from the earlier round. The greater part of theshift seems to come from two other causes: (1) The panel-ists simply reread the questions and understood them bet-ter, and (2) the panelists are biased by the group's responsein the preceding round of interrogation (that is, they allowthemselves to drift toward the mean or median answer).The difficulty posed by this situationwhich is far fromatypical of the problems presented by Delphiis that noway has yet been found to sort out the effects of thesedifferent influences on the final forecast. AcLordingly, theinvestigator must be extremely careful when interpretingthe results. Claims that Delphi is "working" are alwayssuspect.

On the positive side, though again as a strictly practical.nontheoretical matter, Delphi appears to have a number ofimportant advantages as a group evaluation or forecastingtechnique. It is not difficult to explain the essence of themethod to potential participants or to one's superiors. It isquite likely that some types of forecasts could not be ob-tained from a group without the guarantee of anonymityand the opportunity for second thoughts in later rounds(certainly true when hostile stake holders are jointly evalu-ating the implications of policy actions that might affect

50

them differently). Areas of agreement and disagreementwithin the panel can be readily identified, thanks to thestraightforward presentation of data. Perhaps most impor-tant, every participant's opinion can be heard on the fore-casts in every round, and every participant has the oppor-tunity to comment on every qualitative argument orassessment. For this reason, it becomes much easier todetermine the uncertainties that responsible persons haveabout the problem under study. If the panelists are chosencarefully, a full spectrum of hopes, fears, and other expec-tations can be defined.

When successes with Delphi occur, it would seem thatthe explanation is not that the panel converged from roundto round (which, as indicated earlier, almost always hap-pens). Nor is it that the mean or median response movedtoward the "true" answer (which is something that no onecould know at the time). Rather, it is that the investigationwas conducted professionally and that the results did infact have the efizct of increasing the user's understandingof the uncertainties surrounding the problem, the range ofstrategic options available in light of those uncertainties,and the need to monitor closely the possible, real-worldconsequences of options that may actually be implemented.

Delphi has been used in many policy studies in highereducation. In one case, it was used to determine prioritiesfor a program in family studies (Young 1978). Nash (1978),after reviewing its use in a number of studies concerningeducational goals and objectives, curriculum and campusplanning, and effectiveness and cost-benefit measures,concluded that the Delphi is a convenient methodologyappropriate for a non-research-oriented population. Thetechnique has also been used in a number of planning stud-ies (Judd 1972). For example, it was used as a tool for get-ting planning data to meet the needs of adult part-timestudents in North Carolina (Fendt 1978).

In general, the more successful practitioners of Delphiappear to have tried to follow the 15 steps presented infigure 8. These "rules" may appear platitudinous, and vir-tually no one has ever followed all of them in a singleDelphi. Yet the intrinsic quality and practical value ofDelphi results are certain to be a function of the degree towhich they arc followed.

Everyparticipant'sopinion canbe heard onthe forecastsin everyround, andeveryparticipanthas theopportunity tocomment.


FIGURE 8STEPS IN A PERFECT DELPHI

1. Understand Delphi (for example, that at least two rounds ofinterrogation are necessary).

2. Specify the subject and the objectives. (Don't study "thefuture." Study alternative futures of Xand do so with clearpurpose.)

3. Specify whether the forecasting mode to he adopted is ex-ploratory or normativeor some clear combination of both.

4. Specify all desired products, level of effort, responsibilities,and schedule.

5. Specify the uses to which the results will be put, if they areactually achieved.

6. Exploit the methodology and substantive results developed inearlier Delphi studies.

7. Design the study so that it includes only judgmental ques-tions (except in extreme cases), and see to it that these ques-tions are precisely phrased and cover all topics of interest asspecifically as possible.

8. Design all rounds of the study before administering the first

Other group techniquesDelphi is generally considered one of the better techniquesof pooling the insight, experience, imagination, and judg-ment of those who are knowledgeable in strategic mattersand who have an obligation to deal with them responsibly.Many other ways, however, can be used to exploit thepower of groups in forecasting and futures research: brain-storming, gaming, synectics, the nominal group technique,focus groups, and others, including the Quick Environmen-tal Scanning Technique (QUEST), the Focused PlanningEffort (FPE), and the Delphi Decision Support System(D2S,"). The last three are discussed in this section be-cause they are currently used in futures research.

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round. (Don't forget that this step includes the design offorms or software for collating the responses.)

9. Design the survey instrument so that the questions are ex-plained clearly and simply, can be answered as painlessly aspossible, and can be answered responsibly.

10. Include appropriate historical data and a set of assumptionsabout the future in the survey instrument so that the respon-dents will all be dealing with future developments in thecontext of the same explicit past and "given" future.

11. Assemble a group of respondents capable of answering thequestions creatively, in depth. and on schedule, and largeenough to ensure that all important points of view are repre-sented.

12. Collate the responses wisely, consistently, and promptly.

13. Analyze the data wisely, consistently, and promptly.

14. Probe the methodology and the substantive results constantlyduring and after the effort to identify problems and importantneeded improvements.

15. Synthesize and present the final results to management intel-ligently.

QUEST (Nanus 1982) was developed tospickly andinexpensively provide the grist foi strategic planning: fore-casts of events and trends, an indication of the interrela-tionships among them and hence the opportunities for pol-icy intervention, and scenarios that synthesize theseresults into coherent alternative futures. It is a face-to-facetechnique, accomplished through two day-long meetingsspaced about a month apart. The procedure produces acomprehensive analysis of the external environment andan assessment of an organization's strategic options.

A QUEST exercise usually begins with the recognitionof a potentially critical strategic problem. The processrequires a moderator, who may be an outside consultant,


68

to facilitate posing questions that challenge obsolete man-agement positions and to maintain an objective perspectiveon ideas generated during the activity. The process alsorequires a project coordinator, who must be an "insider,"to facilitate translating the results of QUEST exercises intoscenarios that address strategic questions embedded in theorganizational culture.

QUEST involves tour steps. The first step, preparation,requires defining the strategic issue to be analyzed, select-ing participants (12 to 15), developing an information note-book elaborating the issue, and selecting distraction-freeworkshop sites.

The second step is to conduct the first planning session.It is important that at least one day be scheduled to pro-vide sufficient time to discuss the strategic environment inthe broadest possible terms. This Discussion includes iden-tifying the organization's strategic mission, the objectivesreflected in this mission, key stake holders, priorities, andcritical environmental events and trends that may havesignificant impacts on the organization. Much of this timewill be spent evaluating the magnitude and likelihood ofthese impacts and their cross-impacts on each other and onthe organization's strategic posture. Participants are en-couraged to focus on strategic changes but not on the stra-tegic implications of these changes. This constraint is im-posed to delay evaluations and responses until a comn:eteslate of alternatives is developed.

lot third step is to summarize the results of the firstplanning session in two parts: (1) a statement of the organi-zation's strategic position, mission, objectives, stake hold-ers, and so on, and (2) a statement of alternative scenariosillustrating possible external environments facing the orga-nization over the strategic period. It is important that thereport be attributed to the group, not sections to particularindividuals. Correspondingly, it is important that the reportreflect that ideas were considered on the basis of merit, notwho advanced them. The report should be distributed afew days before the second group meeting, the final step.

The second meeting focuses on the report and the strate-gic options facing the organization. These options are eval-uated for their responsiveness to the changing externalenvironment and for their consistency with internalstrengths and weaknesses. While this process will not pro-

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\.>

duce an immediate change in strategy, it should result indirections to evaluate the most important options in greaterdepth. Consequenily, a QUEST exercise ends with specificassignments vis-a-vis'the general nature of the inquiryneeded to evaluate each'option, including a completiondate.

The Focused Planning Effort\was developed in 1971(Boucher 1972). Like QUEST, it is an unusual kind of face-to-face meeting that draws systematically on the judgmentand imaginatioe of line and staff managers to define futurethreats and opportunities and find practical actions fordealing with them. Because the process is perfectlygeneral:that is, it can be used to address any complexjudgmental quest:ons on future mission or strategicpolicythe range of applications has been widely varied.In recent years, topics have ranged from the potentialmerit of technologies to improve agricultural yields, toalternative futures for the data communications industry,to the assessment of human resources in the future.

The FPE has the following features, which in concertmake it a distinctive approach to strategic forecasting andpolicy assessment:

All topics relevant to the subject chosen for investiga-tion are explored, one by one and in context with eachother. An FPE seeks to be comprehensive. Typically,the participants define the organization's mission,objectives, and goals, and. then identify, forecast, andevaluate several issues: (1) the elements of their busi-ness environment, including relevant prospective so-cial, economic, technological, and political develop-ments; (2) the alternatives open to the organization;(3) criteria for deciding among the alternatives vis-a-

vis the organization's mission, objectives, and goals;(4) the degree to which each important alternativesatisfies the criteria; and (5) the dynamic cross-support interrelationships among the preferred alter-natives.No idea is off-limas. As in brainstorming, the firstobjective is to expand the group's sense of the optionsavailable.All participants have a full and equal opportunity toinfluence the outcome at each step. In particular, each


7o

participant evaluates every important issue raisedafter it has been examined in face-to-face discussionby the group.These individual evaluations become the group's re-sponse, but the range of opinion (that is, the uncer-tainty or lack of consensus) is captured and serves asa basis for clarifying differences and sharpening thegroup's final judgment.Thus, the participants typically respond to the opinionof the group, not to the opinions of individuals withinthe group. In this way, team building is enhanced andpersonal confrontations avoided.The FPE is highly systematic, thanks to the use of aninterlocking combination of methods that have provensuccessful in structuring and eliciting judgment. Un-like QUEST, which uses a fixed combination of tech-niques, the mix used in an FPE varies depending onthe subject, the number of participants, and the timeavailable. It can include relevance tree analysis, brain-stormi.. ;, the Delphi technique, subjective trend ex-trapolation, polling, operational gaming, cross-supportand cross-impact analysis, and scenario development.And while such techniques are used in the FPE, theyare not given a particular prominence; they are treateas means, not ends.All judgments on important issues are quantifiedthrough individual votes, usually taken on privateballots. This quantification permits objective compari-sons of the subjective inputs. Anonymous voting en-ables everyone to speak his mind.The judgment of the group as a whole is available toeach participant at the completion of every step of theFPE. These results then become the basis of the nextstep, thus helping to ensure that each part of the prob-lem being addressed is dealt with in a context.The major results of the FPF, are available at the endof the activity, in writing, and each participa.! has acopy of the results to take with him.

The FPE process has three parts. The firstpremeetirdesignis the key. Each FPE requires its own design,the process does not involve a pat formula. The designphase usually requires 10 to IS days, spread over a few

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calendar weeks. During this phase, the problem is struc-tured, needed historical data'are collected, the FPE logic isdefined in detail, and first-cut answers to the more impor-tant questions are obtained through interviews or a ques-tionnaire or both. These preliMinary answers serve as acheck on the FPE design and as a basis for the discussionthat will occur during the FPE itself. Ordinarily, this infor-mation is gathered from a larger group of people than theone that will participate in the FPE.

The final design is usually formulated in two ways: first,as an agenda, which is distributed o the participants, and,second, as a set of written "modules," each describing aspecific task to be completed in the FPE, its purpose, themethods to be used, the anticipated outcomes, and thetime allotted for each step in the task. These modules serveas the basis of the sign-off in the final pre-FPE review.

The second part of the process is the FPE itself. Thenumber of participants can range from as few as seven oreight to as many as 20 to 25. The FPE normally requirestwo to three full days of intensive work, though FPEs Kayerun anywhere from one to 12 days. The period can be con-secutive or be spread out in four-hour blocks over a sched-ule that is convenient to all participants. Typically, theFPE is preceded by a luncheon or dinner meeting and abrief roundtable discussion, which serves to break the iceand helps to clarify expectations about the work to follow.

The FPE can be manual or computer-assisted. D:S,TM,developed by the Policy Analysis Company, uses a stan-dard floppy disk and personal computer, usually connectedto a large-screen monitor or projector (Renfro 1985). Thelarger the group of participants, the greater the desirabilityof using such computer assistance. Not only is the colla-tion of individual votes greatly speeded; in addition, thesoftware developed by some consulting organizations thatprovide the FPE service (for example, the ICS Group andthe Policy Analysis Company) can reveal the basis of dif-ferences among subgroups of the participants and drawcertain inferences that are implied by the data but not read-ily apparent on the basis of the estimates themselves. InD1S,TM, it includes confidence weighting, vote sharing, andvote assignment.

Although the design of the FPE is quite detailed, it isnever rigid. On-the-spot changes are always required dur-


ing the FPE in light of the flow of the group's discussionand the discoveries it makes. But the design makes it pos-sible to know the opportunity costs of these adjustmentsand hence when it is appropriate to rein in the group andreturn to the agenda.

The final part of the process is postmeeting analysis anddocumentation of the results and specification of areasrequiring action or further analysis. Although the principalfindings will be known at the end of the FPE, this post-meeting activity is important because the results will havebeen quantified, and it is necessary to transcend the num-bers and capture in words the reasons for various esti-mates, the basis of irreducible disagreements, and the ar-eas of greatest uncertainty. Additionally, it may benecessary to perform special analyses to distill the fullimplications of these results.

Cross-impact analysisCross-impact analysis is an advanced form of forecastingthat builds upon the results achieved through the varioussubjective and objective methods described in the preced-ing pages. Although as many as 16 distinct types of cross-impact analysis models have been identified (Linstone1983), an idea common to each is that separate and explicitaccount is taken of the causal connections among a set offorecasted developments (perhaps derived by genius fore-casting or Delphi). Among some futures researchers, amodel that includes only the interactions of events is calleda cross-impact model. A model that includes only the in-teractions of events on forecasted trends but not the im-pacts of the events on each other is called a "trend impactanalysis" (TIA) model. In the general case, however,"cross-impact analysis" is increasingly coming to refer tomodels in which event-to-event and event-to-trend impactsare considered simultaneously. Constructing such a modelinvolves estimating how the occurrence of each event inthe set flight affect ("impact") the probability of occur-rence of every other event in the set as well as the nominalforecast of each of the trends. (These nominal trend fore-casts may be derived through mathematical trend extrapo-lation or subjective projections.) When these relationshipshave been specified, it then becomes possible to let events"happen"either randomly in accordance with their esti-

mated probability or in some prearranged wayand thentrace out a distinct, plausible, and internally consistentfuture. Importantly, it also becomes possible to intro-duce policy choices into the model to explore their poten- .

tial value.Development of a cross-impact model and defining the

cross-impact relationships is tedious and demanding. Themost complex model that can be built today (using existingsoftware) can include as many as 100 events and 85 trends.Although they may seem like small numbersafter all,how many truly important problems can be described withreference to only 85 trends and 100 possible "surprise"events?consider the magnitude of the effort required tospecify such a model. First, it is necessary to identifywhere "hits" exist among pairs of events or event-trendpairs. For a model of this size, 18,400 possible cross-impact relationships need to be evaluated (9,900 for theevents on the events and 8,500 for the events on thetrends). This evaluation is done judgmentally, usually by ateam of experts. Experience suggests that hits will befound in about 20 percent of the possible cases, whichmeans that some 3,700 impacts of events on events orevents on trends will need to be described in detail.

How are they described? In the most sophisticatedmodel, seven estimates are required to depict the connec-tion between an event impacting on the probability of an-other event:

1. Length of time from the occurrence of the impactingevent before its effects would be felt first by the im-pacted event;

2. The degree of change in the probability of the im-pacted event at that point when the impacting eventwould have its maximum impact;

3. The length of time from the occurrence of the impact-ing event until this maximum impact (that is, changein probability) would be achieved;

4. The length of time from the occurrence of the impact-ing event that this maximum impact level would en-dure;

5. If the maximum impact might taper off, the change inprobability of the impacted event when its new, stablelevel were reached;


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6. The length of time from the occurrence of the impact-ing event to reach this stable inipact level;

7. A judgment as to whether or not these effects hadbeen taken into account when estimating the probabil-ity of the impacting and impacted events in theDelphi.

Eight cross-impact factors need to he estimated to de-scribe the hit of an event on a trend. The first seven are thesame as those specified above, except that estimates 2 and5 are not for changes in probability but for changes in thenominal forecasted value of the trend. The eighth estimatespecifies whether the changes in the trend values are to bemultiplicative or additive.

In short, if we have 3,700 hits to describe and if, say, 60percent of them (2;220) are impacts of events on eventsand 40 percent (1,480) are of everts on trench , then 27,380judgments must be made to construct the model (that is,2,220 x 7 + 1,480 x 8). With these estimates, plus theinitial forecasts of the probability of the events arid thelevel of the trends, the model is complete. It can then berun to generate an essentially unlimited number of individ-ual futures In one version of cross-impact analysis, devel-oped at the University of Southern California, the modelcan be run so that the human analyst has the opportunityto intervene in the future as it emerges, introducing poli-cie,, that can change the probabilities of the events or thelevel of the trends. This model operates as follows:

1. The time period is divided into annual intervals.2. The cross-impact model computes the probabilities of

.;ccurrences of each of the events in the first year.3. A random number generator is used to decide which

(if any) of the events occurred in the first year. (Itshould perhaps be emphasized that once the esti-mated probability of an event exceeds zero, the eventcan happen. No one may think it will happen, or con-versely everyone may he convinced that it will. If ithappens--or fails to happenthe event is a surprise.In cross-impact analysis, events arc made to "hap-pen" in accordance with their probability; that is, a10 percent event will happen in 10 percent of all fu-tures, a 90 percent event will happen in 90 percent of

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them, and so on. One would be surprised indeed if heor she were betting on a future world in which the 10percent event was expected not to happen but did,and the 90 percent event was expected to happen butdid not.)

4. The results of the simulated first year are used toadjust the probabilities of the remaining events insubsequent years and the trend forecasts for the endof the first year and their projected performance forthe subsequent years.

5. The computer reports these results to the human ana-lysts interacting with the simulation and stops, await-ing additional instructions.

6. The human analysts assume that the simulated time isreal time and assess the result as they think theywould Lad this outcome actually taken place. Theydecide which aspects of their strategy (if any) theywould change and input these changes to the compu-ter model, which then simulates the next year'sresults, using the same procedure described for thefirstyear.

7. The simulation repeats these steps until all of theyears in the strategic time period have been decided(Enzer 1983, p. 80).

When all intervals are complete, one possible long-termfuture is described by modified trend projections over time,the events that occurred and the years in which they oc-curred, a list of the policy changes introduced by the ana-lysts, and the impacts of those policy changes on the re-sulting scenario. The analysts may also prepare a narrativedescribing how they viewed the .simulated conditions andhow effective their policy choices appeared in retrospect.

By repeating the simulation many times, perhaps withdifferent groups of analysts, it is possi'l develop anumber of alternative futures, thereby minimizing surprisewhen the transition is made from the analytic model to thereal world. Perhaps the most important contribution thatthe USC model (or cross-impact methods generally) canmake in improvilig strategic planning, however, is in itscontinued use as the strategic plan is implemented (Enzer1980a, 1980b). The uncertainty capuired in the initialmodel will be subject to change as- .nticipations give way

Futures Resent( h and the Strategic Planning Process 61

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to reality. Such changes may in turn suggest revisions tothe plan.

Models of such complexity are expensive to develop andcurrently can be run only on a large, mainframe computer.For these reasons, their use is warranted only in the mostseriously perplexing and vital situations. A number of lesscomplex microcomputer-based cross-impact models areunder development, however. For example, the Institutefor Future Systems Research, Inc. (Greenwood, SouthCarolina), has developed a cross-impact model that can berun on an Apple He. Although in the alpha stage of devel-opment, this model has the capability of 30 events and 20policies impacting three ti ends.

Much simpler models are commonplace. In essence,they are the same, but the rigorous calculations requiredfor complex models can be approximated manually whilepreserving much of the qualitative value of the results,such as identifying the most important events in a smallset. In the simplified manual calculation, the impact of theevent is multiplied times its probability: A 50 percent prob-able event will have 50 percent of its impact occur, a 75percent event will have 75 percent of its impact occur, andso on. This impact probability is calculated and added orsubtracted, depending on its direction, to the level of theextrapolated trend at point a (see figure 9). The event-impacted forecast for the years from b are determined byconnecting points b and a with the dashed line as shown.This process is repeated for each of the potential surpriseevents until a final expected value of the event-impactedindicator is developed. The event with the highest productof probability and impact is the most important event orthe event having the greatest potential impact on the trend.This simple calculation is the basis of cross-impact analy-sis, though the detail and complexity (not to mention effortand cost) can be much greater in computer simulations.'

Policy impact analysisMost of the techniques of futures research developed in thelast 20 years provide information about futures in whichthe decision makers who have the information are pre-

For a more detailed discussion of this approach, including an examplefrom the held of education, set' Renfro and Morrison 1982,

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.

TREND

FIGURE 9QUALITATIVE EXAMPLE OF AN EVENT-IMPACTED INDICATOR

IMPACT OF EVENT

I

PAST

Source: Renfro and Morrison 1982.

NOW FUTURE

TIME ---.

EXTRAPOLATION


0

sumed not to use it; that is, new decisions and policies arenot included in the futures described by these techniques(Renfro 1980c). The very purpose of this information, how-ever, is to guide decision makers as they adopt policiesdesigned to achieve more desirable futuresto changetheir expected future. In this sense, traditional techniquesof futures research describe futures that happen to thedecision makers, but decision makers use this informationto work toward futures that happen for them. Apart frompolicy-oriented uses of cross-impact analysis, policy im-pact analysis is the first model that focuses on identifyingand evaluating policies, strategies, and decisions designedto respond to information generated by traditional tech-niques of futures research.

The steps involved in policy impact analysis are basedon the results obtained from the probabilistic forecastingprocedure outlined previously. When the events have beenranked according to their importance (their probability-weighted impacts), these results are typically fed back tothe group, panel, or decision makers providing the judg-mental estimates used to generate the forecast. As thisgroup was asked to select and evaluate the surprise events,they are now asked to nominate specific policies thatwould modify the probability and impact of those events.Decision makers may change the forecast of a trend inthree principal ways: first, by implementing policies tochange the probability of one or more of the events thathave been judged to influence the future of the trend; sec-ond, by implementing policies to change the timing, direc-tion, or magnitude of the impact of one or more of theevents; and third, by adopting policies that in effect createnew events. If all or most of the important events affectinga trend have been considered, then new events shouldhave little or no direct impact on the indicator. For someevents, iuch as the return of double-digit inflation, it maynot be possible for the decision makers at one university tochange the events' probability, but it may be possible toaffect the timing and magnitude of their impacts if they didoccur. For example, it may not be possible to affect thepresident's decision to issue a particular executive order,such a:, cutting federal aid to higher education, but its im-pact can be diminished if administrators develop othersources of funding. Usually it is possitle to identify poli-

cies that change both the probability acid the impact ofeach event (Renfro 1980a).

Policies are typically nominated on the basis of theireffect on one particular event. To ensure that primary (orsecondary) impacts on other events do not upset the in-tended effect of the policy, the potential impact of eachpolicy on all events should be reviewed, easily done bythe use of a simple chart like the one shown in figure 10.

Policies can impact the forecasts of an indicator in threeways: through the events, through the events and directlyon the trends, and directly on the trends only. The relation-ship of policies to trends to the indicators might be envi-sioned as shown in figure 1 I. The policies that affect theindicator through events have four avenues of impact. Apolicy can change the probability of an event by making itmore or less likely to occur, or a policy can change theimpact of an event by increasing or changing the level of animpact, changing the timing of an impact, or changing bothlevel and timing of an impact (see figure 12).2

The new estimates of probability and impact are used torecalculate the probabilistic forecasts along the lines out-lined earlier. The difference between the probabilisrc fore-cast and the policy-impacted forecast shows the benefit ofimplementing each of the policies identified. Completedoutput of all of the steps results in three forecasts: the ex-trapolated surprise-free forecast, the probabilistic event-impacted forecast, and the policy-impacted forecast.

To illustrate, suppose that the policy issue being studiedis enrollment in liberal arts baccalaureate programs andthat measurements of those enrollments since 1945 are partof the data base available to a research study team. Fur-ther assume that those enrollments were forecast to de-crease over the next 10 years, although the desired futurewould be one in which they would remain the same orincrease. In this stage of the model, the team would firstidentify those events that could affect enrollments

2if a computer-based routine is used in policy impact analysis, numericalestimates must be developed to describe completely the shape and timingof the impacts. which, for the impact of one event on a trend. may requireas many as eight estimates. These detailed 'mathematical estimatesquickly mushroom into a monumental task that can overwhelm the pa-tience and intellectual capacities of the most dedicated professionals if thetask is not structured and managed to ease the burden. For a discussion ofthe details of the numerical estimates. see Renfro 1980b.

A policy canchange theprobability ofan event bymaking itmore or lesslikely tooccur.


Su

POLICIES

PI

P2

P3

Pn

Source: Renfro 1980b.

FIGURE 10POLICIES-TO-EVENTS MATRIX

EVENTS

El E2 E3 E

4 En

FIGURE 11RELATIONSHIP OF POLICIES TO EVENTS TO TRENDS:

THREE WAYS POLICIES IMPACT TRENDS

InteractionPaths Policies

ThroughEventsOnly

ThroughEvents and

Direct

DirectOnly

P4

PS

P6

Pn


Events Trends

E1

E2

E4

Es

T1

2

T3

T4

Ts

E T6

En Tn

adverselyfor example, a sudden jump in the rate of infla-tion, sharply curtailed federally funded financial aid, asignificant cut in private financial support, and so on. Theteam would also identify events that could positively affectenrollmentsfor example, commercial introduction of low-


82

IMPACT

IMPACT

IMPACT

FIGURE 12IMPACT OF POLICY CHANGES

Original Event Policy - impacted Event

Policy changes level of impact

I '1 IMPACT2 3 4 1 2 3

YEARS YEARS


Policy changes timing of impact

I . i

2 3 4

YEARS

IMPACT

Policy changes both level and timing

2 3 4

YEARS

68

IMPACT

I,

2 3

YEARS

2 3

YEARS

cost, highly sophisticated CAI programs for use on homepersonal computers for mid-career retraining, a new gov-ernment program to help fund the efforts of major corpora-tions to pro v;ie continuing professional education pro-grams for their employees., and so on. Such events maypositively affect enrollments because a widely held as-sumption of liberal arts education is that it facilitates thedevelopment of thinking and communication skills easilytranslatable to a wide variety of requirements for occupa-tional skills.

The next step Would be to identify possible policies thatcould affect those events (or that could affect enrollmentsdirectly). For example, policies could be designed to in-crease enrollments by aggressively pursuing marketingstrategies lauding the value of a liberal arts education asessential preparation for later occupational training. Thisstrategy could be undertaken with secondary school coun-selors and students and with first- and second-year under-graduates and their advisors. Graduate and professional,school faculty could be'encouraged to conside, adoptingand publicly announcing 'admissions policies that grantpreferential consideration to liberal arts graduates. An-other policY could be to form, coalitions with higher educa-tion organizations in other regions to press for increasedfederal aid to students and to institutions. With respect tothe potential market in the business, industrial, and civilservice sectors, policies with respect to establishing jointprograms t I provide liberal arts education on a part-timeor "special" semester basis could be designed and imple-mented.

Policies could also be designed to maintain enrollmentswithin the current student population. For example, onepolicy could concern an "early warning" system to iden-tity liberal arts students who may be just experiencingacademic difficulty. Others could be designed to inhibitattrition by improving the quality of the educational envi-ronment. Such poi; les would involve establishing facultyand instructional development programs and improvingstudent personnel services, among others.

Next, the policies need to be linked formally to theevents they are intended to affect, and their influence canthen be evaluated. (As part of this process it is also impor-tant to look carefully at the cross-impacts among the poll-


34

cies themselves, as several of them may work against eachother.) Re result of this somewhat complex activity is apolicv-impacted forecast for undergraduate baccalaureateprograms, given the implementation of specific policiesdesigned to improve enrollments. Thus, competing policyoptions may he evaluated by identifying those policies withthe most favorable cost-benefit ratio, those having the mostdesirable effect, those with the most acceptable trade' -offs,and so on.

Figure 13 is an example of a complete policy impactanalysis where one may examine the relationship of anorganizational goal for a particular trend, the extrapolative:precast, the probabilistic forecast, and the policy-impacted forecast. Note that the distinction between theprojected forecasts is the result of the difference betweenthe assumptions involved; that is, the extrapolative fore-cast does not include the probable impact of surpriseevents, whereas the probabilistic forecast does. Further-more, the probabilistic forecast includes not only the ef-fects of events on the trend but also the interactive effectsof parto-ular events on the trend. The policy impact fore-cast not only incorporates those features distinguishingprobabilistic forecasts: it also includes estimates of theimpact of policies on events affecting the trend as well ason the trend itself.

Evaluation occurs when the policy impact analysismod,:l is iterated after the preferred policies have beenimplemented in the real world. That is, the process of mon-itoring begins anew, thereby enabling the staff to evaluatethe effectiveness of the policies by comparing actual im-pacts with those forecast. Implementation of this modelrequires that a data base of social/educational indicators beupdated and maintained by the scanning committee to eval-uate the forecasts and policies and to add new trends asthey are identified as being important in improving educa-tion in the future, that new and old events be reevaluated,and that probabilistic forecasts be updated to enable goal,to he refined and reevaluated. This activity leads to thedevelopment of new policies or reevaluated old ones,which in turn enables the staff to update policy impactedl'orecast (Morrison 1981b).1

'The techniques of Futures resear:h described here. particularly the prob-abilistic tolecasting methods. have been developed only within the last 10

FIGURE 13EXAMPLE OF A COMPLETE POLICY IMPACT ANALYSIS

Forecasts:

Goal...0

Policy Impacted

.0# .`-' Extrapolative.....

. Probabilistic

PAST FUTURE

Source; Renfro 1950c.

to 20 years, and they hay. been used primarily in business and industry,with mixed results. The success of this model depends upon the ability ofthe staff to identify those events that may affect a trend directly or indi-rectly, accurately assign subjective probabilities to those events, designand obtain a reliable and valid data base of social /educational indicators,,and specify appropriate factors that depict the interrelationships amongthe events, the trends, and the policies. The efficacy of the policy impactanalysis model depends upon the close interaction of the research stuffand decision makers within each stage of the model.

ratures Research and tlu, Strategic Planning Process

s

71

11

LimmooddwombasmAamorroomma.........

The wenarioA key t.lol of integrative forecasting is the scenarioastory about the future. Many types of scenarios exist !Bou-cher 1984) but in general they are written as a history ofthe future describing uevelopments across a period rangingfrom a few years to a century or more or as a slice of timeat some point in the future. The scenarios as future historyare a more useful tool in planning because they explain thedevelopments along the way that lead to the particularcircumstances found in the final stete in the future.

A good scenario has a number of properties. To he use-ful planning, it should he credible, it should be self-contained (in that it includes the important developmentscentral to the issue being addressed), it shouid he inter-nally consistent. it should he consistent with one's impres-sion of how the world really works, it should clearly iden-tify the events that are pivotal in shaping the futuredescribed. and it should he interesting and readable toensure its use. Scenarios have been used both as launchingdevices to stimulate thinking about the future at the begin-ning of a study and as wrap-ups designed to summarize,integrate, and communicate the many detailed results of aforecasting, study. !'or example, the information generatedin the policy impact analysis process can easily he used togenerate scenat los. A random number generator is used todetermine whicii, events happen and ,heti. This sequenceof events provides the outline of a scenario. With this tech-nique. a wide range of scenarios can quickly be produced.

Frequently. several alternative scenarios arc written,eeh based upon a central theme. For example, in. the1970s many studies on energy resource's focused on threescenarios: (I! an energy-rich scenario, in which continuedtechnological innovations and increased energy productioneliminate energy shortages: (2) a muddling-through sce-nario. in which events remain, e:isentially out of control andno te.Aution of the energy situation is realized; and (3) anenergy-scarce scenario, in whieh we are linable to increaseproduction or to achieve desired love is of conservation.

By creating multiple scenarios. one hopes to gain furtherinsight into not only the potential rznge of demographic.technological, political, social. and economic trends iindevents hug also laity these developments may interact witheach °the', given various chance events and I olicy initia-

Lives. Each scenario deals with a particular sequence ofdevelopments. Of.cottNe. if the scenarios are based on theresults from earlier forecasting, the range of possibilitiesshould already be reasonably well known, and the sce-narios will serve to f,ynthesize this knowledge. If, how-ever, the earlier reseatch has not been lone., then the see-naricE must be m of whole cloth. ins practice is verycommon; indeed, s. .te consulting organizations recom-mend it. Such scenarios can be quite effective, as long asthe user recognizes that the product is actually a form ofgenius forecasting and shares all of the strengths and weak-nesses of that approach.

Slice-of-time scenarios serve to provide a context forplanning indeed, they are similar to the budgeting or en-rollment assumptions that often accompany planning in-structions. Yet instead of single assumptions for each plan-ning parameter, a range of assumptions may be considered.In turn, assumptions for different parameters are woventogether to form internally consistent wholes, each ofwhich forms a particular scenario, and the set may then bedistributed as backgrounkl for a new cycle of planning.

Multiple scenarios communicate to planners that whilethe future is unknowable, it may be anticipated and itspossible forms can surely be better understood. In thelanguage of strategic planning, a plan may be assessedagainst any scenario to test its "robustness." An .ffectiveplan, therefore, is one that recognizes the possibility of anyplausible scenario. For example, in a planning conferencewith the president, the academic vice president might spec-ulate how a particular strategy being proposed would "playitself out" if the future generally followed Scenario I and,then, what would happen given Scenario II. Heydinger hasdeveloped several plausible scenarios for higher education,which, although lacking the specificity requited for actualinstitutional ,.fanning purposes, convey the flavor of a sce-nario (see figure 14).

The analysis of multiple scenarios requires attention to anumber of factors discussed elsewhere in this monographimprobable yet important developn.ents (Heydinger andZentner 1983). Moreover, in developing the scenarios, it ishelpful to recognize that they can be used to describe fu-tures en almost any level of generality, from higher educa-tion on the national level to the outlook for an individtaki

Futures- Resrarch and ilk' Strategic Planning Proem 73

FIGURE 14POSSIBLE SCENARIOS FOR HIGHER EDUCATION

I. The Official FutureEnrollments are down, and while adult and part-time students aremore numerous, their presence has not offset the decline oftraditional-age students. One in 10 state colleges ha!, closed in thelast seven years, and 25 percent of liberal arts colleges haveclosed since 1980. With the supply of traditional college-age stu-dents resurging, however, a mood of optimism is returning tocampuses.

Industry establishes its own training facilities at an unheard-ofpace and competes with higher education for the best postgradu-ate students.

In high-tech areas, cooperative research arrangements withindustry are commonplace. Most campuses now find that aca-demic departments divide into the "haves' (technology-relatedareas) and "have-nots" (humanities and sociai sciences I.

2. 'fooling and RetoolingWith job skills changing at tin ever quickening pace. individualsnow make several career changes in a Iii-etime. and college is stillconsidered the hest place for training. Nationwide enrollment hasthus fallen only 1.5 percent.

Students are more serious ah "ut their studies. Passive accept-ance of poor teaching is a r of the past and lawsuits by stu-dents are commo .Motif view that the professor is some-how superior to tht, student (left over from the days of in locoparentis) is gone. As students focus almost exclusively on jobskills, faculty who pri,t.e the liberal arts become a minority.

3. Youth Reject SchoolingThe plummeting ceonomy makes structural unemployment a

department. In addition, agreement on a -time horizon- isnecessary Because many colleges and universities dependheavily on enrollment for income. the time horizon mighthe IS years a foreseeable horizon with regard to 1:011egeattendance rates, si Ills' demographic characteristics,and composition of the faculty.

Scenario developmedt is essentilly a proce's of select-ing from the total environment those external and internalelements most relevant to the purpose of the strategic plan.This process migin well embrace information on dim-

reality. With fewer job openings that require a college degree, allbut the most elite youth reject formal schooling. Most youngpeople, weaned on fast-paced information with instant kedback,come to find college teaching methods archaic.

Student bodies are smaller and more homogeneous, com-prised mainly of those who can afford the high cost or istsec-ondary education. A spirit of elitism grows on campus. Amongfaculty, the .flood is one of "minding the sore" while waitilbgfor better days.

4. Long-Trrm Malaiserhe long-aweed enrollment decline hits, with full force, and theadvent of lifelong learning never materializes. The slumpingeconomy forces the states to make deeper funding cuts and closesome public campuses.

Faculty attention is focused on fighting closure, and little discus-sion of programmatic change is evident. Feeling themselves underincreasing pressure, many of the best faculty flee the academy.Higher education becomes a shrunken image of its former Y:lf.

S. A New Industry is BornHigh technology creates a burgeoning demand for job skills. Tomeet the new challenge, some professional schools break awayfrom their parent university to set up independent institutions.Private corporations establish larger training programs. Evenindividuals now hang out a shingle and offer educational training.Amid this explosion of new educational forms, the traditionalresearch university breaks down. Community colleges flourish asthey adapt to the new needs of the educational market.

Source: Richard Heydinger, cited in Administrator 3 ( 1): 2-3.

graphic characteristics of students, legislative appropria-tions, research contracts, the health of the economy, pub-lic opinion (about the value of a college degree, forexample), developments in the field of information proc-essing and telecommunications, and so on.

Furthermore, assumptions about the behavior of a par-ticular variable in a particular scenario must be explicated.Thy:;, if the size and composition of the 18- to 20year-oldcohort were the variable under consideration, differentassumptions might be developed vis-a-vis college attend-

Futures Research and the Stratexic Planning Process 75

U

76

mice rates. One scenario, for example, might assume thatin 1995 the number of students in attendance would he thesame as in 1983 but that the number of students in the 25--to 45-year-old group would equal the number of students inthe 18- to 24-year-old group. An alternative scenario mightassume that the number of students would increase by 1995and that most of them would he third-generation studentsin the 18- to 2I-year-old group. Similar assumptions mustbe developed for each variable included in the scenario.

Explicating these assumptions is the most important partof creating scenarios and can require a good deal of nriorresearch or, in the case of genius forecast scenarios, greatexperience, knowledge, and imagination. Once the as-sumptions are established, however, the nature of eachscenario is established. Accordingly, to ensure that theyare credible within the institution, it may be worthwhile toreview them with local experts. For example, for key fac-tors concerning students, the admissions office might beconsulted. For economic variables, the economics depart-ment should be consulted. Such consulu., ails are likelynot only to improve the quality of the final products butalso to build "ownership" into the scenarios, thereby en-hancing the chances that they will be considered reason-able possibilities throughout the institution.

In addition to their other advantages, multiple scenariosforce those involved in planning to put aside personal per-spectives and to consider the possibility of other futurespredicated on value sets that may not otherwise be articu-lated. Grappling with different scenarios also compels theu.,er to deal explicitly with the cause-and-effect relation-ships of selected events and trends. Thus. multiple sce-narios give a primary role to human judgment, the mostuseful and least well used factor in the planning process.Scenarios therefore provide a useful coiuf.xt in which plan-ning discussions may take place and provide those withinthe college or university a shared frame of refetcnce con-cerning the future.'

See ilevdinger and ientlicr (1984) for a min.!: complete discussion ofmultiple scenario drit6sis: see also Boucher and Ralston (1984) andIlawken. Ogilvy. and Selmartr t 19811 for a more detailed discus,,ion ofthe types and uses of scenarios.

Goal SettingSome years ago, in what was apparently the first seriousattempt to understand the range and severity of difficultiesthat face long-range planners, UCLA's George Steinersurveyed real-world experiences in U.S. corporations(Steiner 1972). Steiner's questionnaire, which was com-pleted by 215 executives in large corporations (typically,long-range planners themselves), presented a list of 50possible planning pitfalls, invited the respondents to sug-gest others, and then asked three basic questions for each:(1) How would you rank the pitfalls by importance? (2)Has your own corporation recently fallen into any of thepitfalls, partly or completely? (3) If it has, how great animpact has the pitfall had on the effectiveness of long-rangeplanning in your company?

Steiner used the answers from the first questiona moreor less global assessment of the influence of the pitfalls onlong-range planningto rank order the items. He did not,however, exploit the much more interesting informationabout actual experience revealed by the answers to thesecond and third questions. Fortunately, he published theraw data in an appendix. An analysis of those data pro-duces a very different picture of the obstacles to effectiveplanning than does his rank-ordered list. If, for example,one looks for the pitfalls that the largest percentage ofcompanies confess they have recently encountered,"partly" or "completely," the top 10 items are thoseshown in figure 15. This list is most instructive for plannersin all types of organizations, including educational institu-tions, but seven of these 10 items did not appear anywhereamong Steiner's top 10!

Far more significant, however, are the results from thethird question, which asked the impact of the pitfalls on theeffectiveness of the organization's long-range planning.After all, some mistakes or barriers are more serious thanothers. If one ranks all of the pitfalls on the basis of thefrequency with which real -world planners cited them ashaving great negative impacts on their effectiveness, an-other list of the top items emerges (see figure 16). Again,the list is different from Steiner's, but this time five of hiscandidates appear.

The results for pitfall 28 clearly underscore the impor-tance of appropriate goal setting in an organization. Not

Futures Res, arch anti die Strategic' Planning Process 77

92

FIGURE 15THE TEN PLANNING PITFALLS MOST COMMONLY FALLENINTO BY THE LARGEST PERCENTAGE OF CORPORATIONS:

RESULTS FROM A SURVEY

PitfallNumber Pitfall

49 Failing to encourage managers to do good long-rangeplanning by basing rewards solely on short-range per-formance measures.

16 Failing to make sure that top management and majorline officers really understand the nature of long-rangeplanning and what it will accomplish for them and thecompany.

24 Becoming so engrossed in current problems that topmanagement spend :.,sufficient time on long-rangeplanning, and the process becomes discredited amongother managers aid staff.

47 Failing to use plans as standards for measuring man-'agers' performance.

31 Failing to make realistic plans (as the result, for exam-ple, of overoptimism and/or overcautiousness).

50 Failing to exploit the fact that formal planning is a mana-gerial process that can be used to improve managers'capabilities throughout a company.

10 Failing to develop a clear understanding of the long-range planning procedure before the process is actuallyundertaken.

Failing to develop company goals suitable as a basis forformulating long-range plans.

37 Doing long-range planning periodically and forgetting itbetween cycles.

39 Failing, on the part of top management and/or the plan-ning staff, to give departments and divisions sufficientinformation and guidance (for example, top manage-ments interests, environmental projections, etc.).

Source: Steiner 1972.

7ti

Percentage ofCorporations Rank

82 1

78 2-4

/8 2-4

78 2-4

74 5

71 6

69

67 8

65 9-10

65 9-10

FIGURE 16THE ELEVEN PLANNING PITFALLS WITH GREATEST IMPACT

ON THE EFFECTIVENESS OF CORPORATE LONG-RANGE PLANNING:RESULTS FROM A SURVEY

PitfallNumber Pitfall

28 Failing to develop company goals suitable as a basis forformulating long-range plans.

42 Failing, by top management, to review with departmentand division heads the long-range plans they have devel-oped.

24 Becoming so engrossed in current problems that topmanagement spends insufficient time on long-rangeplanning, and the process becomes discredited amongother managers and staff.

45 Top management's consistently rejecting the formalplanning mechanism by making intuitive decisions thatconflict with formal plans.

38 Failing to develop planning capabilities in major operat-ing units.

7 Thinking that a successful corporate plan can be movedfrom one company to another without change and withequal success.

3 Rejecting formal planning because the s:/.}tem failed inthe past to foresee a criticki problem and/or did notresult in substantive decisions that satisfied top manage-ment.

49 Failing to encourage managers to do good long-rangeplanning by basing rewards solely on short-range per-formance measures.

I Assuming that top management can delegate the plan-ning function to a planner.

23 Assuming that long-range planning is only strategicplanning, or just planning for a major product, or simplylooking ahead at likely development of a present product(that is, failing to see that comprehensive planning is anintegrated managerial system).

32 Extrapolating rather than rethinking the entire processin each cycle (that is, if plans are made for 1971 through1975, adding 1976 in the 1972 cycle rather than redoingall plans from 1972 to 1975).

Source: Steiner 1972.

Percentage An-swering "Much" Rank

43 1-2

43 1-2

40 3

37 4

36 5

35 6

34 7

34 8

33 9-11

33 9-11

33 9-11


J4

only is failure to do it well one of the most frequently en-countered harriers to long-range planning (as indicated infigure 15); it also surfaces at the top of the list of pitfallsthat can most debilitate comprehensive planning (as shownin figure 16). Moreover, this finding has a certain face va-lidity, for even if' an organization has a good idea of what itwants to be (if, that is, it has what is known in strategicplanning as a good "mission statement"), it is exceedinglyimprobable that its forecasting and planning will be fruitfulin the absence of clear, actionable statements about how itwill know it' it is getting there, Such statements are vari-ously called "goals" or "objectives."

Some confusion surrounds these terms in the planningliterature. Most authors assert that objectives are moregeneral than goal statements, that objectives are long rangewhile goals are short range, that objectives are nonquanti-tative ("to provide students with a thorough grounding inthe humanities") while goals are quantitative ("to requireeach student to complete two years of instruction in En-glish, philosophy, and ! ory"), that objectives are "time-less" statements t provide quality education that prop-erly equips each student for his chosen career") whilegoals are "time-pegged" ("to implement a program of edu-cation, career counseling, and placement by 1989 such thatat least 60 percent of graduates find employment for whichthey are qualified by virtue of their education at this insti-tution"), and so on. But other authors argue other posi-tions. This problem of vocabulary is in large part one ofhierarchies or levels of discourse. as one person's objec-tive can obviously he another person's goal (see Granger1964 or Kastens 1976, chap, 9). For purposes of this paper,the terms are used interchangeably to mean simply a broadbut nonplatitudinous statement of a fundamental intentionor aspiration for an organization, consistent with its mis-sion. Metaphorically, a goal or objective in this sense islike a trend around which the actual performance of theinstitution is expected to fluctuate as closely as possible.

The purpose of goals is to provide discipline. More spe-cifically, the "objectives for having objectives" include:

To ensure unanimity of purpose with the organization.provide a bask for the motivation of the organiza-

tion's resource,.

To develop a basis or standard for allocating an organi-zation's resources.

, To establish a general tone or organizational climate,for example, to suggest a businesslike operation.To serve as a focal point for those who can identifywith the organization'S purpose and direction and asan explication to deter those who cannot from partici-pating further in the organization's activities.To facilitate the translation of objectives and goalsinto a work-breakdown structure involving the assign-ment of tasks to responsible elements within the orga-nization.To provide a specification of organizational purposesand the translation of these purposes into goals (thatis, lower-level objectives) in such a way that the cost,time, and performance parameters of the organiza-tion's activities can be assessed and controlled (Kingand Cleland 1978, p. 124).

The last two purposes lead especially to management con-trol systems, such as the Planning-Programming-Budgetingsystem, Zero-Based Budgeting, and Management by Ob-jectives.

To these ends, goals are necessary for every formalstructure within an organization, inciuding temporary taskforces. If, for example, futures research itself is recognizedas a distinct function, the failure to specify goals ade-quately can lead the futures researcher to assume that hisor her domain includes all possible future states of affairs.But the job then becomes futile; all too often the planner isreduced to rummaging in the future, looking willy-nilly forthe hitherto.unanticipated but "relevant" possibility (Bou-cher 1978)

Steiner's surprise that pitfall 28 ranked so high on thelist of dangerous pitfalls prompted his asking several re-spondents why they had given it such prominence. Theiranswers clarify some of the attributes of an "unsuit-able" goal:

It is too vague to be implemented ("optimize profits"or "establish the best faculty").It is excessively optimistic. For example, an educa-tional iistitution with a total annual budget of $10


5i 6

million would be deluding itself if it sought to "estab-lish the nation's 'premier faculty in physics."It is clear enough to those on the top level who formu-lated it, but it provides "insufficient guidance" tothose on lower levels.Finally, it simply has not been formulated. For exam-ple, top management has recognized the need to de-velop goals for lower levels and lower levels wouldclearly welcome them, but management has not yetbecn able to specify goals.

How are goals or objectives developed? The short an-swer is that because they are about the future, they must atbottom he subjective and judgmental. In many organiza-tions, especially small ones. no formal process is requiredto capture these judgments: The ultimate goals, at least,are the articulated or unarticulated convictions of thefounder or top executives about how the organization islikely to look it' everyone works intelligently to achieve themission in the years ahead. The absence of a formal goal-setting process need not mean that the organization is do-ing something wrong. Indeed, for some of the largest andbest-run firms in corporate America, it would appear thatthe presence or absence of such a process apparently doesnot matter greatly; what matters more is that a vision isshare -A ind is regularly reinforced by the key peoplethrough direct, persistent contact with everyone else. Forthese companies, this process is a part of what has beencalled "Management by Wandering Around"to discoverwhat employees, customers, suppliers, investors, andother stake holders actually think about the organizationand its products or services (Peters 1983). By reinforcing avision through such contacts, these companies are able toadjust their behavior by comparing their mission, goals,and interim performance toward those goals and thenshucking subgoals that arc blocking the performancethey seek.

No educational institution, to our kn )wledge, practicesManagement by Wandering Around. Educational plannersam' policy makers are more likely to use a formal processfor setting goals of some sort, particularly those recom-mended by business schools for use in strategic planning.The many models available (Granger 1964; Hughes 1965;

82

King and Cleland 1978; Steiner 1969a) tend to be badmodels in at least one respect: Alm )st without exceptionthey fail to recognize the contribution that futures researchitself can make to the process of setting goals. The ten-dency in the literatureand hence in practiceis to sug-gest that one should, of course, look ahead at the organiza-tion's alternative external and internal environments, buthaving done that job, one should then proceed to other,more or less independent things, such as setting goals. Butfutures research can contribute much to this activity, and itcan make this contribution directly. Indeed, when futuresresearch is operating in the normative mode, goals or ob-jectives may be its principal output.

The key to exploiting this source of information is forthe organization to explicitly establish the preliminarystatement of goals as one of the goals of its futures re-search. We can make this notion more tangible by a simpleexample. King and Cleland (1978, p. 148 ff.), among others,recommend a process of goal setting that is based largelyon "claimant analysis." In that procedure, each of theorganization's claimants, or stake holders, is identifiedfor a public university or college, for example, they mightinclude the trustees, the faculty, other employees, the stu-dents, government on all levels, vendors of one sort oranother, competing universities, alumni, the local commu-nity, and the general publicand each group's principal"claims" on the organization listed. The claims of stu-dents, for example, might include obtaining a quality edu-cation, varied extracurricular opportunities, contact withfaculty, a good library and computer center, nonbureau-cratic administrative support services, and so on. Then, foreach such claim, a numerical measure is devek,ped,whether direct or indirect. Although the measures willoften be difficult to specify, especially in an enterprise assoft as education, the effort should be made. (For example,the quality of education at an institution can be measuredin a variety of indirect ways, from counting the number ofapplications or the number of dropouts to summing thescores on teacher rating sheets, to tracking the results ofoutside evaluations of the institution's own schools or de-partments, to measuring the socioeconomic status ofalumni.) Finally, past and current levels of these measuresare compared to discern whether the institution has been

Futures Research aml the Strategic Planning Process 83

moving toward fulfilling each claimant's proper expecta-tions. When it has not, the institution has found a newobjective. When it has. the current objective has beensustained or rejustified.

This processwhatever its meritscould be strength-ened considerably through futures research. If we knowwho our claimants have been and are now, it is immedi-ately relevant to ask how the nature and mix of claimantsmight change in the futureor how it should he made tochange. The same is true for the claims they might make.By the same token, having measures of their claims, it isclearly worthwhile to project these.measures into the fu-ture, perhaps using a technique like Delphi, to see whatsurprises may lie ahead, including conflicts among fore-casted measures. With projections of the measures, it isreadily possible to ask about the forces that might upsetthese projections, using a method like cross-impact analy-sis. Having these results makes it possible to explore thepotential efficacy of alternative strategies. Discovering howthese strategies might work can then he the source of in-sight into the need for new or revised goalsgoals that notonly are responsive to present conditions but also arelikely to provide useful guidance as the future emerges.And all of these considerations could then easily hewrapped up in a small set of scenarios (or planning as-sumptions), which could serve as a framework for the de-velopment of future strategic and operational plans.

ImplementationForecasting and goal setting work together to define twoalternative futures: the expected future and the desiredfuture. The expected future is one that assumes that thingscontinue as they area It is the "hands -off" future, in whichdecision makers do not use their newly acquired informa-tion about the future to change it. The desired future is the"hands-on" one, and it assumes that whatever the decisionmakers decide to do works and works well. In stable envi-ronments, the two worlds are the same for complacentadministrators. But where stability is vanishing and com-placency is much too dangerous (as seems to he the case ineducation today), management must lead in taking a finalactive step in the strategic planning process: to establish

9

the policies, programs, ank; plans to move tne organizationfrom the expected future to the desired future.

If forecasting and goal setting have been done rigorouslyand professionally, much of the information needed toaccomplish this stage is already identified. A completeforecast contains the structure. framework. and context inwhich it was produced so as to enable the user to identifyappropriate policy responses (De Jouvenel 1967). whichcan then be implemented. Bardach (1977), Nakamura andSmallwood (1980), Pressman and Wildaysky (1973), andWilliams and Elmore (1976) include excellent discussionsof this type

MonitoringMonitoring is an integral part of environmental scanningand of strategic planning. Although the specific functionsof monitoring are different. in the two processes, they servethe same purposesto renew the process cycle.

In many planning models, monitoring constitutes one ofthe first steps, for it is in this step that areas of study areidentified and the indicators descriptive of those areas se-lected. These indicators are then prepared for analysisthrough the development of a data bank, which can then heused to display trend lines showing the history of the indi-cators. For example. if enrollments are the area of con-cern, it is important to select indicators that have histori-cally shown important enrollment patternsiand can heexpected to do so in the future. That is, one would collectdata containing information about entering students (sex.race, age, aptitude scores. major, high school. and rank inthe school's graduating class) and perhaps ow these stu-dents fared while enrolled (grade point aver ge. graduationpattern, and so on). Furthermore, one might select infor-mation concerning characteristics of entering college stu-dents in similar institutions or nationally iil all institutionsso that entering students at one's own institution could hecompared with others. Such comparisons are readily avail-able through data gathered by the Cooperative InstitutionalResearch Program, an annual survey of new college fresh-men conducted by UCLA and the American Council onEducation (Actin et al. 1984) and available directly fromACE or from the National Center for Education Statistic,

Futures Research and the .S.tralegir l'roce.ss

MM.Forecastingand goalsetting worktogether todefine twoalternativefutures: theexpectedfuture and thedesired future.

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In this first role of monitoring, historical information isdeveloped and prepared for analysis. This role dependsupon the identification of selected areas for study. In themodel described here, the areas for study would he devel-oped around the issues identified from environmental scan-ning and rated as important during evaiiratioth-Monitoringbegins its initial cycle at this point in strategic planning.That is, indicaicA that describe these prioritized issues areselected and prepared for analysis during forecasting.

A number'of criteria determine the selection of variablesin this cycle. For r .mple, does the trend describe a his-torical development related to the issue of concern? Is thetrend or variable expected to describe future develop-ments? Are the historical data readily available? Gatheringdata is expensive, and novel sources of data will introduceerrors until new procedures are standardized and under-stood by those supplying the data.

A primary consideration involves the reliability and ac-curacy of the data. Several writers have dealt thoroughlywith criteria for developing and assessing reliable and validhistorical data (see, for example, Adams, HawkinS, andSchroeder 1978 and Halstead 1974), but information con-tained in variables derived from the data must belndepen-dent of other factors that would tend to mislead the analy-sis. For example, if the issue concerns educational costs, isthis measurement independent of inflation?.

Finally, history must be sufficient so that the data coverthe cycle needed for projections; for example, ifone isprojecting over 10 years, are 10 years of historical dataavailable on that trend?

The second role of monitoring begins after decisionmakers have developed goals and alternative strategies toreach those goals and have implemented a.specific programto implement policies and strategies to move toward thegoals. That is, new data in the area of concern are addedfor analysis so that managers can determine whether theorganization is beginning to move toward its desired futureor is continuing to move toward the expected future. Forexample, if the strategies discussed during implementationto increase liberal arts enrollment were employed, the sec-ond cycle of the monitoring stage would involve collectingdata on enrollments and comparing "new" data to "old"data. Thus, in effect, monitoring is the stage where the

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effects of programs, policies, and strategies are estimated.The' information thus obtained is again used during fore-casting. In this fashion, the planning cycle is iterated.

For the environmental scanning model, the specific tech-niques of monitoring are a function of where an issue is inthe development cycle of issues. For some issues, it maybe useful to apply some concepts from the emerging fieldof issues management.' The issues development cycleshown in figure 17 foCuses on how issues move from theearliest stages of changing values and emerging socialtrends through the legislative process to the final stages offederal regulations (Renfro 1982). This model is used tounderstand the relative development stages of issues and toforecast their likely course of developments. Thus, one cansee, for example, how the publication of Rachel Carson'sSilent Spring led to a social awakening of the problems ofenvironmental pollution, which eventually culminated inthe formation of the Environmental Protection Agency in1970. Similarly, Betty Friedan's The Feminine Mystiquehelped to organize and stimulate the emerging social con-sciousness of the women's movement.

Championing issues through publications is not a newphenomenon. Upton Sinclair used the technique at the turnof the century to alert the country to the issue of foodsafety in Chicago's meat packing houses with The Jungle.Richard Henry Dana used it in Two Years before the Mast,published in 1847, to alert the country to the plight of sea-men, whose lives were in many ways similar to those ofslaves. Thomas Paine's revolutionary pamphlet, CommonSense, may be the earliest use of the technique in thiscountry.

Other key stages in the development of public issues area defining event, recognition of the name of a national is-sue, and the formation of a group to campaign about theif sue. The early stages have no particular order, but eachhas been essential for dealing with most recent public is-sues. For example, the nuclear power issue had everythingexcept a defining event to put it into focus until Three MileIsland. Usually the defining event also gives the issue its

5The Issues Management Association was first conceived in 1982 andformally established in 1983 with over 4(X) members. The major conceptsand methods of issues management are still in the experimnial and devel-opmental stages.

Futures Research and the' .Strategic Planning Process 87

102

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name--Love Canal, the DC-10, the Pinto. Of course, allevents do not make it through these stages, and manyifnot most--are stopped somewhere along the way.

In addition to these general requirements for the devel-opment of an issue several specific additional criteria areneeded to achieve recognition by the media: suddenness,clarity, confirmation of preexisting opinions or stereotypes,tragedy or loss, sympathetic persons. randomness, abilityto serve to illustrate related or larger issues, the arroganceof powerful institutions for the little guy, good opportuni-ties for photos, and articulate, involved spokesmen. Issuesthat eventually appear in the national media usually havehistories in the regional and local media, where many ofthe same factors operate (Naisbitt 1982).

At this stage, an issue is or already has been recognizedby Congressrecognition being defined by the introduc-tion of at least one bill specifically addressing the issue.Now the issue must compete with many others for priorityon the congressional agenda.

For those issues legislated by Congress and signed intolaw by the president, the regulatory process begins. Thebasic guidelines for writing new rules are the Administra-tive Procedures Act (APA) and Executive Order 12291,which require streamlined regulatory procedures, specialregulatory impact analyses, and plain language. After thevarious notices in the Federal Register, proposed rules,and official public participation, the regulations may gointo effect. This process usually takes three to 10 or moreyears, making the evolving regulatory environment rela-tively easy to anticipate using this model and a legislativetracking and forecasting service like Legiscan® or Con-gresScanTm or following developments in the Congres-sional Record.

This model of the national public issues process is ofcourse continuously evolving. The early stages haveshifted from national issues with a single focus to nationalissues with many local, state, or regional focusesas thedrun4 driving, child abuse, spouse abuse, and similar is-sues demonstrate. The legislative/regulatory process hasalso been evolving. First, many of the regulations them-selves became an issue, especially those dealing with hori-zontal, social regulation rather than vertical, economicregulation. Regulatiors for the Clean Air Act, the Equal


1 0 4

Employment Opportunity Commission, the Clean WaterAct, the Occupational Safety and Health Administration,the Environmental Protection Agency, and the FederalTrade Commission, among others, have all defined newissues and stimulated the formation of new issue groups,which, like the original issue group, came to Congress forrelief. Thus, Congress now is deeply involved in relegisla-tion between organized, opposing issue groupsa slow,arduous process with few victories and no heroes.

With Congress stuck in relegislation at such a detailedlevel so as to itself redraft federal regalations, new issuesare not moving through Congress. As a result, the list ofpublic issues pending in Congress witheY. resolution con-tinues to grow. Frustrated with congressional delays, issuegroups are turning to other forumsthe courts, the states,and, directly to the regulatory agencies. No doubt the proc-ess of recycling issues seen by Congress will emerge hereeventually (see figure 18).

The emergence of the states as a major forum for ad-dressing national public issues is not related to new feder-alism, which is a fundamentally intergovernmental issue.States are taking the lead on a wide range of ism., that adecade ago would have been resolved by Congress .thetransportation and disposal of hazardous wastes, the rightof privacy, the right of workers to know about carcinogensin their work environment, counterfeit drugs, Agent Or-ange, and noise pollution. The process of anticipating is-sues among the states requires another model, one focusednot on the development of issues across time but acrossstates. In most states, legislators do not have the resourcesor the experience to draft complicated legislation on majorpublic issues. Moreover, issues tend to be addressed ordropped within one session of the legislative body, andsuch a hit-or-miss process is almost impossible to forecast.Thus, the legislative ideas from the first state to address anissue are likely to become de facto the national standardfor legislation among the other states. The National Con-ference of State Legislators and the Council of State Gov-ernments encourage this cribbing from one state to an-other, even publishing an annual volume of "SuggestedState Legislation." A state legislator need only write in hisor her state's name to introduce a bill on a major publicissue. The process of forecasting legislative issues across

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the states then involves tracking the number of states thathave introduced bills on the issue and the states that havepassed or rejected those bills. While the particular lan-guage and detailed implementation policies will of coursevary from state to state, this model is reasonably descrip-tive of the process and represents the current state of theart (Henton, Chmura, and Renfro 1984)

Like the model of the national legislative process, thismodel has been refined several times. Some states tend tolead on some particular issues. While it was once theorizedthat generic pre:ursor states exist, this concept has beenfound to be too crude to be useful today. On particularissues, the concept still has some value, however. Oregon,for example, tends to lead on environmental issues; itpassed the first bottle bill more than 10 years ago. Califor-nia and New York lead on issues of taxes, governmentalprocedures, and administration. Florida leads on the issuesof right of privacy.

The piggy-backing of issues is also important. Twenty -

two states have passed legislation defining the cessation ofbrain activity as deqth. The issue is an important moral andreligious one but without substantial impact on itsown.Seven states have, however, followed this concept with theconcept of a "living will"; that is, a person may authorizethe suspension of further medical assistance when braindeath is recognized. This piggy-backed issue has tremen-dous importance for medical costs, social security, estateplanning, nursing homes, and so on.

A state forecasting model would be incomplete withoutanother phenomenon, policy cruss-over. Occasionally afteran issue has been through the entire legislative process, thelegislative policy being implemented is reapplied to anotherrelated issue without repeating the entire process. Theconcept of providing minimum electric service to the poor,the elderly, and shut-ins took years to implement, but theconcept was reapplied to telephone service in a matter ofmonths. And telephone companies did not foresee the de-velopment.

The monitoring stage of the strategic planning processtherefore involves tracking not only those variables oftraditional interest to long-range planners in higher educa-tion (enrollment patterns, for example) but also issues

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identified through environmental scanning. Moreover, byidentifying issues as to where they are in the developmentcycle of issues, more information is introduced for itera-tion in the planning process.


11Th

DEVELOPING A STRATEGIC PLANNING CAPABILITY

While the link between environmental scanning and long-range planning is conceptually straightforward, using bothwithin an organization can be complex and confusing, atleast initially. This chapter addresses the issues associatedwith developing a strategic planning process within anexisting organization, emphasizing the connection betweenthe scanning function, forecasting/futures researchmethods, goal setting. implementation, and monitoring.While organizational change can be accomplished from thetop down, creating a new function and/or department isoften expensive, di4ruptive, and difficult. More often, suc-cessful organizational change is accomplished by moreevolutionary processes, in which the new function and/ordepartment grows into being over some period. The proc-ess outlined here is focused on this evolutionary growth.

Eany Stagesstrategic planning begins with the selection of 3 panningmodel (the one discussed in The Strategic PL. ,.ing Proc-ess" or another in the wide range of scanning nd long-range planning models available for selection) Some of thefactors to be considered in the selection of a model of stra-tegic planning include the formality of the model, the re-sources available within the institution, the size of the in-stitution, available staff and professional resources, andplanning requirements imposed on the institution by theexternal world. The purpose of the model is to providestrategic planning with a structure, a context, and a time-table for producing the plan itself.

An important axiom to remember is that perhaps one ofthe least important products of the planning process is theplans. Although an obvious overstatement, it serves tounderscore the point that the planning process is an ongo-ing, continuously changing, organic activity. A corollary ofthe axiom is the perversion of the political axiom, "Planearly and often." The jokes about planned economies stemfrom the idea that we will today do a 10-year plan and 10years from row will still be locked into the same plan.Properly understood, however, the strategic planning proc-ess creates 10 to 20 or more visions of the interesting fu-ture every year. No outr it of the planning process is everfixed if its basic assumptions are disrupted.

The strategicplanningprocesscreates 10 to20 or morevisions of theinterestingfuture everyyear.


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The strategic planning process model has two basiccomponentsthe external perspective and the internalperspective. As the intersection of these cycles suggests,the two perspectives overlap, requiring some activities ineach to be carried forward concurrently. As most collegesand universities traditionally have had an internal perspec-tive in their long-range planning function, the discussion inthe following paragraphs begins with a focus on the exter-nal perspective with the intent of merging it with the inter-nal perspective.

An excellent starting place for building an external per-spective for an organization is surveying decision makerswithin the institution to determine several key points: theirviews of the organizatioi's mission and clientele served,emerging issues in the external world that may affect theirresponses to the first question, and the kinds of resourcesthey use to stay in touch with this world. A series of infor-mal interviews, which might run 60 to 90 minutes, couldaccomplish the purpose: Five to 10 decision makers fromthroughout the institution would be asked to suggestemerging issues of which they are aware and that theybelieve the institution has not yet begun to address. Therequest will usually result in five to 10 ideas from eachindividual interviewed, or from 20 to 30 separate emergingissues potentially important to the future of the institution.Most of the information thus gathered will not be "known"to all those at the institution because of territorial bounda-ries, crush of daily responsibilities, and immediate fire-fighting requirements. For example, the dean of studentaffairs may know of an emerging issue in the area of gov-ernment regulations but have no authority, resources, orincentive to respond or to contact those who doif theyare known,

The second question from this first round of interviewsfocuses on a survey of the resources administrators use tostay in touch with the external world. The purpose of thissurvey is to develop a profile of the information resourcesthe senior leadership of the institution currently use to stayin touch with current or emerging issues. Typical results ofthis survey would show that the information base isnarrowthat virtually everyone reads the same thing andthat few senior administrators read Ms., Working Woman,Ebony, Mother Jones, or The Futurist.

In a second round of interviews, the first questionchanges from identifying the issues to determining howimportant they are and how likely they are to affect theinstitution. A simple probability-impact chart could beused for this question. With those issues where there issufficient consensus, 'the probability and the impact aremultiplied together and the weighted importance therebydetermined. The consensus issues are then ranked accord-ing to their weighted importance, both positive and nega-tive. The issues for which consensus on either probabilityor impact is insufficient require additional rounds of discus-sion and evaluation.

The second question in the process focuses on modifyingthe resources managers use to stay in touch with the exter-nal world. This step takes the form of a simple question-naire that shows the resources currently :,canned and fo-cuses on what additional resources someone in the insti-tution should be reviewing to monitor a particular issue.

The results of this process are not only the improvedprofile of information resources it, be used in the organiza-tion and a rank-ordered iist of emerging issues but also agrowing familiarity within the orgatticati;r. of the conceptof environmental scanning. While most organizations resistchange imposed on them to some degree, they are lesslikely to resistor may even seekchange resulting fromtheir own initiative. The evolutionary, open process ofconsulting the major decision makers .vithin the institutionthat systematically produces understandable qualitativeand quantitative results provides a most successful way ofintroducing the idea of environmental scanning in the orga-nization.

The substantive results of the issues evaluationthat is,a rank-ordered list of important emerging issuesprovidethe basis for the planning assumptions of the external envi-ronment for the forecasting stage in the internal perspec-tive. This stage in the process is where the two perspec-tives first intercept. A simple procedure for evaluating theinteraction of these external events on the internal fore-casting is an impact chart with the various trends beingforecasted for the internal perspective on the vertical axisand the various emerging issues on the horizontal axis.This matrix can be incorporated in a Delphi questionnairefor evaluation by the panel of respondents used in the pre-


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ceding steps. The question at this point is, on a scale ofone to ten, how important each emerging is,ue is to eachone of the components being forecasted for the internalperspective. For example, the trends from the internalperspective might include the number of students, the en-rollment mix (science versus liberal arts), labor costs, me-dian faculty salary, percentage of graduate students, per-centage of federal aid to the institution, and so on. AT&Tbefore its breakup, for 'example, produced a set of environ-mental planning assumptions for use by its member tele-phone companies in their internal planning. While themember companies were not required to use the parentcorporation's planning assumptions, they were required toarticulate whatever planning assumptions they used. Whena member company used alternative planning assumptions,the alternatives were automatically included in the envi-ronmental scanning.process of the corporation for its con-sideration in developing the planning assumptions for theentire corporation the following year. This examplehighlights the advisory nature of the results produced byscanning. The scanning group thus has no authorization toimpose its particular perspective on any division or func-tion of the institution.

For the issues that emerge as the most important, thenext stage is to review the institution's scanning resourcesand match those most important issues with the resourcebase being used by administrators. At this point, the focusis to develop a monitoring capability to provide the earliestwarning to the institution of any further developments asmost important issues. For example, if university manage-ment is concerned about the percentage of students need-ing English as a second language, it may be desirable thatone of the periodicals scanned is the rnaszine, Demo-graphics. Again, a simple chart of events versus periodi-cals can quickly lead to the identification of issues that arenot now being monitored. Results of the monitoring, then,arc to change the resource base of information flowing tothe organization.

When this process has been completed for the first timeat an informal level, the cycle is ready to be repeated. Bynow, the executives who have been interviewed should heaware of a central point for reporting new ideas about thechanging external world. They should he invited to con-

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tinue to report on new or emerging issues again and again.Periodically the process of soliciting and evaluating issuesshould be repeatedeventually through regularly sched-uled meetings in which everyone is "interviewed" at once,thereby, saving time for those running the scanning system,decreasing the amount of time the process takes, and mak-ing the flow of external information more timely.

Eventually these meetings may evolve into a quasi-formal scanning committee that will meet periodically toreview and analyze ideas about emerging issues and for-ward the most important ones to the formal long-rangeplanners. To explore the issues in more detail than thesimple probability-impact chart (pages 31-35), members ofthe scanning committee may want to use a tool like theimpact network (pages 36-40) to develop a sense of ienature and kinds of impacts an event may have. Note thatthe probability-impact chart provides for an evaluation ofboth positive and negative impacts. The scanning commit-tee, for example, may want to consider the impact of anevent on the institution's individual operations andwhether these impacts are positive or negative. The pur-pose of this step is to provide more information about thenature and context of emerging issues and the possibleopportunities and threats they pose.

As the scanning cycle is repeated, the function can be-come more formal with, for example, organized issuesfiles, which might be based on the categories identifiedinitially.

Link to Long-Range PlanningTraditional long-range planning begins with a thoroughanalysis of the current situation. As time passes, the proc-ess of keeping this status report current is known as moni-toring. Monitoring produces the kind of information con-tained in annual reportsnumbers of students, capitalexpenditures, number of faculty members, number of de-grees granted, and so on. It provides a history of the insti-tution's key features up to the moment. The focus of long-range planning has been to project this information into thefuture. But the difficulty with this kind of forecasting lies inthe fact that the future fails to cooperate. Sooner or laterthe extrapolations of the past will be upset by externaldevelopments, surprises, and changes. A long-range plan-


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ning function might have a dozen or more indicators ofinstitutional performance as the subject of its forecasts, butas long-range planners discovered during the 1970s, theseforecasts must be modified by a systematic inclusion of thepossibility of surprise developments in the external world.No better method to evaluate change in long-range plan-ning and forecasting can be found than that of calculatingthe impact of surprise events on trends through the proba-biliStic forecasting techniques like Monte Carlo and trendimpact analysis where events are allowed to happen or nothappen according to their probabilities, creating distribu-tions of possible futures. Decision makers can then usethese distributions of possible futures to expand their vi-sion of what could happen to the trends they are monitor-ing and thereby provide the information needed to set insti-tutional goals. Moreover, by using the probabilisticforecasting techniques described earlier, it is possible toobtain a range of forecasts of the impacts,that differentpolicies designed to implement these goals would have,thereby facilitating decisions about which policies to imple-ment. Linking internal and external perspectives thusserves to enhance college and university planning.

Thus, the inside perspective was based upon a muchmore stable society, economy, and overall environmentthan was to be the case in the 1960s and 1970s. Conse-quently, forecasters and planners developed methods antconcepts to include more and more of the external world ininternal forecasting. For example, the method of trendextrapolation was modified to include the effects of "sur-prise" events from the outside world on trend extrapola-tions. This new method became trend impact analysis.Cross-impact analysis was developed to explore the in-teraction and interconnection of events. The concept ofsystems modeling was modified to include externalchanges., it became known as probabilistic systems dy-namics.

Increased emphasis on taking account of changes in theexternal world continues today in issues management.That is, issues management reverses the inside-out per-spective of traditional forecasting and planning to anoutside-in perspective in which developments in the exter-nal world redefine the issues on which planning must fo-cus. Implicit in this change is the recognition that external

100

developments may have more influence over the future ofan institution than previously thought. Moreover, the alto-cation of significant resources to external scanning as,sumes that the external environment of the 1980s and be-yond will increase in importance as the pace of changecontinuesor accelerates.


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THE RELEVANCE OF ENVIRONMENTAL SCANNING ANDFORECASTING TO HIGHER EDUCATION

College and university planning has evolved through sev-eral major stages (Heydinger 1983). Initially, planning con-stituted part of the annual budgeting process because anyplanned change must necessarily be considered in projec-tions of revenues and expenses. Although extreme social,political, and technological trends were considered to someextent, the future was viewed primarily in terms of internalfinancial considerations. It became apparent, however, thatnot only was an exclusively financial perspective limitingbut so also was the one-year time frame. The next stageexpanded the time frame for planning beyond the first year,and as the need for qualification and accountability grew,the specification of institutional goals and objectives be-came a standard against which programs could be mea-sured. The perspective embodied in this stage was that of acause-and-effect relationship between specifying an institu-tional future and implementing plans to allocate resourcesto reach that future.

As our ability to store and manipulate quantitative infor-mation increased with the advent of computer centers and.more recently, personal computers, it became possible toproject historical data about external forces and forecastthe future. But further experience with planning and fore-casting revealed not only that the future is unpredictablebut also that the forces and interactions affecting collegesand universities were so complex and dynamic that a newplanning system was needed. This system needed io bebased on the strengths of the previous stages (the budgetcycle, specific organizational goals, and the utility of fore-casting), but it was also essential that the organization bemuch more sensitive to the influence of emerging long-termexternai trends and unprecedented future events that couldaffect the organization profoundly unless it has carefullyprepared itself well in advance to cope with them. Thisnew stage is the era of advanced, comprehensive, and sys-tematic strategic planning.

As modern strategic planning adds a special emphasis onidentifying those forces external to the organ on thatcan affect the attainment of its goals, assessment of theenvironment becomes an importantaspect of organiza-tional planning. It also places much greater emphasis onthe need to recognize uncertaintythe necessity to con-

Futures Research and the Strategic Marini'', Process 103

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side'. a range of possible conditions rather than a singlefuture.

Futures research, intended to provide the tools and per-spectives required by planners and decision makers whowished to operate most effectively, has developed in paral-lel with these changes in thinking. The field of futures re-search has always been controversial, and many academicsdoubt its legitimacy, particularly those who have been ledto believe that futures research seeks to predict the future(which it does not) or that it is a science (which it is not) orthat it will somehow supplement established fields liketechnological or economic forecasting (which it cannot).The approaches, the techniques, and the very philosophyof futures research have been developed to augment thecapability of individuals and institutions to deal intelli-gently with change, especially long-term change. Experi-mental practitioners are well aware that, in historical pet.-

__.spective,_the_ficld_is very-new -and-t hat-it-has-only--begun-to-solve some of the problems it must face to achieve thisobjective. Major figures in the field (for example, Helmer1983) note that the discipline is not yet on a solid concep-tual foundation, a condition caused in part by steady de-mands for immediate pragmatic results. The fact that tech-niques of futures research are based upon using theintuitive judgment of experts and require multidisciplinaryperspectives has been particularly troublesome to somewho value "hardness- and objectivity. These observers, aswell as serious practitioners in the field, have also beendisturbed by the fact that some charlatans. dilettantes, andincompetents have associated themselves with the field(though they ore steadily being shaken out).

Despite imr.niections like these, the techniques of fu-tures researchin responsible handscan greatly facilitateplanning because they are designed to provide as dear anaccounting as possible of expected changes in the operat-ing environment for which the plans are being formulated(Helmer 1983). Planning staffs and decision makers canquickly learn and use effectively the techniques describedin this volume.

Based on experience 'th successful strategic forecast-ing and planning in other organizationsthe military, pri-vate business, trade and protessional associations, forexamplemerging environmental scanning and forecasting

104

with conventional planning approaches will enhance plan-ning in higher education. Although arguing from analogy isalways dangerous, there seems to be no reason why manyof the lessons painfully learned in other organizations can-not be transferred into the administration of colleges anduniversities. In the late 1960s, educational institutions at alllevels were leading in the development and application ofthe tools and concepts reported here. But strategic fore-casting and planning became a subject that is taught, notused, in education. This situation is no longer tolerable,given the developinents facing education today.

Many higher education administrators realize that ttneed for new approaches is growing. When they recoF ..izethat they already have a wealth of information about theirinstitutions and about society and that futures methods andtechniques like those described here can provide modelsfor structuring and improving the quality of this informa-

- be- ready -to- adopt -new-- methods to build theirfuture.

If we are to respond creatively. we must begin to lookbeyond our own organizational boundaries and antici-pate internal changes brought on by changing externalconditions. We must take our early warning signals.combine them with our existing internal data forecastingtechniques, and ensure that the tap the wealth of creativ-ity and resourcefulness higher education has to offer

. (Heydinger 1983, p. 86).


APPENDIX AJOURNALS FOCUSING ON THE HELD OF

HIGHER EDUCATION

AAHE BulletinAcademeAGB Reports.Alternative Higher Education: The Journal of Nontraditional

StudiesAmerican Journal of Pharmaceutical EducationAmerican ScholarAssessment in Higher EducationAustralian Journal of EducationCanadian Journal of Higher EducationCASE CurrentsCAUSE/EFFECTChangeCollege and UniversityCollege Board Review

---t---Cottege Store-JournalEducation Policy BulletinEducational RecordEuropean Journal of EducationGraduate WomanHigher EducationHigher Education ReviewImproving College and University Teaching

--International Journal of Institutional Management in HigherEducation

Journal of Architectural EducationJournal of College and University LawJournal of Dental EducationJournal of Education for Social WorkJournal of Higher EducationJournal of Legal EducationJournal of Medical Education.Journal of Optometric EducationJournal of Podiatric EducationJournal of Student Financial AidJournal of Tertiary Education and AdministrationJournal of the College and University Personnel AssociationJournal of the Society of Research AdministratorsJournal of Veterinary 1V,:clical Education

Modified from a list of .turnals used by the ERIC Clearinghouse onHigher Education in its indexing and abstracting articles for the monthlybibliographic journal, Current Index of Journals in Education.


1.19

Liberal EducationNACADA JournalNational Forum: Phi Kappa Phi JournalNew Directions for Experiential LearningNew Directions for Higher EducationNew Directions for Institutional AdvancementNew Directions for Institutional ResearchNew Universities QuarterlyPlanning for Higher EducationResearch in Higher EducationThe Review of Higher EducationStudies in Higher EducationTeaching at a DistanceUniversity AdministrationVestes

108

1 2 9

APPENDIX BPUBLICATIONS SCANNED FOR THETRENDS ASSESSMENT PROGRAM.

AMERICAN COUNCIL OF LIFE INSURANCE

'Across the BoardAdministrative ManagementAdvertising AgeAgingAging & WorkAmerican BankerAmerican Bar Association

JournalAmerican DemographicsAmerican HealthAmerican Medical NewsAmerican ScholarAmerican ScientistArchitectural RecordAtlantic MonthlyBehavior TodayBrain Mind BulletinBrookings ReviewBulletin of Atomic ScientistsBusiness & Society ReviewBusiness HorizonsThe Business QuarterlyBusiness WeekCalifornia Management

ReviewCanadian Business & ScienceCenter MagazineChangeMagazine of Higher

EducationChannelsChristian Science MonitorChronicle of Higher EducationCo Evolution QuarterlyColumbia Journalism ReviewDaedalusDatamationDiscoverDun's Business MonthlyEast West JournalThe EconomistEmerging Trends (religiousissues)

Family Planning Perspectives

Financial PlannerFinancial TimesFootnotes to the FutureForbesForeign AffairsFortuneFree LanceFuturesFuture SocietyThe FuturistThe GerontologistHarper'sHarvard Business ReviewHarvard Medical LetterHastings Center ReportHigh TechnologyHumanistIndustry WeekInstitute of Noetic SciencesNewsletter

In These TimesJournal of Business StrategyJournal of CommunicationJournal of Consumer AffairsJournal of Contemporary

BusinessJournal of InsuranceJournal of Long Range

PlanningJournal of Social IssuesLeading EdgeManagement WorldMedical EconomicsMedical World NewsMoney MagazineMonthly Labor ReviewMother JonesMs.Nation's BusinessNew AgeNew England Journal of

MedicineNew Repub'ic


121

New ScientistNewsweekNew TimesNew York Review of BooksNew York TimesNuclear TimesOff Our BacksOmniPersonal ComputingPersonnel JournalPolicy Studies ReviewThe ProgressivePsychology TodayPublic InterestPublic OpinionPublic Relations JournalRainResurgenceRolling StoneQuestSaturday NightSaturday ReviewSavvyScienceScience and Public PolicyScience DigestScience 82 (83, 84, 85, etc.)Science NewsThe Sciences (NY Academy of

Sciences)

/Science Technology/8r. Human

ValuesScientific AmerioUnSloan Management ReviewSmithsonian /Social PolicySocietySolar Age/Tarrytowh LetterTechnology ForecastsTechnology IllustratedTechnology ReviewTimeTo The PointUrban Futures Idea ExchangeUSA TodayUS News & World ReportVital Speeches of the DayWall Street JournalThe WartonWashington MonthlyWhat's NextThe Wilson QuarterlyWorking Papers for NewSociety

Working WomanWorld Future Society BulletinWorld Press Review

110 .

122

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The ERIC Clearinghouse on Higher Education abstracts andindexes the current literature on higher education for the Na-tional Institute of Education's monthly bibliographic journalResources in Education. Most of these publications are availablethrough the ERIC Document Reproduction Service (EDRS). Forpublications cited in this list of references that are available fromEDRS, ordering number and price are included. Readers whowish to order a publication should write to the ERIC DocumentReproduction Servic,:, 3900 Wheeler Avenue, Alexandria, Vir-ginia 22304. When ordering, please specify the document number.Documents are available as noted in microfiche (MF) and papercopy (PC). Because prices are subject to change, it is advisable tocheck the latest issue of Resources in Education for current costbased on the number of pages in the publication.

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ASHE-ERIC HIGHER EDUCATIONRESEARCH REPORTS

Starting in 1983', the Association for the Study of Higher Educa-tion assumed cosponsorship of the Higher Education ResearchReports with the ERIC Clearinghouse on Higher Education. Forthe previous 11 years, ERIC and the American Association forHigher Education prepared and published the reports.

Each report is the definiti analysis of a tough higher educa-tion problem, based on a thorough research of pertinent literatureand institutional experiences. Report topics, identified by anational survey, are written by noted practitioners and scholarswith prepublication manuscript reviews by experts.

Ten monographs in the ASHE-ERIC Higher Education Re-search Report series are published each year, available individu-ally or by subscription. Subscription to 10 issues is $55 regular;$40 for members of AERA, AAHE, and AIR; $35 for members ofASHE. (Add $7.50 out3ide U.S.)

Prices for single copies, including 4th class postage and han-dling, are $7.50 regular and $6.00 for members of AERA, AAHE,AIR, and ASHE. If faster 1st class postage is desired for U.S.and Canadian orders, for each publication ordered add $.75; foroverseas, add $4.50. For VISA and MasterCard payments, givecard number, expiration date, and signature. Orders under $25must be prepaid. Bulk discounts are available on Orders of 10 ormore of a single title. Order from the Publications Department.Association for the Study of Higher Education, One DupontCircle, Suite 630, Washington, D.C. 20036, (202) 296-2597. Writefor a complete list of Higher Education Research Reports andother ASHE and ERIC publications.

1%2 Higher Education Research Reports

I. Rating College Teaching: Criterion Studies of StudentEvaluation-of-Instruction Instruments

Sidney E. Benton

2. Faculty Evaluation: The Use of Explicit Criteria forPromotion, Retention, and Tenure

Neal Whitman and Elaine Weiss

3. The Enrollment Crisis: Factors, Actors. and ImpactsJ. Victor Baldridge, Frank R. Kemerer, and Kenneth C.Green

4. Improving Instruction: Issues and Alternatives for HigherEducation

Charles C. Cole, rt.

5. Planning for Program Discontinuance: From Default toDesign

Gerlinda S. Melchiori


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6. State Planning, Budgeting, and Accountability: Approachesfor Higher Education

Carol E. Floyd

7. The Process of Change in Higher Education InstitutionsRt,bert C. Nordvall

8. Information Systems and Technological Decisions: A Guidefor Non-Technical Administrators

Robert L. Bailey

9. Government Support for Minority Participation in HigherEducation

Kenneth C. Green

10. The Department Chair: Professional Development and RoleConflict

David B. Booth

1983 Higher Education Research ReportsI. The Path to Excellence: Quality Assurance in Higher

EducationLaurence R. Marcus, Anita 0. Leone, and Edward D.Goldberg

2. Faculty Recruitment, Retention, and Fair Employment:Obligations and Opportunities

John S. Waggaman

3. Meeting the Challenges: Developing Faculty CareersMichael C. T. Brookes and Katherine L. German

4. Raising Academic Standards: A Guide to LearningImprovement

Ruth Talbott Keimig

5. Serving Learners at a Distance: A Guide to ProgramPractices

Charles E. Feaslev

6. Competence, Admissions, and Articulation: Returning to theBasics in Higher Education

Jean L, Preer

7. Public Service in Higher Education: Practices and PrioritiesPatricia H. Crosson

8. Academic Employment and Retrenchment: Judicial Reviewand Administrative Action

Robert M. Hendrickson and Barbara A. Lee9. Burnout: The New Academic Disease

Winifred Albizu Melendez and Rafael M. de Guzmdn10. Academic Workplace: New Demands, Heightened 'tensions

Ann E. Austin and Zelda F. Gamson

1 3)

1984 Higher Education Research Reports1. Adult Learning: State Policies and Institutional Practices

K. Patricia Cross and Anne-Marie McCartan2, Student Stress: Effects and Solutions

Neal A, Whitman. David C. Spendlove, and Claire H.Clark

3. Part-time Faculty: Higher Education at a CrossroadsJudith M. Gappa

4. Sex' Discrimination Law in Higher Education: The' ^sonsof the Past Decade

J. Ralph Lindgren, Patti T. Ota, Perry I Zirkel, and NanVan Gieson

5. Faculty Freedoms and Institutional Accountability:Interactions 4nd Conflicts

Steven G. Olswang and Barbara A. Lee6. The High-Technology Connection: Academic/Industrial

Cooperation for Economic GrowthLynn G. Johnson

7. Employee Educational Programs: Implications for industryand Higher Education

Suzanne W. Morse

8. Academic Libraries: The, Changing Knowledge Centers ofColleges and Universities

Barbara B. Moran

9. Futures Research and the Strategic Planning Process:Implications for.Higher Education

James L. Morrison, William L. Renfro. and Wayne I.Bourher


--11111._

JAMES L. MOiARISON, professor of education at the Univer-sity of No; th Carolina at Chapel Hill, received his B.S.,M.S., and Ph.D. degrees from Florida State University. AtChapel Hill, he teaches courses in educational evaluation,planning, and research in higher education. He is immedi-ate past chair of the Special Interest Group in Futures Re-search for the American Educational -Research Associationand currently serves as vice president (Division JPost-secondary Education) of that association. His researchinterests focus on using futures research techniques ineducational planning. With coauthors Renfro and Boucher,he coedited Applying Methods and Techniques of FuturesResearch in 1983.

WILLIAM L. RENFRO is president of Policy Analysis Co.,Inc. (Washington, D.C.), a forecasting and futures researchfirm. He developed the forecasting services CongresScan,LEGISCAN, and Issue Paks as.well as the first third-generation forecasting concept, policy impact analysis, anda new interactive decision support system based on theDelphi process. Dr. Renfro is a cofounder and director ofthe Issues Management Association and serves as issuesmanagement editor of The Futurist, Among his publica-tions are The Legislative Role of Corporations and chap-ters in The Public Affairs Handbook, Anticipatory Denutc-racy, The Handbook of Futures Research, andNon-extrapolative Methods in Business Forecasting.

WAYNE 1. BOUCHER is executive vice president of the ICSGroup, Inc. (Harbor City, California), a consulting firmthat specializes in strategic and operational planning. Na-tionally recognized as one of the leaders in futures iv-search, Mr. Boucher has been affiliated with the principalorganizations in the field; The Rand Corporation, the Insti-tute fol the Future, The Futures Group, and the Center forFutures Research. His earlier books include The Study ofthe Future (1977) and Systems Analysis and Policy Plan-ning (1968).

ISBN 0-913317-18-7 »$7.50

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