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SMU Institute of Technology 1973 Annual Report.Southern Methodist Univ., Dallas, Tex. Inst. of.

Technology.73SOP.

EDRS PRICE MF -$O.65 HC-$3.29DESCRIPTORS Annual Reports; *Budgeting; *Educational

Administration; *Educational Finance; EnrollmentTrends; *Higher Education; *Program Budgeting;Program Descriptions; Statistical Data;Universities

IDENTIFIERS *Southern Methodist University; Zero baseBudgeting

ABSTRACTThis report discusses the development of a rational

process for making decisions about cu-rent operations and managingchange to secure future goals. The firs'f. section describes the sevenbasic approaches to budgeting, distinguishes between them, andidentifies the principal advantages and disadvantages. The sectioncloses with an overview of a proposal for a comprehensive system ofuniversity budgeting that uses all seven of these approaches, butwhich is critically dependent upon Zero-nase Budgeting and thetechniques of objectives, strategies, and tactics. Section IIpresents a statistical report and evaluation of trends at SouthernMethodist University. Emphasis is placed on enrollment figures andtrends, a brief description of a co-operative program and the TAGERtelevision system, and future prospects in graduate engineering.(MJM)

111..11:1) 1120M BEST AVA T R LE C'01"1.

MU Institute of Technology 1973 Annual Report

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Contents

Fonword3 SECTION I3 SYNOPSIS OF BUDGETING SYSTEMS3 Introduction3 Every Tub On Its Own Bottom (ETOB)4 The King's Decree (KING)4 The L.queaky Wheel Gets the Grease (SWGG)5 The Formula (FMLA)6 Planning, Programming and Budgeting Systems

(PPBS)7 Zero-Base Budgeting (ZBB)8 Objectives, Strategies and Tactics (OST)9 Proposed Budgeting System

10 ZERO-BASE BUDGETING10 introductiOn10 Identification of Decision Packages12 Specification of Decision Packages14 The Ranking Process15 The Cutoff Process17 Examples of University Decision Packages23 OBJECTIVES, STRATEGIES AND TACTICS23 Introduction23 Goals and Objectives24 Intent Structures26 Educational Objectives27 Strategies28 Strategy Statements29 Tactical Action Programs (TAP's) and

Decision Packages30 SOME REFERENCES31 SECTION II31 STATISTICAL REPORT AND EVALUATION OF TRENDS31 Freshman Engineering Enrollment32 Total Undergraduate Engineering Enrollment32 The Undergraduate Engineering Co-operative Program33 Graduate Engineering Enrollment34 The TAGER Television System34 Graduate Degree Production34 Master's Degrees36 Doctoral Degrees36 Graduate Engineering Prospects for the Future36 Semester Credit Hour Production37 Reorganization of the Institute of Technology39 Appendix I

Faculty of the Institute42 Appendix II

Events Affecting the FacultyTextbook Publications

44 Appendix IIIActive Grants/Contracts in Force DuringFiscal Year 1972-73

46 SMU Foundation for Science and EngineeringBoard Officers and Executive CommitteeBoard MembersTechnical Advisory CouncilCorporate and Business DonorsIndividual Donors

2

In the most general case, a budget is merely aspending plan constrained to frill within the bounds ofestimated revenues over some specified interval oftime. But because budgets are so intimately involvedwith the attitudes of the people who must manage them.not everyone views budgets with quite this degree ofacademic detachment. Some people regard a budgetas an open-ended license to spend, assuming thedetails of the budget to merely represent generalexpenditure guidelines: others see it as a preciselydefined spending plan to be followed without exception.Still others view a budget as a carefully definedstrategic plan aimed at achieving specificorganizational objectives, a one-year snapshot of along-range plan that spans several years, There aresome who simply view a budget as the end result of aseries of politically expedient decisions andnegotiated agreements reflecting "business as usual."It is clear that budgets have many differentinterpretations. But, in any case, the process by whichbudgets are constructed reveals much about thedecision-making apparatus of the organization.

Moreover, the techniques used in budget constructionare many and differ significantly in their approaches.It is possible to identify seven such approaches whichare distinctly different from one another and whichhave been used, or could be used, in universitybudgeting. These include the following:

(1) Every Tub On Its Own Bottom (ETOB)(2) The King's Decree (KING)(3) The Squeaky Wheel Gets the Grease (SWGG)(4) Formula (FMLA)(5) Planning, Programming and Budgeting

Systems (PPBS)(6) Zero-Base Budgeting (ZBB)(7) Objectives, Strategies and Tactics (OST)

Each of these approaches to budgeting tries toovercome certain budgeting problems. Thus, the focusof each is quite different and each has certainadvantages and disadvantages. Proponents of eachplan tend to promote the use of one plan exclusively.However, it will appear here that all seven systemsneed to be used to some degree. The key managementproblem is finding the appropriate mix.

The first five approaches are relatively well known inhigher education and receive only cursory attentionhere. However, Zero-base Budgeting and thetechniques of Objectives, Strategies and Tactics arenot generally known and understood in the academic

community. Accordingly, they are covered inconsiderable detail.

It ig the purpose of this year's Annual Report to showthat Zero-base Budgeting and the use of Objectives.Strategies and Tactics are unusually powerful tools inuniversity budgeting and decision making. It is furthershown that all seven budgeting systems listed areinvolved in the proper construction of a universitybudget The overall result is a systematic and rationalprocess for university decision making andlong-range planning.

It will be shown that all budgets should include twocomponents an operating budget covering near-term activities and a strategic budget which aims atlong-term objectives. Many university administratorsprofess to have a strong orientation toward the future,and many do. Yet the typical university budget-makingprocess and apparatus for decision making generallygive little attention to the future.

The concern in this Report is the development of arational process for making decisions about currentoperations and managing change to secure futuregoals. It is within the framework of the much longerpicture that the budgeting techniques becomeimportant. It is essential to remember that it is thedecision-making process that is essentialthe budget is a result.

The emphasis placed here on "decision making"could mislead the reader into believing that universityadministrators are like industrial managers, that theyhave full freedom to choose and control the directionsand goals of the institution. But this is not true and cannever be true because of the uniqueness of universitiesas social instruments and the oddities of their finances.Universities are strongly influenced by gifts, grants,contracts, public and governmental moods and fads.Their directions are correspondingly swayed. Whilemanagers in industry are similarly influenced bysimilar factors, they have a degree of authority to makedecisions that has no parallel in education.Consequently, the discussion here recognizes theselimitations on academic administrators even thoughthe converse may seem to be implied at times.

This study and presentation were made possible by agrant from the Sloan Foundation. This assistance isacknowledged with profound gratitude. Help andguidance were provided by Jim Fischer, Vice Presidentof Texas Instruments Incorporated. His assistanceis greatly appreciated.

Section 1 Part 1: Synopsis of Budgeting Systems 3

JYNOPSIS OF BUDGETING SYSTEMS

This first section describes the seven basicapproaches to budgeting, distinguishes between themand identifies the principal advantages anddisadvantages of each. The section closes with anoverview of a proposal for a comprehensive system ofuniversity budgeting which uses all seven of theseapproaches, but which is critically dependent uponZero-base Budgeting and the techniques ofObjectives, Strategies and Tactics. Because theproposed system is so critically depende.it upon thesetwo approaches. and because they are not generallywell understood in academe, they are covered indetail in later sections.

The proposal actually describes a process forsystematic decision making regarding the allocationof institutional resources for current operations andfor the future.

Every Tub On Its Own Bottom (ETOB)

The ETOB approach to budgeting is more or lessself-explanatory. The ETOB system recognizes variousclearly defined expenditure and revenue centers andthen requires that each such budgeted center generateenough revenue to offset its expenditures, both directand indirect. In theory, this is the way that SMU hasoperated for many years, but the appearance and thereality diverge somewhat. The most famous examplegenerally cited is Harvard University.(')

At first glance this is a very attractive concept to thecentral administration because responsibility for thevery difficult and delicate problem of prudent, yetinnovative, operation within revenue expectations isdelegated downward to deans and other administrators.This saves many headaches for the president andhis staff, but it begets others.

For example, one very important problem ariseslargely as a result of Parkinson's Second Law:

Expenditure rises to meet income.That is, those budgetary units having increasingrevenues always expand their activities so that theincreased costs equal the increased revenues,Unfortunately, the converse almost never occurs; thatis, those units whose revenues fall below expendituresdo not correspondingly reduce their expenditures.With the faculty tenure situation being what it is,universities seldom possess the ability toincrementally reduce expenditures in the mosteffective way. Thus, the particular tub is not supportedfully by its own bottom and is in a deficit positionthrough inability, or unwillingness, to respond tochanged circumstances. The overall universitythereby ends up in a deficit position whenever any oneof its tubs fails to be supported on its own bottom.In the absence of large, uncommitted endowmentfunds, the university does not have the ability toadjust to the problem.

The Harvard University Committee on Governance;examined the advantages and disadvantages of ETOBin considerable detail. They noted that:

"ETOB, in combination with a host of specificrestrictions on specific gifts agreed between the

donor and the member of the university pursuinghim, has Iwo related. specific consequencesworth noting.

Only a small traction ol the total resources onHarvard's books are Iree,'y available forallocation by the President and Fellows.The fortunes of each school and 'tub' have beenexceedingly sensitive to the pocketbooks of its ownalumni; the popularity of its subject matter amongrich patrons, foundations, and the government; theincome status and expectations of its students;and in some cases, to the general state of thefederal budget."

Moreover, there are some additional problems thatarise because of the ambiguous character of thosecentral university functions such as the library,computing laboratory, admissions office and the like,which are exposed to the hazards of all things that areboth everybody's business and nobody's."(0

The most telling criticism of budgeting by ETOB iscontained in the Report of the Harvard GovernanceCommittee" in the following statement:

"On its face, there is something peculiar about thenotion that it is somehow right for a great universityto be shaped more or less by happenstance, by thelargely uncoordinated entrepreneurial activities ofdeans, professors, and administrators, and theproclivities of donors. No doubt, 'Every Tub On ItsOwn Bottom' has much to commend it. 11 sidesteps agood many unresolvable arguments about purposes;decisions about the shape of the university aread hoc, sequential, and by and large implicit. Butso are the results. (The proposition that such aregime is 'right' because every activity whichsurvives is 'self supporting', is indefensible. This isnot a domain where one can count on Adam Smith'sinvisible hand to make 'competition' efficient inserving any reasonable set of values.)"

This criticism is most appropriate when there are manysmall tubs which differ widely in their income andcost potentials.

Moreover, it must be said that in certain instancesthe ETOB method of budgeting and operational controlhas worked. It has certainly served Harvard well in thepast because it stimulated many different people in theadministration, in the office of the President, and evenindividual professors, to participate in the fund-raisingenterprise. This occurs with ETOB because it isnecessary for those who care about an activity to findsome way of financing it. It provides great incentives atthe grassroots to raise money and to increase the returnfrom money that is spent. If the extra income broughtin by a unit is siphoned off to another unit there is littleincentive to raise the extra money. Similarly, if a tub isefficient and saves money that is then taken away,the desire to be efficient is cancelled. ETOB thus tendsto make the university quite "sensitive to changingsocial needs as perceived by different parts ofthe community."(71

The Harvard Governance Committee squarely facedthe issue of whether ETOB should continue as the basicbudgeting mode at Harvard or whether it should be

replaced with some more centralized decision-makingand control apparatus. In substance, the Committeeconcluded thud total withdrawal from ETOB is probablynot possible for Harvard. But even if it were possible itwould not be desirable. They concluded that ETOBshould be retained in part and mixed w'sh otherbudgeting and decision-making apparatus, the mixbeing more important than exclusive use ofany one method.

There is a fairly Jovi ous industrial counterpart toacademic ETOB. This is a case of decentralization inwhich every profit, or cost, center is constrained tooperate like a small, complete business with its ownresponsibilities in marketing, personnel, finance andso on. This approach is widely used in business andindustry with considerable success and has itsadvocates on the campus. It is not withont its faults,however, as noted by Grant Dove:0')

"1 he difficulty with this approach by itself (myemphasis) is that the innovative ellorts, even whenthey exist, tend to come out fitting the size andresources of the decentralized units. In other words,if left alone, there is likely to be lit le or no real break-through strategic efforts, that is: action which, ifsuccessful, could impa;:st the whole corporation in amajor way and exploit the whole corporation's totalvariety of resources, far exceeding the vision of anysingle manager of a decentralized unit."

Dove then concludes his statement by saying:"A major role of management is to shape the goalstructure toward opportunities and problems whichare the right scale for the total corporation."

This is generally impossible in a wholly decentralizedETOB budgeting pian because resources and optionsare not left to the discretion of the administration .

at the center.

The King's Decree (KING)In this mode of budgeting the total revenue pool is

estimated by the central administration. The centraladministration, with or without consulting variousadvisors, then determines the amount of money to beallocated to each of the operating and servicedivisions of the university. This is a completelyauthoritarian system whose effectiveness depends inlarge measure upon the accuracy of the informationpresented to the decision maker by the supporting staffand organizational heads prior to the time theallocations are made. It is the exact converse of ETOB.

The advantages of the King's Decree over ETOBobvious in certain respects. It makes it possible forresources to be allocated to carefully defined andinternally consistent objectives sought by the entireorganization, at least as the King perceives them.In contrast, ETOB tends to be a haphazarddevelopment, depending upon the fund-raising abilitiesof individual members of the faculty and theintentions of donors as outlined darlier,

While there can be many objections to anauthoritarian system of management. the unusualcombination of factors influencing the future of highereducation Oh the United States suggests that the time

has come for strong and decisive action which is notpossible in the internally competitive entrepreneurialatmosph,,re created by the ETOB system. There is noquestion but that the costs of higher education aregoing to rise, and it is not at all clear that theavailability of supporting funds will increaseproportionately. Consequently, it is occasionallyargued that We ability of the strong executive at Wecenter to carefully allocate resources in anauthoritarian way may ee crucial to the survival ofmany educational institution';.

Given the foregoing advantage, it is also fair to saythat it is unlikely that any individual, no matter howtalented nor how well he surrounds himself withtalented advisors. is in a position to accurately assessthe needs for resources and to allocate them in such away as to achieve the most broadly sought objectivesof an institution as complex as a university.

For all practical matters the opportunity to operateentirely on the basis of the King's Decree has longsince vanished. The complex governance systems invogue at many universities couple with the tenuresystem and federal laws governing employment to sucha degree that university administrations retain very fewdiscretionary options. While the King's Decree is not arealizable mode of operation, even if it were desirable,the essential quality of decisive leadership can beachieved and mixed with other systems.

Most importantly, the King's Decree suffers from abasic limitation singularly appropriate to highereducation it ignores the intrinsic faculty hostility toarbitrary authority at the center.F. [, Terman put it this way:

"In practice, the King cannot be completelyauthoritarian in dividing the pie without generatingrebellious subjects, who when once antagonized,forget very slowly. This is true irrespective of howlair or right the King's decision may be, because eachdean, department head and faculty member isbiased toward his special interest and feels he isshort-changed when he is actually being. treatedequitably. As a result, the King's Decree approachgenerates intense internal competitiveentrepreneurship with the King at the centerof the pressure.

In contrast, ET03 avoids internal competitionbecause each tub has available the entire world as itssource of funds, and any successes that one tub mayhave in obtaining extra money clearly and obviouslydoes not take money away from the other tubs.However, with the King's Decree, everyone islighting for the same money and what the King givesto one tub is considered by the other tubs tohave been taken away from them."

The Squeaky Wheel Gets the Grease (SWGG)The Squeaky Wheel Gets the Grease (SWGG)

method is fairly obvious and quite common in practice.This is usually found in universities which do not havesystematic budgeting and goal-setting procedures. Theadministration at the center may be weak andindecisive, or it may be strong and capricious. In either

5

case. because of the lack of commonly understoodgoals, the annual revenue pool is attacked by the headof each budgetary unit with the aim of securing themaximum portion for his unit independent of its trueneeci. This causes budgetary allocation to bedetermined largely by bureaucratic infighting,politicking, extravagant claims. misleading statistics,and all the other tools of the squeaky wheel. Theresulting budget is a political document instead of agoal-oriented financial plan.

In common with ETOB, The Squeaky Wheel Gets theGrease fails to provide a budgeting system whichfocuses upon accepted institutional Lbjectives. Instead,progress tends to be erratic and dependent upon therelative success of different academic bureaucratsin their ability to persuade or coerce the administrationat the center to allocate a disproportionate share of theavailable revenue to their operating divisions. Suchoperating conditions breed a situation in which theuniversity is not controlled by intelligently setobjectives, but by the arbitrary resolution ofantagonistic efforts by different members of theadministration. This is scarcely a rational process, andone which cannot produce long-term organizationalsuccess. Nevertheless, in far too many cases,administrators feel that it is their responsibility tofunction in this mode.

The revenue pool for universities has fourcomponents: tuition income (or the state appropriatedequivalent), contracts and grants, gifts and endowmentincome. In most schools the tuition component (or stat.eequivalent) of the pool is predominant. Givencontemporary college population statistics then, therevenue pool for a university is, to a large degree,essentially fixed during any reasonable budgetaryperiod. Consequently, what is known in mathematics asa "zero-sum game" is being played. That is, as thehead of one budgetary unit takes more of the revenuepool for his uses, there is usually less available for theuse of other operating divisions. This is recognizedby all on the campus and breeds suspicions abouteveryone's motives. Interdepartmental cooperation iscorrespondingly difficult, if not impossible:

It would be unfair to drop the Squeaky Wheel at thispoint. In most cases, the Squeaky Wheel is not s .nplyan aggressive, threatening desk pounder. Instead, hevery often succeeds because he is more articulate,more persuasive and more imaginative than hiscompetitors. It is not a uniformly bad thing to give suchpeople greater access to resources because they arelikely to accomplish more with it. Indeed, the SWGGsystem tends to put a premium on this type ofindividual and he tends to surface into leadershippositions in such organizations.

Thus, as with all systems, SWGG has its advantagesand disadvantages. While it would be a mistake touse it as a system to the exclusion of all others, it doeshave the feature of drawing out persuasive peoplewith attractive ideas.

The Formula (FMLA)To overcome the obvious problems of SWGG, and to

achieve greater equity in the allocation of resourcesto the various operating divisions, more and moregroups, particularly in state-supported institutions, aregoing to the use of formula-based budgetary plans.In these schemes available funds are allocated to thevarious operating divisions in accordance with someunit of production generally the Student Credit Hour(SCH). The SCH are often weighted according to level--- lower division, upper division, graduate, doctoral,etc. Other quantitative factors such as full-timeequivalent students. or "head count," or othereasily obtainable factors may be used.

Formulas are one form of a more general techniqueknown as resource allocation models.011 Theseattempt to translate the inputs to the resourcesrequired for example. translating enrollment changesinto changes in demand for courses, faculty, facilities,support functions. and so on. The advantage offormulas and resource allocation models is that theyallow the budgeter to systematLally play the game of"What if?" That is, what if enrollment goes down (up)in engineering (business), arts (science), etc.?As such, this approach is more commonly _ad as adecision-making tool rather than as a specifictechnique for budgeting.

An extensive study was made of funding formulas foreducation, particularly in engineering education, andreported in 1971.031 As a result of this survey, thefollowing general observations were made:

"(1) Of those using or anticipating a formula, anasking figure is calculated and, in general. apercent (of the asking figure) is funded.In general, complex state-supported systemsview a formula as necessary or desirable.Less than ore-half of the formulae in use orbeing considered differentiate betweenlevel and discipline.

(4) If a differentiation is made as to discipline,engineering is lumped with other sciences andnot with professicnal colleges.

(5) Less than half of the formulae used or beingconsidered, consider research needs separately.

(6) Slightly over one-half of the formulae in use orbeing considered, consider administration,maintenance and services as separate itemsinstead of as percent allowances as determinedby instruction.

(7) The most prevalent fundamental basis offormula allocation seems to be based on SCH(Student Credit Hour) and FTES/FTEF (full-timeequivalent student/full-time equivalent faculty)ratio or combinations of these.

(8) Generally, funds are not allocated on a formulawithin institutions."

These are significant results. For example, the firstobservation shows that schools receive only apercentage (less than 100 percent) of the fundsrequested according to the formula. They survive andapparently perform creditably at this reducedexpenditure level. Thus, it must be concluded thatformulas are generally not accurate predictors of actual,justifiable educational expense. Instead,-they

(2)

(3)

seemingly establish the point at which budgetarynegotiations begin.

The second point that state-sbpported systems viewa formula as necessary is hardly surprising. In thehighly charged atmosphere of state -level budgetmaking and in the allocation of funds to competingschools, formula systems may be the only recourse topork-barrel politics.

There is a strong tendency for formula systems toreflect certain intuitive preconceptions about whoshould receive the most for what, despite the claim ofattempts to achieve equity. For example, in the Texasformula system there is an allocation of funds forresearch, an allocation that can be substantial. Thefunding level is calculated through the use of aninstitutional complexity factor, or IC,which is defined as follows:

IC.015U (.50M, i .10M; .25M1) q. (6D, 1D, i 3D,)

U -t M Dwhere:U Undergraduate FTSEM Masters FTSE

M, Masters FTSE in Science and EngineeringM, Masters FTSE in Teacher EducationM, Masters FTSE in all other programs

D Doctoral FTSED, Doctoral FTSE in Science and EngineeringD, Doctoral FTSE in Teacher Education0, Doctoral FTSE in all other programs

The amount of money requested for research iscomputed by multiplying the IC by the faculty salarytotal and then adding 5 percent of the sponsoredresearch funds expended in the previous biennium.

It is clear that the formula strongly supports(1) existing, well-established graduate schools of

large enrollment(2) doctoral programs(3) science and engineering more strongly than

teacher educationThus, it is not equitable in the truest sense -- it is onlya base for calculations of the approximate effects ofenrollment changes on resource requirements.

This conclusion is reinforced by the eighth and lastconclusion drawn from the aforementioned survey.It indicates that universities use formulas to requestfunds, and they are often allocated within large statesystems in accordance with these formulas. Howeverdespite careful formula distinctions between costsin different academic fields, once the money isappropriated to the university, these alleged costdifferentials are largely ignored and funds are disbursedeither by Kingly Decree or by SWGG. It has beennoted recently, however, that as financial resourcesavailable to educational institutions have dwindled,there has been an increasing tendency for the centraladministrations of large state universities to try tocompel the subdivisions within the university to complymore nearly with formula allocations.

Formulas are one type of resource allocation modelas noted earlier. Allocation parameters are anyconveniently available data base, most commonly one

or more of the following:(1) student credit hours(2) student contact hours(p) full-time equivalent faculty(4) lull-time equivalent employees(5) student head count(6) total salary expenses(7) assignable square feet

Other parameters, usually less easily obtained orapplied, include:

(1) number of sections(1) percent of usage

The National Center for Higher Education Manage-ment Systemso" '9) (NCHEMS) is developing a ResourceRequirement Prediction Model (RRPM), using suchallocation parameters. In addition to direct estimatesof faculty costs, it allocates the expenses of allsupporting functions (registrar, health center, com-puting laboratory, library, etc.) to any one of sevenprogram classifications. The model has been testedsuccessfully and is under constant refinement.

A somewhat more complex system was developedand used at the University of Toronto. It is known asComputerized Analytical Methods in PlanningUniversity Systems, or CAMPUS. There are a numberof other systems.Po

In any event, these systems are basically not toolsfor budget construction. Instead, the,/ are intendedas tools to play the game "What if," Lo supply asystematic basis for decision making, for choosingbetween various possible alternatives.

Planning, Programming andBudgeting Systems (PPBS)

It is clear from the name of the system Planning,Programming and Budgeting Systems that thereare three major steps in the process. The first step,planning, sets goals, objectives and makes policy.It requires a selection of specific objectives whichare analyzed systematically in terms of cost andbenefits, presumably using formulas and resourceallocation models. Each potential course of actionto attain these objectives is analyzed on thiscost/benefit basis. This is intended to be long-rangeplanning within a time frame of 5-15 years.Programming is a selection process in which specificcourses of action, which are known as programs,are chosen and mechanisms for review and controlare enunciated. These are usually defined within ashorter time frame of 1-5 years. The final step isbudgeting, the translation of planning and program-ming decisions into specific financial plans in timeframes of about one year. BudgetS are specificfinancial, manpower and policy plans to be imple-mented during the budget period.('' The budgetingprocess analyzes organizational functions and activitiesnecessary to achieve the goals and objectives bymany and various alternatives that have beenidentified.

The objective of PPBS is to improve the basis uponwhich major program decisions are made. It forces

the identification of program objectives and theconsideration of alternate methods of achievingthese objectives. These are subjected to systematiccomparison to determine the "best" way. Additionally,PPBS rellecls future, as well as current, implicationsof decision., which might be rnade and allows for theappropriate planning of contingencies. Somewhatmore implicitly, the principal purpose of PPBS hasbeen defined as follows:0)

To compare a/lethally° methods of pursuing animperfectly determined policy objective; analyzingalternative ways to accomplish objectives,. seeingthe complementary relationships among programsor subprograms; allowing for overlapping structureswhere objectives call for them; and planningtotal costs."it is obvious that PPBS depends upon multi-year

planning. Moreover, it attempts to relate in directways outputs and inputs, consequences with decisions,and effects with causes. Simultaneously, it aims toquantify and evaluate both direct and indirectcosts in systematic ways.

PPBS has seven identifiable characteristics.1")These can be identified very briefly as follows:

(1) Identification of goals(2) Definition of objectives(3) Program description to accomplish objectives(4) An extended time frame(5) Expl;cit consideration of alternative approaches(6) Evaluation of all approaches and selection

of the "best" route(7) Replanning

This makes it clear that the effective implementationof Planning, Programming and Budgeting Systemsdepends in a critical way upon the existence of effective,quantitative Management Information Systems(MIS). It is the combination of MIS and PPB systemswhich combine to produce the effect finally desired.

"MIS and PPB systems act as powerful, heuristicand recollective devices their impact uponadministrators: The progmm planning disciplinerequires that the university leadership confront withgreFt concreteness questions of objectives, evalu-ation criteria, and priorities which are otherwiseeasily let slide in the press of daily affairs."(29)Unfortunately, there are very few schools which

currently have adequate management informationsystems and appropriate, well-defined data bases.The most outstanding examples of partial successhave occurred at Ohio State University, StanfordUniversity, University of Pittsburgh, University ofToronto, University of California, and a few otherinstitutions. In an effort to overcome this problem, theNational Center for Higher Education ManagementSystems (NCHEMS) has been established at theHeadquarters of the Western Interstate Commissionon Higher Education, in Boulder, Colorado. It is hopedthat there will be forthcoming from this enterprisemanagement information systems appropriate to .

university operations which would enhance theimplementation of PPBS.

Unfortunately, PPBS has not succeeded very well,neither in universities nor in government. The ton-ciency has been lor the proponents of PPBS to locusmore upon activities rather than objectives, moreupon the mathematical models than upon the resultsthey were hopefully to achieve, more upon themechanics and formalism rather than upon theconcept and spirit. It is clear that if PPBS rs to succeedin higher education, some way must be found tochange this, to place the emphasis upon the conceptand spirit of the idea rather than upon the mechanicsand formalism of the process. However, there arethose who believe that the formalism of PPBS is soorganic to the process itself that it will never be worththe costs which are introduced by the enormousmachinery necessary to respond to the formalisticrequirements of the system.

It should not be surprising that PPBS has notgenerally been successful because it is extremelydifficult to identify systematically the benefits pro-duced by the activities of educational institutions.Costs can be determined, but benefits are very elusiveand depend upon a degree of consideration of the aimsand objectives of_higher education which has notyet been approached systematically.

In spite of the criticism of the detailed mechanicsof PPBS, the concept anc, the spirit are certainlyvalid, particularly in the realm of higher education.Traditionally, universities develop their programs andactivities simply in accordance with what theyestimate the available funds to be. This is certainlynot a rational process and will not be acceptable inthe future. Such an approach fails to consider theoverall goals of the university. Until resources areallocated in accordance with clearly defined goals andobjectives it is unlikely that resource utilization inhigher education will approach the efficiency ofbusiness and industry.

A method for accomplishing PPBS in universitiesis described in this presentation. The method over-comes most of the criticism of excessive formalism whilemaintaining compliance with the spirit of the system.

Zero-Base Budgeting (ZBB)

It is quite common to speak of the budget and torefer to the budget-making process. But, in reality,there either are, or should be, two distinctly differentbudgets serving two distinctly different purposes. Thereis the operating budget which is concerned with near-term objectives, and there is the strategic budget whichis concerned with long-term objectives. This sectionis concerned only with the operating budget.

The operating budget is the one that concerns mostpeople and which involves most of the availablefunds. It deals with those cost elements necessary tomaintain current operating levels, those items necessaryto meet existing commitments, those activities neces-sary to near-term objectives. Accordingly, theoperating budget is concerned primarily with non-discretionary funds. It provides for the planning andcontrol of month-to-month operations, usuallyseeking to optimize year-end results.

8

Generally speaking. most operating budgets aremade by taking the current year's operating level andthen increasing it to lake care of inflation, salary raises.aril certain additional actitvities, Budget defense isthen largely a matter of justifying the increase; thecurrent year base is accepted on the premise that itwas justified previously.

But limes change, often with startling rapidity.. andwhat was justified one year may not be justifiable thisyear. This is the origin of the concept of Zero-baseBudgeting, a process that requires each manager tojustify his entire budget in detail, just as though itwas being started for the first time.

The originator of practical Zero-base Budgeting(ZBB) is Texas Instruments Incorporated, a high-technology, large corporation home-based in Dallas.The individual originator was Peter A. Pyhrr.l' 41)

The first step in the use of ZBb requires that eachdiscrete organizational activity be described in termsof a "decision package." Secondly, each of thesedecision packages is carefully evaluated and rankedin sequential order by the methods of cost/benefitanalysis and according to some system of priorities.Finally, the available resources are allocated byestablishing an expenditure cutoff level in the rank-ordered list of decision packages; all packages abovethis cutoff line are funded. The mechanics of thisprocess are described in detail later in this Report.

A decision package identifies and describes aspecific activity in such a manner that the administrationcan evaluate and rank it against other activities, alsodescribed in terms of a decision package, competingforthe same or similar limited resources of money,manpower or facility. In addition, decision packagesmust include enough detail so that the administrationcan decide whether to approve or disapprove ther)quest for action on that decision package.

There are fundamentally three types of.decisionpackages. The first of these, the base package, satis-fies requirements for the minimum operating level ofthat particular activity. The second type of packageis mutually exclusive; these identify alternative methodsfor performing the same function. Of course, thebest alternative is chosen and the others are thendiscarded. Finally, there are :ncrernental packageswhich reflect different levels of effort that may be ex-pended on a specific function. The "base package"establishes the minimum level. The other decisionpackages identify higher levels of activity or higherlevels of cost.

In industry, Pyhrr found that Zero-base Budgetingis most appropriate when applied to service andsupport functions. In contrast, manufacturing activitytends to be determined by its sales volume, and theresulting production level then determines how muchthe company shall spend on labor, materials, andoverhead. In other words, it would be possible toincrease expenditures for manufacturing and therebyincrease production, but there is,no assurance thatthis would increase sales. Consequently, there is nosimple relationship between the cost and the benefit

of the activity under discussion. Hence. Zero-baseBudneting cannot be applied directly to manu-facturing operations as easily as it can to service andsupport functions. Put somewhat differently, Zero-base Budgeting finds its principal LISO in areas whereexpenditures are not determined directly by thecreations themselves. It is most helpful in areaswiere it is necessary to choose between differentactivities. or levels of activity, having different directcost and benefits. This would be in such areas asmarketing, finance, quality control, engineering,research, personnel, data processing, and so on.

is shown later that ZBB can be applied to allphases of the university operation. including academicactivities. Despite the superificial similarity to manu-facturing because of academic "production," academicactivities will be st- awn to have the same fundamentalcharacteristics as service and support activities.

The entire process of Zero-base Budgeting iscovered in extended detail later in this Report. Itshould be noted at this point, however, that ZBB isclosely related to PPBS PPBS tends to look atproblems from the top down while ZBB tends to lookat problems from the bottom up. Both depend uponclear statements of organizational objectives.

Objectives, Strategies and Tactics (OST)

This section deals with one method for handlingthe second part of the total budget, the strategic,budget. This is composed of items that are discre-tionary to current operations and which seek tooptimize long-term results. These are activities thatare related to growth. expansion, new programs andnew activities. Such expenses are always avoidableor postponable, in contrast to current operating ex-penses which are not. Not surprisingly, there is alwaysa tendency on the part of administrators to delay and cutback on strategic efforts every time an operating crisisoccurs or appears imminent. This is a hard adminis-trative decision. Indeed, one of the most basic questionsconfronting the administration is how to decide howmuch of the total revenue pool should go into currentoperations and how much into investments in thefuture in the strategic budget, Some assistance inmakieg this decision is given later in this Report.Unfortunately, very few universities have a strategicbudget so that the decisica seldom even comes up.

In business and industry, strategic budgeting iscrucial to long-term corporate success. Company assetsare deployed into activities which are expected toprovide significant returns from the investments inthe future. Univeisities have a semantic problem inthis connection because few administrators considerthe possibility of a return on investment. Budgetingis constrained primarily by the desire to retain whatcurrently exists.

The most effective syStem of strategic budgeting isknown as OST where the letters stand for Objectives,Strategies and Tactics. OST was the brainchild ofPatrick Haggerty and evolved during the time he wasPresident of Texas Instruments Incorporated. Haggerty's

9

aim was to systematize innovation oecause heclearly perceived that innovation is the essentialingredient of the strategic budget. He had noted thatthere were important similarities in the thoughtprocesses and procedures that had been followed inthe achievement of each major breakthrough at T.I.,whether in products or in processes. In each case,he found that major innovations had occurred whencompany leadership was able to focus on objectivesand goals without worrying too much about themethod and techniques, the strategies and tacticsinvolved in the achievement of these objectives.

In his plan, the word objective denotes broadly-defined, quantitative statements of intentions andpurposes. Strategies are then resource allocationsin selected plans designed to achieve an objective:they are long-term, general courses of action. Finally,tactics are short-term courses of action in supportof a strategy. These ideas, and their implementation,are covered later in much greater detail.

it should be clear frorn the hierarchical nature ofOST that a single objective could eventuate in a largenumber of tactical actions. These tactical actionsare then grouped together into logical, stand-alonedecision packrges of the same type as were used anddescribed in the discussion of Zero-base Budgeting.A decision package is ordinarily a simply statedproposal on a page or two outlining one or more TacticalAction Programs (or TAF's) for the use of funds ina short-term activity supporting a strategy. Duringthe long-range planning of the strategic budget, thesedecision packages are rank ordered by managementaccording to priority. It is then possible to decidewhich of these packages is to be funded into thestrategic budget. After funding, each package isreduced into one or more tactical action programs.

OST is a system for management planning, reviewand control which cuts across.organizational lines.And, it provides a mechanism for coupling long-rangestrategic planning to near-term budgetary operations.The details of OST are presented later.

Proposed Budgeting SystemSeven different methods for budgeting have been

described very briefly in the preceding discussion.While each of these appears to be a separate systemand while there are probably examples thatcan becited of some organization that uses one schemeexclusively, in the most practical sense all systemsand approaches should be used simultaneously. Atleast, that is tne position taken here.

The complete budget for a university, or any ofits subordinate units, should consist of two distinctparts:

(1) The operating budget which should be con-structed in accordance with the principles ofZero-base Budgeting.

(2) The strategic budget which should be con-structed in accordance with the principles ofOST.

Both of these techniques are discussed in much greater

detail in the sections that follow.Zerobase Budgeting techniques produce an oper-

ating budget in the form of a series of rank-ordereddecision packages in association with a projectedcutoff level for operating expenses. Similarly, thetechniques of OST produce a strategic budget in theform of a series of rank-ordered decision packagesin association with a proposed expenditure cutoff level.The two budgets together represent the total overallinstitutional expense budget, which is the sum of allthe expenses of both types of decision packagesappearing above their respective cutoff levels. Whenthe complete budget is presented in th;.3 form it iscomparatively easy to assess the impact of changes incutoff levels. Obviously, increasing the investmer,t inthe future by increasing the number of strategicdecision packages will cause a correspondingdecrease in funding of operating decision packages.The effects of such variations can therefore be assessedwith some precision and this is a considerable aidto budgetary decision making.

The most difficult decision in academic budgeting,in all budgeting for that matter, arises ai preciselythis point how to proportion expenditures, whereexactly to set the two cutoff levels. While there is nofinal easy solut,on, the techniques of ZBB and OSTbring the problem down to manageable proportionswhere understandable trade-offs can be made.

The merging of the two lists of rank-ordered decisionpackages achieves a number of desirable results.

(1) It assures that the desired balance is achievedbetween near-term and long-term objectives.

(2) Duplication of effort is minimized.(3) Fast growing aspects of the university do not

suffer because of lagging programs or activities.(4) It is useful in securing the best mix between

low risk, low payoff programs and those withhigh risks and high payoffs.

While these advantages are secured, it is still possibleto keep the investment in the future separate fromthe day-to-day pressures of the surplus and deficitconsiderations of the operating budget.

It should be clear that the combined approachesof ZBB and OST, with the decision package technique,provide rational and practical mechanismf, to carryout the intentions of Planning, Programming andBudgeting Systems. Thus, ZBB and OST add up tointelligent PPBS.

Each of the other four budgeting systems describedalso plays a role in this overall process. Consider thedecision packages and their rank ordering. It is clearthat the extent to which a decision package truly standson its own revenues is unquestionably a very importantfactor in establishing its priority at a high level com-pared to other decision packages which do notreflect ETOB. Thus, the attitudes associated with theETOB process manifest themselves in significant ways.

The Squeaky Wheel Gets the Grease appears tcsome degree in this plan also. The entrepreneurialability of department heads and deans to present theirdecision packages attractively and persuasively will

Part 2: Zero Base Budgeting 10

undoubtedly affect the rank-ordering process. Aggres-sive-and somewhat abrasive administrators may alsoaffect the final decision regarding the locations ofthe two cutoff levels

The development of decision packages alwaysinvolves'the consideration of alternatives. It alsorequiresihat estimates be made of the costs of boththe ,ecommencied solution and all its alternatives.It is in this process that. tae formula ry,sif.Lrr; an<iresource Allocation models firiti the.,because they provide sys??..ralficstandards for cost est;matillg. Even trich formulasor motels may be somewhat irnpren3se. e resultsare-more amenable to rational i.onsidR-f9.4,..)[ thanthose obtainable by any other method.

Finally, of course, the eventual decision on theactual expenditure cutoff levels, and the proportionbetween the two, can only be made by the King'sDecree.

To recapitulate. the proposed budgeting plan presented here involves a mixture of all seven budgetingsystems described briefly thus far: .

(1) SWGG yields imaginative decision packagesand ,affects the ranking.

(2) ETOB is a major consideration in rankingdecision packages.

(3) FMLA is used to provide a basis for costcomparisons between alternative decisionpackages.

(4) The King decrees the expenditure cutoff levels.(5) ZBB develops the operating budget decision

packages.(6) OST develops the strategic decision packages.(7) PPBS results from the foregoing.Detailed procedures for the use of ZBB and OST are

covered in the two major sections that fonow.

ZERO-BASE BUDGETINGThe general concepts underlying Zero-base Budget-

ing were presented earlier. It is the purpose hereto expand on those ideas in greater detail and to outlinethe general methodology developed by the originator,Peter A. Pyhrr.(' 33) Bear in mind that ZBB is appliedto the development of the current operating budget,not to the strategic budget. Thus, it deals with thosefunds necessary to maintain current operations. ZBBis primarily a decision-making technique rather thana procedure for budget management or control.

In its most general form, Zero-base Budgetinginvolves only three steps:

(1) Identify and specify all organizational activitiesor functions in terms of decision packages.

(2) Rank the decision packages in order of impor-tance according to some system of priorities.

(3) Decide where to cut off the funding of decisionpackages so that all packages above the cutoffline are funded.

While it is easy to make these three statements,their execution is considerably more difficult.

The process is spelled out in great detail here, atleast from the university perspective. Full implementa-

tion would probably be resisted by the faculty becausemost would feel that the process is too regimentedand complex with too much paperwork and emphasison detail. Such criticism may well be valid in somecases. The obvious answer is simply to streamline theprocess into a less formal procedure which still elicitsthe data necessary to rational decision- making, therebyretaining the essential concept while removing Someof the apparent operational complexity.

Identification of Decision PackagesA decision package describes a discrete actlitypty in

enough detail so that decisions about its relativeimportance can be made. Pyhrr(" n-51( identifies sixgeneral subject areas in which one might likely definedecision packages:

(1) People(2) Projects or programs(3) Service received or provided(4) Line item of expenditure(5) Cost reduction(6) Capital expenditures

The lao jive of these are fairly obvious. But that firstone people creates mental stumbling blocks rightaway. rynrr funned' observes that the problem is doublysevere because, "People are the most commonsubjects for decision packages because they bothspend money and create expenses through their wagesand salaries." Because the aim of Zero-base Budgetingis to improve effectiveness primarily by reducing costs,and because costs can be reduced by eliminatingdecision packages, and because "people" comprise alarge number of decision packages, it is not surprisingthat many people feel threatened by ZBB.

Pyhrr addressed this difficulty directly when heinstalled ZBB in the Georgia state system. Heobserved: (33. pp. 128-1291

"Some agency managers in Georgia challenged theeffectiveness of Zero-base Budgeting in state gov-ernment because of the potential impossibility offiring state employees and commented.that 'goodemployees terminate or qualify for transfers whilepoor employees hang on forever'. However, with a20 percent turnover rate experienced in manygovernment agencies, significant reductions cantake place as long as specific operations and jobsare designated to be reduced or phased out. Thiswill accomplish the major cost savings desired evenif there are a few 'hangers-on'."

Much the same objection to Zero-base Budgetingcan, and will, be made by the academic communitywhere the turnover of personnel is nowhere near 20percent per year. Granted that the application of ZBBwill be more difficult in academe than in business, it isnot impossible because there is some turnover and itstill offers many advantages not otherwise availableto the administrator.

The basic educational and general budget* of the

The E and G budget does not ordinarily include student hous:ng,food service, health services, student center, book store, inter-collegiate athletics, and all other expenses associated withauxiliary enterprises.

11

typical university rather closely resembles the operatingbudget of an industrial company. Both include twomajor components to cover (1) the producing oper-ations and (2) the service and support operations.The university's academic budget includes the costsof all academic departments of instruction, the libraryand computing laboratory, principal academic officers,and so on. Though it will probably make the professors.wince, this is closely analogous to the manufacturingpart, the producing operation, of an industrial budget.Similarly, the expenses associated with services andsupport in the university for all nonacademicfunctions which support the academic enterprisehave their exact service and support analogs inindustry and which support the manufacturing activity.In the university these supporting functions include suchthings as the registrar, admissions office, personneldeans and student services, physical plant operationand maintenance, and so on.

The reason for making these distinctions derivesfrom the fact noted earlier that the "services andsupport" function in industry has been found to bethe one most susceptible to Zero-base Budgeting.Correspondingly, it is reasonable to expect a similarsusceptibility for such functions in the university.

Pyhrr asserts that Zero-base Budgeting is moredifficult to apply to the manufacturing budget becausemanufacturing activity tends to be determined by sales.Moreover, at any given moment, unit manufacturingcosts are essentially fixed because wage scales areset, material costs and operating expenses are known.They may change, or new techniques may be intro-duced, but theso are essentially perturbations in thnsystem and can, in many cases, be handled as decisionpackages. The essential point is that the expendituresare determined primarily by the activity itself. As aresult, this is not a place where Zero-base Budgetingis particularly appropriate.

It would appear that similar considerations shouldapply to a university academic budget. In addition tothe "people" and tenure problems alluded to in theGeorgia effort, there is the added fact that studentenrollment (sales) largely determines the academicbudget. This is the basis for virtually all appropriationformulas and resource allocation schemes as notedearlier. Thus, the analogy to manufacturing operationsseems appropriate. But the situation differs from thatin industry because there is nothing immutable aboutmany of the components of the academic costs, noteven at a given instant. While faculty salaries maybe fixed, such factors as average class size, averageteaching load, and student-faculty ratio can be variedat will, producing wide variations in potential academiccosts. Thus, it would appear that academic mattersdo lend themselves to Zero-base Budgeting equallyas well as budgeting for services and support. Ofcourse, the tenure problem is a serious constraint, butone that can be accommodated if sufficiently long-time spans are used in setting objectives.

In the academic budget, decision packages shouldbe developed at the departmental level. This is usually

the lowest budgeted cost center and the departmentchairman and his faculty colleagues are more knowl-edgable about departmental activities and correspond-ingly best able to identify decision packages. Thisidentification process is a much more difficult problemin the purely academic departments of the universitythan in the service and support areas or in industry.

However, there are certain activities in academicdepartments which readily lend themselves to thedecision package approach. Not surprisingly, theseare primarily in the service and support functions whichthe department provides for itself, for others, orpurchases from someone else. These include suchthings as secretarial and technician services, travelrequirements, duplicating and copy services, and soon. Another type of fairly obvious decision packagesare those proposing to add something or to changesomething already present. Examples include a pro-posal to add a new faculty position, or to build, expandor change a laboratory facility.

The almost invariable first tendency among academicaaministrators is to conclude that each faculty membermust be treated as a separate decision package.This is a fairly natural inclination because it is anarticle of faith in universities that individual facultymembers are central to all university accomplishments.But this generally proves unworkable. For example,decisions on tenure, promotion and, in some cases,in decisions involving continuance rf a nontenuredfaculty member are major strategic decisions. Butthere are usually well-established university criteriaand procedures dealing with these matters that, quitebluntly, resist conformance to the decision packageformat. And, of course, if a faculty member already hastenure no "decision" is involved given presentcircumstances.

Moreover, one aim of Zero-base Budgeting and thedecision package approach is to allow considerationof varying levels of support for each activity, increasingincrementally above some minimum level, It is difficultto apply this concept to the case of a single facultymember. Thus, although faculty can be involved indecision packages, either singly or in groups, thedecision package should not be defined in terms ofa single faculty member.

There is a way out of this apparent dilemma. Everyacademic department tends to be a collection of sub-disciplines. These may arise simply from administrativeconvenience, or they may represent traditional sub-divisions of a classical discipline with a long historyof acceptance. Each of these subdisciplines is definedby a grouping of several courses associated withat least one faculty member, but with as many as two,three,.or four, or more in other cases. Decisionpackages should be developed for each of theseactivities within the department although cases do arisein which entire departments or even schools may betreated as decision packages.

But consider the definition of subdisciplines asdecision packages. For example, an electrical engi-

12

neering department might be defined in terms of thefollowing main subject areas:

(1) Electronic/Electrical Materials(2) Electronic/Electrical Devices(3) Quantum Electronics and Electromagnetics(4) Networks and Circuits(5) Information and Communication(6) Comput&rs(7) Large-Scale Electronic/Electrical Systems'8) Societal Systems(9) Biomedical Technology

Each of these areas typically involves the attention ofone or more faculty members. Depending upon institu-tional objectives and environmental constraints, anacceptable Electrical Engineering Department couldbe defined which did not include all of these areas.For example, many departments currently exist whichdo not include items (1), (7), (8) and (9). These areappropriate activities for description in decisionpackages.

Other departments can be partitioned in similar waysfrom convenient decision packages for activities. Forexample, the activities of a Mechanical EngineeringDepartment might be specified in terms of the followingareas:

(1) Mechanical Design(2) Thermodynamics and Statistical Mechanics(3) Heat Transfer and Transport Phenomena(4) Fluid Dynamics(5) Lubrication Theory(6) Thermal System Design(7) Materials Engineering and Metallurgy(8) Control Systems(9) Solid Mechanics

(10) Gas DynamicsSimilarly, a Department of Computer Science andOperations Research could be defined in terms of thefollowing:

(1) Computer Systems Software(2) Digital Hardware(3) Deterministic Models and Techniques(4) Stochastic Models and Techniques(5) Information Systems(6) Mathematics of Computation

Specification of Decision PackagesAs noted before, decision packages are developed

around discrete functions or activities or, in specialcases, around people. Once these are identified itis necessary to clearly delineate their purposes orobjectives. The specification of the decision packagethen begins with an exploratory phase. First, an analysisis made of all of the possible ways that the objectivesmight be achieved. The "best" one, however defined,is chosen and recommended. Second, with therecommended method established, the effects of dif-ferent levels of effort must be analyzed and understood.Finally, a minimum level of effort must be identified

'These are nonunique, but consistent. Energy and power tech-nology are not included as separate areas because they areassumed to be included in various other areas such as electro-magnetics, systems and societal technology.

which will attack the most important elements of thefunction or activity. even though the purpose of thefunction may not be fully achieved at this minimumlevel. This defines the decision package for theminimum level of effort. Except in rare cases, theminimum level of support so identified should alwaysbe less than the current year's level of support.Additional levels of support are identified as separatedecision packages.

The complete written specification of a decisionpackage should be reduced to a single page. or twopages at most, and must include the followingcomponents:

(1) A statement of goals, purposes, objectives orintentions of the function or activity or peopleassociated with the decision package.

(2) The program. or course of planned actions,by which the objectives are currently or willbe achieved.

(3) The benefits and achievements to be expectedfrom the planned actions.

(4) Consequences of not approving the package.(5) Quantitative measures of performance appro-

priate to the actions of the package.(6) The expenditure of funds, personnel and other

resources needed to implement the activity. Alsonecessary to show the sources of the fundsrequired.

(7) The alternatives to the recommended decisionpackage:(a) Different levels of effort, but following the

same action plan.(b) Different ways of performing the came

function.

The key point in formulating a decision package is themaintenance of a clear focus on the benefits derivedfor a given cost what is accomplished at wha'cost. A sample form for use in defining academicdecision packages is shown in Figure (1).

The formulation and specification of decisionpackages is a very difficult process, especially the firsttime. Pyhrr(") identifies six difficulties that commonlyarise in the process.

(1) It is difficult to decide which activities. functions,or people should be described in terms of adecision package.

(2) It is difficult to define the minimum level ofeffort as being be/ow the current level. Thedifficulty is that people then naturally assumethat this minimum level will become the actuallevel of support. This will occur in some cases,but not all. It is not a precise level. For anacademic department it could be defined asthat level necessary to support the minimumacceptable and survivable program in its par-ticular environment. What is minimally acceptableand survivable are tough questions to facesquarely, but they can be answered approxi-mately even if the answers are unpleasant.For example, in engineering, a minimallyacceptable and survivable program must include

13

the B.S. and M.S. levels but not necessarilythe Ph.D.

(3) It is difficult to avoid the tendency to try to keeppersonnel requirements at current levels, evenwhen overall costs are being reduced. Thereduction of needed incidental expenditureswhile keeping unnecessary people is a commonproblem which can effectively cripple organi-zational effectiveness.

(4) It is difficult to identify meaningful quantitativemeasures of performance. Even when they aredefined, it is often difficult to find adequatehistorical data. This is a particular problem inmost universities which have inadequatemanagement information systems.

(5) It is difficult to estimate costs associated withdecision packages. Formulas can be used here,though they are often of dubious validity.

(6) It is difficult to identify cost reduction potentiali-ties within the action plan described for eachdecision package.

The general procedure for the specification ofdecision packages is basically a three-step processaccomplished within initial constraints specified bythe top administration. Thus, in consultation with

deans and other advisors, the president of the universityis expected to issue a formal set of assumptionsregarding enrollment levels in various schools andat various levels, estimated revenues from tuition andfees. gifts and endowment. state and federal' or othergovernmental funding. projucted wage and salaryincreases. and so on. With these established. decisionpackage formulation proceeds in three steps:Step 1 As described earlier. current operaticns are

analyzed and separated into discrete decisionpackages.

Step 2 These packages are identified basically as"business as usual" packages, because theymerely cast this year's operations in termsof next year's costs,-using the assumptionsissued by the president.

Step 3 These "business-as usual" packages areseparated into two categories:(1) True "business as usual" packages in

which no variations are possible orjustifiable as far as the department heador dean can see. This would include allthose people on tenure, for example.

(2) Alternatives to "business as usual"packages. These decision packages

FIGURE 1

Sample Form Used for Defining Decision Package

PACKAGE NAME SCHOOL OEPARTNENT ACTIVITY RANK

STATEMENT OF PURPOSES OR OBJECTIVES OF DECISION PACKAGE

PROGRAM, OR COURSE OF ACTIONS, TO ACHIEVE OBJECTIVES

BENEFITS AND ACHIEVEMENTS EXPECTED FROM THE PLANNED ACTIONS

CCNSEQUENCES OF NOT APPROVING THE DECISION PACKAGE

QUANTITATIVEPACKAGE

MEASURES (PROGRAM)

FY FY FY RESOURCES MIMEDS IN THOUSANDS

FY FY FY

SALARIES, WAGES

CAPITAL OUTLAY

EXPENSE/SUPPLY

TOTAL

PWPLE (NUMBER)

Front

PACKAGE NAME SCHOOL DEPARINENI ACTIVITY RANI:

ALTERNATIVES (DIFFERENT LEVELS OF EFFORT AiN1 COST)

ALTERNATIVES (DIFFERENT WAYS OF PERFORMING THE SAME FUNCTION)

SOURCE OF FUNDS$ IN THOUSANDS

FY FY FY FUTURE RESOURCE NEEDS

Federal

Salaries, Privateand Wages

S.M.U.

Federal

Capital PrivateOutlay

S.N.U.

federal

Expenses. PrivateSupplies

S.N.U.

Back

would consist first of a base packagerepresenting the minimum level of effort.and incremental packages whichdescribe different levels of effort ordifferent ways of securing the objective.Remember that. in almost every case, the"minimum level- of effort should beless than the level for the current year

The next step requires that all of the decision pack-ages so developed be ranked in order of priority. Thisprocess is described in the next section.

The Ranking Process,' )

The various decision packages are developedinitially at the cost center level at the departmentallevel and their nonacademic counterparts in auniversity It is :.fen necessary to rank all of thesedecision packages to be able to answer two questions.

(1) How much money should the university spend onits operations?

(2) Where should the money be spent?

It is obvious that the ranking could be done at thepresidential level where overall university goals arepresumably known and appreciated, or at the depart-mental level where the greatest degree of informedjudgment can be brought to bear. Each of these pos-sibilities is beset by its own unique and fairly obviousproblems. including the lack of detailed expertknowledge in the president's office and the tendencytoward the parochial view in the department.

Consequently. ranking is best accomplished throughconsolidation as the decision packages move upwardthrough the administrative hierarchy of the university.That is, the department heads submit their rank-ordered decision packages to the dean. The deanconsolidates all of his departmental decision packagesinto one consolidated. overall rank-ordered list. Thisconsolidation in ianking is probably best made bya committee of the department heads with the deanserving as chairman. The final rank-ordered list is thentransmitted to the president. The president consolidatesthe deans' lists similarly in a committee composed ofthe deans, with the president serving as chairman.The final rank-ordered list is then transmitted to thegoverning board.

It is obvious that this process leads to an excessivenumber of packages to be considered and rankedat the presidential level. Moreover, many packagesare required. either legally or operationally; no decisionis really involved in such cases and there is no reasonfor administrators to waste their time worrying aboutthese types of decision packages. Consequently, somecutoff method must be introduced to limit the numberof decision packages requiring detailed considerationat any level. This cutoff procedure is described inthe next section.

The rank-ordering process is extremely difficult inany case, but the use of committees, as describedearlier, would render it impossible if unanimous agree-ment or ranking was required. Obviously, some sortof voting mechanism must be used. The simplest plan

is to give each committee member one vote on somenumerical scale of points Then ranking is made inaccordance with the number of pomts the committeevotes for that decision package A sarnple ballot isshown in Figure (2) Pt-4W -1 stales that ballots withan even number of points say 6. 8. or 1.0 are bestbecause they force a decision. it is not posstlelo betotally neutral by voting directly at the mid-point aswould be possible on a scale of 5. Of course. muchmore complex voting schemes could be use. withvoting on several criteria But the problem is difficultenough. particularly at the outset. and further compli-cations should be avoided where possible. It isprobable that the committee chairman. in each case.should have two or three votes. depending upon thecommittee size

The ranking and voting process is also madedifficult because everyone involved knows that thefunding requests are virtually certain Ito exceed availablerevenues. Moreover. almost all requests have somedegree of legitimacy given the usually cloudy andimperfectly stated goals of a university. Additionally,there tend to be a great many moral or implied demandson the available revenues. further limiting the rangeof choice. Finally, universities seldom have anywell-defined methods of program evaluation andgenerally resist all attempts to introduce them. Yet.evaluation is the crux of the budgeting process.The difficulties must be accepted, but they cannotbe used as an excuse not to evaluate. Rational budget-ing by any process requires systematic evaluationthis is obvious n ZBB. Unfortunately, most presentbudgeting is not rational and evaluation is notsystematic.

FIGURE 2

Sample Voting Sailor

Packages ranked here must be funded because(1) they satisfy minimum legal or operating

requirements(2) they have a high probability of significant

impact

Packages here have some probability of impact.but would be the test to cut if the expendituregoal is reduced

cutoff level

Packages here have some probability of impact.and would be the first to be added if the expendi-ture goal is raised

Packages ranked here should not be consideredseriously given projected expenditure goals

Adapted from p. 118 of Ref. 33.

Interaction analysis may be a useful aid in the rankingprocess The process involves two types of matricesas shown in Figure (3). a self - interaction matrix anda cross-Interaction matrix. For example, the interactionamong the faculty members (indicated by A. B. P)in a given department could be displayed with a self-interaction matrix. If Professors A and B interactstrongly. an X would be appropriately placed in thematrix On the other hand, a cross-interaction matrixcould be used to analyze the degree of interactionbetween faculty members (A, 8, C. etc.) in one depart-ment and those 11, 2, 3, etc.) in other departments. Thesell-interaction matrix is appropriate in analyzing themajor subject area divisions within a department whichprovide the basis for many decision packages. Thecross-interaction matrix is useful in assessinginteractions such as:

(1) between subject areas (decision packages) indifferent departments

(2) between subject areas and degree programs(3) between subject areas and faculty members

While this process reveals nothing new, it doessystematically display what is known and assists in theassessment of the compeTative importance of variousfactors. This assists in the ranking process. Obviously,for example. a subject area which interacts Slightlywith only a few degree programs would receive a lowrank among decision packages.

The Cutoff Process('The chief executive officer of he university. president

or chancellor as appropriate, mist estimate We expensethat might be approved by the governing board. Thisestimate is derived in part from his estimates of

-s119/ 15

revenues He must then make a tentative first decisionregarding how much of this total revenue can be appliedto the operating budget and how much as a result.Is available for investment in the future in the strategicbudget It is precisely here that rational universitybudgeting usually breaks down because very, veryfew {if any) aniversities have any funds generally_available for a strategic budget Revenues from tuition.research, gifts and endowment are nearly alwaysvirtually committed in total to sustaining current opera-tions Investments in the luture. if any. depend uponthe relative success of the entrepreneurial activitiesof faculty and deans with private foundations.

As a result, it is obvious that the budgeting plan pro-posed here can only be implemented gradually over aperiod of 10 years or so. For example, in the first year,perhaps only hall to one percent of the total revenuemight be assigned to the strategic budget. But itwould be a start, and it could be increased possiblyhalf to one percent per year unto it reached ten percentor more.

With the operating budget revenue thus estimated.the president then defines an expense cutoff point toapply to the administrative level below him, at thedeans' level or other equivalent operating divisioninvolving several cost centers. finis cutoff level is lessthan what he expects to be approved, say X percent ofwhat the governing board might reasonably beexpected to approve for the operating budget. X mightbe about 80 percent, for example. This allows somefreedom later in making trade-offs between divisionswhose packages are being ranked relative to oneanother. It permits similar trade-offs to be madebetween the operating budget and the strategic budget.

FIGURE 3

interaction Matrices

B

C

O

E

F

K

N

O

p 0 N M txji H GF E bCEI A

O no anteraction

xx

moderate interaction

Fistrong interaction

C

D

E

F

J

K

N

40

1 2 3 4 5 6 7 8 11 10 11 12

noInteraction

amoderateinteraction

stronginteraction

t6

Each dean or operating division head is then givena preliminary total expense allowance for the yearto use as a target in his budget p'- ing This could bedetermined T. sevi ZI ways It might simply be lastyear s expense budget for operations Better couldbe his share of the projected revenue pool based uponforecastS of enrollmer I research and gifts Addition-ai ly the X percent cutoff level is specified

At the dean s level or the level of other major aurnin-istralive units a cutoff point of Y percent is set Y isalways less than X In fact Y should be significantlyless than X as for example X might range from between60-85 percent while Y might i ange between 60-65percent This process allows the exercise of discretionand trade-oils al each level above the original costcenters The amount ol flexibility depends upon thevalues selected t N' X and Y In universities these shouldprobably be larger than industry because there is lessflexibility in universities through the effects Of tenureand other spec'dlized constraints which greatly limitthe range of ari,ministrative discretion

In the cons iliclation process the packages stoveupwards thriugh the hierarchy The packages sub-mitted from the departments to the deans. or otheradministrative officials. are reviewed and the top on.:(totaling Y percent of last years budget, are skimmedoff and checked for reasonableness The remainderare then consolidated evaluated. and ranked andhanded up to the president Obviously, all packagesranked above the Y level wilt be funded In addition.many of those tailing between the X and Y levels

will be funded depending upon how they fare nCompen on with those from other units

With ti e cutoff level set at X percent the prs?sidentlooks over the package rankings handed up to himfrom thr deans ani nis other administrative heads

irst r C skims oil the highest-ranked ones until theirexpenditures total X percent of last year s budget forthe area in question These packages are then quicklyreviewing for general reasonableness The remainfngpackages are tnen examined carefully. ranked andpassed up to the governing board along with the other,-These are the more discretionary packages and thefinal budget is determined by Board action in decidingwhere ft will draw the actual cutoff level and which ofthese decision packages it will fund The overallprocess is shown schematically in Figure (4) The finallevel set will depend upon the relationship betweenthe operating budget and the strategic budget 11 isobvious that approval of more operating decision pack-ages will reduce the number ot strategic packagesthat can be funded

It is clear that this process allows attention to beconcentrated on those packages at the Cutoff levelsand keeps the total number of packages that need tobe ranked within manageable proportions at eachadministrative level Simultaneousty, it allows eachadministrative level some flexibility so that trade-offsare possible and administratove discretion can beexercised This is possible with competing operatingdecision packages and with strategic decisionpackages

FIGURE 4

The Cutoff and Consolidation Process'

-From Ref 33. p 118

President s levelHighest ConsolidationLevel

Deans LevelLower ConsolidationLevel

Department LevelCost Center

Examples of University Decision Packages

PACKAGE lik7' SCHOOL DEPARTMENT ACTIVITY RANK

CS & 01? o-crutcy. ..,7:clo*,ecComputer so,ftware Faculty ICS'_

STATEMENT OF PURPOSES OR I.JECTlVES OF DECISION PACKAGE

Strengthen and provide leadership in the area of computer systems softwarein research activities and educational programs (B.S., M.S., and Ph.D.) ofthe Department of Computer Science and Operations Research.

PROGRAM OR COURSE OF ACTIONS TO ACHIEVE OBJECTIVES

Rgaruitment of a faault:f member in the Computer Systems Software area withthe rank of a Pmfessor with Tenure.

BENEFITS AND ACHIEVEMENTS EXPECTED FROM THE PLANNED ACTIONS

(1) Increased teaching capability in the computer software area.(2) Younger faculty win get relief from advising a Large number of graduate

stu4ents.(3) Provide research Leadeeehip for younger faculty.(4) Increased prospects of obtaining research funds,

.....k .....11......elLivgyiatEAPUENCESOFIVINGTHEDECISIONPACKAGE

il) Lack of leadership in computer software area.(2) Deterioration of standards, through tack of experience.(3) Deterioration of standards, thipvugh overburden to younger faculty.(4) Dim prospects of obtaining research funds.

QUANTITATIVEPACKAGEMEASURES

FY74/75

FY75/76

FY

76/77RESOURCES REQUIRED$ IN THOUSANDS

FY74,175

if75/76

FY

76/77

NO. OF PH.D.'S PRO-DUCED

2 4 -ALARIES. WAGES 28.9 30.3

NO. OF M.S. STU-DENTS ADVISED 10 12 12 CAPITAL OUTLAY 3 -

NO. OF SCH'S PRO-DUCED 210 240 270 EXPENSE /SUPPLY b 6.5

EXPECTED RESEARCHFUNDING IN

13.5 32.1 41.2 TOTAL 36.5 35.4 37.3

IN THOUSANDS - PEOPLE (NUMBER) 1 1 1

18

PACKAGE NAME SCHOOL

Computer Software Faculty IDT

DEPARTMENT

CS 6 OR

ALTERNATIVES (DIFFERENT LEVEES OF EFFORT AND COST

ACTIVITY

Computer Science

(1) hecruitment of a faculty member in the computer software area at theAssociate Professor level. Cost: $24,ZOD BaCQUae Of the aspect,F;of leadership and experience, benefit ratio between this alternative andthe course of action will be much smaller than the cost ratio = 2/3 approx-imately.

(2) Recruitment of a faculty member at the Assistant Professor level - unaccept-able bemuse of reasons stronger than in (1).

ALTERNATIVES (DIFFERENT WAYS OF PERFORMING THE SAME FUNCTION

(3) Ate of Visiting Professors 40 Instructors in courses. Does not solve theproblem of the tack of leadership.

ff) Encourage students to work in other areas. This may result in turning manystudents way from our Department.

($) Appoint a Visiting Professor on a short-term basis. This will not give con-tinuea' strength to the area.

SOURCE OF FUNDS FY FY ,FY FUTURE RESOURCE NEEDS$ IN THOUSANDS 74/75 75/76 76/77

Federal 10.5 28.6 37.2

Salaries, Private 7

Continued salary supportincreasing annually at

about 6%.

and WagesS.M.O. 10 0.3 sINE,

Federal

Capital Private 1111.

OutlayS.N.U. MID

Federal 3.5

Expenses, PrivateSupplies

S.N.U. 3 3

PACKAGE NAME SCHOOL DEPARTMENT ACTIVITY RANK

lOTDu.licatinc Lab

ISTATEMENT OF PURPOSES OR OBJECTIVES OF DECISION PACKAGEI .

To provide duplicating and copy service at one central location for thedepartments of the it at a mtnitum cost and best acceptable quality.

Etymalpit COURSE OF ACTIONS, TO ACHIEVE OBJECTIVES

(1) Install a XEROX 7000 with metered usage and reitction capabilit:es to providecopy service for departments. Also, provide 30 bin sorter for collatinglettere, reports, eta., which will reduce labor-time spent with presentequipment without any sorting attachments.

(2) /natal an inexivneive ($275 to $250) Ditto machine in each of the depart-menta to pmei4e alma notes), test papers and other duplicating items notrequiring better quality oopy.

BENEFITS AND ACHKVEMENTS EXPECTED FROM THE PLANNED ACTIONS

(1) The features of the XEROX 7000 allow greater versatility; can reproduce allthe work pesently being done on seven (7) machines.

(2) It permits two-sided copping, colored stock and copies onto letterhead stack.(3) Addiaonat benefits are no master preparation, no shined operator, no capi-

tal invextment, reduction of oversi4ed originals, no obsolescence and fewerservice and supply problem.

(4) Service will be available on a 24-hour-a-day basia, rather than 40 hoursper week.

CONSEQUENCES OF NOT APPROVING THE DECISION PACKAGE.

The present standard of service and quality is not acceptable but would be contin-ued if this package is disapproved. Pe are dependent upon commercial repair, and',service for the off-set printer, master-maker, mechanical collator, ditto duplica.tor, and the thermo-fax machine. The XEROX 720 and IBM copier are rentedam!ser-vicedby those companies. There are no back-up machines nor operator. The "turn-around" time for service is from one to eight working hours. There are periods ofdelays from one to three days, when the operator is absent.

QUANTITATIVE

PACKAGEMEASURES I

FY70/71

FY71/72

FY72/73

RESOURCES REQD.$ IN THOUSANDS

FY70/71

FY71/72

FY72/73

TOTAL COPIES 1277.000 283,330 280.000 SALARIES, WAGES 8 6 -

CAPITAL OUTLAY 1 3 1

COST PER COPY .065 . .05 EXPENSE/SUPPLY 9 8 13

TOTAL 18 17 14

PEOPLE (NUMBER) 1.5 1.5

20

PACKAGE NAPE SCHOOL

Duplicating Lab IOT

DEPARTMENT

ALTERNATIVES (DIFFERENT LEVELS OF EFFORT AND COST)

(1) Discontinue the ditto duplicating and replace with one (1) IBM Copier near thehigh-volume user. Additional expense estimated to be $200 per month. Discon-tinue both offset and ditto processing,expense estimated to be 0450 per monthfor two (2) IBM copiers.

ALTERNATIVES (DIFFERENT WAYS OF PERrORNING THE SAYE FUNCTION)

(2) Discontinue the offset operation and route all orders to the printshop. Costper copy will increase due to minimum copies of WV per run.

(3) Discontinue the ditto operation, and allow the departments to procure theirown Ditto machine, supplies, etc., and arrange for the work to be done bythe secretaries and/or students. It is doubtful if any savings would berealizes; because maintenance would increase and higher-paid personnelwould be spending their time on duplicating.

(4) Persuade the University to set up a central copy center in our area to ser-vice engineering and other colleges surrounding. Doubtful at this timethat resources would be availabte to the University for such an installa-tion.

SOURCE OF FUNDS$ IN THOUSANDS

(*) Federal

Salaries, Privateand Wages

S.I.U.

CapitalOutlay

(*) Federal

Private

SAD.

(*) Federal

Expenses, PrivateSupplies

S.M.U.

FY

70/7FY

71/7

(*) Estimated Cross-Charged to Grants /Contracts.

FUTURE RESOURCS NEEDS

21

PACKAGE NAME SCHOOL DEPARTMENT ACTIVITY RANK

Industrial Engineering TOT CS & ORB.S. and 11.5.

programs in I.E.

STATEMENT OF PURPOSES OR OBJECTIVES OF DECISION PACKAGE

Maintaining an Industrial Engineering Program that will satisfy the needs of theNorth Texas. region (oriented towards computer sgstema, operations research andmanufacturing engineering).

PROGRAM, OR COURSE OF ACTIONS, TO ACHIEVE OBJECTIVES

To offer a program accredited by the Engineering Council for PropsolonalDevelopment (ECPD).

BENEFITS AND ACHIEVEMENTS EXPECTED FROM THE PLANNED ACTIONS

(1) Satisfy the needs of the region by training graduates in I.E. oriented towardscomputer systems, operations research and manufacturing engineering.

(2) An ROD accredited program is valuable to students for future employment.(3) Chances of attracting a larger number of students are better.

ISIKEItcpjWHAMCOhliGliCKAGE(1) Lack of ECPD accreditation may handicap students in future employment.(2) Lack of ECPD accreditation may result in decreased number of students.(3) If offered under Systems Engineering Program, problem of identification may

arise.

QUANTITATIVEPACKAGEMEASURES (PROGRAM)

FY

73/74FY

74/75FY

75/76RESOURCES REQUIRED$ IN THOUSANDS

FY

73-74FY

74-75FY

75-76

NUMBER GRADUATING(B.S.) 3 5 16 SALARIES, WAGES 17.5

---,,

23 24.2

NUMBER GRADUATING(14..S.) 2 5 5 CAPITAL OUTLAY 2.5 - -

NUMBER OF STUDENTSIN U.G. PROGRAM 25 40 65 EXPENSE/SUPPLY 6 6.5 7

NUMBER OF STUDENTSIN M.S. PROGRAM

2 5 5 TOTAL 26.0 29.5 31.2

PEOPLE (NUMBER) 1 1 1

PACKAGE NAME SCHOOL DEPARTMENT ACTIVITY RANK

B.S. & M..Industrial Engineering IOT CS & OR Progrm in

ALTERNATIVES (DIFFERENT LEVELS OF EFFCRT AND COST)

(1) Add two more Industrial Engineering faculty. It would strengthen the prograin

considerably. Additional cost will be about .25,000 per year. Return

is unlikely to be anywhere near this range. This alternative unacceptable.

ALTERNATIVES ( DIFFERENT WAY:.> Uk PERFORMING THE SAME FUNCTION)

(2) Offer the same programs (I.E.) without concern for ECPD accreditation. Butit will affect student enrollment. Accreditction is crucial in many employ-ment categories.

(3) Offer the same programs under the accredited program of System Engineering.There may be some dissatisfaction among students who would prefer to becalled industrial Engineers.

SOURCE OF FUNDS$ IN THOUSANDS

FY

73/74

FY

74/75

Federal 9

Salaries, Private 12 8.5

and WagesS.M.U. 1.5

Federal

Capital PrivateOutlay

S.M.U. 2.5

Federal

Expenses, Private

SuppliesS.M.U. 6 4.5

FY

75/76

10

8.7

5.5

2.5

4.5

FUTURE RESOURCE NEEDS

Clearly, continued funding from

private sources (foundation)

would be needed.

Part 3: Objectives, Strategies and Tactics 23

OBJECTIVES, STRATEGIES AND TACTICSZero-base Budgeting, as described, is a decision-

making technique for dealing with the operating budget.But a different approach is required for the StrategicBudget which attempts to manage charge. Changingthe level, scope or character of activity within anorganization is the purpose of the strategic budget.Accomplishment of these changes requires systematicattention to the following:

Objectives Broadly defined quantitative state-ments of intentions and purposes.

Strategies Long-term general plans of actionsaimed at the achievement of an objective; resourceallocations in selected plans.

Tactics Short-term action programs in supportof a strategy.

The purpose of the OST technique developed byHaggerty* is to make organizational objectives clearthrough documented quantitative statementsstatements that ideally are aw) "shocking challenge tojolt rnanagers away from traditional, in-a-rut thinking."The chance for innovation is enhanced by separatingthe setting of Objectives from the methods for achievingthem, through separation of Objectives from theStrategies and Tactics.

Before moving into a simplified explanation of OST,a short digression is in order to clarify the distinctionsbetween the words "goals" and "objectives." Thus,about the first third of the discussion that follows isdevoted to goals, objectives and intent structures. Theremaining two-thirds present a simplified summaryof the techniques of OST.

Goals and ObjectivesThe budgeting process is fundamentally a formal

system for the allocation of institutional resources.These commitments of resources obviously have im-.portant effects upon the subordinate units in theorganization, effects that are complex and which oftenpropagate in many directions through the. organization.

.It is obvious that decisions allocating resources willbe most beneficial when made to conform to well-defined organizational goals. Moreover, the existence ofwell-understood goals at the top permits every levelwithin the organization to formulate its goals so that allcomponents are working together toward commoninstitutional goals.

There is generally a great deal of confusion regardingthe usage of the words "goals" and "objectives" be-cause they tend to be used interchangeably. However,for the purposes of this presentation it is necessaryto make a rather precise differentiation between the

'meanings of the two words. This will be done shortly. Inthe meantime, it is assumed that objectives andgoals are two different types of intentions.

Various management methodologies attach differentmeanings to these words. For example, the techniqueof Objectives, Strategies and Tactics, as used by TexasInstruments, depends upon intentions stated in quanti-tative terms within specified time frames. In contrast,

'Patrick E. Haggerty, Chairman of the Board, Texas InstrumentsIncorporated.

in the theory of intent structures as developed by War-field(') it is necessary to state organizational intentionsin both quantitative and nonquantitative terms whichignore time frames. Yet, both techniques use the words"goals" and "objectives" essentially interchangeably.It seems necessary to remove such ambiguities.

It is essential to note that the plural has been used inall three words intentions, goals, and objectives.Complex organizations, such as universities, are charac-terized by a complex multiplicity of interrelatedintentions. Not surprisingly, the formal expression ofinstitutional intentions and the description of their inter-relationships is an extremely difficult process. It is sodifficult, and people generally object to the process sovehemently, that many institutions simply do not haveclearly defined intentions against which daily actions, oreven long-range decisions, can be evaluated.

The process is made very difficult by a series ofattitudes and factors summarized by Warfield.P) For ex-ample, he notes that there is nearly always confusionbetween "goals" and "objectives," over whether one islong range and the other short, or whether one ismeasurable and the other is not. Consequently, all toooften, attempts to define intentions bog down intoarguments over these matters and, as Warfield says,"Nothing gets done."

To avoid that difficulty in this exposition, the meaningsattached to these two concepts are differentiated asfollows:

(1) A goal is a statement in the following form:To (action word) (object) (qualitative modifyingphrase)

For example, the following statements are examplesof goals.

To prepare students for professional careers.To pursue research fundamental to national needs.To provide students a basic liberal education.

Goals are axiological intentions because their at-tainment is a matter of subjective judgment.

(2) In contrast, an objective, as used here, denotesan intention whose degree of achievement can bedetermined by comparison with specific ob-jective measures, very often within specific timeframes. Thus, objectives are statements inthe following form:To (action word) (object) (quantitative modifyingphrase).

For example, the following statements of intentionsare objectives.

To increase freshman enrollment by 10 percentin two years.To reduce utility costs by $10,000 in six months.

It is not always necessary to include a time frame.For example:

To reduce vandalism in the dormitories.This is a measurable intention and is an objective asdefined here; the objective measure is not specif-ically identified, however.

Thus, in this presentation, objectives denote measur-able intentions.

The foregoing distinction between goals and ob-

24

jectives is reasonably consistent with the fine differencefound in the dictionary. There we find that a goal isan end, or a final purpose; the line or place at which arace is ended; an end to be achieved. In this sense,goals represent ideals, or pinnacles of aspiration for theorganization, in contrast, objectives are not ends. In-stead, their achievement marks progress towardidealized intentions.

Intent StructuresWarfieldio notes that many people are reluctant to

discuss institutional intentions because of the semanticdifficulties just noted. In addition, they often feel thatorganizations and people have intentions and valuestructures they do not wish to discuss. This may be be-cause the statement of these intentions or valuescould lead to discord, conflict and divisiveness. Thus,these people feel that there is an "invisible intent"structure that can never be formally and publicly iden-tified. Other difficulties originate because peoplequite generally find it difficult to state theft goals; othersprefer to concentrate on actions; still others worryover who "owns" what goal and how these differentowners may be brought into conflict. Despite these ob-jections, large, modern organizations must haveformally stated coals. Organizations without clearlydefined goals floi.inder. As Grant Dovel321 put it:

We believe that few things can paralyze an organiza-tion more than uncertainty about the strategies andvalue systems of the chief executive. It is also true that

uncertainty about goals at any level of organizationhas a paralyzing effect, not only on that particular unit,but also on its role with other units.

When goals are lacking, or not clearly expressed,conflicts may occur at middle management levels andlead to compromise solutions which are invisibleto top management and not in the best interests ofthe corporation."Warfield (3) explains that mci of these problems can

be overcome, or at least minimized, through the meth-odology of intent structures. An intent structure is amultilevel, hierarchical array of goals. Objectives mayalso be included in the overall intent structure. How-ever, it is generally best, particularly in the early stagesof goal definition, to omit any consideration of time,or comparative time phasing. Thus, time constraintsappearing in objectives should be neglected at thisstage. Accordingly, the general term intentions is usedin this discussion to denote both goals and objectivesspecified without constraints of time.

A modern university is characterized by a multiplicityof intentions. These are interconnected so that somereinforce others; others are independent of one another.Thus, a hierarchy of intentions can be discerned andshown as -a graph. An example of part of such a graphfor a university was given by Warfield(3) and isreproduced in Figure (5). This is E special type of graphknown to mathematicians as a tree for reasons obviousfrom an inspection of Figure (5). Although the treeform is fairly common, it is probable that most graphs

FIGURE 5

Part of a University's Objectives Tree

To develop self-renewing people

To assiststudents to relateto their world

To provideCOhtinuOua: :education for

'graduates

To preparestudents who willbe functional incivic affairs

6

To establish;credit grantingprograms foroarticioatiOn in

. studentgOvernment

1

To establishinternship/cooperativeeducationprograms

12

To help eachstudent establishhis identity

To meet thepersonal, emotional,psychological needsof the student in aliving, seamingenvironment

7

To provide anenvironment Mwhich the studentsbelonging needsare satisfied In aconstructive way

13

To preparepeople capableof adapting tochange

4

To stress self-initiation oflearning

To teach eachstudent how toplan, starting withhis owneducation

14

To provide abasic and broadliberal educationthat prepares theIndividual to adaptto new situationD

9

To build future-orientedprograms

10

25

of organizational intentions are not simple trees.The relationships between the various intentions may

be any one of three types:

(1) To attain intention A it is first necessary to attainintentions B, C, D, etc. Thus, B, C, D, etc.,are necessities for the achievement of intentionA. In the hierarchy of intentions it is clearlynecessary that B, C, D, etc., fall below A as shownin Figure (6 a). In logic theory this is known asan AND logic element.

(2) Intention A can be attained if any one or combina-tion of intentions B, C, D, etc., and their variouscombinations, are achieved. Thus, there aremany alternatives, or different ways, to achieveintention A. Consequently, in the hierarchy ofintentions, the alternatives B, C, D, etc., alwaysfalls below intention A as shown in Figure(6 b). In logic theory this is known as an inclusiveOR element.Intention A can be attained by achieving thesubordinate intentions B, or C, or D, but not byattaining them collectively. In this case thealternatives are mutually exclusive, rather thaninclusive. Not surprisingly, this is known asan exclusive OR element. As shown in Figure

(3)

(6 c), the exclusive alternatives B, C, D, etc., fallbelow A in the hierarchy of intentions.

The addition of these logic elements to the graph ofintentions produces the characteristic intent structure ofthe organization.

The use of these graphs and logic functions canbe very helpful in the identification of the inter-relationship between organizational intentions. It is asystematic approach to dealing with complexity thatdoes not bog down into excessive formalism. Moreover,as Warfieldo) notes, the elimination of time sequencingat this stage in the planning process permitsconcentration upon the important initial issues:

(1) What is it that the organization is to accomplish?(2) What are the alternative ways to accomplish these

intentions?It is generally not possible to construct an organi-

zational intent structure systematically. Rather, anintensive effort is mounted initially to identify as manyintentions as possible without regard to their inter-connection or position in the hierarchy. Once these havebeen assembled, trial and error plus revision of inten-tions are used to develop the hierarchy and logicelements in accordance with some organizational valuestructure.

FIGURE 6

Logic Elements Found in Intent Structures

(a) The AND function: attainment of intentions B,C, D, is necessary to achieve intention A.

(b) The inclusive OR element: intention A isachieved if any one or combination of intentionsB, C, D are attained.

(c) The exclusive OR element: intention A isachieved only by attaining intention B, or C, orD, but not by attaining them collectively.

26

A self-interaction matrix (2) is a useful tool to aid indeveloping the graph of intentions. Such a matrix isshown in Figure (7) for a case of 15 intentions. Thus, forexample, if intention 1 depends upon intention 3, thisinteraction is indicated by blackening the squarecorresponding to the intersection of intentions 1 and 3.Figure (8) shows the interaction matrix for the graphof university intentions of Figure (5). While this matrixcontains exactly the same information as the graph:

(1) The matrix is most useful in the early stageswhen intentions are being ranked relative to oneanother.

(2) The graph is most useful in visualizing andunderstanding the complex structure of organiza-tional intentions.

Educational ObjectivesAt this point we return to the specifics of the technique

of strategic budgeting through OST. As has beenshown, Objectives are specific quantitative statementsof purpose clearly enunciating university intentions.They permit the measurement of progress and showthat organizations are always characterized by a multi-plicity of interrelated objectives.

Educational objectives may be specified in termsof the following quantitative objective measures, but arenot limited to these:

(1) enrollment; also distribution of commuting andresidential students

(2) faculty size(3) faculty qualifications

FIGURE 7

Self-interaction Matrix Useful in DevelopingGraphs of Intentions

1

2

3

4

5

6

c70

5 8

9

10

11

12

13

14

15

Intentions15 14 13 12 11 10 9 8 7 6 5 4 3 2

(4) annual degree production: by level, by field; newfields

(5) cost of producing each degree(6) enrollment per course: per curriculum; per pro-

fessor(7) number and dollar value of research contracts;

degree of agency penetration(8) expenditure rates on contracts; invoicing time(9) research dollars per graduate student

(10) faculty teaching and/or research productivity(11) faculty Ph.D. productivity(12) space utilization(13) enrollment per degree program(14) distribution of students by geogrophy, sex, ethnic

group, or area of studyThese are only suggestive areas for objectives.

Others in student health care, building maintenance,public service and the like can also be identified.The key point, to once again quote Dove,(32) is that theObjectives should be set as a "shocking challengeto jolt (department heads) away from traditional, in-a-rutthinking." An objective such as To reduce tuitionby 20 percent in three years is indicative of the sortof shock that is desired.

In the general sense, it is the responsibility of thepresident to set the objectives for the university in con-sultation with appropriate advisors and with the approvalof his governing board. Deans and other administrativeheads are responsible for setting the objectives oftheir respective units, and in such ways as to contributeto and support the university goals and objectives

FIGURE 8

Self-interaction Matrix for The Tree of IntentionsShown in Figure (5)

Intentions14 13 12 11 10 9 8 7 6 5 4 3 2 1

1

2

3

4 X X

5

6

7

8

10

11

12

13

14

27

within the specified time period of each.The foregoing statement regarding the matter for

setting objectives suggests that they originate at the top.This could well be the case; but it is more likely thatthe original impetus came from elsewhere. For example,a professor in the Civil Engineering Department mightobserve that the ability of his department to attractstudents would be greatly enhanced by the acquisitionof a faculty member with a background in OperationsResearch. As the suggestion moves upward through thedepartment head, to the dean, to the office of thepresident, similar needs are perceived in Electrical,Industrial and Mechanical Eng iieering, in the BusinessSchool and in Computer Science. Out of this might comethe eventual objective to establish a capability in thefield of Operations Research to serve the needs of theentire university to acquire this capability and toenroll 100 full-time undergraduate students majoring inOperations Research within ten years. It is importantto note that the objective does not tell how it is to beaccomplished; for example, a department of OperationsResearch could be set up; or capabilities could beintroduced into the various interested departments andan interdepartmental program established, and soon. These are strategies which aim to achieve theobjective. The strength of OST is that it separates theObjective from the means of its accomplishmentthereby encouraging courage in setting objectives andinnovativeness in devising strategies.

Objectives must be set to produce a maximum con-tribution toward the achievement of university goals:but they must also be realistically achievable ratherthan mere wishful thinking. Therefore, each objectivemust be supported by a written statement which pro-vides specific answers to the following questions:Concerning the Objective

(1) What is the specific quantitative Objective andthe date for its accomplishment?

(2) is the Objective associated with the e, tire uni-versity? If it is owned by subordinate unitsschools, institutes, departments who are they?

(3) What is the present performance of the affectedunits relative to this Objective?

Concerning the Characteristics and Capabilities(4) In the abstract and general sense, what funda-

mental characteristics and capabilities define theunit, or units, involved with the Objective?(a) Which of these are essential, or fundamental

to the success of The unit?(b) Which of these will determine if the objective

can be achieved?Which of the characteristics and capabilitiesdescribed in (4) are(a) existing strengths in the affected units?(b) Which are existing weaknesses?

(6) To achieve the Objective(a) what capabilities need strengthening and at

what estimated cost?(b) What new capabilities need to be developed,

and at what cost?(c) To what extent, if any, do the new or

strengthened capabilities conflict, overlap, or

(5)

augment the activities of other administrativeunits?

Concerning the Unexpected(7) What external influences and limitations may

interfere with the achievement of the Objective?(8) What contingencies and/or uncertainties in

the achievement of the Objective are introducedby the negative factors listed in (7)?

With the Objectives fully documented by theresponses to these questions, the next and mostimportant step is to devise the Strategies, the long-range plans, by which thrse Objectives will be achieved.

StrategiesStrategies are selected plans by which resources

are deliberately aligned to capitalize an opportunity de-spite potential limiting factors. They outline the broadactions and innovations required over the plannedperiod to reach the Objective, designate critical checkpoints, and assign responsibility for accomplishment. Atleast one Strategy must be developed for eachObjective, although one Strategy may often contributeto more than one Objective. Moreover, morethan one Strategy may support a given Objective.

Although all strategies possess the same generalcharacteristics, it is helpful to distinguish three differenttypes:

(1) Educational or research strategies(2) Financial enhancement strategies(3) Organizational support strategies

Each of these is described briefly ;n the paragraphsthat follow.

Educational or Research Strategies are those whichare basically academically oriented. Their purpose is toassure a position of creative leadership rather thana responding acceptance-type posture which providesfor mere participation rather than aggressive innovation.Such strategies are associated with such objectivemeasures as enrollment, degrees produced, researchvolume, and so on. Earlier an example of an Objectivewas given as follows:

To establish a capability in Operations Research toserve the needs of the entire university and to enroll100 undergraduate majors, all within ten years.

The creation of a new department to achieve thiswould be one example of an educational strategy. Analternative strategy might be to expand the charterof another department, Computer Science or Statisticsor applied Mathematics, to encompass OperationsResearch.

Financial Enhancement Strategies are internallyoriented to control costs and/or expenses. These arelong term and may be university wide, or could relate toa single school or department. Their progress isrelated to such objective measures as faculty produc-tivity, cost per FTE student, graduate students perdollar of research support, and so on. For example, anobjective could be to increase faculty productivityfrom 270 student credit hours per year to 350 over aseven-year period. One way to accomplish this,one strategy, would be to keep faculty acquisitions be-low losses on a schedule to achieve the Objective.

28

Another strategy concerned with student recruitingcould also be involved. Both are financial enhancementstrategies.

Organizational Support Strategies refer to strategiesassociated with necessary staff and support functionssuch as the central shops, libraries. the computingcenter, admissions office, registrar, and other adminis-trative activities. For example, an Objective in thisarea might be to increase undergraduate student t:se ofthe library resources by 25 percent in five years.Possible strategies could then involve the opening ofbranch libraries, one possibly in the Student Center.

The Strategy Manager is the key figure in'this entiresystem of operation. Ordinarily, he will be a dean,vice president, department head, or head of someadministrative unit, but professors and staff membersmay also serve. Once appointed by the president (ordean as appropriate), the Strategy Manager must:

.(1) Think through and develop a long-range courseof action for the effective use of resources toachieve the Objective.

(2) Formalize the Strategy in the prescribed format(3) Insure the successful pursuit and accomplish-

ment of the Strategy.(4) Hold periodic reviews to evaluate performance

on specific tactical action programs.The formalization of a Strategy involves four basic

-steps: (1) the Strategy Statement, (2) identificationof major long-range checkpoints, (3) evaluation of con-tribution and impact, and (4) an estimate of successprobability. Each of these is discussed briefly in thesection that follows.

Strategy StatementsAs noted earlier, each Objective must be supported

by at least one strategy. However, there can be severalstrategies for each Objective and each Strategy cansupport several Objectives. A Strategy Statement is awritten scenario of the Strategy detailing the principalopportunity to which the Strategy is oriented, theinnovations necessary, the obstacles to be encounteredand the commitments required for achievement. Astrategy ordinarily encompasses a long-time span offive to 15 years. Thus, the Strategy Statement must becomprehensive and complete.

These considerations are represented in the !,ollowingfive Strategy Statements which must be made:

(1) Opportunity: This statement examines the needsto be satisfied and the problems to be solved.The solutions to these needs and problems repre-sent opportunities to reach the Objective whichthis strategy supports. The purpose of thisstatement is to create opportunities, therebyavoiding mere response or reaction to oppor-tunities. Thus, the problem or need must beunderstood well enough so that a solution canbe identified before it becomes critical. Thiscreates opportunities.

(2) Innovations required: Identification of the in-novations needed for the success of the Strategyis the single most important matter. The critical

(3)

innovation, regardless of character, can providethe step function for growth opportunity. Thesupport necessary for achieving tha.innovation,the resulting impact of the innovation, andpossible alternative innovation considerationsmust be described. The required innovationmay consist of a group or sequence of innova-tions over a period of time, If so, their inter-dependence and optional approaches should beexplained. particularly when several differentadministrative units are involved.Competitive action: Competitive action mayappear in a variety of ways -- by directly com-peting programs or services, faculty or studentrecruitment programs of other institutions, ora new program or institution that eliminates theneed for a current program. An analysis ofcurrent and potential competition Strategiesmust be developed. The impact of the proposedStrategy on competition must be developedtogether with a description of how this impactmay be exploited.

(4) Contingencies: In any long-term program thereare contingencies that can alter significantlyany planned course of action. Such contingenciescan arise from many sources governmentaction (wars, laws, regulations, new state schools,and so on), industry associations, high schoolprograms, economic expansion or deflation, andso on. The most significant contingencies mustbe identified and their impacts analyzed.Major Commitments: Once a strategic programis developed, its implementation requirescommitments of people, facilities, organizations,finances, and so on. Both the near and long-term commitments of these items must be de-lineated specifically. Those commitments whichwill be required and which are significant de-partures from current operations should be pre-sented and explained clearly: those implementedare the initial manifestation of the establishmentof the Strategy.

This completes the Scenario for the Strategy.An essential ingredient in the formalization of a

strategy is the identification of checkpoints, or mile-stones. The major long-range checkpoints representa sequence of key accomplishments considerednecessary for the success of the Strategy. Althoughnear-term checkpoints are more readily identified, evententative long-range checkpoints and actions shouldbe described: otherwise there is no basis for evaluatingthe direction of the needed near-term effort. A flowchart or diagram is usually helpful in developing thesecheckpoints. Tactical Action Programs (TAP's) areactions aimed at achieving each of these checkpointswithin the Strategy.

The Strategy is completed by a statement designedto indicate its probable results. Because the successprobability will vary with time, it should be expressed foreach year.

Capital requirements, personnel, and financial

(5)

29

commitments must be evaluated relative to the impacton current operations. compared to the gains to besecured. and their estimated payoff probabilities.

Tactical Attion Programs -TAP's"And Decision Packages

Tactical Action Programs (TAP's) are discreteaction programs aimed to achieve each major check-point or milestone in a given strategy. There may bemore than one TAP per milestone. Or, one TAP maycontribute to the achievement of more than onechedkpoint. in any case, the TAP required for eachstrategic milestone must specify explicitly:

(1) The title of the program (TAP Title)(a) The Strategy which it supports.(b) and the Objective the Strategy supports.(c) The strategic checkpoint it aims to achieve.

(2) The name of the person responsible for the TAP.(3) The start and completion dates of the activity.

These should range from six to 18 months.A quantitative statement explaining how theprogram will contribute to reaching the strategiccheckpoint.

(5) An accurate, nonambiguous statement ofsupport requirements or personnel. facilities,finance, and so on.

(6) A step-by-step statement of measurable tacticalactivities, .using a schedule bar graph or PERTNetwork, to show each start and stop date, theperson responsible and the commitments ofresources.

This information can generally be confined to a pageor two by devising appropriate forms.

The eventual output desired from this process is a setof rank-ordered strategic decision packages whichcan then be considered M parallel with the decisionpackages produced for Ike operating budget by Zero-base Budgeting procedures. It sometimes happensthat certain TAP's can be treAed as decision packages.However, in other cases, the TAP's may fall ratherlogically into groupings which form stand-alone decisionpackages. any event, all of the TAP's, either singlyor in groups. must be organized into Strategy decisionpackages using the formal tOT presentation describedin Zero-base Budgeting.

Once the strategic decision packages are identified,they must be ranked and a cutoff process appliedsimilar to that used in ZBB. The rank-ordered list ofdecision packages then moves ,up through theOST hierarchy in the consolidation and cutoff process.The process was then explained by Dovei") as follows:

The tactics are then grouped into logical, stand-alone decision packages which are rank ordered bythe Strategy Managers. Based upon the guidelines forstrategic funding, a cutoff line is drawn, andpackages above the line are given a tentative ap-proval. Those falling below the line . . . remain in . . .

(the) 'creative backlog' and have an opportunityto move up for approval at a later lime -whenresources become available. This process is repeated

at The Obiective level. where adiustments in theallocation between strategies may be made anddecision packages Tailing below the cutoff line ar theStrategy level have another opportunity for approval

. Finally, a segment of the strategic holding isallocated directly at the corporate level to certaindecision packages; This is primarily a methodfor starting new ventures which for many reasons.might not be started by one of The divisions."

It is clear that this process is exactly equivalent tothat followed in Zero-base Budgeting.

It is clear that the OST process yields a hierarchicalset of objectives that ,usually. but not always. follows thehierarchy of the organization. This is so becauseTactics are usually carried out by department heads,Strategies by deans. and Objectives commonly are,enuncTated at the presidential level. There are some ex-ceptions, however But. mainly, the administrativehierarchy coincides with the OST hierarchy of goals.Correspondingly. in most cases, decision packages willbe consolidated first at the deans' level (StrategyManagers) and then passed on to the presidential Ob-jectives) level. But, despite this, the Strategy Managercan reach across school and departmental boundariesto implement his TAP's so the system does getaroutwl the usual organizational rigidities. This can beunderstood from the sketch shown in Figure (9). Thebasic university organization is shown at the top and the(OST structure at the left. Each X denotes responsibilityfor a TAP.

After approval. decision packages are disaggregatedinto TAP's, individual assignments are made for eachtactic,and a system of periodic TAP review is instituted.

FIGURE 9

The OST and Operating Matrix

THE uttvialsrm

Institute etTechnology

School olHumanities and Sciences

DePt OePtME OR

El gedPi =ES! Ipept

OE/ CS/

mustimmerais,,111EMEM111111111111111111111111111111101111111:11O1111111M11111111111.IMUMIIIIIIIMIIIM1111)

13131===111111111131MM111111111rCIIIIIMMEM11111111111111E11:11111111111111111111111111111111LalIBEIMIIIMMINIMIIIMEDUMMERUMIIMMIMIIIIILNmealmiommommar

11131MENIEMINIIIIIIIIIMININIIIIIetC.

PART 4: Some References 30

1. Peter A. Pyhrr, "Zero-Base Budgeting," HarvardBusiness Review, Nov.-Dec., 1970, pp. 111-121.

2. J. Douglas Hill, John N. Warfield, "Unified ProgramPlanning," IEEE Transactions on Systems, Manand Cybernetics, Vol. SMC-2, No. 5, Nov., 1972,pp. 610-621.

3. John N. Warfield, "Intent Structures," unpublishedpaper as of 1972.

4. Survival Through Change, Management Division,Academy for Educational Development. N. Y.

5. Joseph L. McCarthy, David R. Geener, "The Costsand Benefits of Graduate Education: A Com-mentary With Recommendations," The Councilof Graduate Schools in the United States, April 30,1970, Wash.. D. C,

6. Lloyd D. Andrew, Leon Robertson, "PPBS InHigher Education: A Case Study," EducationalRecord, Winter, 1973, pp. 60-67.

7. "Harvard and Money A Memorandum on Issuesand Choices," The University Committee onGovernance, Harvard University, Cambridge,Mass., Nov., 1970.

8. Max S. Peters, "Teaching and Space Require-ments for Quality Engineering Education," Engi-neering Education, April, 1971, pp. 480-859.

9. John F, Wetjen, The Ten Commandments ...of evaluating change," Infosystems, Aug., 1972,pp. 24-25.

10. Amitai Etzioni, On the Art of University Pruning,"Science, April 30, 1971, V. 1972, N. 3982, editorial.

11. Frederick E. Terman, "Economic Factors Relatingto Engineering Programs," Engineering Education,Feb., 1969, V. 59, N. 6, pp. 5 i 0-514.

12. Max S. Peters, "Ratios and Factors for Teachingand Space Requirements for Quality EngineeringEducation," 78th Annual Meeting ASEE,Columbus, Ohio, June 23, 1970, event No, 65.

13. Fred Benson (?), "Funding Formulas forEngineering Education," 8th Annual Institute forEngineering Deans, Austin, Texas, April 5-7, 1971.

14. Texas Formulas For Higher Education (1969).15. R. D. Shelton, J. C. Prabhakar, "Efficiency

Ratios for Engineering Schools," (mimeo paperfrom Texas Tech).

16. George B. Weatherby, "Educational Planningand Decision Making," Ford Foundation Programfor Research in University Administration,Paper P-6, May, 1970, Berkeley, Calif.

17. F. E. Balderston, "Cost Analysis In Higher Edu-cation," Ford Foundation Program for Researchin University Administration, Paper P-33, July,1972, Berkeley, Calif.

18. "Implementation of NCHEMS Planning andManagement Tools at California State University,Fullerton," National Center for Higher Education,Management Systems at WICHE, Boulder,Colorado, Aug., 1972.

19. K. M. Hussian, "A Resource Requirement Pre-diction Model (RRPM-1): Guide for the ProjectManager," National Center for Higher Education

Management System at WICHE, Boulder, Colo.,Tech. Report 20, Oct., 1971.

20. Robert A. Huff, "Overview of the Cost EstimationModel," National Center for Higher EducationManagement System at WICHE, Boulder, Colo.,April. 1971.

21. George B. Weatherby and Frederick E. Balderston,"PPBS In Higher Education Planning andManagement," Ford Foundation Program forResearch in University Administration, Berkeley.Calif., Paper P-31, May, 1972.

22. Paul C. Reinert, S.J., "Rescue Begins at Home,"Management Division, Academy for EducationalDevelopment; adapted from "To Turn the Tide,"Prentice-Hall, Inc., April, 1972.

23. Anna Jo W. Behrens, "Higher Education withFewer Teachers, Some Examples of Current.Practice," Management Division, Academy forEducational Development, Inc., Oct., 1972.

24. "319 Ways Colleges and Universities are Meetingthe Financial Pinch," Management Division,Academy for Educational Development, Inc.

25. "Personnel Management in Higher Education,"Nitanagement Division, Academy for EducationalDevelopment, Inc.. Oct., 1972.

26. David G. Clark, Robert A. Huff, "InstructionalProgram Budgeting in Higher Education,"NCHEMS at WICHE, Boulder, Colo., Sept., 1972.

27. Robert A. Huff, Charles W. Manning, "HigherEducation, Planning and Manag .=ment Systems,"NCHEMS at WICHE, Boulder, Colo., May, 1972.

28. Richard H. LeTourneau, "Solving the DilemmaFacing Private Education," ASEE Gulf SouthwestSection, S.M.U., March 15-17, 1973, Dallas,. Tex.

29. "Managing the University A SystemsApproach," ed. by Paul W. Hamelman, PraegerPubl., N. Y., 1972.

30. Can a System Perform Like a Hero?" InnovationMagazine, N. 8, 1969, pp. 16-31.

31. James L. Fischer, "Decision Systems forPlanning and Control," The Society for Manage-ment Information Systems, Speech at theFounder's Conference, Sept. 8-9, 1969, U. Minn.,Minneapolis.

32. Grant A. Dove,* an address made to the LondonGraduate School of Business Studies, May 22,1970. (* Vice Pres., Corporate Development,Texas Instruments Incorporated, Dallas, Tex.)

33. Peter A. Pyhrr, "Zero-Base Budgeting,"Interscience, John Wiley & Sons, Inc., N.Y., 1973,231 pp.

34. Roger G. Schroeder, "A Survey of ManagementScience in University Operations," ManagementScience, V. 19, N. 8, April, 1973, pp. 895-906.

35. Anne E. Scheerer, "A Formula for Determininginstruct4Dnal Costs, College Management,Nov., 1972, pp. 25-29.

36. Harry J. Hartley, Educational Planning-Program-ming-Budgeting: A Systems Approach, Prentice-Hall, Inc., Englewood Cliffs, N.J., 1968.

Section II Statistical Report and Evaluation of Trends 31

Freshman Engineering EnrollmentFrom the mid 1960's through 1970. the number of

freshmen enrolled at Southern Methodist Universityincreased from 96 in 1965 to 192 in 1970. This steadyrise in admissions was the direct result of a reorga-nization of the Engineering School at SMU. Thereorganizing of the Institute of Technology broughtnew programs of study, and a strong recruitingprogram was launched. As shown in Figure (10), therise in freshman enrollment through 1970 actually rancounter to the national trend for freshman engineeringenrollment.' In the late 1960's, the competition amongengineering schools for top high-school graduatessharpened as the pool of potential freshman engineer-ing students began to decline across The country.The drop in freshman enrollments at SMU in 1969 wasthe direct result of intense competition in the Southwestregion. The sharp falloff in freshman registrationssince 1970, which followed the national trend, can beattributed to two important factors: the "badpress" given the engineering profession and thechanging pattern of educational options for high-school graduates. Another significant deterrent tofreshman enrollment at the SMU Institute of Technologyhas been the sharp rise in tuition and fees since 1970.

The quality of the students attracted to engineeringSMU has remained high as measured by college

entrance test scores shown in Figure (11). Fortunately,the trends in freshman enrollment appear to be turningup again, and engineering educators are more opti-mistic as they view freshman enrollment predictionsfor the fall of 1973. This is definitely the case at theSMU Institute of Technology where there has been amore favorable response to recruiting efforts anda marked rise in admissions activity.

'Engineering Manpower Comm scion of Engineers Joint Council."Engineering and Technology Enrollments." Fall, 1972, p. 11.

FIGURE 10

Freshman Engineering EnrollmentAll Schools Offering Engineering Programs

80,000

75,000

70,000

65,000

60,000

55,000

50:000

45,000

40,900

FULL -TIME ENROLLMENTS`

1967 ,'1968FALL TERM

1969 :1970 1971 1972

SMU Institute of Technology

FIGURE 11

Freshman Engineering Student Characteristics

n79 9181 19AR 1885 1589 11

87- 13..

FALL. TERM

32

Total Undergraduate Engineering EnrollmentThe rise in freshman enrollment along with an

increase in sophomore transfers, in the period from1966 through 1970, caused the total undergraduateengineering population at SMU to rise steadily eventhough the number of students registered in engi-neering schools across the nation began to declinein the late 1960's.' See Figure (12). The drop inundergraduate engineering registrations at SMU since1970 to some extent reflects the results of the falloffin freshman enrollment, but more than that, it pointsup an attrition problem occurring at the sophomore andjunior level. The reports of mass layoffs of practicingengineers and the invisioned slim prospects foremployment upon graduation caused a significantnumber of upper-division students to reconsider theircareer goals and transfer to other preprofessionalprograms such as'prelaw and premedicine. The impactof the freshman enrollment problem and the attritionof upper-division students will be felt for some time.On the plus side, however, the word is getting out tostudents that employment prospects for engineeringgraduates are very good, and it is expected that thestrong employment situation for graduates and prac-ticing e7-igineers will alleviate th;s temporary attritionproblem.

The prospects for increasing the number of under-graduate engineers at SMU are actually very brightat present because of a new program aimed atenrolling persons employed as technicians in profes-sional engineering degree programs.

The plan, developed in conjunction with TexasInstruments Incorporated of Dallas, is in a sense areverse of the traditional co-operative education plan.Instead of students leaving the campus for an employ-ment experience, employees are coming to the campusfor regularly scheduled undergraduate course offeringson a half-time basis and are continuing in their jobshalf-time while receiving full pay. More than 40 TexasInstruments employees with some engineering educa-tion background have registered for summer refreshercourses, and the number of students in the programis expected to reach as many as 75 for the 1973 fallterm. In addition to providing the needed engineeringtalent for their employer, this arrangement wt!I morethan offset the declining freshman enrollment andattrition problems of the past two years. As the studentscurrently registered for the program progress towardtheir degree goal, it is anticipated that other employersin the North Texas area will consider similar arrange-ments for their employees.

The Undergraduate Engineering Co-operativeProgram

Co-operative education has been an importantprogram since the inception of the Engineering Schoolat SMU in 1925. Originally, the Co-op Plan, combiningalternating periods of study and engineering work in

7,bid p 11

FIGURE 12

Undergraduate Engineering EnrollmentsAll Schools Offering Engineering Programs

FULL- TIME ENROLLMENTS240,000

230,000

220;000

210,000

200,000

loopoo-

180,000

170,000 -.

180,0001967 1968 1969 1970

FALL TERM

1971 1972

SMU Institute of Technology

FULL -TIME ENROLLMENTS550

500

450,

350

2001987 1988

FALL TERM1969. 1970 1971 1972

33

industry, was a requirement for all students. The planwas made voluntary in 1965. Figure (13) shows thetrends of student participation in ',:ie plan. It appearsthat a relatively stable situation has been a',.hievedwith the total number of students enrolled in the planremaining constant. During the past year, industrialdemand for co-op students has been strengtheningand far exceeds the number of students available.

The companies participating in the Co-op Programin 1972-73 are:

Baylor University Medical CenterBlue Cross-Blue Shield of TexasHerman Blum AssociatesBell Helicopter CompanyCity of DallasCore Laboratories, Inc.Dallas Power and Light CompanyE-Systems, IncorporatedGeneral Electric Corporation (Tyler, Texas)Haggar CompanyAlbert H. Halff and Associates, Inc.LTV CorporationMobil Oil GroupRaymond D, Nasher CompanyNASAOtis Engineering CorporationSouthwestern Dell Telephone Company

(Dallas and Houston)Toleswitcher CorporationTexas Highway DepartmentU. S. Air Force (Security Service, San AniDnio)Weben IndustriEr:.Western Union

Graduate Engineering EnrollmentFigure (14) compares the changes in full-time

student enrollment levels for all U. S. schools offeringgraduate engineering programs with the enrollmentin graduate engineering at SMU.' It should be notedthat SMU enrollments are shown using the full-timeequivalent measure rather than the head-count statistic.The full -time equivalent more accurately reflects thegraduate programs at SMU because all of the industrialstudents are enrolled in regularly scheduled graduatecourse sections with on-campus students. The onlydifference is that the students from industry participatein the courses via the TAGER Television System, theclosed circuit "talk-back" TV network which inter-connects North Texas industry and North Texashigher education.

p. 11.

FIGURE 13

Engineering Cooperative Program

400 -

300 -

200 -

100 -

01967 1968 1969 1970 1971 1972

FALL TERM

FIGURE 14

Graduate Engineering EnrollmentAn Schools Offering Engineering Programs

50,000 -

45,000 -

40,000 -

35,000 -

30,000 -

25,000 -

20,000 -

15,000

FULL-TIME ENROLLMENTS

1987 1968 1989 1970 1971 1972FALL TERM

SMU Institute of Technology

34

The sharp rise in graduate enrollments in 1968 and1969 reflects the growth of the North Texas science-based industries and the overall strengthening of thequality of the Institute's graduate programs. This isapparent in Figure (15) which shows the graduateenrollment head count. Again, prior to 1970, as wasthe case with the undergraduate population, theenrollment increases recorded at the graduate levelcountered the decline which appeared on the nationalscene in 1968. The dramatic cutbacks in federalspending, coupled with the industrial recession; causedenrollments to fall off rapidly from 1970 through 1972.This downturn resulted in the loss of large numbers ofindustrial students enrolled via the TAGER TV Network.

The TAGER Television SystemSince the inception of the TAGER television network

in 1967, almost all of the graduate courses offered bythe Institute have been presented on the network tothe various industrial affiliates. The enrollment patternon the network is shown in Figure (16). The effect ofthe declining economic situation in the science-basedindustries is apparent from this distribution and Figure(17).

The number of industrial students enrolled ingraduate courses offered by the Institute is a functionof the number of "new hires" of engineers by theTAGER industrial affiliates. Since 1969, the number of

new hires" by industrial affiliates has been greatlyreduced while in the same period the unusually largenui-nber of graduate degrees awarded has had theeffect of pumping out the pool of available graduateengineering students. Figure (18),which shows acomparison of on-campus and off-campus enrollmentson the network by academic centers, indicates a slightrise in off-campus enrollments for 1973 and suggeststhat the increase in new hires" by industrial affiliates,which occurred in early 1972, is beginning to show apositive impact on the off-campus enrollment category.The decline in on-campus graduate enrollments shownin this figure can be attributed to the shifting patternsin federally sponsored research which resulted in areduction of the amount of support available for full-time graduate students.

Graduate Degree ProductionMaster's Degree

The number of Master's degrees conferred in 1972held up well and is still above the 1968 and 1969levels, as shown in Figure (19). For the past severalyears, including 1972, the Institute of Technology hasbeen the leading producer of Master's degrees inTexas and, in this category, ranks above all engineeringschools in the South and Southeast with the exceptionof Georgia Institute of Technology. The sharpincrease in Master's degrees conferred in 1970 and1971 served to reduce the pool of Master's degreecandidates, but it is likely that the number of degrees tobe awarded in the next two years will hold constantwith the possibility of a slight decline.

FIGURE 15

Graduate Engineering Enrollment

1,100

1,000

900

800

700

600

500

400

300

200

100

Student Head Count

1086

871

1966 1967 1968 1969 1970 1971 1972FALL TERM

FIGURE 16

Geographical Distribution of TV Enrollments

Atlantic Richfield 7 3 1

Collins Radio 8E.Systems Garland 3 12 11

General Dynamics 23 50 35 10 28 19LTVGrand Prairie 3 21 19 8 19 11

Mobil 3 12 11 4 4Texas Instruments

Dallas 38 169 163 53 210 174Texas Instruments

Sherman 2 1 3SMU-On-Campus 122 406 378 65 367 331Southwestern

Medical School 2Texas Christian

University 5 1

Univ. of Dallas 3Univ. of Texaa

at Dallas 5 4

Total 200 674 813 137 657 564

FIGURE 17

TV Enrollment

FIGURE 18

Graduate TV Enrollments by Centers (1971-1972 & 1972-1973)

Center

Computer Science/Operations Research

Electronic SciencesInformation /ControlSolid MechanicsThermal/Fluid Sciences

Summer 1971off on

campus campus total

12 70 820 0 0

49 39 8815 7 22

2 6 8

78 122 200

11 Courses

Fall 1971off On

campus campus total

98 208 30635 39 ,99 121 220 .

268 406 674

35 Courses

Center

Computer Science/Operations Research

Electronic SciencesInformation/ControlSolid MechanicsTherinal/Fluid Sciences

Summer 1972off on

campus campus total

22 46 680 0 0

40 11 51

6 4 10

4 4 8

72 65 137

8 Courses

Fall1972off on.

campus campus total

'196sf 43'9717

Spring 1972off on

campus campus total

52 207 25931 32 6394 88 18214 33 47

10 16 26

201 376 577

33 Courses

Spring 1973off on

campus campus total

81 172 25337 24 6177 78 15527 25 52

11 32 43

233 331 564

38 Courses

FIGURE 19

Master's Degrees in Engineering

250

200

150

100

50

Masters Degrees Awarded

136

180

148

141

20:

0-1966 1967 1968 1969 1970

School Year Ending in May

196

62

143

1971 1972 1973

36

Doctoral DegreesWhen the Doctoral program was launched in 1966,

a goal of 25 Ph.D.'s per year was set for 1972. Thisgoal was actually achieved in 1971, and 1972 turnedout to be a banner year with the awarding of 42 Ph.D.'s,See Figure (20). The goal of a stable output of 25 to30 Ph.D.'s a year is a reasonable expectation in lightof the stable enrollments in the Doctoral program.Even though the large number of Ph.D.'s conferredin the past three years has reduced the number ofDoctoral students in the pipeline, current enrollmentstill stands at 120. In addition to the Ph,D. candidates,11 students are enrolled in the Doctor of Engineeringdegree program.

The Engineer's degree, which falls midway betweenthe M.S. and the Doctorate, continues to meet a definiteneed. In 1971, 12 students received this degree, 13were conferred in 1972, and 7 in 1973. There arepresently 17 students enrolled in this degree program.

Graduate Engineering Prospects for the FutureHistorical'y, graduate enrollments in engineering

have responded to two outside forces: the employmentsituation for practicing engineers and the availabilityof sponsored research funds for graduate studentsupport. These factors have been dominant during thepast decade when the number of B.S. degrees beingproduced was essentially constant. Now, the markeddacline in B.S. degree production will make itselffelt, tending to offset increases that would otherwiseoccur because of improvements in the economy andfederal support for university research. The challengefor the Institute of Technology and for all of engineeringeducation is to find ways to recoup the losses inundergraduate students in recent years. The answerto this challenge may be in further developing newprograms such as the forward-looking employeedevelopment plan instituted by Texas InstrumentsIncorporated, which was described earlier in this Report

A preoccupation with all of the factors causingthe downward trend in graduate engineering educationcould well leave the interested observer in a permanentstate of depression. Fortunately, there are signswhich indicate the trend lines have bottomed out.Although no sharp upturns are predicted for graduateenrollments in the fall of 1973, there is plenty of reasonto forecast some increase in enrollments in bothfall and spring terms. There has been a definite increasein graduate level admissions activity from the "newhires," e.-)d former students who suspended their workon degree programs are again making enrollmentinquiries. These prospects for a rise in graduateenrollments stem directly from the positive economicclimate experienced by the science-based industriesin the past 18 months.

FIGURE 20

Ph.D. Degrees in Engineering

50

40

301972 Goal = 25

20

10

Ph.D.'s Awarded

01967-68 1968-69 1969-70 1970-71 1971-72 1972-73

Year

FIGURE 21

Expense Budget*

$ 254,2954%7621%960

130,8509A00

245,357185,087278,713

0167,353175,515

00

$ 273,13350,8000

41,78011,665

316,2640

0476,284

00

295,107279,155

Revenue/Expense Summary*

$ 706,08836,900

, 11,00069,22435,i)00.

658,110

$1,516,292'$1,516,292'

. .

$ 680,00030,000

70,03335,000

650,0002'79,155

$1,744,188$1,744,188

37

Semester Credit Hour ProductionThe basic unit of academic production is the student

semester credit hour, Known as SCH, it is defined asthe product of the enrollment in each class multipliedby the semester credit hours assigned to that course.The SCH production for the three terms of 1971-72,and 1972-73 is shown in Figure (22).

Reorganization of the Institute of TechnologyA number of events intersected during the past

year which suggested that the time had arrived toconsider a rather simple 130 constructive reorganiza-tion of the Institute of Technology. This decision wasstrongly influenced by the reports of the visitingcommittees of the SMU Technical Advisory Councilwhich were completed in the spring of 1972. All of themembers of the Council hold positions of primaryresponsibility for research and development in science-based industrial firms in the North Texas Metroplex,and most of the members hold an earned doctoratein engineering. The Council provides an importantlink with the local technical community and servesin an advisory capacity to the. Institute of Technology.The conclusions of the Council's visiting committeeswere confirmed by the ECPD (Engineering Councilon Professional Development) inspection which wasconducted in January of 1973. Also, it had been appar-ent to the faculty and the administration of the Institute,that there WFS a definite need for improvement inachieving coordination of the undergraduate programsand laboratory activities that should be characteristicwith a school of a general quality corresponding tothe Institute's goals.

The grid form of organization structure, which hasbeen in operation at the Institute of Technology since1967, was introduced as an administrative device tobring about a major change in the fundamentalcharacter of what was then known as the School ofEngineering at SMU. The School of Engineering hadon-going accredited programs in several fields ofundergraduate engineering including Civil Engineering,Electrical Engineering, Industrial Engineering, andMechanical Engineering.

The School's graduate programs were limited to theMaster's degree and the Ph.D. in ME and EE; they werenot as extensive or as comprehensive as local industryrequired. The grid structure was created with the for-mation of the five principal Engineering ScienceCenters.

(1) Computer Science Operations Research(2) Electronic Sciences(3) Information and Control Sciences(4) Solid Mechanics(5) Thermal Fluid SciencesThis organization permitted a major upgrading in

the graduate programs and research activities of theInstitute to the point where these operations at theDoctorate and Master's level are now comparable tothose offered by the best schools in the United States.This conclusion agrees with observations by boththe Technical Advisory Council and the recent ECPDinspectors. Thus, in viewing the possibility of change,it was considered to be essential that any plan forreorganization of the Institute preserve the strengthswhich have been developed while acting to correctweaknesses that had been observed.

FIGURE 22

Semester Credit Hours Production

Summer 1971Fall 1971Spring 1972

Total

1,2575,3564,914

11,527

3452,3832 046

-4,774

6752,1692.163

5,007

'Summer 1972Fall 1972Interterm 1973Spring 1973

Total

,1,160'5;1.21

4.495`.10,782

4502,158

2 003

4,614

237 912804705 , 2 868,',-

1,746 '!,5,753

Ade 858774 7 2',929.

0699 :2 702'

1,8817 6,495,;

38

The results of the reorganization effort are shown inFigure (23). The administrative responsibilities assignedin the revised structure provide a stronger focus onthe responsibility for coordinating the undergraduatecurriculum and enhancing the undergraduate student'sprofessional identification.

FIGURE 23

Department ofCivil and Mechanical

EngineeringJack P.Holman

..''..Department of... COMOuter Science and

Operations. Research'' U. Narayari

Best

Curricula:

CivilEngineering

EnvironmentalSystems

MechanicalEngineering

Computer Science

OperationsResearch(EngineeringAdministration)

IndustrialEngineering

ElectronicSciences

ElectricalEngineering

SystemsEngineering

Public andSocietal Systems

BiomedicalEngineering

denotes faculty

Department ofElectrical

Engineering.Andrew P.

Sage

Appendix I Faculty of the Institute 39

FACULTY As of May 31, 1973

Computer Science/Operations Research CenterResident FacultyU. Narayan Bhat

Professor and DirectorPh.D. (Stat) University of Western Australia

Leon CooperAssociate Dean and ProfessorPh.D. (Ch.E.) Washington University

Dennis J. Frei leyAssistant ProfessorPh.D. (CS) Purdue University

Myron GinsbergAssistant ProfessorPh.D. (CS) University of Iowa

Harvey J. GreenbergAssociate ProfessorPh.D. (OR) Johns Hopkins University

Robert R. KorfhageProfessorPh.D. (Math) University of Michigan

Richard E. NanceAssociate ProfessorPh.D. (1E) Purdue University

William C. NylinAssistant ProfessorPh.D. (CS) Purdue University

Robert J. Smith, IIAssisant ProfessorPh.D. (CS) University of Missouri

Stephen A. SzygendaProfessorPh.D. (CS) Northwestern University

Alan C. WheelerAssociate ProfessorPh.D. (Stat) Stanford University

Visiting Industrial ProfessorsCharles R. Blackburn, II

Assistant ProfessorMBA (OR) Tulane University

Howell N. Forman, Jr.Associate ProfessorM.S. (IE) Southern Methodist University

Raj K. MinochaAssistant ProfessorM.S. (IE) University of Pittsburgh

Electronic Sciences CenterResident FacultyKenneth L. Ashley

ProfessorPh.D. (EE) Carnegie-Mellon University

Jerome K. ButlerAssociate ProfessorPh.D. (EE) University of Kansas

William N. CarrProfessorPh.D. (EE) Carnegie-Mellon University

Shirley S. C. Chu

Assistant ProfessorPh.D. (Chem.) University of Pittsburgh

,Ting L. ChuProfessorPh.D. (Chem.) Washington University

Jon W. EberleAssociate ProfessorPh.D. (EE) Ohio State University

Kenneth W. HeizerProfessorPh.D. (EE) University of Illinois

Lorn L. HowardProfessorPh.D. (EE) Michigan State University

William F. LeonardAssociate ProfessorPh.D. (EE) University of Virginia

Thomas L. Martin, Jr.ProfessorPh.D. (EE) Stanford University

Charles R. VailProfessorPh.D. (EE) University of Michigan

Visiting Industrial ProfessorsGordon Cumming

Assistant ProfessorPh.D. (EE) University of Southern California

Jack S. KilbyProfessorM.S. (EE) University of Illinois

Jack P. MizeAssociate ProfessorPh.D. (Phys.) Iowa State University

Jack ReynoldsAssistant ProfessorPh.D. (Phys.) University of Lund

Information and Control Sciences CenterResident FacultyDavid L. Cohn

Assistant ProfessorPh.D. (EE) MIT

Yumin FuAssociate ProfessorPh.D. (EE) University of Illinois

Someshwar C. GuptaProfessorPh.D. (EE) University of California at Berkeley

James L. Me IseProfessorPh.D. (EE) University of Arizona

Louis R. NardizziAssociate ProfessorPh.D. (EE) University of Southern California

Behrouz PeikariAssociate ProfessorPh.D. (EE) University of California at Berkeley

Andrew P. SageProfessorPh.D. (EE) Purdue University

40

John A. SavageProfessorM.S. (EE) University of Texas

Edmund W. SchedlerAssociate ProfessorM.S. (EE) Oklahoma State University

Mandyam D. SrinathProfessorPh.D. (EE) University of Illinois

Finley W. TatumProfessorPh.D. (EE) Texas A&M University

Visiting Industrial ProfessorsJames M. Davis

Assistant ProfessorPh.D. (EE) University of Illinois

William S. EwingAssistant ProfessorPh.D. (EE) Southern Methodist University

Manus R. FosterProfessorPh. D. (Math-Physics) University of Kansas

Robert E. GriffinAssistant ProfessorPh.D. (EE) Southern Methodist University

Gustave HoehnAssociate ProfessorPh.D. (EE) Stanford University

Stephen K. JonesAssistant Professoi-Ph.D. (EE) Southern Methodist University

Lucien MasseProfessorPh.D. (Geophysics) Colorado School of Mines

J. Robert McLendonAssistant ProfessorPh.D. (EE) Southern Methodist University

Theo J. PowellAssistant ProfessorPh.D. (EE) University of Illinois

Solid Mechanics.CenterResident FacultyCharles E. Balleisen

ProfessorM.S. (ME) MIT

jan CernosekAssociate ProfessorPh. D. (Exper.Mech.) TechnicalUniversity of Prague.

Le Van GriffisProfessorPh.D. (CE) California Institute of Technology

David B. JohnsonAssOciate ProfessorPh.D. (EM) Stanford University

Robert M. JonesAssociate ProfessorPh.D. (Appl.Mech.) University i Illinois

W. Scott McDonald, Jr.Associate Professor and DirectorPh.D. (EM) University of Kansas

Hal Watson, Jr.Associate Professor

. Ph.D. (EM) University of ThxasMarion W. Wilcox

ProfessorSc.D. (Engr.Sci.) University of Notre Dame

Visiting industrial ProfessorsBill L. Gunnin

Assistant ProfessorPh.D. (CE) University of Texas

Vernon A. LeeAssociate ProfessorPh.D. (AE) University of Texas

Robert C. McWherterAssistant ProfessorM.S. (AE) University of Texas

Raymond P. PeloubetAssociate ProfessorM.A. (SE) Ohio State University

Kondhamur S. RajagopalanAssistant ProfessorPh.D. (CE) University of Texas

Edward M. SchellAssistant ProfessorPh.D. (Appl.Mech.) Michigan State University

Wilbur C. SchoellerProfessorPh.D. (C2) University of Texas

Thermal and Fluid Sciences CenterResident FacultyHarold A. Blum

ProfessorPh.D. (Ch.E.) Northwestern University

Michael A. CollinsAssistant ProfessorPh.D. (CE) MIT

Carlos W. CoonAssociate ProfessorPh.D. (ME) University of Arizona

Jack P. HolmanProfessor and DirectorPh.D. (ME) Oklahoma State University

Roger L. SimpsonAssociate ProfessorPh.D. (ME) Stanford University

Cecil H. SmithAssociate ProfessorPh.D. (CE) University of Texas

Edmund E. WeynandProfessorSc.D. (ME) MIT

W. Gerald WyattAssociate ProfessorPh.D. (ME) University of Minnesota

41

Special Studies CenterThomas P. Hughes

ProfessorPh.D. (History) University of Virginia

Adjunct Faculty from The University of Texas HealthScience Center Southwestern Medical Schoolat Dallas Biomedical Engineering Program

Gunnar C. BlomqvistAssistant Professor of internal MedicineM.D. University of Lund

Ivan E. DanhofAssociate Professor of PhysiologyM.D. University of Texas Southwestern MedicalSchool

Javad FiuzatAssistant Professor of Thoracic and CardiovascularSurgeryM.D. University of Tehran

Charles F. GregoryProfessor of Orthopedic SurgeryM.D. Indiana University School of Medicine

Robert L. Johnson, Jr.Assistant Professor of internal MedicineM.D. Northwestern Medical School

Robert M. LebovitzAssistant Professor of PhysiologyPh.D. (Neurophysics) University of California

Jere H. MitchellProfessor of Internal Medicine and PhysiologyM.D. University of Texas SouthwesternMedical School

Steven P. PekesAssociate Professor of Veterinary MedicineDVM Ohio State University

Louis H. ParadiesAssociate Professor of Orthopedic SurgeryM.D. Northwestern Medical School

John C. porterProfessor of PhysiologyPh.D. (Phys.) Iowa State University

William J. ReaAssistant Professor of Thoracic andCardiovascular SurgeryM.D. Ohio State University College of Medicine

Floyd C. Rector, Jr.Professor of Internal MedicineM.D. University of Texas SouthwesternMedical School

William E. RomansAssistant Professor of BiophysicsM.S. (EE) Southern Methodist University

Winfred L. SuggAssociate Professor of Thoracic andCardiovascular SurgeryM.D. University of North Carolina School of Medicine

George H. TempletonAssistant Professor of PhysiologyPh.D. (Biophys.) University of TexasSouthwestern Medical School

John C. VanattaProfessor of PhysiologyM.D. Indiana University School of Medicine

Hal T. WeathersbyProfessor of AnatomyPh.D. (Anatomy) Tulane University

Appendix Events Affecting the Faculty 42

Faculty AwardsDr. James L. Me Ise. Professor of Information and

Control Sciences, received the 1972/73 WesternElectric Fund Award of the American Society forEngineering Education, Gulf Southwest Section. Thisaward was in recognition of his extensive and out-standing contributions to the engineering profession.

Also in 1972, Dr. Thomas P. Hughes, Professor ofHistory of Technology, was awarded the Dexter Prizefor his book, Elmer Ambrose Sperry: Inventor andEngineer. Dr. Hughes was singled out for thisinternational honor by the Society for the History ofTechnology.

New AppointmentsDr. Jan Cernosek, Associate Professor of Solid

Mechanics, joined the faculty of the Civil/MechanicalEngineering Department on April 1, 1973. Dr. Cernosekcame to SMU from Brazil.

Dr. Jeff L. Kennington received his Ph.D. fromGeorgia Institute of Technology. He joins the facultyof the Department of Computer Science and OperationsResearch as Assistant Professor on June 1, 1973. Hisarea of specialization is Mathematical Programmingand Production Control of Operations Research.

Dr. Larry J. LeBlanc received his Ph.D. fromNorthwestern University. He specialize in Mathe-matical Programming and Network Theory of Opera-tions Research and joins the faculty of the Departmentof Computer Science and Operations Research asAssistant Professor on September 1, 1973.

Dr. John L. Fike received his Ph.D. from SouthernMethodist University. He specializes in Digital SystemsDesign and Fault-Tolerant Computing in ComputerScience and joins the faculty of tie Department ofComputer Science and Operations Research asAssistant Professor on June 1, 197'3. He has alsospent a year as a postdoctoral fellow in the Departmentprior to joining the faculty.

PromotionsEffective Fall Semester 1973

Shirley S. C. Chu, to Associate ProfessorMichael A. Collins, to Associate ProfessorRoger L: Simpson, Associate Professor, giventenureHal Watson, Jr., Associate Professor, given tenure

Changes and LeavesIn October 1972, Jr. Robert R. Korfhage resigned

as the Director of the Computer Science/OperationsResearch Center, and Dr. U. Narayan Bhat, AssociateProfessor in the Center from 1969-1971 and aProfessor since 1971, took over the responsibilitiesas Director soon thereafter.

Dr. Hal Watson, Jr. returned from a six month leaveof absence in Brazil where he served on the faculty ofthe Federal University of Rio Grande do Sul fromMay, 1972 to January, 1973.

ResignationsDr. David L. Cohn, Assistant Professor of Information

and Control Sciences for the three-year period from

September. 1970 to May, 1973, resigned effectiveMay 31, 1973, to accept a position as Assistant Profes-sor of Electrical Engineering at the University ofNotre Dame.

Dr. Carlos W. Coon, Associate Professor of Thermaland Fluid Sciences, resigned effective May 31, 1973,to go into private business.

Dr. Harvey J. Greenberg, Associate Professor ofComputer Scic,nce/Operations Research, resignedeffective May 31. 1973, to accept a position atManagement Science Systems, Rockville, Maryland.

Dr. David B. Johnson, Associate Professor of SolidMechanics, resigned effective May 31, 1973, to gointo private business.

Dr. James L. Melsa, Professor of Information andControl Sciences for the six-year period from June,1967 to August, 1973, resigned effective August 31,1973, to accept a position as Professor and Chairmanof the Electrical Engineering Department at theUniversity of Notre Dame.

Dr. Richard E. Nance, Associate Professor ofComputer Science/Operations Research, resignedeffective July 31, 1973, to accept the position ofDepartment Head, Computer Science Department,Virginia Polytechnic Institute and State University,Blacksburg, Virginia.

Dr. Stephen A. Szygenda, Professor of ComputerScience/Operations Research and ElectricalEngineering, resigned effective May 31, 1973, to accepta position as Professor in Electrical Engineering atthe University of Texas at Austin.

Textbook PublicationsU. NARAVAN BHAT, Ph.D., (University of WesternAustralia) Professor and Department Head

A Study of Queueing Systems M/G/1 and GUM/ 1,Springer Verlag, 1968.Elements of Applied Stochastic Processes,John Wiley & Sons, 1972.

HAROLD A. BLUM, Ph.D., (Northwestern University)Professor

A Compact Course in Fortran Programming,Audio Tutorial Associates, Inc., Dallas, 1970.

LEON COOPER, Ph.D., (Washington University)Professor and Associate Dean of the Institute ofTechnology

An Introduction to Methods of Optimization,with D. I. Steinberg, W. B. Saunders and Co.,Philadelphia, 1970.

SOMESHWAR C. GUPTA, Ph.D., (University ofCalifornia at Berkeley) Professor

Transform and State Variable Methods in LinearSystems, John Wiley and Sons, 1966.Fundamentals of Automatic Control, with L. Hasdorff,John Wiley and Sons, 1970.Circuit Analysis: With Computer Applications toProblem Solving, with J. W. Bayless and B. Peikari,tntext Educational Publishers, 1972.

JACK P. 'HOLMAN, Ph.D., (Oklahoma State University)Professor and Department Head

Heat Trans!er, McGraw-Hill Book Co.: first edition,May, 1963; second edition, February, 1968;third edition, January, 1972.

43

Experimental Methods for Engineers, McGraw-HillBook Co.: first edition. February. 1966; secondedition, May, 1971.Thermodynamics, McGraw-Hill Book Co., June, 1969.Review of Heat Transfer, Audio Tutorial Associates,inc., Dallas, 1969.Experiment Planning and Data Analysis, AudioTutorial Associates, Inc., Dallas, 1970.Review and Problem Sessions in Heat Transfer,McGraw-Hill Book Co., January, 1972.

THOMAS P. HUGHES, Ph.D. (University of Virginia)Professor

The Development of Western Technology Since 1500,Macmillan, 1964.Elmer Sperry: Inventor and Engineer, The JohnsHopkins Press. 1971.

STEPHEN K. JONES, Ph.D., (Southern MethodistUniversity) Assistant Professor

Computer Programs for Computational Assistancein the Study of Linear Control Theory, with J. L. Me Ise,McGraw-Hill Book Co., second edition, 1973.

ROBERT R. KORFHAGE, Ph.D., (University of Michigan)Professor

Logic and Algorithms, John Wiley & Sons, 1966;Spanish edition, 1970: Japanese edition, 1971.Calculus, with H. Flanders and J. J. Price,Academic Press, 1970.A First Course in Calculus with Analytic Geometry,with H. Flanders and J. J. Price, Academic Press,1973.

WILLIAM F. LEONARD, Ph.D., (University of Virginia)Associate Professor

Electrons and Crystals, with Thomas L. Martin, Jr.,Brooks/Cole Publishing Co., 1970.

THOMAS L. MARTIN, JR., Ph.D., (Stanford University)Professor and Dean of the Institute of Technology

Ultrahigh Frequency Engineering, Prentice-Hall,Inc., 1950.Electronic Circuits, Prentice-Hall, Inc., 1955;Japanese edition, 1956; Russian edition, 1957.Physical Basis for Electrical Engineering, Prentice-Hall, Inc., 1957; British edition (MacMillan), 1958;Japanese edition, 1963.Strategy for Survival, with D. C. Latham,University of Arizona Press, 1963.Electrons and Crystals, with W. F. Leonard,Brooks/Cole Publishing Co., 1970,The Britannica Review of Developments inEngineering Education, Chapter 1, "AdministrativeOrganization," Vol. 1,1970, Encyclopedia Britannica;ed. Newman Half, sponsored by A.S.E E.

JAMES L. MELSA, Ph.D., (University of Arizona)Professor

Linear Control Systems, with D. G. Schultz,McGraw-Hill Book Co., 1969,Computer Programs for Computational Assistancein the Study of Linear Control Theory, with S. K.Jones, McGraw-Hill Book Co., second edition, 1973.Introduction to Probability and StochasticProcesses, with A. P. Sage, Prentice-Hall, Inc., 1972.State Functions and Linear Control Systems,McGraw-Hill Book Co., 1967.

Estimation Theory with Applications toCommunication and Control, McGraw-Hill Book Co.,1971,System Identification, with A. P. Sage.Academic Press, 1971.

LOUIS R. NARDIZZI, Ph.D., (University of SouthernCalifornia) Associate Professor

Basic Circuits and Electronic Experiments aunified laboratory manual and text. Van Vostrand.1973

BEHROUZ PEIKARI, Ph.D., (University of Californiaat Berkeley) Associate Professor

Circuit Analysis: With Computer Applications toProblem Solving, with S. C. Gupta and J. W. Bayless,Intext Educational Publishers, 1972.

ANDREW P. SAGE, Ph.D., (Purdue University)Professor

Optimum Systems Control, Prentice-Hall, Inc., 1968.Estimation Theory with Applications toCommunication and Control, with J. L. Melsa,McGraw-Hill Book Co., 1971.System Identification, with J. L. Melsa,Academic Press, 1971.Introduction to Probabilitty and Stochastic Processes,with J. L. Melsa, Prentice-Hall, Inc., 1972.

CHARLES R. VAIL. Ph.D., (University of Michigan)Circuits in Electrical Engineering, Prentice-Hall. 1950.

Appendix III Active Grants/Contracts in Force During Fiscal Year 1972-73 44

80-60 K. L. Ashley $15.000Title: "Amphoteric Dopants in the Active Regionof GaAs Lasers"Sponsor: Department of the Army, DAAK02-73-C-G226Duration: April 1, 1973 to December 31, 197385-04 K. L. Ashley $54.648Title: "Recombination in Semiconductors ThroughNegatively-Charged Recombination Chambers"Sponsor: N.S F. GK-24145Duration: June 1, 1970 to May 31, 197385-05 U. N. Shat $90,396Title: "Analysis of Some Oueueing Systems"Sponsor: N.S.F. GK-19537Duration September 1, 1970 to October 31. 197387-92 H. A. Blum $10.000Title: "Solar Energy Applications Research"Sponsor: Alcoa FoundatiOnDuration: November 13, 1972 to December 31. 197388-68 H. A. Blum $2,650Title: "Massive Solar Energy Applications"Sponsor: N.S.F. Institutional Grant (84-92)Duration: August 1, 1972 to July 3, 197380-43 J. K. Butler $30,658Title: "Study of Semiconductor Laser Modal Fieldsand Their Radiation Patterns"Sponsor: USAMERDC-DAAK02-71-C-0263, P00001Duration: May 4, 1971 to July 3, 197380-59 J. K. Butler $16,216Title: "Electromagnetic Field Studies in Solid StaleInjection Lasers"Sponsor: Department of the Army, DAAK02-73-C-0154Duration: January 19, 1973 to December 31, 197383-44 J. K. Butler $19.151Title: "Optical Field Distributions and Model SelectionProperties of GaAs (ALGA) as Lasers"Sponsor: N.A.S.A. (Multidisciplinary Grant,Duration: June 1, 1971 to December 31, 197386-78 J. Cernosek $15,000

"Photoelastic Analysis of Helicopter Structures"Sponsor: Bell Helicopter CompanyDuration: April 1, 1973 to December 31, 197383-32 T. L. Chu $127,292Title: "Boron Arsenide Luminescent Devices"Sponsor: N.A S.-NCR-44-007-042Duration: July 1, 1970 to June 30, 197483-47 T. L. and S. S. Chu $15,790Title: "Gallium Nitride Opteolectron4c Devices"Sponsor: N.A.S.A.-Langley-NGR 44-007-052Duration: September 1, 1972 to August 31, 197283-48 T. L. Chu $7,400Title: "Study of Physical Pry.momena Related toCrystal Growth in the Space Environment"Sponsor: N.A.S.A., NAS1-118699Duration: July 21, 1972 to January 23, 197387-84 S. Chu $24,443Title: "Crystal Structure Studies of Heterocyclic SulfurCompounds"Sponsor: Welch Foundation N-495Duration: May 1, 1972 to April 30, 197488-66 D. Cohn $6,585Title: "Modeling Social Epidemics"Sponsor: SMU "Seed Grant"Duration: February I, 1972 to May 31, 1973

86-07 M. Collins $113,507Title: "Optimal Operating Policy for MetropolitanMultiple Water Supply Reservoir System"Sponsor: OWRR 14-31-0001-3739Duration: June 1. 1972 to July 31, 197488-62 M. Collins $5,118Title: "Transient Dynamics of Two-Liquid PorousMedia Flows"Sponsor: SMU "Seed Grant"Duration: January 1, 1972 to December 31, 197282-88 J. W. Eberle $1,000Title: "Supply Allowance for Douglas E. Whitley"Sponsor: HEW PHS 1F03 GM55506-01Duration: November 1, 1972 to October 31, 197382-90 J. W. Eberle $1,000Title: "Supply Al',!owance for Herbert K. Hagler"Sponsor: HEW PHS 1F03 GM55621-01Duration: November 1, 1972 to October 31, 197384-94 D. J. Frailey $22,150Title: "Undergraduate Research Participation"Sponsor: N.S.F. GY-7383Duration: January 1, 1970 to July 31, 197388-57 D. J. Frailey $5,925Title: "A Study of Storage Allocation Methodsfor Simple Data Structures"Sponsor: SMU "Seed Grant"Duration: June 1, 1971 to June 30, 197380-51 S. C Gupta $50.527Title: "Minimum Rate Digital Voice Transmission"Sponsor: Defense Communication Agency#100-72-C-0023Duration: May 1, 1972 to June 30, 197383-30 S. C. Gupta $43,271Title: "Digital Phase Locked ':echniques for AerospaceCommunications"Sponsor: N.A.S.A. NGR 44-007-037Duration: September 1, 1969 to August 30, 197283-39 S. C. Gupta $62,432Title: "Digital Communications for Aircraft"Sponsor: N.A.S.A. NGR 44-007-049Duration: January 1, 1971 to August 31, 197382-84 J. P. Holman $33,041Title: "Air Pollution Control fluidized VortexIncineration"Sponsor: Environmental Protection Agency R-801073Duration: May 1, 1972 to October 30, 197385-20 J. P. Holman $35,568Title: "Experimental and Analytical Studies of JetBoiling Cooling Techniques"Sponsor: N.S.F. GK-24637Duration: September 1, 1971 to February 28, 197482-79 L. L. Howard $1,000Title: "Fellowship Supply Allowance for Charles L.Meyers, Jr."Sponsor: HEW-1-F03-GM52121-01-BENDuration: August 1, 1971 to July 31, 197383-45 D. B. Johnson $22,573Title: "Dynamics of Flexible Spacecraft"Sponsor: 'N.A.S.A. (Multidisciplinary Grant)Duration: January 1, 1971 to February 28, 197380-61 R. M. Jones $17,296Title: "Plastic Volume Change Effects in Deformationof Graphitic Materials"

45

Sponsor: Wright-Patterson AFB. F33615-73-C-5124Duration: March 1, 1973 to November 30, 197380-63 R. M. Jones $10.555Title, "Mechanics of Composite Materials with DifferentModuli, in Tension and Compression"Sponsor: ONR No. N000r 4-72-A-0296Duration: April 1, 1973 to March 31, 197487-88 R. R. Korthago $11,000Title: "Statistical Survey of Health Sciences Library"Sponsor: American Medicai Assn., 5R01-LM-0064-1Duration: June 1, 1972 to February 23, 197380-52 W. F. Leonard $70,977Title: "Characterization and Optimization of InfraredDetector"Sponsor: WPAFB (4950 Test Wing) F33615-72-C-1818Duration: June 1, 1972 to December 31. 197483-46 W. F. Leonard $14,288Title: "Vacuum Deposition and Characterization of

Antimonide Alloys"Sponsor: N.A.S.A. (Multidisciplinary Grant)Duration: June 1, 1971 to December 31, 197385-29 W. F. Leonard $68,475Title: "Thermoelcttric Power of Noble Metals"Sponsor: N.S.F. GH-33178Duration: March 15, 1972 to February 28, 197483-29 W. S. McDonald $18,170Title: "Photoelastic Model for the Evaluation ofAxisymmetric Composite Structur'Js"Sponsor: N.A.S.A. (Multidisciplinary Grant)Duration: September 1, 1968 to December 31, 197387-78 J. L. Mersa $9,800Title: "Development of a Remote Time-Sharing HybridComputer Terminal' System for Off-Campus StudentsVia TAGER TV"Sponsor: Alfred P. Sloan FoundationDuration: August 1, 1971 to August 31, 197282-55 L. Nardizzi $2,536Title: "Fellowship Support - Stokely"Sponsor: HEW-4F03-GM42941-04Duration: June 2, 1969 to December 1, 197285-02 L. Nardizzi $25,000Title: "Instructional Scientific Equipment"Sponsor: N.S.F. GY-8251Duration: July 1, 1970 to July 31, 197285-10 L. Nardizzi $27,030

"Cooperative College-School Science Program"Sponsor: N.S.F. GW6557Duration: January 1, 1971 to September 30, 197285-25 L. Nardizzi $32,664Title: "Cooperative College-School Science Programs"Sponsor: N.S.F. GW-7078Duration: January 4, 1972 to June 30, 197385-32 L. Nardizzi $17,600Title: "Instructional Scientific Equipment Program"Sponsor: N.S.F. GY-10155Duration: July 1, 1972 to June 30, 197488-74 W. C. Nylin, Jr. $5,964Title: "Study of 2.n Automatic Reorganization Systemfor Modular Programs"Sponsor: SMU "Seed Grant"Duration: April 1, 1973 to August 31, 197383-41 B. Peikari $17,297

Title: "Design of Linear Time-Varying Networks"Sponsor: N.A.S.A. (Multidisciplinary Grant)Duration: January 1, 1971 to July 31, 197280-35 A. P. Sage $72,309Title: "Automatic Navigation"Sponsor: A.F.O.S.R.Duration: September 1, 1967 to August 31, 1972(5 year total SSOOK)80-54 A. P. Sage $131,034Title: "Development of a Configuration Concept ofa Speech Digitizer Based on Adaptive EstimationTechniques"Sponsor: Defense Communications Agency100-72-C-0036Duration: June 1, 1972 to July 31, 197385-31 A. P. Sage $37,994Title: "System Identification in Large-Scale Systems"Sponsor: N.S.F. GK-33348Duration: September 1, 1972 to August 31, 197380-48 R. L. Simpson $28,651Title: "Making Laser Anemometer Measurements ina Separating Boundary Laser Produced by an Advet sePressure Gradient"Sponsor: AROD-DA-ARO-D-31-124-72-G31Duration: October 1, 1971 to September 30, 197383-43 R. L. Simpson $22,261Title: "Development of a New Airfield Anemometerto Improve Operations Efficiency"Sponsor: N.A.S.A. (Multidisciplinary Grant)Duration: January 1, 1971 to September 30, 197285-07 R. L. Simpson and W. G. Wyatt $21,730Title: "Hot-Film Anemometer Measurements ofConcentration in Turbulent Flow"Sponsor: N.S.F. GK-20016Duration: November 15, 1970 to April 30, 197380-42 S. A. Szygenda $211,174Title: "Analysis and Synthesis of Diagnosis andDesign Techniques for Digital Systems Requiring HighMaintainability / Reliability"Sponsor: DNR-N00178-71-C-0148Duration: January 1, 1071 to August 31, 197385-16 F. W. Tatum (J. E. Brooks) $6,100Title: "Fellowship for S. K. Jones"Sponsor: N.S.F.-7131-12Duration: June 1, 1971 to August 31, 197383-34 W. G. Wyatt $21,344Title: "Film Conductance Coefficients"Sponsor: N.A.S.A. (Multidisciplinary Grant)Duration: June 1, 1969 to November 30, 1972

SMU Foundation for Science and Engineering 46

Board Officers and Executive CommitteeMr. Mark Shepherd, Jr. Chairman

PresidentTexas Instruments Incorporated

Mr. Jerry S. Stover Vice ChairmanPresidentCommunications Industries, Inc.

Mr. Spencer Taylor Vice ChairmanPresident of the Drilling DivisionSEDCO, Inc.

Mr. Charles M. Mayhew SecretaryDirectorGardner-Denver Company

Dr. Frederick E. Terman PresidentProvost EmeritusStanford University

Dr. Thomas L. Martin, Jr. Vice PresidentDeanInstitute of TechnologySouthern Methodist University

Mr. Joe C. BridgefarmerPresidentURS/Forresa and Cotton, Inc.

Dr. Paul HardinPresidentSouthern Methodist University

Mr. J. Erik JonssonHonorary Chairman of the BoardTexas Instruments Incorporated

Dr. Willis M. TateChancellorSouthern Methodist University

Mr. C. A. Tatum, Jr.Chairman of the Board and Chief ExecutiveTexas Utilities Company

Dr. Robert WidmerVice President of Research and EngineeringGeneral Dynamics Corporation

Board MembersMr. Richard A. Arnett

PresidentTeledyne-Geotech

Mr. John W. BeattyPresidentBeatty Eng .neering Company

Mr. A. Earl Cullum, Jr.Managing PartnerA. Earl Cullum, Jr. & Associates

Mr. John DixonChairman of the Board and PresidentE-Systems, Inc.

Mr. E. J. DucayetFort Worth, Texas

Mr. Leroy EricksonPresidentVaro, Inc.

Mr. Cecil H. GreenDirectorTexas Instruments Incorporated

Mr. Stephen J. HayChairman of the BoardHesse Envelope Company

Dr. Wiliam B. Heroy, Jr.Vice President-TreasurerSouthern Methodist University

Mr. L. B. HoustonDallas. Texas

Mr. Harding L. LawrenceChairman of the Board and Chief Executive OfficerBraniff International

Mr. Eugene McDermottDirectorTexas 1,nstruments Incorporated

Mr. Joseph F. McKinneyPresident and Chief Executive OfficerTyler Corporation

47

Mr. Robert H. McLemorePresidentOtis Engineering Corporation

Mr. Herman L. Philipson, Jr.PresidentRecognition Equipment Incorporated

Mr. Marion B. SolomonChairman of the BoardAustin Bridge Company

Mr. Paul ThayerChairman and Chief Executive OfficerThe LTV Corporation

Mr. Lee S. Turner, Jr.President and Chief ExecutiveDallas Power & Light Company

Mr. Carl P. WallaceChief Executive OfficerSam P. Wallace Co., Inc.

Mr. Robert C. WilsonPresident and Chief Executive OfficerCollins Radio Company

Mr. John D. WisenbakerPresidentCore Laboratories, Inc.

Technical Advisory CouncilDr. Wernei J. Beyen

Director, Semiconductor Researchand Development Laboratory

Texas Instruments IncorporatedDr. F. E. Brooks

Senior Scientific ConsultantE-Systems, Inc.

Mr. Warren B. BrueneSenior Technical StaffTelecommunications Systems EngineeringCollins Radio Company

Dr. Robert L. CarrelExecutive Vice PresidentElectrospace Systems, Inc.

Mr. Thomas R. CuthbertEngineerTexas Instruments Incorporated

Dr. Henry B. FergusonManager of Exploration ResearchAtlantic Richfield Company

Dr. Y. P. GuptaManager, Structural Mechanics and MatersAdvanced Technology Center, Inc.

Dr Albert H. HalffPresidentAlbert H. Halff & Associates

Mr. Bertram KelleySenior Vice PresidentBell Helicopter Company

Dr. Lloyd K. LauderdaleVice President of Research and EngineeringE-Systems, Inc.

Dr. J. Ross MacdonaldVice President, Corporate Research and EngineeringTexas Instruments Incorporated

Dr. Bruce MayoDirector of Equipment Research

and Development LabTexas Instruments Incorporated

Dr. Leo S. PackerVice President, Corporate ResearchRecognition Equipment Incorporated

Dr. Ted S. Webb, Jr.Director of Aerospace TechnologyGeneral Dynamics Corporation

48

Corporate and Business DonorsAlfred P. Sloan FoundationAllied Components, Inc.Alpha Systems, Inc., EmployeesAshland Oil Foundation, Inc.Atlantic Richfield CompanyAustin Bridge CompanyAustin Paving CompanyAustin Steel CompanyAvery Mays Construction Co.Beard Plumbing CompanyBeatty Engineering CompanyBell Helicopter CompanyCarrier-Bock CompanyChemetron FoundationCoca-Cola Bottling CompanyCollins Radio FoundationComputer Technology, Inc.Conley-Lott-Nichols Machinery CompanyContinental Telephone Service CompanyCore LaboratoriesCullum, A. Earl, Jr., & AssociatesDallas Air Conditioning CompanyDallas Power and Light CompanyDelta P, Inc.Delta Steel BuildingsDr Pepper CompanyDresser Industries, Inc.Earth ResourcesEmployer's Casualty CompanyExcellence in Education FoundationFischbach & Moore, Inc.Forrest & Cotton, Inc.Gardner-Denver CompanyGeneral Dynamics CorporationGeneral Portland Cement CompanyGifford-Hill Pipe CompanyGoodson, Raymond L. Jr., Inc.Grace, W. E., Mfg. Co.Halliburton Educational Fdn,Hall-Mark Electronics Corp.Herman Blum Consulting EngineersHughes Aircraft CompanyIndustrial Properties CorporationInternational Business Machines

J. C. Penney Company, Inc.Jones-Blair Paint CompanyJonsson FoundationKemp Engineering CompanyKraft FoodsL. & B. LabsThe LTV CorporationLone Star Gas CompanyMosher Steel FoundationOKC CorporationPew Memorial TrustReliance Clay ProductsSaturn Industries, Inc.SEDCO, Inc.Southwest Airmotive CompanyStandard Manufacturing CompanyTech Club ofTELSCO IndustriesTeledyne-Geotech, Inc.Texas Bitulithic Co., Inc.Texas Distributors, Inc.Texas Employers Ins. Ass'n.Texas Instruments FoundationTexas Power and Light CompanyThe Lummus CompanyTyler CorporationWestern Electric FundIndividual DonorsAlexander, Mrs. C. N.Box, Cloyce K.Brooks, Marvin J.Chu, Drs. T. L. & ShirleyClements, W. P., Jr.Constantin, E., Jr.Dotson, Cecil P.Ellis, Van C.Forrest, Mrs. T. CarrGattis, R. D.Green, Cecil and IdaGronberg, Mrs. M. JaneGupta, Dr. Someshwar C.Haggerty, P. E.Harkey, Jack W.Harrison, Ed. M.Heray, Dr. W. B., Jr.

Holman, Dr. Jack P.Ingram, Elliott H.Johnson, Dr. David B.Jones. Dr. and Mrs. R. M.Jonsson, J. ErikKeys. John D.Kilby, Jack S.King, James D.Kitchen, Ronald E.Lee, Mr. and Mrs. Joe T.Lindsley, Porter, Jr.Martin, Dr. Thomas L., Jr.McDermott, Mr. and Mrs. EugeneMcDonald, Dr. W. S., Jr.McLemore, RobertMeaders, L. B.Me Ise, Dr. J. L.Olson, Mr. and Mrs. R. W.O'Rourke, G. Paul, Jr.Parnell, Mr. and Mrs. D. M., Jr.Pruett, J. R.Randle, L. VernonRichards, Fred F.Riley, Mr. & Mrs. James C.Sage, Dr. Andrew P.Scruggs, William L.Shannon, StanShepherd, Mark, Jr.Smith, BryanSolomon, Marion B.Spencer, Morris G.Stover, Jerry S.Tate, Raymond L.Tate, Dr, Willis M.Terman, Fred B.Thompson, SophusThomsen, Carl J.Turner, L. S., Jr.Vail, Dr. C. R.Walling, B. G.Watson, Dr, Hal, Jr.Weynand, Dr. E. E.Wilcox, Dr. M. W.Wisenbaker, J. D.

FILMED FROM BEST AVAILABLE COPY

The School of Engineering at Southern MethodistUniversity was organized in 1925. Over the yearsit provided traditional undergraduate education inengineering within the framework of a compulsorycooperative work-study program. The programs, whilecompetent, were not completely responsive to theneeds and requirements of the burgeoning Dallas/FortWorth scientifically based industry which developedin the 1960's. These companies experienced an intenseneed for graduate programs at the Master's level andat the Ph.D. level, programs which would be at thecutting edge of modern technology. This was recog-nized in 1965 with the organization of the SMUFoundation for Science and Engineering. A new Deanwas hired in 1966, and plans were drawn up to makea major change in the character of the engineeringprogram at SMU.

In 1967, the old School of Engineering was trans-formed into the institute of Technology, an organizationto be devoted to the development of superior programsof education and research and to superior students atall.acadernic Ariclitionally, it was specifiedthat the new InstiMe should set its objectives to standamong the very top engineering schools of the UnitedStates, using whatever standards of performancedefined such ranking.

Many schools set such lofty goals for themselvesbut all too often fail to specify how they will knowwhether they are making progress toward thosegoals. Thus, at a very early stage, it was determinedthat the quantitative evaluation of all elements of theeducational process would be necessary for theInstitute of Technology to determine whether it wasmaking progress toward its goals and at what speeds.As a result, each year special attention is directed tosome fundamental aspect of Institute operations and

attempts are made to quantify them. In every casethese matters have been written up and presentedin the first part of the Annual Report for that year.The second part of each Annual Report then presentsa systematic, quantitative review of significant factorswhich reflect the progress, or lack, of the Institutetoward its goals.

A review of the subject matter of past AnnualReports indicates the extent of this effort towardquantNative evaluation.

1969 Annual ReportIdentification of the 11 factors which are commonto the very top engineering schools.

1970 Annual ReportThe measurement of quality in schools of engi-neering and sciencecan it be done and whatare the critical factors?

1971 Annual ReportThe quantitative evaluation of faculty performanceand the identification of standards of performancenecessary to secure quality and excellence inengineering education.

1972 Annual ReportQuantitative evaluation of the American economyand college-age population to determine theiimpact of these factors on the future directions(of engineering education.

1973 Annual ReportNew concepts in educational decision makingand budgeting which are drawn from industrialmethods of Zero-base Budgeting and thetechniques of Objectives, Strategies and Tactics.

The 1973 Report, in common with all the others,closes with a quantitative summary of significantfactors during the year which reflect on the performanceof the Institute.