supporting business decision-making good information is essential for fact-based decision- making

Supporting Business Decision-Making

Good Information is Essential for Fact-Based Decision-Making

The Importance of Knowledge

For centuries managers have used the knowledge available to them to make decisions

The amount of knowledge used to make decisions has increased exponentially

The Importance of Decision MakingDecisions today determine the landscape of

tomorrow's world

Decision Making

The common thread that runs through all managerial functions

Decision = a choice of one course of action from a number of alternatives leading to a certain desired objective

Classifying Decisions

Functional area Finance decisions Marketing decisions Production decisions Personnel decisions, etc.

Managerial Function Planning decisions Organizing decisions Control decisions, etc.

Classifying Decisions

Management LevelStrategic decisionsTactical decisionsOperational decisions

Structure of decisionStructured/Programmed decisionsSemi-structured decisionsUnstructured decisions

Decision Support System Definition

A decision Support System is an interactive computer-based system or subsystem that helps people use computer communications, data, documents, knowledge and models to identify and solve problems, complete decision process tasks, and make decision

“DSS comprise a class of information system that draws on transaction processing systems and interacts with the other parts of the overall information system to support the decision-making activities of managers and other knowledge workers in organizations” (Sprague and Carlson, 1982, p. 9).

DSS are ancillary or auxiliary systems; they are not intended to replace skilled decision-makers

Reference - Power (2008)

DSS Assumptions

Is good information and analysis essential for fact-based decision-making?

Build DSS when good information is likely to improve decision-making

Build DSS when managers need and want computerized decision support


MIS and DSS Brief History

Late 1960s, MIS focused on providing structured, periodic reports Late 1960s, first DSS built using interactive computer systems,

Scott-Morton 1975-1980 DSS using financial models with “What if?” analysis 1975 Steve Alter MIT dissertation 1979-1982 Theoretical foundations Mid-1980s Executive Information Systems and GDSS Early 1990s shift to client/server DSS, Business Intelligence, Bill

Inmon and Ralph Kimball 1995 Data warehousing, data mining and the world-wide web 1998 Enterprise performance management and balanced scorecard 2000 Application service providers (ASPs) and portals


DSS History - Specifics 1951 Lyons Tea Shops used LEO 1 digital computer to factor in weather forecasts to

determine what “fresh produce” delivery vans would carry to Lyon’s UK shops Later SAGE a control system for tracking aircraft used by NORAD from the 1950s to

the early 1980s (real time control, communications) Mid-1960s NLS first hypermedia groupware system was the forerunner to GDSS 1965 more cost effective due to the IBM System 360 and other more powerful

mainframes and minicomputer systems 1970s companies were implementing a variety of DSS 1982 DSS considered a new class of IS 1980s financial planning systems became popular “What-if” analysis Mid-1980s DSS were supporting managers in operations, financial management,

management control and strategic decision making (scope, purpose and targeted user base was expanding)

1985 P&G built a DSS that linked sales information and retail scanner data


DSS Conceptual Perspective

DSS are both off-the-shelf, packaged application and custom designed systems.

Alter (1980) Designed specifically to facilitate a decision process Should support rather than automate decision making Should be able to respond quickly to changing needs

of decision makers

Business intelligence, knowledge management


Characteristics of DSS

Body of knowledge Record keeping Provide structure for a particular decision Decision maker interacts directly with DSS Facilitation Ancillary. Not intended to replace decision makers Repeated used Task-oriented Identifiable Decision impact. Improve accuracy, timeliness, quality and overall

effectiveness of a specific decision or a set of related decision


Characteristics of Decision Support Information Right Information – accurate, relevant and

complete Right Time – current, timely information Right Formation – easy to understand and

manipulate Right Cost – Cost/Benefit Trade-off


Is a DSS an MIS?

MIS describe a broad, general category of information systems or a functional reporting system.

MIS is used to identify an academic major Data-Driven DSS meet management reporting

needs Decision Support Systems is a broad category of

interactive, analytical management information systems


Transaction Processing

What is a transaction? A work task recorded by a data capture system. i.e., Purchase, order, payment

Record current information but does not maintain a database of historical information

Emphasize data integrity and consistency


DSS vs. Transaction Processing Systems (TPS) TPS is designed to expedite and automate

transaction processing, record keeping, and business reporting

TPS is related to DSS because TPS provides data for reporting systems and data warehouses

DSS are designed to aid in decision-making tasks and/or decision implementation


DSS Applications

Major airlines use DSS for many tasks including pricing and route selection

DSS aid in corporate planning and forecasting Specialists use DSS that focus on financial and simulation models Frito-Lay has a DSS that aids in pricing, advertising, and promotion Monsanto, FedEx and most transportation companies use DSS for

scheduling trucks, airplanes and ship Wal-Mart has large data warehouses and data mining systems There are many DSS on the Internet that help track and manage

stock portfolios, choose stocks, plan trips, and suggest gifts

Alter’s Categories of DSS

Data-Driven File Drawer Systems Data Analysis Systems Analysis Information Systems

Model-Driven Accounting and Financial Models Representational Models Optimization Models

Knowledge-Driven Suggestion Models



Data-DrivenFile Drawer SystemsData Analysis SystemsAnalysis Information Systems



Model-DrivenAccounting and Financial ModelsRepresentational ModelsOptimization Models



Knowledge-DrivenSuggestion Models


Framework

Primary framework dimension is the dominant component or driver of the decision support system (Power, 2002)

Secondary dimensions areThe intended or targeted users,The specific purpose of the systemThe primary deployment or enabling

technology


Identify the system component that provides primary functionality dominant component

Communication technologies Data and data management Documents and document management Knowledge base and processing Models and model processing


DSS Framework

Communications-driven DSS Interactive computer-based systems intended

to facilitate the solution of problems by decision-makers working as a group

Group DSS may be communications-driven or model-driven


DSS Framework

Data-driven Includes File Drawer/Management Reporting, Data

Warehousing and Analysis Systems, Executive information Systems (EIS), and Geographic Information Systems external data

Emphasize access to and manipulation of large databases and especially a time-series of internal company data and sometimes external data

Document-driven DSS Retrieve and manage unstructured documents and

web pages


DSS Framework

Knowledge-driven Built using AI tools, data mining tools and

management expert systems

Model-driven Include systems that use accounting and financial

models, representative models, and optimization models

Emphasize access to and manipulation of a model, Whit If? analysis


DSS Framework

Intended Users, e.g. Inter-Organizational DSS Designed for customers and suppliers Data, model, document, knowledge, or

communications-driven Purpose, e.g. Function and Industry-Specific

DSS A DSS that is designed specifically for a narrow task Specific rather than General purpose Vertical Market/Industry-Specific


Describing a Specific DSS

A web-based, model-driven DSS for truck routing used by a dispatcher

A handheld PC-based, knowledge-driven DSS for accident scene triage used by an EMT

A web-enabled, data-driven DSS for real-time performance monitoring used by a factory manager

A PC-based, model-driven DSS for planning supply chain activities used by logistics staff


Enabling Technology

USE the Web to deliver and category of DSS = Web-based DSS

Web-based, Communications-driven DSS Web-based, Data-driven DSS Web-based, Document-driven DSS Web-based, Knowledge-driven DSS Web-based, Model-driven DSS


Building DSS - components

Internal Data• Personnel• Production• Finance• Marketing

External Data• Dow Jones• Reuters

Database Component• Knowledge• Data• Documents

Model Component• Interface Engine• Models

Communications Component• DSS Architecture• Network• Web server• Client/Server• Mainframe

User Interface Component• Dialog• Maps• Menus, Icons• Representations• Charts, graphs• Web Browser

Users


Building DSS – User Interface

User InterfaceMost Important ComponentTools needed

DSS Generator Query & Reporting Tools Front-End Development Packages


Building DSS – Database

DatabaseCollection of current and historical data from a

number of sourcesLarge databases are called data warehouses

or data martsSize of data warehouses are discussed in

terms of multiple Terabytes (TB)


Building DSS – Models

Mathematical and Analytical ToolsUsed and manipulated by managersEach Model-driven DSS has a specific

purposeValues of key variables and parameters are

frequently changed – “What IF?” analysis


Building DSS – Architecture

DSS Architecture and NetworkingHow hardware is organizedHow software and data are distributed and

organizedHow components of the system are integrated

and connectedCommunications component


Challenges of DSS

Rapid technology change Managers as users and customers Major issues

What to computerize? What data? Source? What processing and presentation? Are current DSS results decision-impelling? What technology for a new DSS?


Gaining Competitive Advantage

DSS can create a Competitive Advantage if the following 3 criteria are met Must be a major or significant strength or capability of

the organization DSS must be unique and proprietary to the

organization DSS must be sustainable for approximately 3 years

How can DSS provide a competitive advantage? Internet technologies have opened doors

for innovative Web-based DSS Inter-organizational DSS can improve

linkages with customers and suppliers Increasing efficiency and eliminate staff

and activities, cost advantage New products and services, differentiation

How can DSS provide a competitive advantage? Communications-Driven DSS can remove

time and location barriers Increase focus on specific customer

segments Better fact-based decision-making Decrease decision cycle time

Strategic DSS Examples

Frito-Lay L.L. Bean Lockheed - Georgia Mrs. Fields Cookies Wal-Mart

A company needs to continually invest in a Strategic DSS to maintain any advantage.

Classic examples!!


Frito-Lay

Route Sales people were all given a hand-held computerEnables sales people to have decision-

making roleAllows Frito-Lay to track productsThe data is put into a Data-Driven DSS

Automated a cumbersome process and improved the quality of data


L.L. Bean

Consultants hired to design a system that would provide better allocation of resources in telemarketing

Economic Optimization Model System (EOM) This Model-Driven DSS examined variables such as

the number of telephone lines to carry incoming traffic, number of agents, and the queue capacity

System generates specific resource amounts the company should deploy to be most economically advantageous


Mrs. Fields Cookies

Developed MIS in early 1980’s to provide uniformity in store management; also supporting rapid expansionDesigned to serve two purposes

Control and better management decision-making

Enabled each store to be run as Debbie Field ran the original store


Mrs. Fields Cookies

Knowledge-Driven DSS developed that automated routine activities and responded to exceptions by prompting the store manager for inputTracked financial performance of each store,

provided comprehensive scheduling of operations, including market support, hourly sales goals, and assisted with candidate interview selection


Wal-Mart

Creates a competitive advantage that other retailers have tried to mimic but have not duplicated Result of Retail Link and FAR

Less inventory in stores, more inventory of the right products at the right time and place, and improved revenues for both supplier and retailer

Collaborative Forecasting and Replenishment Initiative (CFAR) Evaluating ways to apply wireless technology in stores.

Testing emerging RFID smart-tag systems, to replace bar codes with a more efficient product-tracking mechanism.


Advanced Scout

IBM has prototyped software to help National Basketball Association (NBA) coaches and league officials organize and interpret the data collected at every game. Using software called Advanced Scout to prepare for a game, a coach can quickly review countless stats: shots attempted, shots blocked, assists made, personal fouls. But Advanced Scout can also detect patterns in these statistics that a coach may not have known about. Advanced Scout software provides an easy and meaningful way to process information. "It helps coaches easily mine through and analyze a lot of data and no computer training or data analysis background is required," says Dr. Inderpal Bhandari, computer scientist at IBM's T.J. Watson Research Center. Patterns found through analysis are linked to the video of the game. Coaches can look at just those clips that make up an interesting pattern.

FedEx Business Intelligence System Federal Express, based in Memphis, Tenn., rolled out

Business Intelligence capabilities to a global base of 700 end-users. FedEx created a central, integrated data warehouse hub, which provides Web-based, real-time access to financial and logistical information necessary for planning and decision-making. The solution, from Pinnacle Solutions Inc., was deployed on a group of Dell PowerEdge servers running Windows NT Server 4.0. Data is stored in an Oracle database, and analytical queries are run against a separate server running Hyperion Essbase, an online analytical processing (OLAP) engine. Most access is from browsers over the corporate intranet, along with some standard client/server deployments using Excel spreadsheets.

DSS Benefits

Improve personal efficiency Expedite problem solving and improve

decision quality Facilitate interpersonal communication Promote learning or training Increase organizational control


Other DSS Benefits

Extending decision-makers’ ability to process information and analyze it

Helping decision-makers deal with complex, large-scale problems Decreasing the amount of time needed to make a decision, reducing

the decision cycle Improving the reliability and enforcing the structure of a decision

process Encouraging exploration and discovery by the decision-maker in

less structured or more novel decision situations related to the domain or scope of the DSS;

Creating a competitive or strategic advantage for an organization.

Some DSS development opportunities are better than others.


Risks

Gaining any advantage may require large financial investments

Competitors’ responses may result in a heated race to gain or regain market share

Technology risks include: Picking the wrong vendor, using new technology

too early in technology life cycle, and using a technology that might soon become obsolete


Risks

People cause the greatest risk Inability to predict human behaviors and

reactionsBasic human instinct to resist changePower strugglesPersonal motives* No matter how wonderful a proposed DSS, if people resist the

change the system fails


Questions for Further Thought

Do managers need the support provided by DSS?

Do managers want to use DSS?