Lecture Business management information system - Lecture 27: Supporting decision making

The topics discussed in this chapter are: Use of IT to support decision making covers a broad swath of territory; some technologies aim to alert people to anomalies, discontinuities, and shortfalls; others aim to make decisions, either as recommendations to people or to act on behalf of people; handing over decisions to systems has its pros and cons, thus their actions need to be monitored.

Supporting Decision Making

Lecture 27

Systems for Supporting

Knowledge-Based Work

n Today we shall look at,

¨ Decision Support Systems (DSS)

¨ Data Mining

¨ Executive Information Systems (EIS), and

¨ Expert Systems

¨ Agent-based Modelling

n How to create a real-time enterprise

n Case examples include: a problem-solving scenario, Ida Foods, a major services company, Harrah’s

Ore-Entertainment, Xerox Corporation, General Electric,

American Express, Delta Air Lines, a real-time interaction

on a website, and Western Digital

n Most computer systems support decision making because all software programs involve automating decision steps that people would take

n Decision making is a process that involves a variety

of activities, most of which handle information

n A wide variety of computer-based tools and

approaches can be used to confront the problem at hand and work through its solution

A PROBLEM-SOLVING SCENARIO

Case Example – Supporting Decision Making

n Using an executive information system, (EIS) to

compare budget to actual sales

n Discover a sale shortfall in one region

n Searches for the cause of the shortfall

n But couldn’t find an answer

A PROBLEM-SOLVING SCENARIO Case Example – Supporting Decision Making

cont.

Investigate – several possible causes

n Economic Conditions – through the EIS & the Web

accesses:

¨ Wire services

¨ Bank economic newsletters

¨ Current business and economic publications

n Competitive Analysis – through the same sources

investigates whether competitors:

A PROBLEM-SOLVING SCENARIO Case Example – Supporting Decision

Making cont.

¨ Have introduced a new product

¨ Have launched an effective ad campaign

n Written Sales Report – browses the reports

¨ “Concept based” text retrieval system makes this easier

n A Data Mining Analysis

¨ Looking for any previously unknown relationships

A PROBLEM-SOLVING SCENARIO

Case Example – Supporting Decision Making

cont.

n Then accesses a marketing DSS – includes a set of

models to analyze sales patterns by:

¨ Product

¨ Sales representative

¨ Major customer

Result – no clear problems revealed

Action – hold a meeting, in an electronic meeting room

supported by group DSS (GDSS) software

A PROBLEM-SOLVING SCENARIO

Case Example – Supporting Decision

Making cont.

n This scenario illustrates:

¨ The wide variety of activities involved in problem

solving, and

¨ The wide variety of technologies that can be used to assist decision makers and problem solvers

Technologies that Support Decision Making

n The purpose of tractors, engines, machines etc = to enhance humans’ physical capabilities

n The purpose of computers has been to enhance our mental capabilities

n Hence, a major use of IT is to relieve humans of

some decision making or help us make more

informed decisions

Technologies that Support Decision Making

Decision Support Systems

n Systems that support, not replace, managers in their decision-making activities

n Decision modeling, decision theory, and decision

analysis, attempt to make models from which the ‘best decision’ can be derived, by computation

n DSS are defined as: Computer-based systems

¨ That help decision makers

¨ Confront ill-structured problems

¨ Through direct interaction

¨ With data and analysis models

n Wide range of technologies can be used to assist

decision makers and problem solvers

Decision Support Systems The Architecture for DSSs

n Figure 11-1 shows the relationship between the three components of the DSS model

n Software system in the middle of the figure consists of:

¨ The database management system (DBMS)

¨ The model base management system (MBMS)

¨ The dialog generation and management system (DGMS)

Decision Support Systems The Architecture for DSSs cont.

The Dialog Component

n The DSS contains a dialog component to link the user

to the system

n Was ‘mouse’ (Mac) now = browser interface

The Data Component

n Data sources – as the importance of DSS has grown,

it has become increasingly critical for the DSS to use all the important data sources within and outside the organization

Decision Support Systems The Architecture for DSSs cont.

n Data warehousing

n Data mining

¨ Much of the work on the data component of DSS has taken the form of activities in this area

The Model Component

n Models provide the analysis capabilities for a DSS

¨ Using a mathematical representation of the problem, algorithmic processes are employed to generate

information to support decision making

Decision Support Systems

Types of DSS

n The size and complexity of DSS range from large

complex systems that have many of the attributes of major applications down to simple ad hoc analyses that might be called end user computing tasks

n Institutional DSSs tend to be fairly well defined

¨ They are based on pre=defined data sources

n Heavily internal with perhaps some external data

Decision Support Systems

Types of DSS

¨ Use well established models in a prescheduled way

n Quick-hit DSSs are developed quickly to help a manager make

either a one-time decision or a recurring one

¨ Can be every bit as useful for a small or large company

¨ Most today = Excel spreadsheets (and not ‘called’ DSS)

ORE-IDA FOODS Case Example – Institutional DSS

n Frozen food division of H.J Heinz

n Marketing DSS must support 3 main tasks in the

decision making process:

1. Data retrieval – helps managers find answers to

the question, “what has happened?”

2. Market analysis – addresses the question, “Why

did it happen?”

3. Modeling – helps managers get answers to, “What

will happen if…?”

n Modeling for projection purposes, offers the greatest

potential value of marketing management

n For successful use – line managers must take over

the ownership of the models and be responsible for keeping them up-to-date

A MAJOR SERVICES COMPANY Case Example – “Quick Hit” DSS – Short Analysis

Programs

n Considering – new employee benefit program: an

employee stock ownership plan (ESOP)

n Wanted a study made to determine the possible impact

of the ESOP on the company and to answer such

Technologies that Support Decision Making

Data Mining

n A promising use of data warehouses is to let the computer uncover unknown correlations by searching for interesting patterns, anomalies, or clusters of data that people are

unaware exist

n Called data mining, its purpose is to give people new

insights into data

n Also covered in Chapter 7

n Most frequent type of data mined = customer data

HARRAH’S ENTERTAINMENT Case Example – Data Mining (Customer)

n To better know its customers, Harrah’s encourages them to sign up for its frequent-gambler card, Total

Rewards

n Harrah’s mined its Total Rewards database to

uncover patterns and clusters of customers

n It has created 90 demographic clusters, each of

which is sent different direct mail offers –

encouraging them to visit other Harrah’s casinos

¨ Profit and loss for each customer calculating the likely ‘return’ for every ‘investment’ it makes in that

customer

HARRAH’S ENTERTAINMENT Case Example – Data Mining (Customer)

cont.

n Much of its $3.7B in revenues (and 80% of its profits) comes from its slot machines and electronic gaming-machine players

¨ Found = locals who played often

n It was not the ‘high rollers’ who were the most

profitable

n Within the first two years of operation of Total

Rewards, revenue from customers who visited more than one Harrah’s casino increased by $100 million

Technologies that Support Decision Making

Executive Information Systems (EIS)

n As the name implies EISs are for use by executives

n They have been used for the following purposes:

1. Gauge company performance: sales, production,

earnings, budgets, and forecasts

2. Scan the environmental: for news on government

regulations, competition, financial and economics

developments, and scientific subjects

Technologies that Support Decision Making Executive Information Systems (EIS) cont.

n EIS can be viewed as a DSS that:

1. Provides access to summary performance data

2. Uses graphics to display and visualize the data in an

easy-to-use fashion, and

3. Has a minimum of analysis for modeling beyond the

capability to “drill down” in summary data to examine components

n In many companies, the EIS is called a dashboard and

may look like a dashboard of a car

XEROX CORPORATION Case Example – Executive Information

System

n The EIS at Xerox began small and evolved to the point where even skeptical users became avid supporters

n Its objective was to improve communications and

planning, such as giving executives pre-meeting

documents

n It was also used in strategic planning and resulted in better plans, especially across divisions

Executive Information Systems (EIS)

Pitfalls in EIS Development

1. Lack of executive support: executives must provide

the funding, but are the principal users and supply the needed continuity

2. Undefined system objectives: the technology, the

convenience, and the power of EIS are impressive, but the underlying objectives and business values of

an EIS must be carefully thought through

3. Poorly defined information requirements: EIS typically

need non - traditional information sources -

judgments, opinion, external text-based documents -

in addition to traditional financial and operating data

4. Inadequate support staff: support staff must:

– Have technical competence

– Understand the business, and

– Have the ability to relate to the varied responsibilities

and work patterns of executives

6. Poorly planned evolution: highly competent system

professionals using the wrong development process will fail with EIS

n. EIS are not developed, delivered, and then maintained

¨ They should evolve over a period of time under the

leadership of a team that includes:

n The executive sponsor

n The operating sponsor

n Executive users

n The EIS support staff manager

Executive Information Systems (EIS) Pitfalls

in EIS Development cont.

Executive Information Systems (EIS)

Why Install an EIS?

n Attack a critical business need: EIS can be viewed as an aid to dealing with important needs that involve the future health of the organization

n A strong personal desire by the executive: The executive sponsoring the project may

¨ Want to get information faster than he/she is now

getting it, or

¨ Have a quicker access to a broader range of

information, or

¨ Have the ability to select and display only desired

information and to probe for supporting detail, or

¨ To see information in graphical form

Executive Information Systems (EIS)

A Weak Reason to Install an EIS

n “The thing to do”: An EIS is seen as something that

modern management must have, in order to be current

in management practices

n The rationale given is that the EIS will increase

executive performance and reduce time that is wasted looking for information and by such things as telephone tag

Executive Information Systems (EIS)

What Should the EIS Do?

n A Status Access System: Filter, extract, and compress

a broad range of up-to-date internal and external

information

¨ It should call attention to variances from plan

¨ It should also monitor and highlight the critical

success factors of the individual executive user

¨ EIS is a structured reporting system for executive

management, providing the executive with the data and information of choice and desired form

GENERAL ELECTRIC Case Example – Executive Information

System

n Most senior GE executives have a real-time view of

their portion of GE via an executive dashboard

¨ Each dashboard compares expected goals (sales, response times, etc) with actual, alerting the

executive when gaps of a certain magnitude appear

n GE’s goal is to gain better visibility into all its operations

in real time and give employees a way to monitor

corporate operations quickly and easily

n The system is based on complex enterprise software that interlinks existing systems

n GE’s actions are also moving its partners and business ecosystem closer to real-time operation

Technologies that Support Decision Making

Expert Systems

n A real-world use of artificial intelligence (AI)

¨ AI is a group of technologies that attempts to mimic

our senses and emulate certain aspects of human behavior such as reasoning and communication

¨ Promising for 40 years + Now = finally living up to

promise

n An expert system is an automated type of analysis or

problem-solving model that deals with a problem the way

Technologies that Support Decision Making

Expert Systems cont

n The process involves consulting a base of knowledge or

expertise to reason out an answer based on the

characteristics of the problem

n Like DSSs, they have:

¨ A user interface

¨ An inference engine, and

¨ Stored expertise (in the form of a knowledge base)

n The inference engine is that portion of the software that

contains the reasoning methods used to search the

knowledge base and solve the problem

Expert Systems Knowledge Representation

n Knowledge can be represented in a number of ways:

1. One is as cases; case-based reasoning expert

systems using this approach draw inferences by comparing a current problem (or case) to

hundreds or thousands of similar past cases

2. A second form is neural networks, which store

knowledge as nodes in a network and are more intelligent than the other forms of knowledge

representation because they can learn

3. Third, knowledge can be stored as rules (the

most common form of knowledge representation), which are obtained from experts drawing on their own expertise, experience, common sense, ways

of doing business, regulations, and laws

AMERICAN EXPRESSCase Example – Expert System

n One of the first commercially successful ESs and a

fundamental part of the company’s everyday credit card operation

n Authorizer’s Assistant is an expert system that

approves credit at the point of sale

n It has over 2,600 rules and supports all AmEx card

products around the world

n Authorizes credit by looking at:

¨ Whether cardholders are creditworthy

¨ Whether they have been paying their bills

¨ Whether a purchase is within their normal spending patterns

n It also assesses whether the request for credit could be

a potential fraud

AMERICAN EXPRESS Case Example – Expert System cont.

n The most difficult credit-authorization decisions are still referred to people

n Avoids ‘sensitive’ transactions

¨ Restaurants

¨ Airline queues

n The rules were generated by interviewing authorizers with various levels of expertise – comparing good

decisions to poor decisions

n The system can be adapted quickly to meet changing business requirements

Expert Systems Degree of Expertise

1. As an assistant, the lowest level of expertise, the

expert system can help a person perform routine analysis and point out those portions of the work where the expertise of the human is required

2. As a colleague, the second level of expertise, the

system and the human can “talk over” the problem until a “joint decision” has been reached

3. As an expert, the highest level of expertise, the

system gives answers that the user accepts,

perhaps without question