SUPPORTING DECISION MAKING

Chapter (12 8E, International)

Information Systems Management In Practice 8EMcNurlin & Sprague

PowerPoints prepared by Michael MatthewVisiting Lecturer, GACC, Macquarie University – Sydney Australia

PART IV: SYSTEMS FOR SUPPORTING KNOWLEDGE-BASED WORK This part consists of three chapters that discuss

supporting three kinds of work – decision making, collaboration, and knowledge work

As shown in the book’s framework figure, we distinguish between procedure-based and knowledge-based information-handling activities

The two previous chapters, in Part III, dealt mainly with building systems for procedure-based work

This part focuses on supporting knowledge-based activities: the systems that support people in performing information-handling activities to solve problems, work together, and share expertise

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PART IV: SYSTEMS FOR SUPPORTING KNOWLEDGE-BASED WORK CONT.

Chapter 12 discusses supporting decision making by first presenting five underlying technologies and some examples of their use: Decision Support Systems (DSS) Data Mining Executive Information Systems (EIS), and Expert Systems (ES) Agent-based Modelling

The chapter then discusses the fascinating subject of the real-time enterprise, which has a goal of gaining competitive edge by learning of an event as soon as possible and then responding to that event quickly, if necessary

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CHAPTER 12 This lecture / chapter discusses technologies for

supporting decision making: Decision Support Systems (DSS) Data Mining Executive Information Systems (EIS), and Expert Systems Agent-based Modelling

It then discusses IT issues related to creating the real-time enterprise

Case examples include: a problem-solving scenario, Ore-Ida Foods, a major services company, Harrah’s Entertainment, Xerox Corporation, General Electric, American Express, Delta Air Lines, a real-time interaction on a website, and Western Digital

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INTRODUCTION

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

Decision making is a process that involves a variety of activities, most of which handle information

A wide variety of computer-based tools and approaches can be used to confront the problem at hand and work through its solution

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A PROBLEM-SOLVING SCENARIOCASE EXAMPLE – SUPPORTING DECISION MAKING

Using an executive information system, (EIS) to compare budget to actual sales

Discover a sale shortfall in one region

Searches for the cause of the shortfall

But couldn’t find an answer

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A PROBLEM-SOLVING SCENARIOCASE EXAMPLE – SUPPORTING DECISION MAKING CONT.

Investigate – several possible causes Economic Conditions – through the EIS & the Web

accesses: Wire services Bank economic newsletters Current business and economic publications

Competitive Analysis – through the same sources investigates whether competitors: Have introduced a new product Have launched an effective ad campaign

Written Sales Report – browses the reports “Concept based” text retrieval system makes this easier

A Data Mining Analysis Looking for any previously unknown relationships

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A PROBLEM-SOLVING SCENARIOCASE EXAMPLE – SUPPORTING DECISION MAKING CONT.

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

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

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TECHNOLOGIES THAT SUPPORT DECISION MAKING

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

The purpose of computers has been to enhance our mental capabilities

Hence, a major use of IT is to relieve humans of some decision making or help us make more informed decisions

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TECHNOLOGIES THAT SUPPORT DECISION MAKING DECISION SUPPORT SYSTEMS

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

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

DSS are defined as: Computer-based systemsThat help decision makersConfront ill-structured problemsThrough direct interactionWith data and analysis models

Wide range of technologies can be used to assist decision makers and problem solvers

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DECISION SUPPORT SYSTEMS THE ARCHITECTURE FOR DSSS

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

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)

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DECISION SUPPORT SYSTEMS THE ARCHITECTURE FOR DSSS CONT.

The Dialog Component The DSS contains a dialog component to link the user to the

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

The Data Component 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

Data warehousing Data mining

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

The Model Component 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

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DECISION SUPPORT SYSTEMS TYPES OF DSS 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

Institutional DSSs tend to be fairly well defined They are based on pre=defined data sources

Heavily internal with perhaps some external data Use well established models in a prescheduled way

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)

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ORE-IDA FOODSCASE EXAMPLE – INSTITUTIONAL DSS

Frozen food division of H.J. Heinz 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…?” Modeling for projection purposes, offers the

greatest potential value of marketing management For successful use – line managers must take over

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

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A MAJOR SERVICES COMPANYCASE EXAMPLE – “QUICK HIT” DSS – SHORT ANALYSIS PROGRAMS

Considering – new employee benefit program: an employee stock ownership plan (ESOP).

Wanted a study made to determine the possible impact of the ESOP on the company and to answer such questions as: How many shares of company stock will be needed in

10,20 and 30yrs to support the ESOP? What level of growth will be needed to meet these stock

requirements? The information systems manager wrote a

program to perform the calculations & printed the results

Results = showed the impact of the ESOP over a 30yr period Surprising results

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TECHNOLOGIES THAT SUPPORT DECISION MAKING DATA MINING

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

Called data mining, its purpose is to give people new insights into data

Also covered in Chapter 7

Most frequent type of data mined = customer data

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HARRAH’S ENTERTAINMENTCASE EXAMPLE – DATA MINING (CUSTOMER)

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

Harrah’s mined its Total Rewards database to uncover patterns and clusters of customers

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

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HARRAH’S ENTERTAINMENTCASE EXAMPLE – DATA MINING (CUSTOMER) CONT.

Much of its $3.7B in revenues (and 80% of its profits) comes from its slot machines and electronic gaming-machine playersFound = locals who played often

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

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

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TECHNOLOGIES THAT SUPPORT DECISION MAKING EXECUTIVE INFORMATION SYSTEMS (EIS)

As the name implies EISs are for use by executives

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

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TECHNOLOGIES THAT SUPPORT DECISION MAKING EXECUTIVE INFORMATION SYSTEMS (EIS) CONT.

EIS can be viewed as a DSS that:1. Provides access to summary performance

data2. 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

In many companies, the EIS is called a dashboard and may look like a dashboard of a car

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XEROX CORPORATIONCASE EXAMPLE – EXECUTIVE INFORMATION SYSTEM

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

Its objective was to improve communications and planning, such as giving executives pre-meeting documents

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

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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

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EXECUTIVE INFORMATION SYSTEMS (EIS) PITFALLS IN EIS DEVELOPMENT CONT.

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

5. Poorly planned evolution: highly competent system professionals using the wrong development process will fail with EIS

EIS are not developed, delivered, and then maintained They should evolve over a period of time under the leadership

of a team that includes: The executive sponsor The operating sponsor Executive users The EIS support staff manager, and The IS technical staff

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EXECUTIVE INFORMATION SYSTEMS (EIS)WHY INSTALL AN EIS?

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

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

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EXECUTIVE INFORMATION SYSTEMS (EIS) A WEAK REASON TO INSTALL AN EIS

“The thing to do”: An EIS is seen as something that modern management must have, in order to be current in management practices

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

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EXECUTIVE INFORMATION SYSTEMS (EIS) WHAT SHOULD THE EIS DO?

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

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GENERAL ELECTRICCASE EXAMPLE – EXECUTIVE INFORMATION SYSTEM

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

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

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

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

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TECHNOLOGIES THAT SUPPORT DECISION MAKING EXPERT SYSTEMS

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

An expert system is an automated type of analysis or problem-solving model that deals with a problem the way an “expert” does

Note: Expert Systems are not new LISP Prolog

Languages in the ’70s

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TECHNOLOGIES THAT SUPPORT DECISION MAKING EXPERT SYSTEMS CONT.

The process involves consulting a base of knowledge or expertise to reason out an answer based on the characteristics of the problem

Like DSSs, they have: A user interface An inference engine, and Stored expertise (in the form of a knowledge

base) The inference engine is that portion of the

software that contains the reasoning methods used to search the knowledge base and solve the problem

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EXPERT SYSTEMSKNOWLEDGE REPRESENTATION

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

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AMERICAN EXPRESSCASE EXAMPLE – EXPERT SYSTEM One of the first commercially successful ESs and

a fundamental part of the company’s everyday credit card operation

Authorizer’s Assistant is an expert system that approves credit at the point of sale

It has over 2,600 rules and supports all AmEx card products around the world

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 It also assesses whether the request for credit

could be a potential fraud

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AMERICAN EXPRESSCASE EXAMPLE – EXPERT SYSTEM CONT.

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

Avoids ‘sensitive’ transactionsRestaurantsAirline queues

The rules were generated by interviewing authorizers with various levels of expertise – comparing good decisions to poor decisions

The system can be adapted quickly to meet changing business requirements

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EXPERT SYSTEMSDEGREE 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

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AGENT –BASED MODELLING

A simulation technology for studying emergent behaviour (e.g. traffic jam) that emerges from the decisions of a large number of distinct individuals (drivers) Simulation contains computer generated agents, each

making decisions typical of the decisions an individual would make in the real world Trying to understand the mysteries of why businesses,

markets, consumers, and other complex systems behave as they do

Some examples: Nasdaq; Change its tick size Retailer = redesign its incentive program Southwest Airlines = revamp its cargo operations Company changing its recruiting practices

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TECHNOLOGIES THAT SUPPORT DECISION MAKING CONCLUSION

This section has discussed five seemingly competing technologies that support decision making

In reality they often overlap and combine

The next section demonstrates how these decision support technologies and other technologies are being mixed and matched to form the foundation for the real-time enterprise

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TOWARD THE REAL-TIME ENTERPRISE

Through IT, organizations have been able to see the status of operations more and more toward real time

The Internet is giving companies a way to disseminate closer-to-real-time information about events

The essence of the phrase real-time enterprise is that organizations can know how they are doing at the moment, rather than have to wait days, weeks, or months for analysis results

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TOWARD THE REAL-TIME ENTERPRISE CONT.

It is occurring on a whole host of fronts, including: Enterprise nervous systems

To coordinate company operations Straight-through processing

To reduce distortion in supply chains Real-time CRM

To automate decision making relating to customers, and Communicating objects

To gain real-time data about the physical world

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TOWARD THE REAL-TIME ENTERPRISE

ENTERPRISE NERVOUS SYSTEMS These are the technical means to a real-time

enterprise They are:

Message based - because sending messages is efficient and effective in dispersing information among parties simultaneously

Event driven - when an event occurs, it is recorded and made available

Use a publish and subscribe approach - the event is “published” to an electronic address and any system, person, or device authorized to see that information can “subscribe” to that address’s information feed, and

Use common data formats - data formats from disparate systems are reduced to common denominators that can be understood by other systems and hence shared

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DELTA AIRLINESCASE EXAMPLE – ENTERPRISE NERVOUS SYSTEMS

Delta has built an enterprise nervous system to manage its gate operations by incorporating the disparate systems the airline had in the late 1990s

Information about each flight is managed by the system, in real time, and everyone who needs to know about a change can get the data

The system uses a publish-and-subscribe approach using enterprise application integration (EAI) products, whereby the messaging middleware allows disparate applications to share data

When an event occurs, it ripples to everyone

Delta is now expanding those ripples out to their partners who serve their passengers, such as caterers and security companies

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TOWARD THE REAL-TIME ENTERPRISESTRAIGHT-THROUGH PROCESSING

The notion of a real-time enterprise has generated two “buzzwords”

One is zero latency, which means reacting quickly to new information (with no wait time)

The second is straight-through processing, which means that transaction data are entered just once in a process or a supply chain (like at Delta)

The goal is to reduce lags and latency in supply chains

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TOWARD THE REAL-TIME ENTERPRISEREAL-TIME CRM

Another view of a real-time response might occur between a company and a potential customer- Perhaps via a customer call center or a Website

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A REAL-TIME INTERACTION ON A WEB SITECASE EXAMPLE – REAL-TIME CRM

E.piphany CRM software example A potential guest visits the Website of a

hotel chain, checking for a hotel in OrlandoThe real-time CRM system initiates requests to

create a profile of the customer All past interactions with that customer Past billing information Past purchasing history

Using this information, it makes real-time offers to the Website visitor, and the visitor’s responses are recorded and taken into account for future Website visitors

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TOWARD THE REAL-TIME ENTERPRISECOMMUNICATING OBJECTS These are sensors and tags that provide

information about the physical world via real-time data

A communicating object can tell you:What it is attached toWhere it is locatedWhere it belongs, and A lot more information about itself

It is a radio frequency identification device (RFID), also called “smart tags”Based on WW2 technology

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TOWARD THE REAL-TIME ENTERPRISECOMMUNICATING OBJECTS CONT.

In Singapore, cars carry smart tags, and drivers are charged variable prices for where they drive in the city and whenThe prices are set to encourage or discourage

driving at different places at different timesAlso proposed for Sydney’s new toll ways

It’s an example of real-time traffic control

Smart tags will transform industries because they will talk to one another (object-to-object communication), changing how work is handled

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TOWARD THE REAL-TIME ENTERPRISEVIGILANT INFORMATION SYSTEMS

The premise of the real-time enterprise is not only that it can capture data in real time, but that it has the means to act on that data quickly

US Air Force pilot = bet he could win any dogfightNever lost a bet, even to superior aircraftCalled his theory OODA

Observe where his challenger’s plane is Orient himself and size up his own vulnerabilities

and opportunities Decide which manoeuvre to take Act to perform it before the challenger could go

through the same four steps

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WESTERN DIGITALCASE EXAMPLE: VIGILANT INFORMATION SYSTEMS (OODA)

PC disk manufacturer used OODA type of thinking to move itself closer to operating in real time with a sense-and-respond culture that aims to operate faster than its competitors

Built what they call a Vigilant Information System (VIS) which they define as a system that is “alertly watchful”Complex and builds on the firm’s legacy

systemsEssentially has four layers – Figure 11-5

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WESTERN DIGITALCASE EXAMPLE: VIGILANT INFORMATION SYSTEMS (OODA) CONT.

VIS had to be complemented by appropriate business processes

To operate inside it competitors OODA loops Three new company policies were drafted

1. Company’s strategic goals must be translated into time based objectives and aligned across the company

2. KPIs must be captured in real time and be comparable3. Collaborative decision making to co-ordinate actions

company-wide Shop-Floor OODA loop Factory OODA loop Corporate OODA loop

Benefits of the VIS Quickened all 3 OODA loops and helped to link decisions

across them Corporate performance improved measurably

Margins doubled since introduction 3 years ago Sense and response culture where Western digital learns

and adapts quickly in a coordinated fashion

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TOWARD THE REAL-TIME ENTERPRISETHE DARK SIDE OF REAL TIME What are the drawbacks of real-time

activities?Object-to-object communication could compromise

privacy, since knowing the exact location of a company truck every minute of the day and night can be construed as invading the driver’s privacy That’s a political issue, not a technical issue, and many

CEOs are going to face this question in the futureAlso, in the era of speed, a situation can become

very bad very fast, so people must be constantly watching for signals that something negative is likely to happen

Need for circuit breakers? e.g. NYSE

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CONCLUSION 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

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CONCLUSION CONT.

CIOs need to alert their management team of potential social and economic effects of computer-based decision making because errant computer-based decisions have devastated corporate reputations and cost a lot of money

With vendors pushing toward the real-time enterprise, this is a use of computers that should give pause to explore the ramifications

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