Chapter 11

Information Systems for Managerial Decision Support

LECTURE NOTES

SECTION I: Management Information and Decision Support Systems

11-1Introduction:

This chapter focuses on the major types of information systems and how they support the diverse information and decision-making needs of managers.

Analysing Parsons Brinckerhoff

We can learn a lot from this case about how intranet technologies are changing the face of traditional information systems for managerial information and decision support from the Real World Case of Parsons Brinckerhoff.

Take a few minutes to read it, and we will discuss it (See Parsons Brinckerhoff in section XI)

Information, Decisions, and Management: [Figure 11.2]

The type of information required by managers is directly related to the level of management and the amount of structure in the decision situation they face. You should realize that the framework of the classic managerial pyramid applies even in today’s downsized organizations and flattened or non-hierarchical organizational structures. Levels of management decision making still exist, but their size, shape, and participants continue to change as today’s fluid organizational structures evolve. Thus, the levels of managerial decision making that must be supported by information technology in a successful organization are:

  • Strategic Management: - Typically, a board of directors and an executive committee of the CEO and top executives develop overall organizational goals, strategies, policies, and objectives as part of a strategic planning process.

They monitor the strategic performance of the organization and its overall direction in the political, economic, and competitive business environment.

Unstructured Decisions - Involve decision situations where it is not possible to specify in advance most of the decision procedures to follow.

Strategic Decision Makers - Require more summarized, ad hoc, unscheduled reports, forecasts, and external intelligence to support their more unstructured planning and policy-making responsibilities.

  • Tactical Management - Increasingly self-directed teams as well as middle managers develop short- and medium-range plans, schedules, and budgets and specify the policies, procedures, and business objectives for their subunits of the organization.

They also allocate resources and monitor the performance of their organizational subunits, including departments, divisions, process teams, and other workgroups.

Semistructured Decisions - Some decision procedures can be prespecified, but not enough to lead to a definite recommended decision.

Tactical Decision Makers - Require information from both the operational level and the strategic level to support their semistructured decision making responsibilities.

  • Operational Management - The members of self-directed teams or supervisory managers develop short-range plans such as weekly production schedules.

They direct the use of resources and the performance of tasks according to procedures and within budgets and schedules they establish for the teams and other workgroups of the organization.

Structured Decisions - Involve situations where the procedures to follow when a decision is needed can be specified in advance.

Operational Decision Makers - Require more prespecified internal reports emphasizing detailed current and historical data comparisons that support their more structured responsibilities in day-to-day operations.

Providing information and support for all levels of management decision making is no easy task. Conceptually, several major types of information systems are needed:

  • Management information systems
  • Decision support systems
  • Executive information systems

Management Reporting Versus Decision-Making Support:

Management information systems- Focus on providing managers with prespecified information products that report on the performance of the organization.

- MIS are designed to indirectly support the more structured types of decisions involved in operational and tactical planning and control.

Objective of MIS- Provide information about the performance of basic organizational functions and processes, such as marketing, manufacturing, and finance.

Decision Support Systems- Focus on providing information interactively to support specific types of decisions by individual managers.

- DSS help managers solve typical semistructured and unstructured problems.

Objective of DSS- Provide information and decision support techniques needed to solve specific problems or pursue specific opportunities.

11-2Management Information Systems:

Management information systems were the original type of management support systems, and are still a major category of information systems. MIS produce information products that support many of the day-to-day decision-making needs of management. Reports, displays, and responses produced by information systems provide information that managers have specified in advance as adequately meeting their information needs. Such predefined information products satisfy the information needs of managers at the operational and tactical levels of the organization who are faced with more structured types of decision situations.

Management Reporting Alternatives:

MIS provide a variety of information products to managers. Three major reporting alternatives are provided by such systems:

  • Periodic scheduled reports

- this traditional form of providing information to managers uses a prespecified format designed to provide managers with information on a regular basis.

  • Exception Reports

- reports are produced only when exceptional conditions occur.

  • Demand Reports & Responses

- information is provided whenever a manager demands it.

  • Push Reporting

- information is pushed to a manager’s networked workstation.

Intranet Reporting at CBS

CBS uses enterprise reporting software to create reports that can be stored and updated on an Internet server. The server is accessible over their nationwide corporate intranet, so that any report could be downloaded as needed, allowing users to get only the information that they want (and have the clearance to obtain). CBS end users can use browsers on their desktop PCs to perform virtually any type of ad hoc query on the data in the reports.

Online Analytical Processing: [Figure 11.6]

Online analytical processing is a capability of management, decision support, and executive information systems that enables managers and analysts to interactively examine and manipulate large amounts of detailed and consolidated data from many perspectives.

Online analytical processing involves several basic analytical operations including:

  • Consolidation - Involves the aggregation of data. This can involve simple roll-ups or complex groupings involving interrelated data.
  • Drill-Down - OLAP can go in the reverse direction and automatically display detail data that comprises consolidated data.
  • Slicing & Dicing - Refers to the ability to look at the database from different viewpoints. Slicing and dicing is often performed along a time axis in order to analyse trends and find patterns.

OLAP applications:

1.Access very large amounts of data.

2.Analyse the techniques between many types of business elements.

3.Involves aggregated data.

4.Compare aggregated data over hierarchical time periods.

5.Present data in different perspectives.

6.Involve complex calculations between data elements.

7.Are able to respond quickly to user requests so that managers or analysts can pursue an analytical or decision thought process without being hindered by the system.

OLAP at MasterCard International

MasterCard International developed OLAP software called Market Advisor, which enables members to query a data warehouse and drill down into information to analyse transactions and trends online. Market Advisor also provides a 13-month historical database, extended report graphing, and triggered marketing alerts based on above - or below-average merchant or cardholder activity.

11-3Decision Support Systems:

Decision support systems are a major category of management information systems. They are computer-based information systems that provide interactive information support to managers during the decision-making process. Decision support systems use:

1.Analytical models

2.Specialized databases

3.Decision makers’ own insights and judgements

4.Interactive, computer-based modelling processes to support the making of semistructured and unstructured decisions by individual managers.

DSS are designed to be ad-hoc, quick-response systems that are initiated and controlled by managerial end users. Decision support systems are thus able to directly support the specific types of decisions and the personal decision-making styles and needs of individual managers.

DSS Models and Software:

Unlike management information systems, decision support systems rely on model bases as well as databases as vital system resources. A DSS model base is a software component that consists of models used in computational and analytical routines that mathematically express relationships among variables.

11-4Examples of DSS Applications:

Decisions support systems are used for a variety of applications in both business and government.

  • Institutional DSS - DSS which are developed to solve large or complex problems that continually face an organization.
  • Ad-hoc DSS - DSS which are quickly developed to solve smaller or less complex problems. They are also used to solve one-time situations.
  • Industry DSS - DSS which are developed to solve problems faced by a specific industry.
  • Functional DSS - DSS which are developed to solve problems in a specific functional area.

Examples of DSS applications:

1.DSS at American Airlines

2.DSS at PepsiCo

3.GIS in Business (Geographic information systems)

11-5Using Decision Support Systems:

Using a decision support system involves an interactive analytical modelling process. Typically, a manager uses a DSS software package at his workstation to make inquires, responses and to issue commands. This differs from the demand responses of information reporting systems, since managers are not demanding prespecified information. Rather, they are exploring possible alternatives. They do not have to specify their information needs in advance. Instead they use the DSS to find the information they need to help them make a decision.

Using a DSS involves four basic types of analytical modelling activities:

  • What-If Analysis: -In what-if-analysis, an end user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables.
  • Sensitivity Analysis: -Is a special case of what-if analysis. Typically, the value of only one variable is changed repeatedly, and the resulting changes on other variables are observed. So sensitivity analysis is really a case of what-if analysis involving repeated changes to only one variable at a time. Typically, sensitivity analysis is used when decision makers are uncertain about the assumptions made in estimating the value of certain key variables.
  • Goal Seeking Analysis: - Reverses the direction of the analysis done in what-if and sensitivity analysis. Instead of observing how changes in a variable affect other variables, goal seeking analysis sets a target value for a variable and then repeatedly changes other variables until the target value is achieved.
  • Optimization Analysis: - Is a more complex extension of goal seeking analysis. Instead of setting a specific target value for a variable, the goal is to find the optimum value for one or more target variables, given certain constraints. Then one or more other variables are changed repeatedly, subject to the specified constraints, until the best values for the target variables are discovered.

11-6Executive Information Systems:

Executive information systems (EIS) are information systems that combine many of the features of information reporting systems and decision support systems. EIS focus on meeting the strategic information needs of top management. The goal of EIS is to provide top management with immediate and easy access to information about a firm's critical success factors (CSFs), that is, key factors that are critical to accomplishing the organizations strategic objectives.

Rational for EIS:

Top executives get the information they need from many resources. These include, letters, memos, periodicals, and reports produced manually or by computer systems. Other major sources of executive information are meetings, telephone calls, and social activities. Thus, much of a top executive's information comes from noncomputer sources. Computer-generated information has not played a major role in meeting many top executives' information needs. EIS were developed to meet the need that MIS was not meeting.

SECTION II: Artificial Intelligence Technologies in Business

11-7An Overview of Artificial Intelligence:

Business and other organizations are significantly increasing their attempts to assist the human intelligence and productivity of their knowledge workers with artificial intelligence tools and techniques. AI includes natural languages, industrial robots, expert systems, and intelligent agents.

Question: Is AI possible? Answer: Only time will tell

Artificial intelligence (AI) is a science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, and engineering. The goal of AI is to develop computers that can think, as well as see, hear, walk, talk, and feel. A major thrust of AI is the development of computer functions normally associated with human intelligence, such as reasoning, learning, and problem solving.

The Domains of Artificial Intelligence:[Figure 11-17]

AI application can be grouped into three major areas:

  • Cognitive Science - This area of artificial intelligence is based on research in biology,

neurology, psychology, mathematics, and many allied disciplines. It focuses on researching how the human brain works and how humans think and learn. The results of such research

in human information processing are the basis for the development of a variety of computer-based applications in artificial intelligence.

Applications in the cognitive science area of AI include:

Expert Systems - A computer-based information system that uses its knowledge about a specific complex application area to act as an expert consultant to users. The system consists of a knowledge base and software modules that perform inferences on the knowledge, and communicates answers to a user’s questions.

Knowledge-Based Systems - An information system which adds a knowledge-base and some reasoning capability to the database and other components found in other types of computer-based information systems.

Adaptive Learning Systems - An information system that can modify its behaviour based on information acquired as it operates.

Fuzzy Logic Systems - Computer-based systems that can process data that are incomplete or only partially correct. Such systems can solve unstructured problems with incomplete knowledge by developing approximate inferences and answers.

Neural Network - software can learn by processing sample problems and their solutions. As neural nets start to recognize patterns, they can begin to program themselves to solve such problems on their own.

Genetic Algorithm - software uses Darwinian (survival of the fittest), randomizing, and other mathematical functions to simulate evolutionary processes that can generate increasingly better solutions to problems.

Intelligent Agents - Use expert system and other AI technologies to serve as software surrogates for a variety of end user applications.

  • Robotics: - AI, engineering, and physiology are the basic disciplines of robotics. This technology produces robot machines with computer intelligence and computer-controlled, humanlike physical capabilities.

Robotics applications include:

1. Visual perception (sight)

2. Tactility (touch)

3. Dexterity (skill in handling and manipulation)

4. Locomotion (ability to move over any terrain)

5. Navigation (properly find ones way to a destination)

  • Natural Interface: -The development of natural interfaces is considered a major area of AI applications and is essential to the natural use of computers by humans. For example, the development of natural languages and speech recognition are major thrusts of this area. Being able to talk to computers and robots in conversational human languages and have then “understand” us is the goal of AI researchers. This application area involves research and development in linguistics, psychology, computer science, and other disciplines. Efforts in this area include:

Natural Languages - A programming language that is very close to human language. Also, called very high-level language.

Multisensory Interfaces - The ability of computer systems to recognize a variety of human body movement which allows them to operate.

Speech Recognition - The ability of a computer system to recognizes speech patterns, and to operate using these patterns.

Virtual Reality - The use of multisensory human/computer interfaces that enables human users to experience computer-simulated objects, entities, spaces, and Aworlds@ as if they actually existed.

11-8Neural networks:

Neural networks are computing systems modelled on the human brain's mesh-like network of interconnected processing elements, called neurons. Of course, neural networks are much simpler than the human brain (estimated to have more than 100 billion neuron brain cells). Like the brain, however, such networks can process many pieces of information simultaneously and can learn to recognize patterns and programs themselves to solve related problems on their own.

Neural networks can be implemented on microcomputers and other computer systems via software packages which simulate the activities of a neural network of many processing elements. Specialized neural network coprocessor circuit boards are also available. Special-purpose neural net microprocessor chips are used in some application areas.

Uses include:

1. Military weapons systems

2. Voice recognition

3. Check signature verification

4. Manufacturing quality control

5. Image processing

6. Credit risk assessment

7. Investment forecasting

Neural Nets at Infoseek:

Infoseek has developed a targeted marketing service that more closely targets advertising on its Internet search engine to users’ interests by keeping track of every search that a user makes. The service uses neural network technology to observe all the searches users run every time they visit the InfoSeek search engine. The neural net software then calculates a single numeric value, or “vector”, that describes users’ interests. InfoSeek uses that information to match users to the online ads it sells to advertisers on its Web search pages.

Data Mining a Bank of America:

The Bank of America is using neural net technology in data mining software to develop more accuracy in marketing and pricing financial products, such as home equity loans.

11-9Fuzzy Logic Systems

Fuzzy Logic is a method of reasoning that resembles human reasoning since it allows for approximate values and inferences (fuzzy logic) and incomplete or ambiguous data (fuzzy data) instead of relying only on crisp data, such as binary (yes/no) choices.