Management Support Systems and Decision-Making

1. Management Support Systems and Decision-Making

2. Supporting Managers with Information Systems

3. Models and Methods for Management Support • To understand how computers support managers, it is necessary to understand what managers do. • It is difficult to produce a standard job description for all managers.

4. Fundamental Functions of Management • The traditional description of what managers do was first characterized by French industrialist Henri Fayol in his 1916 classic, Administration Industrielle et Generale. Fayol considered the manager's job as a composite of four separate functions: • Planning • Controlling • Leading • Organizing

5. Fundamental Functions of Management - defined • Planning - establishing goals and selecting the actions needed to achieve them over a specific period of time. • Controlling - measuring performance against the planned objectives and initiating corrective action. • Leading - inducing the people in the organization to contribute to its goals • Organizing - establishing and staffing an organizational structure for performing business activities

6. Mintzberg’s Studies of Managers Myth #1: The manager is a reflective systematic planner. Fact: Study after study shows managers work at an unrelenting pace, that their activities are characterized by brevity, variety, and discontinuity, they are strongly oriented toward action, and dislike reflective activities. Myth #2: The effective manager has no regular duties to perform. Fact: Managerial work involves performing a number of regular duties, including ritual and ceremony, negotiations, and processing of soft information that links the organization with its environment

7. Mintzberg’s Studies of Managers Myth #3: The senior manager needs aggregated information, which a formal management information system best provides. Fact: Managers strongly favor verbal media, telephone calls, and meetings over documents. Myth #4: Management is, or at least is quickly becoming, a science and a profession. Fact: The managers' programs - to schedule time, process information, make decisions, and so on-remain locked deep inside their brains.

8. Classic Study of Managerial Work • The classic study of managerial work was done by Mintzberg, who divided the manager’s roles into three categories: • 1. Interpersonal roles • 2. Informational roles • 3. Decisional roles

9. Management Roles • Interpersonal Roles: • Figurehead, Leader, Liaison • Informational Roles: • Monitor, Disseminator, Spokesman • Decisional Roles: • Entrepreneur, Disturbance Handler, Resource Allocator, Negotiator

10. Mintzberg: The Nature of Managerial Work Formal Authority and Status Interpersonal Roles Informational Roles Decisional Roles

11. Mintzberg’s Management Roles Interpersonal Roles • Figurehead - Carries out a symbolic role as head of the organization, performing duties of a legal or social nature. • Leader - In the most widely recognized managerial duty, the executive is responsible for motivating and "activation" of subordinates, as well as staffing, training, promoting. • Liaison - Develops and maintains a personal network of external contacts who provide information and favors.

12. Mintzberg’s Management Roles Informational Roles: • Monitor - Seeks and receives a wide variety of special information (much of it current) to develop a thorough understanding of the organization and the environment. In this role, the executive serves as the nerve center of internal and external information about the organization. • Disseminator - Transmits information received from outsiders or subordinates to other members of the organization. Some information is factual, some involves interpretation and integration of diverse value positions of organizational influencers. All information is to guide subordinates in decision making. • Spokesman - Communicates information to outsiders on the organization's plans, policies, actions, results, etc. serves as the expert on the organization's industry.

13. Mintzberg’s Management Roles • Entrepreneur - Searches the organization and environment for opportunities and initiates "improvement projects" to bring about change; supervises design of certain projects as well. • Disturbance Handler - Responsible for corrective action when the organization faces important, unexpected disturbances. • Resource Allocator - Allocates organizational resources of all kinds-in effect the making or approval of all significant organizational decisions. • Negotiator - Represents the organization in major negotiations.

14. IS and Mintzberg’s Roles

15. Information Support for Management • Early information systems mainly supported the informational roles. • The purpose of recent information systems is to support all three roles. • We will explore the information support required for all roles, beginning with the decisional roles. • The success of management depends on the execution of managerial functions such as planning, organizing, leading, and controlling. To carry out these functions, managers engage in the continuous process of making decisions.

16. Executive Activities and Information Support • Handling Disturbances (42%) - A disturbance is something that happens unexpectedly and demands immediate attention, but it might take weeks or months to resolve. • Entrepreneurial Activity (32%) - activities intended to make improvements that will increase performance levels. Improvements are strategic and long term in nature. • Resource Allocation (17%) - Allocating resources within the framework of the annual and monthly planning tasks and budgets • Negotiations (3%) resolve conflicts and disputes, either internal or external. • Other Activities (6%)

17. Introduction to Decision-Making • A basic understanding of decision making is essential because most information systems are designed to support decision making in one way or another. • We will survey some models and concepts of decision making and methods for deciding among alternatives. • We will look at their relevance to information systems design.

18. Decision Making:Phases • Herbert A. Simon (1960) proposed the most famous model of the Decision-Making process. • 1. Intelligence • 2. Design • 3. Choice • Some models of decision making include a 4th step: Implementation. • There is a flow activities from one phase, to the next. At any time there may be a return to a previous phase.

19. Simon’s ModelFlowchart of Decision Process Intelligence Design Choice

20. Intelligence Phase • Searching the environment for conditions calling for decisions • Data inputs obtained, processed, examined for clues to identify problems or opportunities • Identify problems for opportunity situations requiring design and choice. • Scanningthe environment, intermittently or continuously, is important. • Organizational objectives • search and scanning procedures • data collection • problem identification • problem classification • problem statement

21. Examples of the Intelligence Phase • Air traffic controller continuously scanning to detect problems in air space. • Each time you start your car, there is a conscious or unconscious scanning (listening, checking gauges, etc.). • Marketing executive makes periodic visits to key customers to review possible problems and identify new customer needs. • A plant manager reviews daily scrap report to check for quality control problems. • An executive reads the industry trade paper to be aware of events and changes in the environment.

22. Summary: Intelligence Phase • Intelligence activities result in dissatisfaction with the current state or identification of potential rewards from a new state.

23. Design Phase • Inventing, developing, and analyzing possible courses of action • This involves processes to understand the problem, to generate solutions and test solutions for feasibility: • Formulate a model. • Set criteria for choice. • Search for alternatives • Predict and measure outcomes

24. Choice Phase • Select an alternative from those available • Select and implement a choice: • Solution to the model • sensitivity analysis • selection of best (good) alternatives(s) • plan for implementation (action)

25. Comment on Simon’s Model • Simon’s Model does not go beyond the choice phase. • There are no steps for implementation, or feedback from the results of the decision. • Although Simon’s model is the most famous, others have adapted it. • Our textbook provides a similar model:

27. Alter Textbook Model • Decision-making is represented as a problem-solving process preceded by a separate problem-finding process. • Problem-solving is the use of information, knowledge, and intuition to solve a problem that ha previously been defined.

28. An Alternative Model: Rubenstein and Haberstroh’s • 1. Recognition of problem or need for decision • 2. Analysis and statement of alternatives • 3. Choice among the alternatives • 4. Communication and implementation • 5. Follow-up and feedback of results

29. Slade’s Model of Decision Making Identify Problem Identify Alternatives Choose Usual Action Evaluate Alternatives Choose Among Alternatives Generate New Alternatives Effect Choice Abandon Problem

30. Summary - I All models indicate the same basic ideas: 1. Problem finding - Identify situations where problems need to be solved. 2 Problem formulation - clearly state the problem. 3. Alternative Generation 4. Evaluate Outcomes. 5. Choice 6. Implement 7. Evaluate..

31. Summary -II • In the models of decision-making, the most important aspects of the intelligence and design phases are: • I - Problem Finding • II - Problem Formulation • III - Alternative Generation

32. I. - Problem Finding • It is the difference between existing state and the desired state • The problem finder usually has an idea of the desired state ( a model) • Compared with the reality and differences noted • A Problem exists when there is a major difference

33. The role of models in decision-making • A major characteristic of decision-making is the use of models. • A model is a simplified representation or abstraction of reality. • It is usually simplified because reality is too complex to copy. • Basis idea is that analysis is performed on a model rather than on reality itself.

34. Pounds’ Categories of Models - Expectations against which reality is measured • Historical- expectation based on extrapolation of past experience. • Planning - the plan is the expectation • Inter-organizational - Models of other people in the organization (e.g. superiors, subordinates, other departments, etc.) • Extra-organizational - models where the expectations are derived from competition, customers, professional organizations, etc.

35. Another classification of models • Iconic Models • Analog Models • Mathematical Models • Mental Models • These four types are distinguished according to their degree of abstraction, with iconic being the least abstract, and mental models being the most abstract.

36. Iconic and Analog Models • Iconic (scale) models - the least abstract model, is a physical replica of a system, usually based on a different scale from the original. Iconic models can scale in two or three dimensions. • Analog Models - Does not look like the real system, but behaves like it. Usually two-dimensional charts or diagrams. Examples: organizational charts depict structure, authority, and responsibility relationships; maps where different colors represent water or mountains; stock market charts; blueprints of a machine; speedometer; thermometer

37. Mathematical Models • Mathematical (quantitative) models - the complexity of relationships sometimes can not be represented iconically or analogically, or such representations may be cumbersome or time consuming.A more abstract model is built with mathematics. • Note: recent advances in computer graphics use iconic and analog models to complement mathematical modeling. • Visual simulation combines the three types of models.

38. Mental Models • People often use a behavioral mental model. • A mental model is an unworded description of how people think about a situation. • The model can use the beliefs, assumptions, relationships, and flows of work as perceived by an individual. • Mental models are a conceptual, internal representation, used to generate descriptions of problem structure, and make future predications of future related variables. • Support for mental models are an important aspect of Executive Information Systems. We will discuss this in depth later.

39. II. - Problem Formulation • There is always the danger of solving the wrong problem. • Here, you try to clarify the problem so that you work on the “right” problem • Frequently, the process of clearly stating the problem is sufficient; in other cases, reduction of complexity is needed. • Some strategies to use for reducing complexity and formulating a manageable problem are shown in the next slide

40. Problem Formulation Strategies • Determine problem boundaries (I.e. what is clearly part of the problem) • Examine changes that precipitated the problem • Break it down into smaller sub-problems • Focus on controllable elements • Relate to a previously solved class of problems, an analogy situation. • For example, recognizing that a problem is really an “allocation” problem allows the problem solver to look at other “allocation” problems and see what was done previously. The idea is to reduce complexity and rely on past experiences.

41. III. Alternative Generation • A significant part of the process of decision-making is the generation of alternatives to be considered in the choice phase. • This is a creative task and creativity can be taught • Can be enhanced by aids such as • scenarios • brainstorming • analogies • checklists, etc • Requires Knowledge of the problem and its boundaries (domain knowledge), as well as motivation to solve the problem.

42. Decision-Making Concepts

43. Decision Making Concepts • Decisions differ in a number of ways. • The differences affect the alternative generation process, and how a final choice will be made. • The differences can also affect how information systems and information technology can support the process at any one of the stages. • Four dimensions of decision types:: • I. Knowledge of Outcomes • II. level of structure/programmability • III. criteria for the decision • IV. level of decision impact

44. Decision Making Concepts I:Knowledge of Outcomes • Outcome - what will happen if a particular alternative or course of action is chosen • Knowledge of outcomes is important with multiple alternatives • Three types of knowledge with respect to outcomes are usually distinguished: • Certainty • Risk • Uncertainty

45. Knowledge of OutcomesThree Types • Certainty • Complete and accurate knowledge of outcome of each alternative. There is only one outcome for each alternative. • Risk • Multiple possible outcomes for each alternative and a probability can be assigned to each • Uncertainty • Multiple outcomes for each alternative and a probability cannot be assigned to each

46. Decision-Making Under Conditions of Certainty: Rationality • If the outcomes are known and the values of the outcomes are certain, the task of the decision-maker is to compute the optimal alternative or outcome. • Are we rational decision makers? • There is ongoing argument pro and con • People are said to be limited rationalists • We might look for a limited number of alternatives and decide

47. Rationality:Example • A rational decision maker is expected to decide on the “optimal alternative” or outcome • The optimal alternative is one that is related to some optimization criteria such as minimize cost, for example • Thus the rational decision maker chooses the one that has the minimum cost • Consider purchasing two products that are identical in all respects and appear equal in value • All other things being equal, the rational decision maker chooses the one with the lower cost • Rare, since all things are rarely equal

48. Decision Making under Risk • Risk is when multiple outcomes of each alternative is possible and a probability of occurrence can be associated with each • In such cases, the general rule is to pick the one that has the highest expected value

49. RiskExpected Value • Which would you choose? • Action 1 offers 1% probability of a gain of $15,000, or • Action 2 that offers 50% probability of a gain of $400 • Solution: use Expected Value • Expected value is defined as the product of the outcome and the probability of the outcome • Expected value = outcome x probability

50. RiskExpected Value (contd.) • Action 1 : Expected Value = 0.01 x 15,000 = $150 • Action 2 - Expected Value. = 0.5 x 400 = $200 • Action 2 has the higher expected value • The rational decision maker chooses the strategy that has the higher expected value • OK strategy if the probability is known