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Unit Two

Unit Two. Decision Making and Computerized support. Decision making introduction and definition. Decisions are made by individuals or groups. Group members may have biases Empowering a group leads to better decisions. Many alternative to consider

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Unit Two

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  1. Unit Two Decision Making and Computerized support

  2. Decision makingintroduction and definition • Decisions are made by individuals or groups. • Group members may have biases • Empowering a group leads to better decisions. • Many alternative to consider • Most decisions made in business are materialized in the future. • Decisions are interrelated. • Decision-making involves thinking leading to the need for data and modeling. • Feedback is important for decision-making.

  3. We want to help decision-makers make better decisions, which does not mean making fast decisions. • Planning function of managers involves a series of decisions: what should be done? When? Where? Why? How? By whom?

  4. Decision making disciplines • Decision-making is influenced by behavioral disciplines or scientific in nature disciplines. • The behavioral disciplines: Anthropology, law, philosophy, political science, psychology, social psychology, and sociology. The scientific in nature disciplines: Computer science, decision analysis, economics, engineering, management science, mathematics, statistics, biology, chemistry,physics.

  5. Decision Making • Is the cognitive process leading to the selection of a course of action among alternatives. Every decision making process produces a final choice called a decision. It can be an action or an opinion. It begins when we need to do something but we do not know what. Therefore, decision-making is a reasoning process which can be rational or irrational, and can be based on explicit assumption or tacit assumptions. • Decision making is a psychological construct, we can not see a decision, but we can infer from observable behavior that it has been made.

  6. Due to large number of considerations involved in many decisions, computer-based decision support systems have been develop to assist decision makers in considering the implications of various courses of thinking. They can help reduce the risk of human errors.

  7. Cognitive and personal biases in decision making • It is generally agreed that biases (تحيز)can affect our decision making process, calling into question the correctness of a decision. How to tell when a decision is biases? Here are some cognitive biases: 1- selective search for evidence: we tend to willing to gather facts that support certain conclusions but disregard other facts that support different conclusions. 2- premature termination of search evidence: we tend to accept the first alternative that looks like it might work. 3-conservatism and inertia(مقاومة التجديد والقصور الذاني): unwillingness to change thought patterns that we have used in the past in the face of new situation (tradition) 4- experiential limitations: unwillingness or inability to look beyond the scope of our past experiences.

  8. 5-selective perception: we actively screen-out information that we do not think is salient (prejudice تعصب). 6- source credibility bias: we reject something if we have a bias against the person, organization or group to which the person belongs. We accept statement by a person we like more.

  9. A decision rule is the approach used by a group to mark the choice that is made. Some of these rules are: 1- unanimity(اجماع): it requires that everyone to agree on a given course of action and thus imposes a high bar of action. 2- majority: requires support of more than 50% of the group. 3- consensus decision-making(اتفاق جماعي في الراي): tries to avoid winners or losers. It requires that a majority approve a given course of action, but that the majority agree to go along with the course of action. In other words, if the majority opposes the course of action, consensus requires that the course of action be modified to remove objectionable features.

  10. 4-subcommittee: involve assigning responsibility for evaluation of a decision to a sub-set of a larger group, which then comes back to the larger group with recommendations for action Less desirable group decision rules are: 1-Plurality: the larger block in a group decides, even it falls short of a majority. 2-dictatorship: one individual determines the course of action.

  11. Decision Making in Groups • A process that refers to the interaction among individuals that lead to the choice of a particular course of action. An outcome is the consequence of that choice. Separating process and outcome is convenient because it helps explain that a good decision making process dose not guarantee a good outcome, and that a good outcome does not presupposed a good process.

  12. Systems • Collection of objects. People, resources, concepts, and procedures intended to perform and identifiable function or serve a goal. Examples: University is a system of (student, staff, faculty, administration, buildings, equipments, ideas, and rules with the goal of educating students, producing research, and providing services to the community. • Each system has it’s defined goals. • Most systems are subsystems of larger one.

  13. The structure of a System • A system consists of 1- inputs: elements that enter the system. 2- processes: all elements needed to convert or transform inputs into outputs. 3-outputs: finished products that come out of the system – information. 4- feedback: finished product that may be reentered into the system as inputs to produce new outputs. It may be modified inputs or processes to produce outputs closer to the target.

  14. 5-Environment: where the system is used. Elements which are outside the system but they affect its performance in achieving its goals. They may be social, political, legal, economical, or physical. 6- boundaries: what are the functions of a system? (functional boundary) Or where the system is located? (physical boundary) Or time of the system (nonphysical boundary).

  15. Closed and Open Systems • Closed system : is a system that does not take any input from human being while in action. Examples, the solar system, computer transaction processing system. It is independent, and isolated from its environment. • Open System: is a system that takes input from human, it interacts with the environment surrounding it, and it may deliver output to environment around it.

  16. System effectiveness and efficiency • Effectiveness is the degree to which goals are achieved (concerned with output of the system). Total sales or earning per share. • Efficiency: is a measure of the use of inputs or resources to achieve outputs. How much money is used to generate a certain level of sales. • Effectiveness is doing the right thing. • Efficiency is doing things right.

  17. An important characteristic of MSS is their emphasis on the effectiveness or “goodness” of the decision produced, rather than on the computational efficiency of obtaining it. • Most Web-based DSS are focused on improving decision effectiveness.

  18. Information System • IS collects, processes, stores, analyze, and disseminates information for a specific purpose. • No organization can function without its IS. • IS accepts input and process data to provide information to decision makers and help them communicate the results • Most consumers and decision makers accept the presence of the WWW and its activities.

  19. Models • Major characteristic of DSS is to include at least one model. • It is to perform the DSS analysis on a model of reality rather than on the real system. • A model is a simplified representation of reality. • Models can represent systems or problems with various degrees of abstraction

  20. Classes of models a- Iconic: • The least abstract type of model. • Physical representation of the original system with different scale. • Examples: three dimensional (building, car, airplane) or two dimensional – photographs.

  21. Classes of models (cont) b- Analog: • Symbolic representation of reality. • Two dimensional (charts or diagrams). • It can be physical model. • Examples: organization hierarchical chart, stock market charts, a blue print of a house.

  22. Classes of models (cont) c- mathematical (quantitative) model: • Expressed as math expressions.

  23. Benefits of models 1- easy to manipulate and change. 2-enable time compression 3- the cost of modeling analysis is less. 4- cost of making mistakes is less. 5-enable managers to estimate the risks. 6-number of possible solutions and alternatives is very large. 7- it enhance and reinforce learning and training. 8-available over the web for free use.

  24. Phases of the decision-making process 1- the intelligence phase: • it begins with the identification of the organizational goals and objectives. • Are they accomplished by the current system? • Is their any dissatisfaction? Why? • if a problem exists, can you identify its symptoms? • Do you know the cause of symptoms? • Does productivity suffers?

  25. The measurement of productivity and the construction of a model are based on real data. • Issues may arise during data collection and estimation: 1- data are not available 2-obtainnig data is expensive 3-data may not be accurate 4- data estimation is subjective 5-data may be insecure 6-important data may be qualitative

  26. 7-too many data (overload) 8-outcome may occur at extended periods • After the primary investigation is completed, we can: 1-determine if a problem exists 2-where it is located 3-how serious it is.

  27. Problem Classification A- programmed: well-structured problems that are repetitive and routine and for which standard models are developed. B- nonprogrammer: unstructured problems that are unique and nonrecurrent. Examples: evaluating e-commerce initiative, what to put on Web site, selecting a job.

  28. Problem decomposition • Complex problems are divided into smaller ones (sub problems). • Decomposition helps in solving complex problems. • It facilitates communication among decision-makers. • It helps decision-makers incorporate both qualitative and quantitative factors into their decision-making models.

  29. Problem ownership • A problem exists only if someone or group identify it and the organization can solve it.

  30. The Design Phase • Developing and analyzing possible course of action. These include: a- understanding the problem b- testing solutions for feasibility c- a model is constructed, tested, and validated. • Modeling involves conceptualization the problem and abstracting it to quantitative and/or qualitative form.

  31. Simpler model leads to: 1-lower development costs 2-easier manipulation 3-faster solution but less representative of real problem and inaccurate results. Models have : 1-decision variables that describe the alternatives a manager must choose among. 2- a result variable of a set of result variables that describe the objective or goal of the decision-making problem. 3- uncontrollable variables that describe the environment.

  32. Selection of a principle of choice • A principle of choice is a standard that describes the acceptability approach. • Types of principle of choice: 1- normative models: are those in which the chosen alternative is demonstrably the best of all possible alternatives. This is done by examining all alternative and choose the best one (optimization). Optimization is accomplished by one of three ways:

  33. Optimization ways:m 1- get the highest level of goal attainment from a given set of resources. 2-find the alternative with the highest ratio of goal attainment to cost or maximize productivity. 3-find the alternative with the lowest cost that will meet an acceptable set of goals

  34. Normative decision theory is based on the following assumptions of rational decision-makers: 1- human are economic being whose objective is to maximize the attainment of goals. 2- for a decision-making situation, all viable alternative courses of action and their consequences are known. 3-decision-makers have an order or preference that enables them too rank the desirability of all consequences of the analysis.

  35. Are decision makers really rational? They may not be for the following anomalies( خروج عن القياس شذوذ): 1-incompetence 2-lack of knowledge 3-multiple goals that are framed inadequately 4-misunderstanding of decision maker’s true expected utility 5-time pressure impacts

  36. Sub optimization • Optimization requires a decision-maker to consider each alternative decision on the entire organization to ensure that a decision in one area of the organization does not negative effects on other areas. • To avoid the negative effects, each department should consult with other departments, but this may require a complicated, expensive and time consuming analysis. • The MSS builder may close the system with narrow boundaries, considering only the department under study, and incorporate relationships into the model that assume away certain complicated relationship describing interactions with and among other departments. The other departments can be aggregated into simple model components.

  37. If a sub optimal decision is made in one part of the organization without considering the details of the rest of the organization, then an optimal solution from the point view of that part may be inferior for the whole. • Once a solution is proposed, its potential effects on the remaining departments of the organization can be tested. If no significant negative effects are found, the solution can be implemented.

  38. Sub optimization may also apply when simplifying assumptions are used in modeling a specific problem (too many details or too many data). • Sub optimization may also involve simply bounding the search for optimal solution by considering alternatives or by eliminating large portions of the problem from evaluation.

  39. Descriptive models • Describe things as they are, or as they are believed to be. • Mathematically based. • Useful for investigating the consequences of various alternative course of action under different configuration of inputs and processes. • Simulation is a descriptive modeling method. (virtual reality) • A narrative to describe a decision-making situation is a descriptive model.

  40. Good Enough or Satisficing • Settling down for a satisfactory solution • Setting up aspirations, goals, or desired level of performance and searching for alternatives until one found that achieves this level. • Reasons for satisficing: 1- time pressure: decision may lose value over time. 2-the ability to achieve optimization. 3-Managerial benefit of a better solution is not worth the managerial cost to obtain it.

  41. Satisficings a form of sun optimization. • There may be an optimal solution but it is difficult to attain. • Bounded rationality: Rationality is bounded by: 1- limitations on human processing capacities. 2-individual differences (age, education, knowledge, attitudes).

  42. Developing (Generating) Alternatives • Alternatives may be generated automatically by the model. In MSS situation it is necessary to generate alternatives manually. This takes log time to process and cost money. • Too many alternative be detrimental to the process of decision-making. (information overload) • Generating alternative is dependent on the availability and cost of information and requires expertise in the problem area.

  43. Measuring Outcomes • Alternatives are evaluated according to goal attainment, outcome may be expressed in terms of a goal. • An outcome such as customer satisfaction may be measured by the number of complaints. • When group make decision, each participant may have different goals. For example, executive want to maximize profit, marketing want to maximize market penetration, operation want to minimize costs, stockholder want maximize the bottom line.

  44. Scenarios • A statement of assumptions about the operating environment of a particular system at a given line. ( narrative description of the decision-situation setting. • Scenarios describe decision and uncontrollable variables and parameters for specific modeling situation. • Scenarios help in simulations and what-if analysis (in both cases we change scenarios and examine the results).

  45. Benefits of Scenarios 1-help identify opportunities and problem areas. 2-provide flexibility in planning. 3-identify the leading edges of changes that management should monitor. 4-help validate major modeling assumptions. 5-allow the decision-maker to explore the behavior of a system through model 6-help to check the sensitivity of proposed solutions to changes in the environment as described by the scenario.

  46. Possible scenarios • Worst possible scenario • Best possible scenario • Most likely scenario • Average scenario. Errors in Decision-making: Errors are possible, you avoid them by: 1-validating the model before use 2- gathering the right amount of information, the right level of precision and accuracy to incorporate into the decision-making process.

  47. 3- the Choice Phase • Here where: 1- the actual decisions are made 2- the commitment to follow a certain course of action is made. • Design and choice phases may overlap. • The choice phase includes searching, evaluating, and recommending of an appropriate solution to the model. • A solution to the model is a specific set of values for variables in a selected alternative. • The solution to the model yield a recommended solution to the problem. The problem is considered solved if the recommended solution is successfully implemented. • DSS can support the choice phase through the what-if and goal seeking analysis.

  48. The Implementation Phase • Putting recommended solution to work. • DSS can used in implementation activities such as decision communication, explanation, and justification.

  49. Personality types, Gender, Human Cognition, and Decision styles • Personality Types: Their is a strong relationship between personality and decision-making. Personality types influences general orientation toward goal attainment, selection of alternatives, treatment of risk, and reactions under stress. Personality affect a decision-maker ability to process large quantities of information, time pressure, and reframing. It influences the rules and communication patterns of individual decision-maker.

  50. Gender • There are gender differences and gender similarities in decision-making, including factors such as boldness, quality, ability, risk-taking attitudes, and communication patterns. • Men are more inclined to take risks than women. • It is unwise to characterize either males or females as better or worse decision-makers • Both genders may take decisions in different ways and have different information style preferences.

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