Lecture 2 Decision Making PDF
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This lecture covers various aspects of decision-making in management. It explores different approaches, the decision-making process, potential biases, and emerging technologies.
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Decision Making Learning Objectives Explain the five approaches managers can use when making decisions Describe the eight steps in the decision-making process...
Decision Making Learning Objectives Explain the five approaches managers can use when making decisions Describe the eight steps in the decision-making process Classify types of problems and decisions Describe how biases affect decision making Identify cutting-edge approaches for improving decision making (self-study) SAMPLE FOOTER TEXT 20XX 2 Decisions Managers May Make1 3 Decisions Managers May Make2 4 Five Approaches to Decision Making 1. Rationality (decision making process model) 2. Bounded Rationality 3. Intuition 4. Evidence-Based Management 5. Crowdsourcing SAMPLE FOOTER TEXT 20XX 5 Rationality Rational Decision-Making – describes choices that are logical and consistent while maximizing value. Assumptions of Rationality The decision maker would be fully objective and logical. The problem faced would be clear and unambiguous. The decision maker would have a clear and specific goal and know all possible alternatives and consequences and consistently select the alternative that maximizes the likelihood of achieving that goal. 6 Decision-Making Process Model Decision - Making choices among alternatives. 8 Illustration of Decision-Making Process Model 9 Step 1: Identify a Problem Every decision starts with a problem, a discrepancy between an existing and a desired condition. Example: Amanda is a sales manager whose reps need new laptops because their old ones are outdated and inadequate for doing their jobs. Problem: a discrepancy between the salespersons’ current computers (existing condition) and their need to have more efficient ones (desired condition). SAMPLE FOOTER TEXT 20XX 10 Step 2: Identify Decision Criteria Decision criteria are factors that are important (relevant) to resolving the problem. Example – Amanda decides the following in her decision: 1) memory and storage capabilities, 2) display quality, 3) battery life, 4) warranty, and 5) carrying weight 20XX 11 Step 3: Allocate Weights to the Criteria If the relevant criteria aren’t equally important, the decision maker must weigh the items in order to give them the correct priority in the decision. The weighted criteria for our example is: SAMPLE FOOTER TEXT 20XX 12 Step 4: Develop Alternatives List viable alternatives that could resolve the problem. In this example, Amanda identifies eight laptops as possible choices. 13 Step 5: Analyze Alternatives Appraising each alternative’s strengths and weaknesses. An alternative’s appraisal is based on its ability to resolve the issues related to the criteria and criteria weight. 14 Step 6: Select an Alternative Choosing the best alternative. The alternative with the highest total weight is chosen. 15 Step 7: Implement the Alternative Putting the chosen alternative into action. Conveying the decision to and gaining commitment from those who will carry out the alternative. SAMPLE FOOTER TEXT 20XX 16 Step 8: Evaluate Decision Effectiveness The soundness of the decision is judged by its outcomes. How effectively was the problem resolved by outcomes resulting from the chosen alternatives. If the problem was not resolved, what went wrong? 17 Bounded Rationality Decision-making that’s rational but limited (bounded) by an individual’s ability to process information. Satisfice – accepting solutions that are “good enough”. 18 Intuition (直覺) Making decision on the basis of experience, feelings, and accumulated judgment. 19 Evidence-Based Management Evidence-based management (EBMgt) – the systematic use of the best available evidence to improve management practice. 20 Crowdsourcing A decision-making approach where you solicit ideas and input from a network of people outside of the traditional set of decision makers. 21 Structured Problems and Programmed Decisions Structured Problems (結構化問題) refer to straightforward, familiar, and easily defined problems (直接、熟悉而容易處理的問題). Manager relies on one of three types of programmed decisions (procedure, rule or policy) to solve the structured problems: Programmed decision (預設決策) is defined as a repetitive decision that can be handled by a routine approach (此種決策適用於重覆或常見的問題). Procedure (程序) – a series of sequential steps used to respond to a well-structured problem. Rule (守則) – an explicit statement that tells managers what can or cannot be done. Policy (政策) – a guideline for making decisions. 22 Example of Procedure 23 Example of Rule 24 25 Unstructured Problems and Nonprogrammed Decisions Unstructured Problems (非結構化問題) refer to problems that are new or unusual and for which information is ambiguous or incomplete (指問題是新的、不常見的) To solve unstructured problems, managers use nonprogrammed decisions – unique and nonrecurring and involve custom made solutions (須就個別問題制定解決辦法) 26 Decision-Making Biases and Errors 1. Overconfidence Bias: holding unrealistically positive views of oneself and one’s performance. 2. Immediate Gratification Bias: choosing alternatives that offer immediate rewards and avoid immediate costs. 3. Selective Perception Bias: selecting, organizing and interpreting events based on the decision maker’s biased perceptions. 4. Framing Bias: selecting and highlighting certain aspects of a situation while ignoring other aspects. 5. Self-serving Bias: taking quick credit for successes and blaming outside factors for failures. 27 Cutting-Edge Decision Making Technology has changed the ability of managers to access information. Two technology driven cutting-edge aides to decision making are: Design thinking: approaching management problems as designers approach design problems. Big Data and Artificial Intelligence: big data refers to huge and complex data sets now available. Big data has opened the door to widespread use of artificial intelligence (A I). Big data: the vast amount of quantifiable data that can be analyzed by highly sophisticated data processing. Can be a powerful tool in decision making, but collecting and analyzing data for data’s sake is wasted effort. 28 Reference Robbins, S. P., & Coulter, M. (2021). Management (15th edition). London, UK: Pearson Education Limited Copyright © 2021 Pearson Education Ltd.