Operations Decision Making Chapter 2 PDF

CHAPTER III OPERATIONS DECISION-MAKING prepared by Ms. Blessa D. Camacho MGT 303 Operations Management INTRODUCTION Thousand of business decisions are made everyday. Not all the decisions will make or break the organization. But each one adds a measure of success or failure to the operations. He...

CHAPTER III OPERATIONS DECISION-MAKING prepared by Ms. Blessa D. Camacho MGT 303 Operations Management INTRODUCTION Thousand of business decisions are made everyday. Not all the decisions will make or break the organization. But each one adds a measure of success or failure to the operations. Hence decision making essentially involves choosing a particular course of action, after considering the possible alternatives. Management as a Science Management scientists hold that, education, scientific training and experience can improve a person’s ability to make decisions. Scientific decision-making rests upon organized principles of knowledge and depends largely upon the collection of empirical data and analysis of the data in a way that repeatable results will be obtained. Thus management as a science is characterized by Organized principle of knowledge Use of empirical data Systematic analysis of data Repeatable results Characteristics of Decisions The appropriateness of a given type of analysis depends on The significant or long Operations decision range from simple judgments lasting decisions to complex analyses, which also involves judgment. The time availability and the Judgment typically incorporates basic knowledge, cost of analysis experience, and common sense. They enable to The degree of complexity blend objectives and sub-objective data to arrive of the decision. at a choice Characteristics of Decisions The significant or long lasting decisions deserve more considerations than routine ones. Plant investment, which is a long-range decision, may deserve more thorough analysis. The time availability and the cost of analysis also influence the amount of analysis. The degree of complexity of the decision increases when many variables are involved, variables are highly independent and the data describing the variables are uncertain. Framework for Defining the problem Decision-Making Establish the decision criteria An analytical and scientific framework for decision Formulation of a model implies the following systematic steps Generating alternatives Evaluation of the alternatives. Implementation and monitoring  Defining the problem enables to identify the relevant variables and the cause of the problem. Finding the root cause of a problem needs some questioning and detective work. If a problem Defining the Problem defined is too narrow, relevant variable may be omitted. If it is broader, many tangible aspects may be included which leads to the complex relationships. Establish the decision criterion is important because the criterion reflects the goals and Establish the Decision Criteria purpose of the work efforts. Formulation of a model lies at the heart of the scientific decision-making process. Model describes the essence of a problem or relationship by abstracting relevant variables from the Formulation of a Model real world situation. Models are used to simplify or approximate reality, so the relationships can be expressed in tangible form and studied in isolation. Generating Alternatives Alternatives are generated by varying the values of the parameters. It is relatively objective in an analytical decision process because the criteria for evaluating the Evaluation of the Alternatives alternatives have been precisely defined. The best alternative is the one that most closely satisfies the criteria. Write a brief explanation hereThe best course of action or the solution to a problem Implementation and Monitoring determined through a model is implemented in the business world. Decision Methodology Complete Certainty Methods ALGEBRA CALCULUS MATHEMATICAL PROGRAMMING This basic mathematical The branch of logic is very useful for mathematics provides a Programming techniques both certainty and useful tool for have found extensive uncertainty analysis. With determining optimal applications in making a valid assumptions, value where functions product mix decisions; algebra provides such as inventory costs, minimising transportation deterministic solutions are to be maximized or costs, planning and such as break-even minimized. scheduling production analysis and benefit cost and other area. analysis. Risk and Uncertainty Methods STATISTICAL ANALYSIS QUEUING THEORY SIMULATION Objective and subjective probabilities with the use of The analysis of queues in Simulation duplicates the probability and probability terms of waiting-time essence of an activity. distribution, Estimation and tests length and mean waiting Computer simulations of hypothesis, Bayesian statistics, time is useful in analyzing are valuable tools for the Decision theory, Correlation and regression technique for service systems, analysis of investment forecasting demand and Analysis maintenance activities, outcomes, production of variance are some of the and shop floor control processes, scheduling techniques used for decision- activities. and maintenance making. activities. Risk and Uncertainty Methods HEURISTIC NETWORK ANALYSIS UTILITY THEORY METHODS TECHNIQUES Utility theory or Heuristic methods involve Network approaches include preference theory allows set of rules, which facilitate decision trees, CPM and PERT decision-makers to solutions of scheduling, methods. They are helpful in incorporate their own layout and distribution identifying alternative course experience and values problems when applied in a of action and controlling the into a relatively consistent manner. project activities formalized decision structure. Extreme Uncertainty Methods GAME THEORY COIN FLIP Game theory helps decision- Flipping a coin is makers to choose course of sometimes used in action when there is no situation where the information about what decision-makers are conditions will prevail. wholly indifferent. Decision-Making Under Uncertainty MAXIMIN MAXIMAX Determine the worst possible pay-off for Determine the best possible pay-off, and each alternative, and choose the alternative choose the alternative with that pay-off. that has the “best worst.” ” The Maximin The Maximax approach is an optimistic, “go approach is essentially a pessimistic one for it” strategy; it does not take into because it takes into account only the account any pay-off other than the best. worst possible outcome for each alternative. The actual outcome may not be as bad as that, but this approach establishes a “guaranteed minimum.” Decision-Making Under Uncertainty LAPLACE MINIMAX REGRET Determine the average pay-off for each Determine the worst regret for each alternative, and choose the alternative with alternative, and choose the alternative with the best average. The Laplace approach the “best worst.” This approach seeks to treats the states of nature as equally likely. minimize the difference between the pay- off that is realized and the best pay-off for each state of nature. Decision Their purpose is to provide the information and analytical Support System support that enables managers to better control and guide the (DSS) decision process. This helps the managers to learn better, how to apply data processing and Decision support system (DSS) is computer-based modeling capabilities of systems designed to aid decision-makers of any computers to the analysis of ill- stage of the decision process in the development structured and value based of alternatives and evaluation of possible course of decisions. action.  Economic Models Break-even Analysis is an economic model describing cost-price-volume relationships. It is a complete certainty type of model because costs and revenues are known quantities. One of the techniques to study the total cost, total revenue and output relationship is known as Break-even Analysis. ‘A Break-even Analysis indicates at what level of output, cost and revenue are in equilibrium’. In other words, it determines the level of operations in an enterprise where the undertaking neither gains a profit nor incurs a loss.  Break-even Chart (BEC) It is a graph showing the variation in total costs at different levels of output (cost line) as well as the variation in the total revenues at various levels of output. Break-even Point BREAK-EVEN It is that point of activity (sales volume) where total revenues and total expenses are equal. It is point of zero ANALYSIS profit, i.e. stage of no profit and no loss. BEP can be used to study the impact of variations in volume of sales and cost of production on profits Angle of incidence It is an angle at which total revenue line intersects total cost line. The magnitude, of this angle indicates the level of profit. Larger the angle of incidence, higher will be the profits per unit increase in sales and vice versa  Margin of safety It is excess of budgeted or actual sales over the break- even sales volume i.e. margin of safety = (actual sales BREAK-EVEN minus sales at BEP)/actual sales. A high margin of safety would mean that even with a lean period, where sales go ANALYSIS down, the company would not come in loss area. A small margin of safety means a small reduction in sale would take company to cross BEP and come in red zone.  Margin of safety (MOS) It is defined as the ratio between Operating Profit and Contribution Margin. It signifies the fractional reduction in BREAK-EVEN the current activity level required to reach the breakeven point. ANALYSIS Sales turnover (STO) It is defined as ratio between Sales Revenue and the Capital Employed. It represents the number of times capital employed is turned over to reach the sales revenue level that is called Operating management performance [OMP]  A company interested in improving its OMP will have to IMPROVING improve its operating profit. Following any of the strategies given below or a combination of them can do this: OMP (a) By reducing variable costs (b) By reducing fixed costs (c) By increasing sales price (d) By increasing the activity level STATISTICAL MODES There are three types of probabilities. Namely classical, empirical, and subjective probabilities. (a) Classical probabilities are based upon equally likely outcomes that can be calculated prior to an event on the basis of mathematical logic. (b) Empirical probabilities are based upon observed data and express the relative frequency of an event in the long run. (c) Subjective probabilities are based upon personal experience or judgment and are sometimes used to analyse one-time occurrences Decision Tree A decision tree is a schematic representation of the alternatives available to a decision maker and their possible consequences. The term gets its name from the tree like appearance of the diagram. Although tree diagrams can be used in place of a pay-off table, they are particularly useful for analyzing situations that involve sequential decisions. thank you! in order to be irreplaceable, one must always be different.