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The Strategy of Decision Analysis - Literature review Example

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The paper discusses the strategy of decision analysis. It analyses the method of selecting the decision out of possibilities that are best for a business or any new venture. The project also extensively researches the process of decision making with respect to supply chain management of companies…
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The Strategy of Decision Analysis
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Decision Analysis of the Contents Basic Outline 3 Introduction to the Topic 3 Analysis of the Topic 4 Literature Review 5 Conclusion 8 References 9 Basic Outline The project broadly discusses the strategy of decision analysis. The study analyses the method of selecting that decision out of many possibilities which is best for a business or any new venture. The project also extensively researches the process of decision making with respect of supply chain management of companies. So, there is a basic introduction to the topic where a simple knowledge regarding the decision making process has been formulated. An elaborate discussion has been made under the analysis section where the problems of supply chain management have been identified. The literature review conducted for a research study assists the researcher to develop a theoretical knowledge regarding the subject matter with the help of the research works of eminent authors and scholars. The literature review of the current paper has been framed on the basis of books, journals and other scholarly publications. The purpose behind using such materials is to create appropriate academic basis for accomplishing the research. Through the literature review, the researcher is able to attain clarity of ideas. It also assists in the development of suitable grounds for studying the subject of the study. It has been ensured by the researcher that the literature review lays its focus on the primary objectives of the paper which is to critically evaluate the role of decision analysis in supply chain management. At the end, a conclusion has been formulated on the basis of the study. Introduction to the Topic In the recent age, the concept of decision analysis has gained popularity in the business strategic management. The fast increasing impact which this field of decision making has created on organizations, both private and public is noticeable. The business units are always engaged in making strategic and critical decisions in order to gain over their competitors and to succeed in the long run. Major progress in theory, computational techniques and modeling tools are attributed to the leaps in computer science which has made the decision making process an integral division of business (Cooper & Schindler, 2003). Anderson, et al. (2015) defines Decision analyses as a systematic, visual and quantitative approach utilized by the companies in order to evaluate and address vital choices that the businesses deal with. Decision analysis implements different tools to extract all relevant data that are required to find an optimal solution in the process of decision making. The term decision analysis was first coined by Ronald A. Howard in 1964 (Hatten, 2015). The decision analysis process promotes the application of logical methods with the aim of improving the decision making procedure in private enterprise. Such techniques involve different models for decision making under the situations of uncertainty or numerous objectives. It also involves techniques of risk assessment and risk analysis, experimental and extensive studies of decision making actions. In case of business studies, economic examination of competitive and strategic decisions is conducted with the aid of different statistical tools, expert system and computer modeling software which facilitate decision making process. From yield management to product development and from supply chain management to investment, these techniques are widely used by the large business firms. Some firms are also involved in development of analytical tools so that they can directly apply in their proceedings to optimize their strategies. It has also been observed by Ferrell and Fraedrich, (2014) that earlier some firms which were only focusing on complicated prediction technologies have shifted their concentration towards development of synergetic and powerful coupling of these tools. Analysis of the Topic The main aim of the decision analysis is to determine the best outcome among many possibilities available so that the decision maker is able to take an accurate decision for a business or new venture. Decision analysis is considered as a prescriptive discipline which is constructed to help the personnel in making enhanced decisions. It is termed as prescriptive in the sense that the process applies normative framework, a set of mathematical procedures and tools in order to guide the decision maker to analyze and optimize the model to obtain satisfactory results. However, Hatten (2015) argues that the view of decision making process is descriptive in nature which determines how personnel actually make decisions. This view is considered to be dependent on psychology of the persons which supports the fact that people process data, assess probabilities and make decisions. However, these decisions are found to be conflicting with the rational outcome of decision analysis. These conclusions emphasize the need of using the decision analysis tools to help in making good decisions (Anderson, et al., 2015). According to Hubbard (2014), under uncertain situations most decisions are made. So it becomes essential to differentiate between a lucky outcome and a good decision. While the later is the consequence of pursuing a rational and scientific approach arranged by the decision analysis, the former can be an unlikely favorable result that is produced regardless of decision quality. Decision analysis heavily relies on a number of methodologies namely probability theory, mathematical programming, statistical decision theory, graph theory and paradigms, stochastic dynamic programming, game theory, information theory, etc. to name a few. Firms utilize this concept to forecast the future trading scenarios. This helps firm to organize their goods and services, to manage inventories and to arrange warehousing. These lead to optimistic growth opportunity for both buyers and suppliers in the long run. The supply chain network incorporates buyer-supplier relationships, supplier section, market share and market integrated distributions. Buyer-supplier relationship is considered as the basis of continued long term growth. Hence, it becomes necessary to select the right supplier for the requested demand (Brandenburg, et al., 2014). With the aim of maximizing quality and minimizing delivery time and cost, the firms often use an optimization tool. Other problems related to supply chain management includes ensuring that the company has got required suppliers and channels at the right place and are properly networked to satisfy the market demand in the most economically viable process. The problem can also occur at the logistics level. So, decision analysis is also required to ensure that the company has correctly allocated its capital assets in the right place. However, certain answers to such problems cannot be obtained due to the presence of external factors acting on market and business (Puterman, 2014).  Literature Review The definition of good decision making process has been illustrated by renowned economists, mathematicians and philosophers. They have described decision making process keeping in mind the idea of rational economic man. A rational economic man is one who always maximizes his or her economic wellbeing and attains consumer equilibrium by thinking marginally. Authors have focussed on prescriptive decision analysis a lot. Prescriptive analytics is the field of business analytics which tries to find the best means of action for a specified situation (Alexander, Walker & Naim, 2014). According to Puterman (2014), prescriptive decision analysis can be distinguished into Normative Decision Theory and Descriptive Decision Studies. Sauter (2014) argues that both these lead to prescriptive analyses. Economists try to find the difference between normative decision making and descriptive theory. Normative theory describes a model which reflects how decisions and inferences should be made by the people. Descriptive model on the other hand, describes model of how decisions and inferences are made by the people. Prescriptive analyses direct decision makers towards the ideas determined by the normative theories in the framework of an ill-defined problem. Zsambok and Klein (2014) try to explain the decision analysis by using three-legged stool. The three legs of the stool represent three questions namely, What the persons want? What does he know? What he desires? The first question focuses on the accessible alternatives that a decision maker has. The second question depicts the available data and the preferences of the decision maker are implied by the third question. The basis of the decision is collectively represented by the three legs, without any of these legs a complete decision is difficult to make. Figure: Decision Essentials (Source: Zsambok and Klein, 2014) Cooper and Schindler (2003) propagate the decision hierarchy which splits the process of decision making into three stages. The top level shows the higher level decisions with other alternatives that are considered as constant at a time. The bottom reflects those decisions that are planned to be made in the future after the decision under consideration has been implemented. Ferrell and Fraedrich (2014) proposed the notion that choosing a proper frame is the vital aspect of decision analyses. Figure: The Decision Hierarchy (Source: Cooper & Schindler, 2003) Hatten (2015) discusses another model known as decision quality that is made of six elements. It structures the logic which helps in arriving at a sound course of action. Degree of accomplishment for each element is represented by the distance from inner circle to outer circle. For a specific decision, correct balancing of elements is required which is represented by the outer circle. Too many information makes the analysis an unbalanced approach. Figure: The Decision Quality Spider (Source: Hatten, 2015) Conclusion From the study conducted, it has been cleared that every aspect of business process decision making process becomes crucial. The supply chain management also needs to be critically evaluated by expertise managers in order to run their business successfully. It is an important part of business where decisions are taken at various junctions like what kind of raw materials and in what quantity are needed by the company, who will supply, how inventories have to be constructed, what strategies have to be implemented to market the finished goods, how many distributive networks have to be developed, etc. So organisations are investing in their analytical departments and employing different tools which are helping them in making right decisions in time. References Alexander, A., Walker, H. & Naim, M. (2014). Decision Theory in Sustainable Supply Chain Management: A Literature Review. Supply Chain Management: An International Journal, 19(6), 504-522. Anderson, D., Sweeney, D., Williams, T., Camm, J. & Cochran, J. (2015). An Introduction to Management Science: Quantitative Approaches to Decision Making. Boston: Cengage Learning. Brandenburg, M., Govindan, K., Sarkis, J. & Seuring, S. (2014). Quantitative Models for Sustainable Supply Chain Management: Developments and Directions. European Journal of Operational Research, 233(2), 299-312. Cooper, D. R. & Schindler, P. S. (2003). Business Research Methods. Retrieved from http://78.158.56.101/archive/msor/headocs/31businessresearch.pdf Ferrell, O. C. & Fraedrich, J. (2014). Business Ethics: Ethical Decision Making & Cases. Boston: Cengage learning. Hatten, T. S. (2015). Small Business Management: Entrepreneurship and Beyond. Boston: Cengage Learning. Hubbard, D. W. (2014). How to Measure Anything: Finding the Value of Intangibles in Business. New Jersey: John Wiley & Sons. Puterman, M. L. (2014). Markov Decision Processes: Discrete Stochastic Dynamic Programming. New Jersey: John Wiley & Sons. Sauter, V. L. (2014). Decision Support Systems for Business Intelligence. New Jersey: John Wiley & Sons. Zsambok, C. E. & Klein, G. (2014). Naturalistic Decision Making. London: Psychology Press. Read More
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