Instructor’s Manual
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Chapter Outline
A Decision Tree Model and Its Analysis • The following concepts are introduced through the use of a simple decision tree example (the Bill Sampras ' summer job decision): Decision tree Decision node Event node Mutually exclusive and collectively exhaustive set of events Branches and final values Expected Monetary Value (EMV) Optimal decision strategy • Introduction of the folding back or backward induction procedure for solving a decision tree. • Discussion on sensitivity analysis in a decision tree. Summary of the General Method of Decision Analysis. Another Decision Tree Model and Its Analysis • Detailed formulation, discussion, and solution of the
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If the forecast indicates a rainy day, she should cancel the show. If the forecast indicates a sunny day, she should continue with the show. The EMV of this strategy is $6,200.
Manual to accompany Data, Models & Decisions: The Fundamentals of Management Science by Bertsimas and Freund. Copyright 2000, South-Western College Publishing. Prepared by Manuel Nunez, Chapman University.
Instructor’s Manual
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(a) See decision tree above. (b) Once Monday 's bid is made, Newtone 's optimal strategy is to accept the bid if it is a $3,000,000 bid and reject it if the bid is for $2,000,000. If Monday 's bid is rejected, then accept Tuesday 's bid, regardless of the amount offered. The EMV of this strategy is $2,600,000.
Manual to accompany Data, Models & Decisions: The Fundamentals of Management Science by Bertsimas and Freund. Copyright 2000, South-Western College Publishing. Prepared by Manuel Nunez, Chapman University.
Instructor’s Manual
Chapter 1
5
1.3
(a) As shown in the table below, as p decreases James ' optimal decision changes as to take Meditech 's offer. A break-even analysis where we solve the equation 440p - 200(1-p) = 150 reveals that the break-even probability is p=0.55. In other words, if the probability of successful 3D software is below 0.55, then it is better for James to accept Meditech 's offer, otherwise continue with the project.
Probability of Successful 3D Development p
Lincoln sports case is faced with a major company altering decision. Through relying on expected net present value of the new cleat production and scenario analysis, the company would determine whether or not taking on the new cleat production would benefit the company.
b) Evaluate how this model can be applied to identify study and review patterns of management behaviour.
The concept of analytics-based decision marking takes into consideration industry knowledge and business analytics which includes four acts (Bartlett, 2013). The four acts help prepare analytics to support an anticipated decision and illustrate a process for analytics-based decision making. As a result, the role of statistical thinking, the interaction, and relationship between industry knowledge and analytics, as well as where things can go wrong in a real business problem can be revealed (Bartlett, 2013). In addition, moving from one act to another seamlessly, jumping back from and forth from one act to another or simply following some other route is easy to do in a real business problem. This annotated bibliography will examine articles that contain resources that support the concepts contained in the four acts.
Kessler, E. H. (Ed.) (2013). Encyclopedia of management theory (Vols. 1-2). Thousand Oaks, CA: SAGE Publications Ltd. doi: 10.4135/9781452276090
What does the data show – identify metrics to sell the business case to upper management
The tension between the uses of subjective versus objective data is a literature that formulated after introduction of money ball. Researchers have been keen to dig into the usefulness of the concept posed by the book money ball. The main idea in money ball in simple terms is that statistical analyses are better predictors than our intuition. This paper will explore the literature around moneyball and its influence in management.
A good methodology to organizations such as the PRC is the practice of evidence-base data driven decision making. In fact, evidence-based decision making is a directional approach to organizations when creating or making decisions supported by the collection of data (Power, 2014). Unfortunately, this is a tool which is not practice at the PRC and it is necessary for Mrs. Lewis and her future partners to have in place. According to research, practicing evidence-based data decision making is a lifelong commitment, which keeps on making positive transformations and improvements to organizations (Mandinach & Jackson 2012). Additionally, the importance of adopting such a practice can benefit executive directors like Mrs. Lewis and provides a greater
This lesson changed how I managed my results and I have worked hard over the years to ensure I use data to accurately measure the performance of my teams and to devise strategies to achieve my goals. In my role as the Operations Director at an Executive Search firm, I was tasked with managing our offshore operations. This created a unique challenge since traditional management techniques of observation were ineffective when managing a team on the other side of the planet. I discovered the intricacies of Excel to spot areas of opportunities that most managers would rely on observation. This reliance on data analysis resulted in a highly successful operation that was able to detect early risks to avoid revenue
Kessler, E. H. (Ed.) (2013). Encyclopedia of management theory (Vols. 1-2). Thousand Oaks, CA: SAGE Publications Ltd. doi: 10.4135/9781452276090
Easterby-Smith, M., Thorpe, R. & Jackson, P. (2008) Management research. 4th Edition. London: SAGE Publications (Accessed: 17 October, 2014).
Successful management requires an understanding of the fundamental concepts of effective management techniques and principles. In order to gain such insight, and manage effectively and efficiently, managers must develop an awareness of past management principles, models and theories. From the turn of the 20th Century, the
Why do businesses manage data and use graphics to reveal their overall performance standings, and what type of graphics, tables, or charts should one use to share communicating quantitative information to their business customers that’s not only effective; but easy to understand? Businesses manage data in order to review, and share information received by others; which are displayed by usage of certain graphs that indicates ones performance levels in certain areas. “However, before you can interpret data, the elements must be classified, summarized, and condensed into a manageable size; while the condensed information is meaningful and can be used to answer your research questions” (Lehman, Dufrene, Walker, 2014, p. 169). The purpose for using these type of elements is to display your findings in a way that others can relate to, by simply compiling all the data into a readable analysis technique through the usage of a computer. However, it takes careful planning as to what graphics to use, depending on what results you and the customers are currently searching for. That’s why there are certain steps to follow when gathering the necessary information before selecting the right format to put into existence for others to view. The first step is to gather the information from the survey, then input it into the computer system; so it can be categorized by importance. This system allows it to be broken down into sections, then divided into categories; by
4. Hambrick, D.C; Fredrickson, J.W. “Are you sure you have a strategy”.The Academy of Managemen
Guerra-Lopez (2008) claimed that an organization’s internal sources of data input are often used as a means to identify prior performance and assessments needs and results. The Department would greatly benefit from use of data gained from primary sources such as strategic planning. Since the Department makes functional use of statistics, prior year’s evaluations, and financial projection tools to determine its goals and objectives, the strategic implementation of the
To help sifting through and combining the right data in the right ways, businesses must develop analytical capabilities that far surpass today’s standards. The sheer volume of data impressive, that same volume can lead to confusion, or plain bad direction for decision makers. A great rule to live by in analytics is that “numbers tell THE story, ANY story can be told by the numbers.” What this means is that managers must be certain that they are using the right data set, and designing their analysis to provide an output that solves the business problem they are trying to solve, rather than just providing the answer they are hoping to provide. This is done through the deployment of analysis tools, those that are becoming more and more prevalent, and easier to use, along with building or hiring the capability into the organization. The skills needed for this work include, but are not limited to, a deep understanding of the business, and ability to communicate complex concepts in a way that is easily understood, and a mastery of statistical and analytical methods. While the first two capabilities ensure that the right data is used, and it is analyzed to yield a sound outcome, the final capabilities is often the most important, and biggest stumbling block for organizations.