Quantitative Techniques in Management.
What differentiates good management from bad management? Of course, Great Decision Making Ability! A good management decision is based on logic, rationality and application of quantitative approach to problem solving. Generally, good decisions result in favourable outcomes in the long run. To illustrate, Toyota's decision to release Prius without proper quality checks (a bad decision) resulted in the recall of about 10 million cars across the US, Europe and China and sullied Toyota's much vaunted reputation for Quality (outcome of a bad decision!). Back home, the Tatas decided to shift their Nano plant from Singur, West Bengal (Singur was a bad decision) to Sanand, Gujarat (good decision). With this decision, the trial production of Nano cars at this plant started in February 2010 (favourable outcome). Further, the real estate business which was experiencing one of the worst recessionary periods, received a sudden boost following Tata Motors' move to set up its plant near Ahmedabad. This decision is also expected to convert Gujarat into an auto mobile hub. Innumerable similar examples may be cited to show the significance of good management decision making.
As propounded by Herbert Simon, manager functions according to the Principle of "Bounded Rationality" and thus, the tools of quantitative techniques can act as a boon by reducing the complexity of decision making. The book, "Quantitative Techniques in Management" is an attempt to make the reader understand these tools for effective decision making. The book is organised into nineteen chapters ranging from linear programming, Sequencing, Inventory management, Queuing theory, Replacement theory, PERT-CPM, Decision Theory to Markov Chains, Dynamic Programming, Simulation to Forecasting. A notable strength of the book is the generally consistent structure of each chapter. Each chapter starts with an overview and ends with points to remember. It targets students of post graduation in commerce and management besides students of professional courses like CA and ICWAI.
The plan of the book is as follows. Chapter 1 gives the overview of the quantitative approach to decision making. Linear Programming is addressed in Chapters 2, 3 and 4. Specifically, Chapter 2 explains the formulation of linear programming and its graphic solution. Chapter 3 describes the Simplex technique of solving linear programming problem. Economic interpretation and Sensitivity Analysis are the subject matter of Chapter 4. Chapter 5 deals with Transportation and Transshipment problems. Chapter 6 discusses the tools to minimize the cost or maximize the effectiveness of the Assignment problem. Chapter 7 is addresses integer and goal programming problems. Chapter 8 considers the problem of sequencing which deals with scheduling of different jobs to be performed on various machines. Inventory is the subject of discussion of chapter 9. Chapter 10 deals with the Queuing theory to determine the service level which minimizes the relevant cost. Chapter 11 explains the Replacement theory. The tools of PERT and CPM useful for the purpose of planning and controlling complex projects are addressed in chapter 12. The next three chapters discuss Decision theory, Markov Chains and Theory of Games respectively. Chapter 1 6 explains another important quantitative tool namely, Dynamic Programming. The Monte Carlo analysis, a powerful tool of Simulation, is dealt with in Chapter 1 7. Chapter 18 explains the various tools of Financial Decision Making specifically Capital Budgeting and Break Even Analysis. The last chapter discusses various Forecasting Models.
There are notable weaknesses in various aspects of the book. First, as far as the structure of the book is concerned, the various chapters are given in a random order and not classified under different headings/sections. For example, the book deals with statistical tools, financial investment tools, probability based tools and linear programming under the same category. A better structure would have been to divide the book in three broad sections. The first seven chapters along with Theory of Games and Dynamic Programming dealing with programming problem could be placed under Section-I. Section-II could have included chapter 8 to chapter 12 which are different from linear programming problem. Decision theory, Simulation, Forecasting and Investment analysis dealing with statistical tools could be included in Section-III. Second, the book is supposed to cater to management students but lacks case studies, a prerequisite of any good management text. Third, the book does not provide students familiarity with excel or any other software, making the book outdated in today's IT-enabled decision making environment. The author could have provided CD-Rom modules for students besides providing additional problems and other material in a companion web site. Fourth, the book can be enriched by including introductory chapters on probability concepts and regression analysis for students with non-mathematics background. Moreover, instead of keeping forecasting models at the end, it should have been tackled in the beginning itself. Fifth, the chapter dealing with economic interpretation of duality and sensitivity analysis could be improved further. The reader would be benefited if the introduction of a constraint in sensitivity analysis is also explained with the help of dual simplex method. Sixth, some of the solutions given at the end require revision.
The plus point about the book is that it contains a large number of practice questions. Easy to understand reader friendly style of writing makes this book a must for beginners. Although the book attempts to make the reader comfortable by using simple and lucid presentation, it is definitely not meant for management students. The book requires further revision and up gradation! The reader would be better served if Case Studies are incorporated with Excel based solutions.
FORE School of Management
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|Article Type:||Book review|
|Date:||Jan 1, 2010|
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