The stuff of management science can seem abstract, and students sometimes have trouble perceiving the usefulness of quantitative courses in general. Part of the problem is that the examples used in books often do not seem realistic.
Unfortunately, examples must be made simple to facilitate the learning process. Larger, more complex examples reflecting actual applications would be too complex to help the student learn the modeling technique. The modeling techniques in this course are, in fact, used extensively in the business world, and their use is increasing rapidly because of information technology.
The real objective of management science is to solve the decision-making problems that confront managers by developing mathematical models of those problems
For this course, the main goal is to demonstrate solutions to various problems that managers face every single day. From maximizing profitability, minimizing transportation costs, to optimizing employee scheduling – this course will provide you with a hands-on approach to dealing with management science models and techniques.
There is no mathematical programming in this course or learning complex formulas, as we will use Microsoft Excel as an aid to solving various common business scenarios that you encounter at the workplace.The whole idea is to make these mathematical topics seem less complex and present them in a practical way to your benefit. Each modeling technique is explained with straight forward examples followed by hands-on tutorials.
This course will cover the following topics:
1. Management Science techniques and processes
2. Breakeven analysis
3. Sensitivity analysis
4. Linear programming (without any programming!)
5. Introduction to Project Management and its processes, that is, Scope Statement, Work Breakdown Structure, Responsibility Assignment Matrix, and Project Scheduling and tools
6. Creating a Payoff table
7. Decision making criteria
Management science is the application of the scientific approach to solving management problems. It helps managers make better and effective decisions, and can be used in a variety of organizations to solve different problems. It encompasses a logical, consistent, and systematic approach to problem solving
The purpose of break-even analysis is to determine the number of units of a product (i.e., the volume) to sell or produce that will equate total revenue with total cost. The point where total revenue equals total cost is called the break-even point, and at this point profit is zero.
The break-even point gives a manager a point of reference in determining how many units will be needed to ensure a profit.
Learn through a hands-on tutorial on conducting a Break Even analysis
The term 'programming' does not imply computer programming; rather to a predetermined set of mathematical steps used to solve a problem. Most frequently used and popular technique in management science.
It helps managers determine solutions (i.e., make decisions) for problems that will achieve some objective in which there are restrictions, such as limited resources or a recipe or perhaps production guidelines.
Objectives of a business frequently are to maximize profit or minimize cost. Linear programming is a model that consists of linear relationships representing a firm's decision(s), given an objective and resource constraints.
The linear programming technique derives its name from the fact that the functional relationships in the mathematical model are linear, and the solution technique consists of predetermined mathematical steps—that is, a program.
Linear Programming tutorial: Maximization example
Linear Programming tutorial: Minimizing transportations costs example
Management is generally perceived to be concerned with the planning, organization, and control of an ongoing process or activity such as the production of a product or delivery of a service. Project management is different in that it reflects a commitment of resources and people to a typically important activity for a relatively short time frame, after which the management effort is dissolved.
The two categories of decision situations are:
Probabilities that can be assigned to future occurrences
Probabilities that cannot be assigned
A decision-making situation includes several components
The decisions themselves and the actual events that may occur in the future, known as states of nature.
Suppose a distribution company is considering purchasing a computer to increase the number of orders it can process and thus increase its business. If economic conditions remain good, the company will realize a large increase in profit; however, if the economy takes a downturn, the company will lose money. In this decision situation, the possible decisions are to purchase the computer and to not purchase the computer. The states of nature are good economic conditions and bad economic conditions.
This module is a recap of what was covered in the course
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Syed graduated from University of Wisconsin in 1995 with a BBA in Finance. Subsequently, he obtained an MBA from Concordia University, LLB and DBL degrees from University Law College, and PhD in Management Sciences. Having obtained MCSE (Microsoft Certified Systems Engineer), MCP+I (Microsoft Certified Professional + Internet), and MCT (Microsoft Certified Trainer), Syed has provided training to thousands of students. ClayDesk provides e-Discovery and cloud computing services including technical training to a wide range of clients globally.
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