Decision making is the most fundamental function of management professionals. Every manager has to take decisions related to his or her field of work. Therefore, this is an all-pervasive function of basic management. There are various methods for the process of decision making. The quantitative technique of decision making helps in making these methods more convenient and efficient.
Almost every function of a typical manager will require him or her to make decisions on a routine basis. These decisions mostly depend on the nature as well as the scope of his or her work. Also, it depends on the authority and the powers of the manager.
A decision is a judgment of a course of actions that are always aiming to achieve a specific result. For every task a person wants to achieve, decision forms the foundation of it.
The manager often chooses the best option from a range of alternatives for every task that he or she has to complete within a given time. Every decision has many consequences. Therefore, choosing the right decision is very important.
It can be said that the entire decision making involves selecting a course of action from various alternatives. This is a very curial function that all the managers have to carry out routinely.
While making a decision there are several techniques that a manager of a company or an organization can employ. The quantitative techniques help the manager to take decisions objectively and in an efficient way. Such techniques rely on a scientific and statistical approach to make a good decision. The six important quantitative techniques of decision making are as follows.
This technique helps in maximizing an object that is under limited resources. The main objective can be either optimization of a utility or minimizing of a disutility. In simple words, one can say that it helps in utilizing a resource or a constraint to its maximum potential.
Usually, all the managers use this technique only under conditions that involve certainty. Therefore, this might not be very useful to the manager when circumstances are uncertain or unpredictable.
Probability decision theory is a technique that lies in the case, where the probability of an outcome can only be predicted. In simple words, one cannot always predict the exact outcome of any course of action.
The managers use this approach to determine the probabilities of an outcome using the available information, firstly. The managers can also rely on their subjective judgment for this purpose. Next, they use this data of probabilities to make their decisions. They often use the decision tree or the pay-of matrices for this purpose.
Often, the managers use certain quantitative techniques only while making decisions pertaining to their business rivals. The game theory approach is one such kind of technique.
This technique stimulates the rivalries or conflicts between businesses as a game. The main aim of the managers of a company under this technique is to find ways of gaining at the expense of their rivals. In order to do this, they can use two people or 3 people or even ‘n’ number of people games.
Each and every business often suffers waiting for periods or queues pertaining to their personnel, equipment, resources, or services. For example, sometimes a manufacturing company may gather a stock of unsold goods due to irregular demands. This theory aims to solve such type of problems.
The main aim of this theory is to minimize such waiting periods and also reduce the investments in such expenses. For example, the departmental stores often have to find a balance between the unsold stock and the purchasing of fresh goods. The managers in such examples can employ the queuing theory to minimize their expenses.
The stimulation technique observes several outcomes under hypothetical or artificial settings. The managers try to understand how their decisions will work out under diverse circumstances.
Then they finalize accordingly on the decision that is likely to be the most beneficial to them. Understanding the outcomes under such stimulated environments instead of natural settings reduce the risk drastically.
All the complex activities often require concentrated efforts by the personnel in order to avoid the waste of time, energy, and also the money. This technique basically aims to solve by creating strong network structures for the work.
There are two most crucial quantitative techniques under this approach. These include the Critical Path Method and the Programme Evaluation and the Review Technique. These techniques are effective because they segregate the work efficiently under the networks. They also drastically reduce the time and money.
1) What is the Role of Quantitative Techniques in Decision Making?
Ans: Some of the roles of quantitative techniques in decision making are as follows.
a) These techniques provide executives with a more precise description of the cause and affect the relationship. It also risks the underlying business operations in measurable terms. It eliminates the conventional, intuitive, and also the subjective basis on which the management used to formulate their decisions in the past.
b) It provides solutions for several business problems.
c) It also enables the proper deployment of the resources.
d) It helps in the minimization of waiting time and the servicing costs.
e) It assists in choosing an optimum strategy.
f) It greatly helps in optimum resource allocation.
g) It enables the management to decide when to buy and how much to buy.
h) They also facilitate the process of decision making.
2) What are Decision Trees?
Ans: The decision trees always show the complete picture of a potential decision and also allows a manager to graph alternative decision paths. Decision trees are a very useful way to analyze hiring marketing, investments, equipment purchases, pricing, and also similar decisions that involve a progression of smaller decisions. Usually, the decision tree is used to evaluate the decisions under the conditions of risk.
The term decision tree originates from the graphic appearance of a technique that starts with the initial decision shown as the base. Decision trees also force a manager to be explicit in analyzing the conditions associated with future decisions.