Decision Making Conditions and Tools for Decision Making

Decision Making Conditions:

There are different conditions in which decisions are made. Managers sometimes have an almost ideal understanding of conditions surrounding a decision, but in other situations they may have little information about those conditions. So, the decision maker must know the conditions under which decisions are to be made. Generally, the decision maker must know the conditions under which decisions are to be made. Generally, the decision maker takes decisions under the condition of certainty, risk and uncertainty.

Certainty:

Certainty is a condition under which the manager is well informed and known about possible alternatives and their outcomes. There is only one outcome for each choice. When the outcomes are known their consequences are certain, the problem of decision is to compute the optimum outcome. Similarly, if there are more than one alternative they are evaluated by conducting cost studies of each alternative and then choosing the one which optimizes the utility of the resources. The condition of certainty exists in case of routine decisions such as allocation of resources for production, payment of wages and salary etc. There is relatively low and little ambiguity chance of making an impractical decision.

Risk:

A more common decision making condition is a state of risk. In such a condition, managers have knowledge about alternative course of actions but outcomes are associated with probability estimates. It is more difficult to predict future conditions without full information, so the outcome of an alternative can't be accurately determined. Therefore, managers can guess the probable outcomes on the basis of their experience, research and other available information. They can choose an alternative with highest expected outcome. However, such decisions are largely subjective as no decision criteria are fully reliable. Decision making under conditions of risk is accompanied by moderate ambiguity and chances of an impractical decision.

Uncertainty:

A state of uncertainty occurs when managers are unaware of the problem they face. They do not know all the alternatives, the risk associated with them or the likely consequences of each alternative. This uncertainty arises from the complexity and dynamism of contemporary organization and their environments. Managers have limited information to calculate the degree of risk , so statistical analysis is not possible. The condition of uncertainty arises when the organization introduces a new or innovative product or service; adopts new technology, selects new advertising program etc.

To make effective decision in uncertain conditions, managers must acquire as much as possible relevant information and approach the situation from a logical and rational perspective. Intuition, judgement and experience always play major roles in the decision making process. However, decision under uncertain conditions is the most ambiguous condition for managers and there is more possibility of error.

Tools For Decision Making

Quantitative tools are the mathematical and other scientific means for finding optimum solution to the problem. Many decision in the management are taken by quantitative means. These tools assist the manager to analyze the problems and develop alternative solutions. Under this technique, various elements of a problem and their inter-relationship are presented in the form of a model. The following are the common quantitative tools for decision making:

1. Linear Programming:

Linear programming is a mathematical tool for optimum combination of scarce resources and activities to achieve objectives. Under this tool, mathematical equations are employed to describe the systems in the form of linear relation between variables. It is appropriate when an objective must met within a set of constraints. It is extremely useful for maximizing profit and minimizing cost. There are alternative ways of combining resources to produce a number of outputs and therefore there nay be linear relationship between variables. These models help to determine the future values of certain variables affecting the outcome of objectives.

Linear programming models are used in a variety of situations in which numerous activities compete for limited resources. Managers must find the optimum way to allocate limited resources to achieve an objective within constraints.

2. Simulation:

Simulation represents a model to solve real life problems. Under this technique, related variables, and their inter-relationship are put into a system to find out the outcomes. Basically, computer programming is used to find out a set of output with the combination of different variables. The changes on combination of variable are made until an optimum output is obtained.

Simulations technique is more useful in varying complex situations characterized by diverse constraints and opportunities. It is a descriptive rather than perspective technique. This technique is used in decision making of large organizations that require more resources.

3. Payoff Matrix:

Payoff matrix is a mathematical tool for decision making. It provides a method of computing outcomes of various alternatives available to the manager. In payoff matrix, probability of different alternatives and their expected values are taken into consideration. Probability ranges from Zero (0) to one (1). Most of the probabilities that managers are based on subjective judgment, intuition, and historical data. The estimated value of an alternative course of an action is the sum of all possible values of outcomes from that action multiplied by their corresponding probabilities. The decision maker weighs are the expected value of all available alternatives and the highest expected value should be selected.

For Example, an entrepreneur is interested in investing RS. 5,00,000 in a new business, he identified three possible alternatives: computer assembling, television assembling and refrigerator assembling company. The value of each alternative depends on short run change in the economy. He decides to develop a payoff matrix on the basis of inflation rate. He estimates that the probability of high inflation is 40% and low inflation is 80%. He estimates the probable returns on each investment of both high and low inflation as follows:

The expected value (EV) of three alternative businesses is:

Computer Assembling :EV= 0,40 (-2,50,000)+0,80(12,50,000) = Rs.9,00,000

Television Assembling :EV= 0,40 (22,50,000)+0,80 (-3,75,000) = Rs.6,00,000

Refrigerator Assembling :EV= 0,40 (7,50,000)+0,80 (6,25,000) = Rs.8,00,000

In the above calculation the computer assembling company has the highest expected value so this business should be selected.

4. Decision Tree:

Decision tree is the graphical tool in which managers can study alternative solutions available. It is like a payoff matrix because alternatives are evaluated by calculating the expected value. However, it is most appropriate when a number of decisions are to be made in a sequence. It enables the manager to consider an alternative solution, assign financial value to them, estimate the probability of given outcome for each alternative, make comparisons and choose the best alternative. The following procedures are followed to solve problems through the decision tree model.

• Identify the problem by developing a decision tree diagram.
• Developing the course of action which is represented by a separate branch of decision tree.
• Assign a probability for an outcome of each course of action.
• Determine the financial result of each outcome.
• Calculate the net expected value of each outcome.

The alternative with highest net expected value (NEV) is selected.

5. Queuing Model:

Queuing model is used to analyze the cost of waiting line. This model is used to optimize the waiting lines in the organization so that better service can be provided to the customers. Queuing problem arises when the demand of the customers can not be perfectly matched by a set of well-defined service facilities. There is possibility of loss time, unused labor and excessive cost caused by waiting lines.

The main objective of queuing model is to achieve an optimal balance between the cost of increasing service and the amount of time due to shortage of services, they may get frustrated and the organization may lose the customers. This technique is appropriate in banks, public transport, gas and petrol pumps, hospitals, airports, cinema halls, department stores etc.

6. Game Theory:

Game theory is applied under the competitive environment. It was originally developed to predict the effect of one company's decision on competitors. This story intends to predict how a competitor will react with various activities that an organization undertakes such as change in price, promotion, introduction of new products etc. Therefore, the objective of every competitor in a business is to choose an action and frustrate the others to win the game.

The primary objective of game theory is to develop a rational procedure for selecting a strategy. In business, it is applied in a competitive situation where it is more difficult to assess the competitor's response. It develops a framework for analyzing decision making in competitive situation. It describes various phenomena in conflicting situation. It is highly sophisticated and systematic model that enables to select rational strategies for attaining goals. Generally, game theory is riskier to use in solving business problems due to the rapidly changing environment.

7. Accounting Tools:

In financial decision process accounting tools play important roles. Managers need to collect, analyze and interpret financial information and data. It is essential to evaluate financial strengths and weaknesses of the organization before taking a decision. These financial tools consist of break-even analysis, ratio analysis, standard costing, funds flow and cash flow analysis, budgeting etc.

Reference

(Poudyal S.R., Pradhan G.M., and Bhandari K.P. (2011), Principles of Management. Kathmandu: Asmita Books Publishers and Distributors (P) Ltd.)