In today’s complex and aggressive business environments, it is only an effective decision making that gives organizations an edge over their competitors. Since organizations continuously make decisions, managers should ensure that it is done scientifically so as to minimize the inherent risk of errors in the subjective approach to decision making. This work seeks to appraise the application of operations research techniques in the decision making processes of manufacturing companies. This study therefore sets to identify the various operations research tools applied in decision making, the benefits of using operations research and the various limitations to its application. The target population of this study is made up of the entire top, middle and lower management staff of the selected manufacturing companies; Innoson, Anammco and Juhel Nigeria Limited. Stratified sampling method was adopted so as to give a fair representation to the selected organizations in the ratio of 3:5:2 using the proportionality formular.(Q=A/N × n/1). The study obtained its data from both primary and secondary sources. The questionnaire was the major instrument of collecting data for the research. Interviews were also conducted to complement the information from the questionnaire. Data analysis was done through the use of tabular presentation, pie and bar charts. The five (5) formulated hypothesis were also tested for acceptance or rejection using the chi-square statistical technique. The findings indicates that linear programming, Network Analysis and decision trees are some of the operations research tools used in decision making and that the benefits enjoyed as a result of applying operations research to decision making justifies the expenditure incurred in that respect. The study also recommends that the use of operations research should be encouraged and sustained in view of the numerous benefits it offers to firms and that firms should embark on aggressive training of personnel to reduce resistance to its use.
Everyday, managers makes decisions that commit organizational resources. These decisions determine the survival, growth or even death of an organization. The decision making process is not always activated when a manager perceives a problem as most decisions are made to ensure the stability, continuity and expansion of good prospects and operating performance. (Akintoye and Oluwatosin, 2006; 387).The Process of decision making requires the analysis of alternative solutions and the identification and selection of the alternative that offers the best outcome.
Managers today especially in developing countries use exclusively experience, hunches and rule of thumb in their decision making process. This qualitative approach may be found useful and adequate in certain circumstances but inadequate in others. When the problem is repetitive and the data are quantifiable, we find greater scope for the application of the quantitative techniques to ensure rational and logical decisions.
Okeke (1996; 1) opines that in the qualitative approach to decision making, the manager relies on his personal intuition or past experience in solving similar problems. Such an Intuitive “feel” for the problem may be sufficient for making a decision. He however concluded that there are problems for which more quantitative approach is inevitable.
This quantitative approach that we mean here goes by so many names; Management science, operations research, Quantitative Management, Decision Sciences, Systems Analysis etc. Although attempts have been made by some writers to differentiate these terms, they are quite often used interchangeably, their unifying factor or common denominator being their utilization of the techniques of Mathematics, Engineering, Economics, Computer Science etc in finding solutions to organizational problems.
Operations Research is simply defined as the application of scientific methodology in making more explicit, more systematic and better decisions. (Litterer, 1978:171).Scientific methodology is defined as a process of or logical approach to developing models that explain and predict real-world behavior. (Dannenbring and starr, 1988:1).Thus operation research seeks to describe, understand and predict the behavior of complex systems of human beings and equipment (Stoner, 1982:186).
As the name implies, one can say that operations research means research on operations. Filley and House (1969:10) have noted that organizations and their component units carry on goal-oriented activities referred to as “operations” and that the systematic study leading to decisions as to which operations should be undertaken and how they should be tackled is termed “research”. What management scientists or operations researchers do is to observe decision making environment, try to identify, define and analyze problems, construct models which seek to solve these problems, choose those inputs of data required for a solution, find the optimal solution when it could be found and help in the implementation of the identified solution(Levin et al,1986:5).Operations research provides managers with quantitative basis for decision making and enhance their ability to make long range plans and develop broad strategy.
Operations research is approached in a spirit that demands that decision problems be properly defined, analyzed and solved in a conscious, rational, logical, systematic and scientific manner based on data, facts, information and logic (Loomba, 1978:25).The quantitative techniques inherent in management science are not to be regarded as an explicit formular to be uniformly applied to all types of situations. Rather, it is a style of management, which demands a conscious, systematic and scientific analysis and resolution of decision proba,1978:26-27).But the fact that the use of quantitative data constitutes the corner stone of operations research does not in any way preclude the use of qualitative analysis in arriving at optimal decisions. The quantitative approach, must build upon, be modified by and continually benefit from the experiences and creative insights of managers. The final stage in the decision making process, after all, is the exercise of judgment and in making this judgment, the decision taker has to take different factors-quantitative and qualitative into account. For example, there may be sudden change in government policy or of government itself, change of weather, technological advancement and so on. And this makes it very necessary for managers to involve qualitative approaches in decision making.
The use of operation research tools in decision making presents a lot of challenges to the modern day manager irrespective of the benefits that comes with it.
Mathematical models are applicable to only specific categories of problems since not all business related problems are amenable to Mathematical modeling or configuration. Issues such as motivation, leadership style, organizational politics etc cannot be modeled. (Akintoye and oluwatosin; 2006:336)
The insufficient number of qualified and experienced personnel who could effectively apply these operations research models to firm’s decision making presents another problem. There are few professionals who have acquired practical exposure in the application of operations research to decision making in firms.
Finally resistance to changes is another issue that confronts the manager in the use of operations research in decision making. The use of operations research often generates resistance from employees and management because its implementation usually introduces changes to the known convention within the organization. This fear of the unknown may inhibit objective implementation of the recommendations. (Akintoye and oluwatosin; 2006, 336).
The specific objectives which the study seeks to achieve are;
1) To determine the various operations research models used by organizations in decision making.
2) To identify the benefits derived from applying operations research models in decision making processes of firms.
3) To find out if the benefits derived from implementing operations research techniques in making decisions justifies the expenditure involved.
4) To determine the nature of the relationship existing between the use of operations research in decision making and the productivity levels of firms.
5) To identify problems which manufacturing firms encounter in the application of operations research to decision making?
This research study will seek to provide answers to the following research questions;
1) What are the various operations research models used by organizations in making decisions?
2) What benefits do organizations derive from the application of operations research models to decision making?
3) Does the benefit which accrues to firms by using operations research in decision making justify the expenditure involved?
4) What is the nature of the relationship between the use of operations research in decision making and the productivity levels in firms?
5) What are the problems encountered by manufacturing firms in applying operations research models in decision making?
The following hypotheses would be tested for acceptance or rejection;
1) HO1: Linear programming, Network Analysis and Decision tree are some of the operations research models used by firms in decision making.
Hi1: Linear programming, Network Analysis and Decision tree are not some of the operations research models used by firms in decision making.
2) Ho2: Cost reduction, increased productivity and efficiency are some benefits enjoyed by firms that apply operations research tools in decision making.
Hi2: Cost reduction, increased productivity and efficiency are not some of the benefits enjoyed by firms that apply operations research tools in decision making.
3) Ho3: The benefit that accrues to firms by using operations research in decision making justifies the expenditure incurred in implementing it.
Hi3: The benefits that accrue to firms by using operations research in decision making do not justify the expenditure incurred in implementing it.
4) Ho4: There is a positive linear relationship between the use of operations research in decision making and the productivity levels in firms.
Hi4: There is no positive linear relationship between the use of operations research in decision making and the productivity levels in firms.
5) Ho5: Employee resistance, lack of commitment and insufficient number of specialists are some limitations encountered in using operations research in decision making.
Hi5: Employee resistance, lack of commitment and insufficient number of specialist are not some of the limitations encountered in using operations research in decision making.
This study has both practical and Academic significance to the society. The basic significance of this study is that it focuses on a subject on which very little has actually been written on so far.
Though manufacturing companies have existed for decades, very few authors have really explored how operations research models could be applied to organizational decision making in manufacturing companies. In this light, this study would contribute in building a literature on operations research.
The study is on the appraisal of the application of operations research models to the decision making process of manufacturing companies. The study is limited to selected manufacturing companies in Enugu, south eastern Nigeria. Manufacturing companies are scattered in Enugu and it will be difficult to cover all of them given the constraints involved in such exercise.
The study will therefore concentrate on the following companies;
These companies were chosen because of their large market share and most importantly the use of the scientific method in their decision making process.
In addition to the above named organizations, the work will make general references to all manufacturing organizations as the need arises.
The basic limitations to this study are those that have to do with time, finance and the attitude of the respondents.
In spite of these limitations, the findings of this research will still be valid.
e) Productivity: This has to do with the rate at which a firm produces goods and the amount of goods produced compared with how much time, work and money is needed to produce them.
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