Multiple Linear Regression Approach for Strategic Decisions on Industrial Productivity under Limited Available Budget

Abstract

Proper planning and improved productivity is highly desired in industrial settings to optimize the available resources when there is limited resources and to control excessive spending in time of surplus.  Productivity is achievable by good levels of Materials, Time and Labor inputs which needs to be measured scientifically in order to maintain long run profit. This study explored processing data and incorporated Statistical Package for Social Science (SPSS) to find the relationship and predict the response of the available budget with the inputs of Materials, Time and Labor using Olam Cocoa Processing Industry, Nigeria as case study. The analyses were done using Multiple Linear Regression Model developed (i.e. ), it was discovered that the inputs of the selected strategic decisions  collectively affected the response of the available budget with F-value of 88.48 but each of them cannot reduce or increase the amount of budget except for manpower which has 0.069 or 93.1 % significant effect on the available budget. Also, Coefficient of determination established a strong fitness of the relationship between the strategic decisions and the available budget with the value of 0.974 (or 97.4 %). It is recommended that the project manager should subject his decisions making into scientific measures rather than brainstorming so as to increase productivity in the company.