Computational Aspects of Business Management with Special Reference to Monte Carlo Simulation

Abstract

Business management is concerned with organizing and efficiently utilizing resources of a business, including people, in order to achieve required goals. One of the main aspects in this process is planning, which involves deciding operations of the future and consequently generating plans for action. Computational models, both theoretical and empirical, help in understanding and providing a framework for such a scenario. Statistics and probability can play an important role in empirical research as quantitative data is amenable for analysis. In business management, analysis of risk is crucial as there is uncertainty, vagueness, irregularity, and inconsistency. An alternative and improved approach to deterministic models is stochastic models like Monte Carlo simulations. There has been a considerable increase in application of this technique to business problems as it provides a stochastic approach and simulation process. In stochastic approach, we use random sampling to solve a problem statistically and in simulation, there is a representation of a problem using probability and random numbers. Monte Carlo simulation is used by professionals in fields like finance, portfolio management, project management, project appraisal, manufacturing, insurance and so on. It equips the decision-maker by providing a wide range of likely outcomes and their respective probabilities. This technique can be used to model projects which entail substantial amounts of funds and have financial implications in the future. The proposed chapter will deal with concepts of Monte Carlo simulation as applied to Business Management scenario. A few specific case studies will demonstrate its application and interpretation.