Fuzzy - Expert System for Cost Benefit Analysis of Enterprise Information Systems: A Framework

Enterprise Information Systems (EIS) are collections of hardware, software, data, people and procedures that work together to manage organizational information resources, ultimately enhancing decision making, and strategic advantage. One of the key issues in the acquisition and utilization of EIS is the determination of the value of investment in such systems. Traditional capital budgeting models such as NPV, IRR, payback period, and profitability index focus mainly on quantifiable variables. However, there are many intangible variables that make the use of entirely quantitative measures incomplete and less inclusive. The high level of impact of information systems (IS) on the entire organizational strategy and the information intensity of IS makes the use of such traditional methods less practicable. Attempts have been made to overcome these shortcomings by utilizing other techniques such as the real options model, goal programming model, knowledge value model and intelligent techniques. This paper proposes the adoption of a hybrid intelligent technique (fuzzy-expert system) in carrying out a cost benefit analysis of EIS investment. The study takes high cognizance of intangible variables and vagueness / imprecision in human group decision making that requires a good level of consensus.