A cost-effectiveness analysis is a simplified cost-benefit analysis where one assumes that all of the alternatives have either the same benefits or the same costs. The analysis is simplified because only benefits or costs need to be calculated, not both. In this analysis, the best alternative is the one with the greatest benefits or the lowest cost. This type of analysis is sometimes more feasible when costs or benefits are hard to measure or would be expensive to measure.
Incremental Value Analysis
Peter Keen (1981) proposed a tool that is appropriate with rapid prototyping. This tool examines alternatives, stimulates new ideas, and asks, "what if?". The process is based on value, rather than emphasizing costs. The incremental value analysis process involves five steps:
1. Establish the operational list of benefits that the DSS must achieve to be acceptable.
2. Establish the maximum cost that one is willing to pay to achieve the benefits.
3. Build and assess prototype Version 0
4. Establish cost and determine benefit threshold for Version 1
5. Build Version 1; monitor benefits and costs and evolve to Version N
The main advantages of the value analysis approach are that it is simple and easy to understand. The method attempts to reduce risk by requiring prototyping. Prototyping or staging can be difficult for a data warehouse project. If a corporate data model has been developed then a part of that model can be developed as a data mart. The method evaluates the DSS as an R&D effort rather than as a capital investment.