Effective decision analysis requires that the business analyst/project manager understand:
- The values, goals and objectives that are relevant to the decision problem
- The nature of the decision that must be made
- The areas of uncertainty that affect the decision
- And the consequences of each possible decision
Uncertainty may exist because of:
- Unknown factors that are relevant to the decision problem
- There are too many possible interrelated factors to consider
- Conflicting perspectives on a situation
- Tradeoffs between the different available options
A common method of dealing with uncertainty in decision problems is to calculate the expected value of outcomes. This involves estimating the percentage chance of each outcome occurring and them multiplying the numeric value associated with that outcome by that percentage.
Decision analysis generally requires that the business analyst/project manager to use some form of mathematical model to assess possible financial outcomes. Commonly used financial valuation techniques include:
- Discounted Cash Flow: future value on a specific data
- Net Present Value: future view of costs and benefits converted to today’s value
- Internal Rate of Return: the interest rate (or discount) when the net present value is equal to zero
- Average Rate of Return: estimate of rate of return on an investment
- Pay Back Period: the amount of time it takes for an investment to pay for itself
- Cost-Benefit Analysis: quantification of costs and benefits for a proposed new solution
Not all decision outcomes can be expressed in financial terms. However, effective decision analysis still requires that outcomes be directly comparable. In some cases, there will be a metric that is applicable (defects per thousand, percentage uptime, customer satisfaction rating). When there is not, a relative scoring of possible outcomes will have to be determined.
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