Selection of Estimation Approach
The evidence on differences in estimation accuracy of different estimation approaches and models suggest that there is no “best approach” and that the relative accuracy of one approach or model in comparison to another depends strongly on the context . This implies that different organizations benefit from different estimation approaches. Findings, summarized in, that may support the selection of estimation approach based on the expected accuracy of an approach include:
- Expert estimation is on average at least as accurate as model-based effort estimation. In particular, situations with unstable relationships and information of high importance not included in the model may suggest use of expert estimation. This assumes, of course, that experts with relevant experience are available.
- Formal estimation models not tailored to a particular organization’s own context, may be very inaccurate. Use of own historical data is consequently crucial if one cannot be sure that the estimation model’s core relationships (e.g., formula parameters) are based on similar project contexts.
- Formal estimation models may be particularly useful in situations where the model is tailored to the organization’s context (either through use of own historical data or that the model is derived from similar projects and contexts), and/or it is likely that the experts’ estimates will be subject to a strong degree of wishful thinking.
The most robust finding, in many forecasting domains, is that combination of estimates from independent sources, preferable applying different approaches, will on average improve the estimation accuracy.
In addition, other factors such as ease of understanding and communicating the results of an approach, ease of use of an approach, cost of introduction of an approach should be considered in a selection process.
Read more about this topic: Software Development Effort Estimation
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