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Estimation has always been one of the riskiest aspects of project or program planning. This is not because estimators are regularly unqualified or poorly informed -- it is primarily because of the large and growing number of complexities and dependencies that must be factored into software project estimates. Inevitably, as software projects, software products, and IT environments all become more and more complex, so, too, does the task of estimating what they will cost and how long they will take. To compound the challenge, established parameters that form the basis for many estimation techniques are not as universally applicable, or as straightforward to calculate, as they once were. Many estimators are thus left searching for methods that can yield more accurate results.
In this, Part 1 of a two-part article, I'll examine approaches, techniques, models, and tools that have gained momentum and support among estimation experts, as well as some intriguing innovations that seem to have bright futures. In Part 2 I will discuss different estimation scenarios, what methods are best under what circumstances, and how to most efficaciously apply them.
Why we estimate
We human beings tend to estimate constantly in our everyday lives. We estimate how long something will take, how much something will cost, how many calories are in that dessert, and so on and on. Estimation is just as vitally important to an organization, as its economic viability depends in great part on the quality of the decisions made by its executives. Which, in turn, are driven to a large if not a primary extent by estimates. Business decision-makers estimate for reasons like: * Budgeting. Budgeting is not only about how to spend cash sitting in a bank account, but also about how to strategically allocate available and future resources for the greatest benefit to the organization. Some of the cash you're planning to spend may not yet be readily available; and, indeed, may never materialize --