If you were to ask a group of people at random why estimation fails, you would most likely hear that it is because the person that did the estimating simply estimated incorrectly. The reality of the business world is that there is much more to it than that. Of course, intelligent guesswork is part of estimation, but estimation also requires critical thinking and judgement. Dan Galorath, business expert, recognizes the importance of estimation beyond mere guessing: Estimation is a core process that can be a root cause of project success or failure. A paper by Andy Nolan of Rolls Royce and published by INCOSE (I can’t locate the original paper on the web) identifies the 10 reasons for failure of estimation. He also identified the allocation of estimation error. 19% being attribute for estimation failure; due to tools, 37% related to process issues, and 44% related to behavior issues. Based on a Nolan’s paper, Galorath has compiled the 10 reasons Nolan puts forth for failure of estimation.
- Scope creep
- Poor input to estimate
- Failure to clearly define the initial scope
- Unrealistic expectations and assumptions
- Failure to declare, track and reduce risk and uncertainties
- Lack of internal peer review
- Lack of estimation experience
- Failure to consider environmental factors
- Failure in the estimation tool/process
- Lack of estimation process/technique
Scope creep is perhaps the most common reason for estimation failure. This can occur for many reasons, but the article argues it is most likely because of a lack of defined scope and/or a failure to track or declare changes. Poor input can also negative influence scope. When an estimate is left open, risk and scope variation will surely find their way in. Furthermore, if you fail to clearly define the scope entirely, there is a high chance of argument over what is in and what is out. Another common, and somewhat expected, reason for failure of estimation is the existence of unrealistic expectations. Setting lofty goals is not necessarily a bad thing, but setting estimations that mirror what you want instead of what is likely is. Also, if you fail to point out uncertainties from the get-go, you become more vulnerable to risk than you need to be. Other “failures” that will lead to estimation failures include the failure to consider outside influences as well as failure to select the correct tool for the job. Most of these failures involve being overzealous and moving ahead too quickly, so be sure that you have everything in order before you start estimating. In addition to minor failures, lacking in certain areas will surely cause trouble. A lack of internal peer review means a lack of sharing experience. Since lacking in estimation experience is reason Nolan gives for estimation failure, taking the time to conducting reviews seems like a no-brainer. Finally, if you are lacking in estimation technique—meaning you fail to “apply a systematic estimation tool, method or process”—you are playing a dangerous game. Estimation is truly about more than guessing and hoping for the best, and following Nolan’s steps as Galorath suggests will set you up for success rather than failure.