Barriors to Adopting Estimation Technology & Applications
A reader requested I chime in on The biggest barriers I see to adopting estimation technologies and tools. So here goes the first draft.
- Not Invented Here: Some people think that their environment is so unique that it cant be estimated… or that estimation applications like SEER can’t handle their unique scenarios. I have never seen a case where this was true once the organization tried. Or sometimes an expert has their own spreadsheet and they don’t want to let go of that control.
- Don’t Want To Know: Sometimes the answers from estimation technology are longer or more costly than stakeholders want to hear.
- Scared That Management Will Beat Them With The Numbers: The basic reason people don’t like to estimate is because someone will be there to tell them if they are wrong. This issue points to a needed culture change.
- If we have an estimate our people won’t work as hard: This is one of the worst reasons of all. Management applying unobtainable deadlines and trying to “motivate” developers to work to these. Results from such death marches are low morale, failure to achieve goals, and overall dysfunctional projects.
- Fear That Other Immature Processes Can’t Support Estimating; Having an achievable plan is a keystone to mature software development. Yet some organizations think they are not organized enough to even develop a plan.
- Disbelief That Software Can Be Estimated and Planned: Chaotic developments and changing requirements make some organizations believe it is not possible to estimate.
- Perceived Lack of Time To Spend On Estimating: Steven Covey calls this sharpening the saw… taking the time to improve the entire process. Estimation can be a complex task. Parametric estimating can speed it by up to 95% compared to manual (bottoms up) but still there is work involved.
- Belief That You Cant Estimate Until All Requirements Are Known: If we have “all” the information it is no longer estimating, it is accounting. Estimates must consider risks, likely scenarios and things that may go wrong. They need to size before all requirements are known. Applications like SEER provide significant support for estimating within uncertainty.
- Political Considerations: An estimate may be the last thing management wants. Schedule, cost, quality may all be dictated by contract or politics. Never mind that these may be impossible.
- Manual Estimation may Have Yielded Poor Results: There are two phenomenon I see regularly in estimating. 1) gross underestimate based on technical optimism and 2) overestimation to ensure the estimator doesn’t overrun. Each of these has mitigation approaches. And applications like SEER provide a framework for such mitigation.
I am sure there are a number of others… So this list will grow.
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