Variances In Personnel Can Change Productivity By a Factor of 10

April 20, 2010 · Filed Under Software Estimating  - 0 Comment(s)

I got a question today from someone defining best practices on productivity based on personnel.  They wanted to know what the differences might be based on their capabilities.  It was easy to perform such a trade study in SEER-SEM for the overall productivity or just a partial. 

Knowledge bases normally set these so no work is required unless there are known or anticipated specific circumstances.  But this trade study took seconds.  Here is part of the answer provided:

SEER people-specific parameters include:

 Analyst Capabilities: Capabilities of the team  to function (not just the individuals) and the impacts of management, motivation, etc. on that team

Analyst Application Experience:  Average experience of the software team that will work on the project with the overall domain (such as finance or command & control)

Programmer Capabilities: Capabilities of the team  to function (not just the individuals) and the impacts of management, motivation, etc. on that team

Programmers Language Experience:  Average team experience with the programming language(s) that will be used in this implementation activity

Development System Experience: Average team experience with the computers, operating systems and other items that will be used to develop the software

Target System Experience:  Average team experience with the target computers, operating systems and other items that will be used to execute the software in the end (target) environment

Practices & Methods Experience:  Average team experience with the development processes, methods, standards and procedures used on this project

 Knowledge bases set these in normal ranges so individual  ratings are not required.  And if you do know or want to do tradeoffs: One of the important things is to rate the team, not just the individuals, and how they will perform together. And of course the range allows the expressions of your uncertainty up-front.

 Looking at the full range, from the worst of the worst to the best of the best, can provide a 10 to 1 variance in cost.

Also, here is a chart showing how those parameters increase costs when they are at the worst case.

 


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