What happens when data falls outside valid range of PPM ?

PPMs are valid within the data used or building them. We cannot extrapolate the data for prediction. Now we use these PPMs to check the probability of confidence in achieving the targets. That is, we are simulating subprocess parameters which could be outside the valid range of PPM. In that case, how can we expect the PPM to give a convincing result..?

Let me illustrate it with an example .

I have made a productivity PPM, such as Xs are coding speed, expertise index, requirements stability index and Y is the productivity. The data comes from current performance baselines of the organization (stable process). In the PPM, adjusted R-sq factor, VIF, individual correlation factor, everything as required itself. While performed simulation to check, the probability ‘to achieve above the mean of productivity PPB’, >50% observed.

Organizational PPO is to improve productivity from 30 LOC/PD to 40 LOC/PD though some improvements identified in coding process so that increase in coding speed will lead to increase in productivity. Suppose current PPB of coding speed is 25 to 45 LOC/Hr and the increased expected range is 35 to 55 LOC/Hr (proven through some piloting/validation). Now project A want to use this PPM for productivity. Here actually the subprocess performance data is outside the stable limits/outside the valid range of PPM. In such a scenario, the project team cannot use the previous PPM at all. So what is the use of organizational PPM in that case..?

To summarize, if PPO is targeted higher to current PPB and to achieve the same, organization comes up with improvement initiatives with an improved rage on subprocess limits (outside to the valid range), then definitely, the previously defined PPM cannot be used. Or rather in such scenario, organization should come up with a calibrated ppm too..

For Productivity PPM, Code Review Effectiveness (CRE) is a sub process Parameter. CRE, itself is a dependent parameter and hence a sub PPM is built with CRE as the predictor. So while using Productivity PPM, the process shall be composed with CRE PPM first and then the expected range of CRE based on the simulated values shall be put in Productivity PPM.










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