As I have been going deeper into aspects of data science, in general, I am starting to believe that measuring software developer productivity seems to be a machine learning problem and could be solved using logistic regression algorithms. Following can be steps in creating a model that could be used to predict whether a software developer is productive or not:
Following is how the response would look like, given a new data set is fed:
Based on organization baseline, one could than choose a threshold based on which developer could be called as productive or not. For example, let’s say in case of your organization namely ABC, in those cases where there is 60% or more likelihood that developer is productive, only those developers would be termed as productive.
This is just a thought. I am preparing a test data and see if above solution approach could work in real world scenarios and help solve the problem related with predicting software developers productivity. In the meantime, please share your opinion on whether I am on right track.
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