Without measurement there is no control and without any control there is no improvement

Measurement data tells the quantitative nature of activities.  With data we are actually doing a hypothetical judgement. Say for example, in a software industry the effort consumed for a task ‘A’ is 50 Person Days (PDs) while the estimate for the same was 35 PDs only ( Assume there was no schedule slippage). This calls for an analysis. Suppose the reasons identified were related to high complexity of the source code which led to more bugs in the system. The complexity analysis of source code, bug analysis etc. also revealed the same. So here in this scenario, believing in data, we interfere that live complexity analysis should have been taken inside projects, rather than at the end. This would have helped to refactor the code or plan for a focused review or a focused testing initially itself!!

Now let us just have a rewind of the actual process involved in the project…

Case 1   : The tool used for measuring complexity was not calibrated and it had some error with it showing an incorrect value!!

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