Econometric study is always an exciting area of research. We use a plenitude of qualitative and quantitative measurement methods and techniques here. Traditional econometric methods were applied to measure the business performance improvement in software development and maintenance projects. These methods were largely relying on the metrics restricted to the quantitative and qualitative aspects of code. When we apply the traditional methods, the key question will be surrounding the real value of knowledge and software engineering labor accumulated or realized in a code.
Various econometric measures on code are defect density per lines of code, application stability and performance per cycles of compilation etc. These are largely structural measures. The econometric approaches on the scope of code quality and quantity will be successful for linear labor patterns such as waterfall model of project delivery.
At the same time, when we analyze the project management paradigms such as agile, scrum, Personal Software Process (PSP), Team Software Process (TSP), we can see a larger share of non-linearity in their strategy and execution. Hence traditional methods will not be much handy in this regard. Hence we need to explore a stack of non-linear and code independent measures to evaluate and critically analyze agile and lean methodology based projects.
When we think of agile projects, the iterative cycles of code construction, verification, integration, end user validation etc will come to our mind. We can see that people, process, business and technology relevant values are imparted to the labor process here. Hence the econometric aspects of code will be influenced by the environmental factors such as people, process, business and technology. The design of these econometric measures should be able to encapsulate the dynamics of code creation, maintenance and rework in its totality. It will be the key challenge whether you are consciously attempting to measure the success of agile and lean initiatives in your software engineering delivery platforms.