In this second part of a two-part series, Mario Moreira explores the back-end disciplines of a lifecycle that establishes an ALM framework centering on customer value. If your organization has adopted agile and you are looking at building your ALM framework, consider an infrastructure and tooling that will help you establish and build customer value throughout the lifecycle.

No matter how well we plan and execute software development, defects are generated and can escape to the customers. Failure to quickly resolve software problems leads to negative consequences for our customers and increases internal business costs. A quick deterministic
method to prioritize problems and implement their solution helps to reduce cycle time and costs. Achieving this goal requires several steps. The first is to determine a model that links problem resolution performance to institutional variables and problem characteristics. Statistical Design of
Experiments (DOE) is a tool that provides data requirements for estimating the impacts of these variables on problem resolution. Once data has been gathered, the results of statistical analysis can be input into a mathematical optimization model to guide the organization.
This paper describes such an analysis.