Controlled Sub Process Vs Uncontrolled Sub Process

Sub processes are components of a larger defined process. For example, a typical development process may be defined in terms of sub processes such as requirements development, design, build, review and test. The sub processes themselves may be further decomposed into other sub processes and process elements. Measurable parameters are defined for these sub processes to analyse the performance of the sub processes. These sub processes are further studied to identify the critical sub processes which are influencing the process performance objectives i.e. PPO. Measurable objectives are set for the critical sub process measures also. PPOs are derived fromBusiness Objectives (BOs).

In the above paragraph, there is a linkage established starting from sub process to BOs. In fact in an organization, defining starts from BO to critical sub process. i.e. First BOs are set, then PPOs are defined, later objectives for sub process and critical sub process are set. Business Objectives (BOs) should be traceable from top level to bottom level. For a pictorial illustration of this traceability please refer Traceability of Objectives from Business level to Execution Level

Predictions models are built upon the critical sub process using the historical data in the organization. Those entire sub processes need not be used for building prediction models, instead only those sub processes which are critically influencing PPO, need to be used. For more information on Prediction models please refer Process Performance Models (PPM) – Some Guidelines

The critical sub processes parameters can be of 2 types- Controllable parameters and Uncontrollable Parameters

  • Uncontrollable parameters    – Parameters which cannot be quantitatively controlled.
  • Controllable Parameters       – Parameters which can be quantitatively controlled.

Controllable Parameters again can be classified in to two- Statistically controllable and statistically uncontrollable.

  • Statistically uncontrollable parameters- Parameters which cannot be statistically controlled, but can be controlled quantitatively.Quantitative management shall be performed using any of the seven basic tools of quality – Cause and Effect Diagram, Scatter Diagram, Histogram, Pareto Diagram, Flow diagram, Check sheets and Control Charts.
  • Statistically controllable parameters- Parameters which can be statistically monitored and controlled using the planned statistical methods.

For example, consider a project A. The project’s requirements are driven by the customer. The PPO of project ‘A’ is defined to reduce the User Acceptance Testing defects, to 0.05 defects/Kilo Lines of Code. The Sub processes identified are requirement analysis, design, implementation, review and testing. Among these, the critical sub processes which are correlated to the objective are found to be requirement analysis, implementation and review. The measurable parameters for these processes are also defined. Let it be Requirement volatility Index, coding speed and % code review coverage respectively for requirement analysis, implementation and review. Among these parameters, Requirement volatility Index can be measured only and not controlled since requirements are undergoing changes at the discretion of customer. Coding speed is a parameter which can be statistically controlled. Statistical Process control, SPC is applied on this critical sub process. ‘% code review coverage’ is a parameter which can be controlled only, and not statistically controlled since a single value is generated as the output of this metric in a single project, assume no sub modules in this project.

In short,

  • Requirement volatility Index            – An uncontrollable parameter
  • Coding speed                               – A statistically controllable parameter
  • % code review coverage                – A controllable parameter, but not statistically.

Based on the metrics analysis, corrective actions are taken in order to ensure that capabilities of the selected sub process are meeting the specified objective. Read more about the high maturity analysis in CMMI High Maturity in Short..Results of metrics analysis are maintained and communicated to relevant stakeholders