Consider, for a moment, a cautionary tale of two organizations: Organization A and Organization B. Each organization takes a significantly different approach to delivering the project portfolio management (PPM) capability.
Organization A has a relatively immature approach to project portfolio management and performs annual planning on a, well, annual basis. Each business unit compiles a list of project requests which are submitted to a central repository. Months of back channel negotiations and positioning ensue. At the end of the process, the organization has a list of approved initiatives for the next fiscal year…which may then be summarily ignored in favor of last minute project requests thrown out by the business. This is what I would classify as a typical “pull” approach to PPM, where each group submits a request to pull the project through the approval cycle and into execution.
Organization B, on the other hand, takes a different approach to portfolio execution and starts a bit farther back in the value chain with an exercise in defining what organizational performance actually means. This is broken down into strategic programs comprised of projects that are identified by the program management structure. This is more of a push model where the PMO organization is responsible for identifying projects and pushing them into the portfolio. If we apply this to the traditional v-model validation concept, we would end up with something like the graphic below where the traditional PPM measures actually fall at the lowest level, i.e. the “Execution Plan.”
Where do these goals come from? These days, those goals are increasingly being driven by gains in the field of analytics. As analytics platforms mature and the volume of data generated by the Internet of Things expands, analytics are expected to drive ever more decisions as to what projects need to be executed and where capital should be prioritized. Are assets providing the expected return? Is equipment performing as it should? Increasingly, analytics will drive these assessments.
Once gaps are identified, i.e. once we identify reality is not performing according to specifications, what is left but to charter an intervention in the form of a project? Now, however, the project is not driven by a request or saddled by the lack of an ability to track benefits. The project is born of analytics and will support a specific measurable goal.
This then becomes the key indicator for the maturity of a PPM system….not how many strategic drivers are leveraged to assess projects, or how structured the process is. Instead, the single indicator that will drive PPM maturity into the future is how much data, or situational awareness at the highest level, is actually being used to drive the project identification process.