The Maturity Curve of Portfolio Analytics—What Are You Ready to Unlock?

I’m back from vacation and have been thinking about how the type of analysis we can do is closely tied to two things: the quality of our inputs and the technology we have to run our models.

The result is the attached diagram. At the top, we have project input data. At the bottom, the types of analytics we can perform. On the left side, we start with the basics, and as we build maturity in portfolio management, we move right—unlocking more advanced and valuable analyses.

If we only have project timelines and PTRS, we can create launch charts and assess pipeline volume per phase. With access to simulation, we can generate distributions that let us answer questions like Will we meet our launch targets? We can also put a likelihood on that answer.

Next, if we include cost inputs, we can start budgeting at both project and portfolio levels. Simulation again expands the view—offering cost distributions that let us quantify the probability that costs will be under a certain threshold.

Then comes sales forecasts and cost of sales. Often built in Excel and imported into the model, these enable us to calculate financial metrics, prioritize the portfolio, and understand what it will cost to operate.

With simulation, we go even further: generating distributions for NPV, visualizing expected gains and losses, and exposing uncertainty—even if PTRS is the only risk parameter.

To the right, I’ve added potential areas for future exploration. Each one adds another lens for decision-making, but they all require simulation to be effective.

I am curious to hear your thoughts—does this progression resonate with how analytics and capabilities evolve in your organization? Let’s discuss in the comments!