The Need to Develop a Deep Understanding of PPM

Portfolio Management practitioners need to thoroughly understand the implications of various portfolio management practices and disciplines. I read an article last year discussing the misapplications of Lean principles. In contrast to other companies, Toyota’s success with the Toyota Production System is rooted in a deep understanding of the principles and theories so that they can adapt the principles in new situations. Unfortunately, wannabe Lean practitioners (or Six Sigma practitioners, or Theory of Constraints practitioners, etc.) may barely understand the basic theory and principles (but completely lack a deep understanding) and end up misapplying the methods or fixate on tools. The end result is that the methodology is criticized as not working well.

I think we could make a similar case for portfolio management. People commonly talk about various tools such as prioritization without fully realizing the cultural change and governance required or the breadth of influence portfolio management can have on an organization. When well executed, portfolio management can touch many sectors of business not limited to: finance, sales and marketing, engineering, information technology, and operations. Walking in sync with the various functions to make better decisions is a large part of what portfolio management is about. When people fixate on portfolio mechanics, or worse yet, on portfolio software, the whole organization may miss the boat.

With any kind of management discipline or quality improvement methodology, having a deep understanding of the principles and theories is very important in order to best apply the principles to a given situation. One person likened this to teaching someone how to drive a car; there are standards and rules to follow when driving a car under normal circumstances, but during unusual circumstances, an expert driver may adjust the way he/she drives in order to accommodate the conditions. A similar view could hold true with portfolio management—the application depends on a deeper understanding of the methodology. Unfortunately, people are often too quick to develop a deeper understanding and rush into applying the tools. Some time later without realizing the intended benefits, the methodology is blamed rather than the persons who improperly implemented it.

Bubble Charts and Normalization

Bubble charts are common place in portfolio management processes. Without a designated portfolio management tool, I have designed bubble charts by hand using Excel and PowerPoint. To determine a ‘value’, we use our prioritization value scores and compare that among projects. We have risk scores as part of our prioritization criteria that drive the ‘risk’ portion of our bubble charts. The challenge in the past was how to interpret a score. Is a score of 500 good or bad?  Since my organization was experimenting with a new prioritization process, we didn’t know what was good or bad. Therefore, I made the decision to normalize the scores so that we could fairly compare good or bad projects within the portfolio rather than try to determine a threshold for ‘good’ projects. This has been helpful in identifying which projects drive more overall value to the organization compared to other current projects in the portfolio. The downside of this however, is that you are always going to have a few projects that look bad. Until now, I had been normalizing only among current projects in the portfolio, yet it suddenly dawned on me this morning, that I should also normalize among all projects, past and current in order to understand whether we get more value now than in the past.

One advantage of a bubble chart is to locate those projects that are higher value and lower risk and ask the question, “how can we get more of these types of projects in the portfolio?” Likewise with the lower value higher risk projects, we should ask how to avoid those types of projects. By normalizing with respect to past and current projects, we will see whether or not the projects are moving toward the higher value lower risk quadrant.