The world of project portfolio management (PPM) has changed significantly over the years. More specifically, since the early 2000’s, we’ve seen the emergence of new technologies and innovative organizational strategies take project management to an entirely new level—setting new rules of engagement to help organizations run their projects more smoothly and efficiently.
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These advancements have unquestionably defined what we consider to be PPM today as well as where we see this field moving in the future. But what exactly were these advancements? What role have they played in influencing how we approach project management today?
In this two-part article series, we will answer these questions by looking at six PPM trends that emerged in the 2010’s and, since then, have become adopted as de facto project management best practices.
1. Scaled Agile
Since the Agile Manifesto was first published in 2001, it has become a cornerstone of cross-functional and highly collaborative project management: initially revolving around software development and eventually making its way into other business areas where more adaptive project management techniques—as opposed to traditional waterfall methods—were quickly becoming necessary.
It wasn’t until the early 2010’s, however, that companies began to see the promise of Agile as a potentially broader, organization-wide construct that could be successfully applied beyond individual teams.
This was further fuelled by the development of the Scaled Agile Framework (SAFe), defined by Wikipedia as a set of organization and workflow patterns intended to guide enterprises in scaling Lean and Agile practices—adapted to organizations of any size and at varying levels of commitment to Agile methodologies.
SAFe, along with other methodologies focused on solving the problem of scaling Agile methodologies beyond a single team—most notably, large-scale Scrum (LeSS), disciplined Agile delivery (DAD), and Nexus—was aimed at providing a “big picture” view of how work flows through teams and across organizations. At Planisware, we’ve seen a number of our customers, across all industries and categories, experiment with SAFe to increase the effectiveness of their product development and decision-making processes.
2. Artificial Intelligence (AI)
It’s nearly impossible to talk about innovation today without referencing artificial intelligence (AI) and its impact on the broader business environment in some way. To think how much it has advanced over the last decade—as well as just how much people talk about it, even when they don’t really know what AI is at its very core—is truly mind boggling. It is, without any doubt, the biggest tech super-trend of the last decade; its newfound application to the world of project management is no exception to this rule.
The combination of hardware advancements (i.e. more memory, greater processing power), the rise of big data, and the evolution of machine learning algorithms based on neural networks (aka, “deep learning”) has made it possible for technology to harness the power of data to provide actionable insights and automated processes that had only been the thing of fantasy or conjecture until very recently.
This holds a tremendous amount of promise for the world of PPM. As we all know, many projects today typically sit atop large datasets of structured information. Until recently, to make sense of it all, data scientists had to manually “connect the dots” between all sorts of complex variables and dependencies. Not only is this tedious, but it’s also quite time-consuming.
That’s just one of many reasons why we developed our AI-powered Planisware Predictive Analysis solution, in an effort to help our customers quickly and easily spot outliers and data quality issues within datasets or, as Jean-Philippe Castells, IT Director at UCB, one of the world’s largest pharma companies, puts it, “It’s as though the defects simply jump out at your face!”
Similarly, we’ve woven AI into Planisware Predictive Estimation as well, to help our customers discover the elements that influence any given situation (“drivers”) behind estimating trends and data points in order to better understand what’s really driving project activities. This, in turn, makes it easier to predict project costs, timelines, and resource levels as well as help leaders build stronger business cases around those projects.
“Usually the best ideas don’t come from us but from our user base. We are still in the early stages and continue to explore the benefits of using machine learning with our customers. We provide the cool technology, but it’s our customers who show us what can really be done with it.”
– Pierre Demonsant, Planisware CEO
3. Advanced portfolio optimization
Let’s start with a really simple history lesson:
● 1990’s: Businesses discovered the importance of projects.
● 2000’s: Businesses then became aware of the importance of project portfolios.
● 2010’s: Businesses devised advanced portfolio optimization techniques to extract the greatest amount of value out of project portfolios.
Here’s why this is important. Very few organizations have the time or resources to tackle every potential project that rises to the surface, therefore requiring them to develop criteria to determine which projects warrant getting the “green light.” Ideally, these are the projects that provide organizations with the greatest amount of long-term value.
One such portfolio optimization technique is the Efficient Frontier, which allows organizations to identify, from among a set of potential projects, what the ideal portfolio or set of projects would be for driving maximum value for the organization.
Another useful technique is the Waterline Analysis, where you take all potential projects and score them based on what’s more important to your organization—whether that criteria is based on strategic priorities, budgets, or other factors is entirely up to you.
Then, you order the projects from high to low, adding projects to your portfolio, from the top down, until you hit your (budget or resource) limit, aka your “waterline.” All projects that didn’t make the initial cut go below this line; however, this doesn’t mean those projects are dead in the water.
Quite to the contrary, you can make trade-offs between projects above and below the waterline. For example, you could choose to replace one larger project above the line with multiple smaller projects below the line, only if their combined score is higher than the larger one’s on its own.