The evidence is here: Visual portfolio mapping delivers better decisions

More than 4 years ago Optimice approached University of Technology of Sydney with a proposition to see if the visualisation of interdependencies in a project portfolio could bring business value. We first heard about this at a Knowledge Management conference in Canberra, Australia, where Graham Durant Law had looked at it as a part of his PhD research. We wanted to take this even further into other industries and also prove that this actually led to better outcomes. Now we can finally tell you about the exciting findings.

The basic concept of mapping project interdepencies is quite simple. You draw a line between the projects to show the dependency.

Project Interdependency SimpleWhere it starts to get more complicated is when you add more projects and interdepencies. This is where social network mapping comes in. We believed that the core visualisation techniques drawn from the field of social network analysis would provide the best “cognitive fit”, i.e the optimal way to represent information for decision making. Therefore, we put the proposal to UTS to test how well the social network analysis visualisation technique actually works in a portfolio management setting.

The research led to an article in the International Journal of Project Management where we outlined the benefits of using social network visualisation techniques to show project interdependencies. This article also included qualitative evidence of the positive business outcomes the visualisation led to. However, what we really lacked was some more tangible evidence.

Dr Cathrine Killen from UTS then developed an experiment that would allow us to compare the visual map with two traditional techniques for showing project interdependencies. In 264 separate experiments Dr Killen gave each participant exactly the same challenge:

In a portfolio of 26 projects with a total value of $16m, please cut 10% of the budget by removing one or more projects taking into consideration the strategic fit and flow-on effects.

The 264 participants were randomly given one of the following three different representations of the portfolio to work with:

Comparison of techniques
  • Map shows the project interdependencies as a social network map. Each project is represented as a circle, color-coded by ‘strategic fit’, and sized by budget
  • List shows the same information, but in a tabular form
  • Matrix also shows that same information, but as a matrix
The research found that the use of the map was correlated with the highest levels of decision quality. Not just to a small degree, but nearly 3 times better:

“...the percentage of research participants that made the optimal decision was highest for the group that used the network mapping VPM tool, with 28.6 percent of the participants achieving an optimal decision in the time allowed. Just over ten and eleven percent of the decisions made using the other tools, the dependency matrix and the Tabular list were optimal.

The management of interdependencies is an acknowledged area of weakness for project portfolio management. If your organisation’s project portfolio runs into the millions, if not billions, of dollars you will appreciate just how much value you can gain from choosing the best techniques to understand interdependencies. 

In these days where the time-poor executives need to make critical decisions that can have significant flow-on effects across the portfolio, we need to make sure that we provide them with the best possible foundation to make informed decisions. This is exactly what makes the visual portfolio map stand out from the rest.

For those of us who spend our lives mapping networks it is also a bonus to get empirical evidence that visualisation directly and positively impacts business outcomes.

You find a link to the Dr Catherine Killen’s paper which will be presented at the Decision Sciences Institute’s Annual Conference in Baltimore, Maryland in November 2013 here. There you can also find an interactive version of the portfolio map included in the research.