Stacey matrix as decision tool for project management

Last updated on February 18, 2022

Agility is more and more present in business. Agile methods are now more widely used than the traditional approach in software development. The 2011 VersionOne survey named “State of Agile Survey” confirms that project management with Scrum is the most used approach in Agile projects. You may have had some success with Scrum yourself in a pilot project, or you may have now reached the stage where you still use Agility in the realization phase of your development projects. Proud of this new professional success, I find that human beings tend to repeat what has worked well without taking the time to take cognizance of the new situation that arises in front of them. The purpose of this post is not to list situations where Scrum applies. Rather, it wants to remind the reader what kind of problem one can solve with this tool.

Stacey’s Matrix

Ralph Stacey of the University of Hertfordshire has developed a matrix which he calls “The Stacey Matrix“. This matrix makes it possible to understand the degree of complexity of a situation according to the level of uncertainty and the level of agreement regarding the situation.

Stacey’s Matrix

The x-axis shows the level of uncertainty where, on the left, there is little uncertainty (close to certainty) while there will be more and more uncertainty as one moves away towards the law. On the Y axis, we will assess the level of agreement. The closer you get to the origin, the stronger the level of agreement, while the further you get from the origin, the more you disagree on a topic. We can add several themes on these axes.

For example, we can use this matrix in choosing the project management methodologies to be used for a project. Technologies will therefore come to furnish the X axis where the degree of uncertainty will allow us to locate us in the right place. As for the Y axis, during a project, it may represent the requirements. Depending on the level of agreement by the business world (i.e. your customers for whom the final product is intended) with their needs, we can then be on the Y axis.

At a simpler expression of the Stacey matrix, we find 4 states which are listed as follows:

    Known (simple): Everything is known

    Complicated: There are more known than unknown

    Complex: There are more unknowns than known

    Chaotique (anarchy): Very few elements known

In my experience, more or less well known needs and an unknown solution places me in the complex area of  Stacey’s matrix. In my opinion, this often represents the state of several early stage software development projects. The customer has a general idea of  their need but does not yet know what the final solution will look like. In this area of   complexity of the matrix, Scrum is an excellent tool for dealing with the unpredictable. Through its empirical approach, Scrum allows you to take small steps by delivering increments of the final solution to help deal with the unknown. The management style in this area is also prescribed by Scrum. Using leadership in the service of the team, ideas will emerge while increasing the level of communication in the team.

However, not all of your projects are as complex and do not require Agility. And it is this nuance that I see largely ignored. For example, if you are in a maintenance project, ask yourself if you are still in the same area of   complexity. If your maintenance customers have very specific needs that are independent of each other, you will be lower on the Y axis since the level of agreement will be higher. The impact of these requests on the product currently in production may be smaller. In other words, the requested technological change will be small and well understood, pushing us to the left on the X axis.