Agile Planning Poker has a Tell

As an exercise, planning poker can be quite useful in instances where no prior method or process existed for estimating levels of effort. Problems arise when organizations don’t modify the process to suite the project, the composition of the team, or the organization.

The most common team composition for these these types of sizing efforts have involved technical areas – developers and UX designers – with less influence from strategists, instructional designers, quality assurance, and content developers. With a high degree for functional overlap, consensus on an estimated level of effort was easier to achieve.

As the estimating team begins to include more functional groups, the overlap decreases. This tends to increase the frequency of  back-and-forth between functional groups pressing for a different size (usually larger) based on their domain of expertise. This is good for group awareness of overall project scope, however, it can extend the time needed for consensus as individuals may feel the need to press for a larger size so as not to paint themselves into a commitment corner.

Additionally, when a more diverse set of functional groups are included in the estimation exercise, it become important to captured the size votes from the individual functional domains while driving the overall exercise based on the group consensus. Doing so means the organization can collect a more granular set of data useful for future sizing estimates by more accurately matching and comparing, for example, the technical vs support material vs. media development efforts between projects. This may also minimize the desire by some participants to press harder for their estimate, knowing that it will be captured somewhere.

Finally, when communicating estimates to clients or after the project has moved into active development, project managers can better unpack why a particular estimate was determined to be a particular size. While the overall project (or a component of the project) may have been given a score of 95 on a scale of 100, a manager can look back on the vote and see that the development effort dominated the vote whereas content editors may have voted a size estimate of 40. This might also influence how manager negotiate timelines for (internal and external) resource requirements.