6 Ways Project Teams Get Statistics Wrong

PMO's can get statistics wrong

Statistics play an important role in project management. They can justify expenses that are higher than previous projects. They might highlight a problem on the horizon that the organization hasn’t faced before. But project teams sometimes employ statistics in ways that are ineffective. To ensure your data makes the most compelling case possible, consider these six ways project teams get statistics wrong.

PMO's can get statistics wrong

1 – Too little context. Statistics can be powerful tools, but only if your audience understands them. One common mistake PMP®s make is providing too little context to help frame their statistics and make them more relevant to stakeholders. Did the study include participants in your specific industry? Were the survey ‘s respondent’s senior-level leaders? Technical workers? End users? Your audience will get a fuller understanding when they know how the data came together.

2 – Data is either too broad or too granular. There are times when highly detailed or very wide-ranging statistics are useful. However, PMP®s aren’t always adept at identifying which data flavor will resonate with the various stakeholders. Before a statistic is presented, the Project Team should first examine how their audience is likely to view their connection to the project. If you’re providing statistics to the leadership team, will they expect to see high-level information or do they prefer to drill down into the details? Are end users interested in the minutia of the project or have they been happy with overviews? Tailoring statistics to your audience is a good way to make your case more compelling (and understandable).

3 – Using outdated data. Information doesn’t always age well, and statistics based on data that has outlived its usefulness could actually become a liability for the project team. Examples include technology, legislation, and healthcare—these issues change so quickly that data doesn’t need to be terribly old to be outdated. Imagine how irrelevant a statistic about mobile phone technology would be if the underlying data was just five years old. The entire smartphone industry has shifted in that time, and there’s plenty of newer data that would be much more compelling.

4 – Assuming statistics don’t matter. With the scope of responsibilities resting within the project team, it is sometimes easy to conclude that statistics are only of interest to those people who are actively executing the project. That’s often not the case, especially in today’s increasingly data-rich environment. Stakeholders and sponsors likely leverage statistics in other areas of their jobs, and the inclusion of relevant stats during project presentations can help them get a better overall view of what’s going on.

5 – Presenting data that’s too unbelievable. Dropping the jaws of your audience isn’t always a good thing. In fact, if statistics are too outlandish—they don’t reflect the environment most familiar to your audience or they demonstrate an experience opposite of what your team presented previously—stakeholders may begin to mistrust you in other areas of the project. If you have a surprising stat, consider providing additional supporting data to show you didn’t cherry pick the numbers and to help stakeholders wrap their heads around an otherwise improbable figure.

6 – Relying on statistics without interpretation. To make stats truly mean something to others in the project sphere, PMP®s should provide a translation that outlines how the statistic connects to stakeholders. Are your stats a sign your organization is behind the market? Do they indicate the project team is performing better than average? When presented with data, you probably don’t want your audience to draw their own conclusions, especially when it comes to complex statistics. Instead, give stakeholders a foothold that helps them agree with your own findings.