action-oriented stakeholder, the expert-oriented stakeholder, the process-oriented stakeholder, the data-oriented stakeholder and finally the uninterested stakeholder. In this post I will talk about interacting with the data-oriented stakeholder.
The data-oriented stakeholder trusts the data. They don’t care who collected it or what procedure they used, provided the approach was valid. They just want to know the facts. Give them test results, survey results, or the output from your model, and they are ready to make a decision. Give them your opinion, or even the opinion of several subject matter experts, and they will still want to go run a test or do a study to confirm it with facts. They believe that mistakes are made when we make decisions based upon assumptions and opinions - facts are needed to reduce the risk. They may ask where or how you got the facts, but that is just to be certain that you are not making them up or using inappropriate data. And you can count on them to check the math on your presentation slides to be sure everything is adding up. If there is a mistake, they will catch it, and at that point you will have lost credibility.
The key to interaction with this stakeholder will be to communicate through data. You can summarize the data, but always be ready to provide the details behind your summary and conclusions. These individuals will often appreciate a statistical analysis of the data – and they will understand the statistics so be sure you do your calculations correctly. If there are holes in the data, know why you do not have that data and be ready to explain either why it does not matter or what you are doing to collect that data. The types of questions they will be asking are:
“What tests or analysis did you do and what was the result?”
“How many tests have you run? How big was your sample in the study?”
“Is this consistent with other data we have seen? If not, why not?”
They would appreciate getting the full data set from your test or study. You don’t need to provide that in a presentation, but you should have a handout ready to give to them that includes that data.
If the data is clear, they will make a quick decision. If the data is inconclusive or incomplete, they will ask for more studies, tests, and analysis until the data gives a clear picture. They do not want to be rushed or pressured into making a decision.
When discussing your project, have the actual data – cost, schedule, or performance data – associated with the issue being discussed. Be ready to explain the thresholds for what is considered to be good or acceptable levels and what is a problem. You can then defend your position or ask for your change based upon what the data says. The discussions should focus on the validity and completeness of the data followed by the implication for your project or organization. If you don’t have data, don’t ask for a decision. Instead discuss the approach you will be using to collect data.
Good News and Bad News
For these individuals, bad news is missing, suspect or incomplete data and good news is clear valid data that tells an unequivocal story. Even if something catastrophic happened on the project, if the data clearly indicates the cause and you are able to correct or avoid that cause in the future, this will be considered good news. However, if something either good or bad happens and you don’t know why, that is bad news to this stakeholder. It is an indication of an out of control situation. If you find yourself in that position, be ready with a plan for investigation that will lead to facts and data to explain what happened.