Factor Nathan Rosidi, content creation and building tools for data scientists.
You probably hear the word stakeholders quite often. Who are the stakeholders? If you work with data, your main skill is simply to be good at it. But surviving in a company also takes other skills. Getting people to understand your information insights and getting them on board is a skill in itself.
But how do you master this skill?
Who are you and who is the stakeholder?
You’re a technical person in your workplace, probably someone who is passionate about data and spreadsheets. There is nothing wrong with that; you got a job because of that in the first place. You may be an information scientist, data analyst, reporting expert, or some kind of fortune teller. Your work name doesn’t matter; the thing is, you work with numbers. In addition to working with numbers, you (unfortunately) also work with people.
You interact with some, trying to convince them that your numbers, tables, and insights are true. I hope they make decisions based on your information. And by making decisions, they might potentially put their careers on the line. Or at least a small part of it.
It is a stakeholder. Someone you want to trust your insights and understand the data.
Why is it so difficult to communicate with stakeholders?
Because it’s hard to communicate with people in general. And communication with stakeholders? Well, they’re usually not as technical as you. The higher the company hierarchy, the more stakeholders tend to be less and less technical. This means that the higher the level of stakeholder affiliation, the more difficult it becomes for you to communicate.
Because of their position, they have more context than you. In addition, like all people, they have their own responsibilities and goals. They have prejudices. The only difference is that some bias values support the data while some do not. The case is that the only reason they need the information is to confirm what you have already decided. They are looking for validation.
They are just trying to do the right thing. And doing the right thing means they hope they can move forward and achieve success. Often without your information or in the exact opposite direction your information points.
It is frustrating. It shows that your job is not that important. It shows that you are not important.
What can you do?
Understand that you cannot do much. Ask yourself, what can you do to label yourself and your information? Probably not much.
Why? Very simple. That is not your job. And you certainly aren’t paid enough to do your job and someone else’s at the same time. Understanding that you matter, but not so much, can be very liberating. It removes the burden of personal responsibility. You are not solely responsible for making decisions that change the trajectory of your business. You don’t have much leverage as an individual, and no one should. All important decisions always require the unanimity of the team.
So what does that mean for you and your work when you know that stakeholders really aren’t about listening from your heart to what you recommend? How should you approach stakeholders from this station?
When communicating with stakeholders, be flexible. Don’t embed them in data. Instead, create a recommendation that you both accept, taking into account both information, insights, and context. Make them feel good. Send the news in a way that suits them or helps them with the situation. Maybe help them explain themselves, blame someone else, or simply understand that the situation is out of their control.
Bring them on a trip and share the reasonA
Show them what you think and how you think. Show them your assumptions and approach. You’ll be surprised at how different you think compared to them. They have so much more context than you, and they usually think about the problem differently. Sometimes it’s worth listening to a different mindset, especially when you’re trying to get them to listen to that mindset. Obviously, getting to the same page before writing the code or performing the analysis is great.
But the biggest reason why you should take them on a trip is that you can share the reasons together. There is a non-zero chance that any model you build, any prediction, and any recommendation you make is likely to be wrong. Why can’t we be wrong together and share the reasons? You and your stakeholders are living wrong. But they don’t use you as a scapegoat because you all agree on the approach and the solution. Never underestimate the sense of survival that makes people blame everyone but themselves when things go wrong. It is not advisable to say it out loud in companies. They always want to see themselves capable of rising above some basic human emotions and instincts. But you know it’s a lie. Even in the largest and most complete data science companies, people gossip and blame each other for failure. People optimize their own success and career goals. That is normal human behavior. Not that it should be like this, but it is.
So work together and take them on a journey so that your stakeholders think the experience is positive and learn more about you. And you develop an employment relationship with them. You win both.
Don’t accommodate themA
At the very least, don’t heed all their requests. Sometimes you have to push back, and sometimes you have to adjust. Try to find the right balance. Everything becomes easier when you work with your stakeholders from the beginning of the project.
This tip has another advantage. You may have free time not to bend backwards to meet their every need. And you can use your free time to focus on learning something new technical skill or the analysis you are doing. This is an opportunity for you to also develop and get something out of it. Who will ultimately care about your winnings against them? Use project improve your own technical skills.
After all, you will be paid money regardless of the outcome of the project. Remember, try to do your job better, not other people. Make your stakeholders happy, even if it’s not a recommendation you completely agree with. Just make sure they are 100% on board and happy with it. At the same time, make sure you improve at the end of the project, whether it’s a new technique or analysis that you were able to learn. This is something you should really care about.
Original. Re-posted with permission.
Bio: Nathan Rosidi is a data scientist and product strategist. He is also a docent who teaches analytics, and is the founder of StrataScratch, a forum that helps data scientists prepare for their interviews with interview questions from the best companies.