1. Make the business challenges transparent
“The first step you have to take as a company to start working data-oriented is to clarify where the challenges or problems of your business lie. It is important to have a picture of the deeper background. Suppose a manager notices that employee turnover is high. Then you start to wonder: when exactly do you think the turnover is high? Which roles within the company does this apply to? The more concrete the problem is presented, the more valuable the role of data science ultimately becomes.”
2. Define the business opportunities
"Once you've identified the problem, you start looking at the business implications of that problem. Why is that high staff turnover problematic? Does it take a lot of time to refill those vacancies? That way, you make it clear what the business implications of your problem are, and how you will benefit as an organization by solving this problem."
3. Look for the relevant data
“Before you can work on a solution, you look for data to analyze. That is a big step: you are going to consider all the factors that play a role. If you are going to investigate employee turnover, you can, for example, analyze exit interviews and appraisal interviews. But anything can play a role: salary, management style, career prospects, work pressure – there are all kinds of things to think of. And if the data is not immediately available, you ask yourself: how can we get it?”