Flip the pyramid
It's a challenge for a lot of managers to start with data analytics. "We have data, what can we do with it?" We argue that one should not start from data. Instead, start thinking from the business questions.
Big data. Data analytics. Artificial Intelligence.
Managers are convinced that their organisations have to become more data driven. Data is the new gold. It will change how we do business. But they don’t know where to begin. They are no data scientists.

Data, Information, Knowledge, Wisdom
Many explain data analytics using a pyramid. The pyramid has a firm base labelled data. Above that there is a smaller part called information. On top of that we find an even smaller part called knowledge. And the top part, the smallest, is called wisdom. The pyramid suggests a path from data to wisdom. However it gives a wrong view for those who want to start with data analytics. The view that one gets is that data analytics starts with data. Invest in data lakes, data warehouses, data infrastructure, and data management. At huge costs, measured in budget, time and IT resources. We have seen companies doing just that. And after a while they could produce the same dashboards as they had before in a spreadsheet. But now enabled by python! The point is that a lot of organisations have no idea what they want from data analytics. They just went for it, hoping that wisdom would reveal itself at some day.

Wisdom, Knowledge, Information, Data
Managers should flip the pyramid, when they question how to start with data analytics. Think of it. Data can never be more important than wisdom. With wisdom an organisation can grow, innovate, become more sustainable and efficient and more.
The flipped pyramid shows wisdom as biggest and on top. Start thinking about the the wisdom that the organisation needs. What is the key business challenge? Increase market share? Innovate operations? Then, go down. What knowledge is needed to improve sales? How does demand depend on prices in the webshop? Then, go down again. What information is needed to study that relationship? At least, historical demand and prices during sales campaigns. And lastly, at the very thin bottom, the question is what data is needed to provide that information? And if this data does not exist within the organisation, can we obtain it from sources outside? Like any other images for managers, the flipped pyramid does not tell the whole story. It’s not exact science. But it puts data analytics in the right their perspective for managers. Data analytics should not start with IT but with business challenges. Flip the pyramid.