It seems to have arrived everywhere by now: whether it's “the raw material,” “the oil,” or “the gold of the 21st century,” data is of immense value. Provided that they are used sensibly — otherwise they mutate into storage eaters and dust collectors. But how do you establish a true data culture in a team? We will explain the cornerstones to you shortly.
Keyword “empowerment” — a data culture needs an appropriate climate. Anyone who shares information should also place a certain amount of trust in their employees and clearly formulate goals. In addition, more persuasion is often required — especially with established team members. It is important to choose a low-threshold approach here. It is often the case that what is not understood is rejected. That is why it is essential to present and visualize data in such a way that it is easy to understand and, above all, intuitive to use.
Data is information whose value also increases with its users. The more employees interact with the data, keep an eye on their own KPI's and deal with developments in the company, the more responsibility and motivation can be established within the teams. But don't worry about the famous data sovereignty, it's safe. That leads to the next elementary point.
What data is there and who needs access to which information?
Modern analytics tools make it easy to allocate roles and show at a glance which departments or which people have access to what.
In order to decide which information is ultimately relevant, it can be useful to review the KPI's with regard to independent analysis within the team.
Cleanly organized and clear data — that would be the ideal basis for taking the next step towards analysis. In real life, however, the situation usually looks different. Whether it's the source, format or the peculiarities of the different departments — the collected data material is often a rather opaque and constantly growing heap. The resulting data silos often reduce the motivation for analysis, but valuable opportunities fall by the wayside. Getting started doesn't have to be that difficult — once the database is standardized, all incoming data can be fed in in in a structured way and the analysis can start.
The more data is available, the more value can be generated from it. Anyone who is curious about the available information sharpens their analytical skills and can identify hidden patterns, generate growth and drive efficiency in the company.
... so let's get #datadriven:)
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