The challenge: learning to work with data and changing culture

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Now nature often provides checks and balances . For our judgment, that is the deliberate system (Gagestein's renaming of Kahnemann's 'system 2'). This system consciously helps to confirm our quickly formed image. Unfortunately, only at times when it is really necessary. And in a less rational and objective way: we use rules of thumb and ' shortcuts ' in our way of thinking ( heuristics ) and are full of systematic errors and prejudices ( biases ). These are mainly in the way we:

remember things;
dealing with information;
giving meaning to things, and
act when it has to be done quickly.

Mike Hoogveld also describes these thought processes, heuristics and biases in his book Futureproof . In the same book he advocates designing a learning organization: I wholeheartedly agree with that. If you look at the list of applications of heuristics and biases, you immediately understand why data-driven work and our fallible thinking are not immediately a match made in heaven . Couple that with the deeply human desire for manageable boxes, and the necessity becomes even clearer.

The learning organization that I envision therefore pays a lot of attention to learning to work with data . Data-driven work is also a cultural issue . In other words: if employees do not want or cannot work from insights from data, then all initiatives will eventually end up in the graveyard of good intentions.

Different skills are required at different levels
Learning to work with data is not a straightforward south africa telegram data challenge. It requires a different way of looking, because data does not produce one clear picture and you have to build in control mechanisms. It requires a different attitude, for example because data can undermine assumptions that are accepted as truths. That is where learning to work with data touches on the cultural issue. Furthermore, different skills are needed at different levels in an organization.



Strategic-administrative level: ultimate responsibility requires steadfastness
First of all, we have the strategic, administrative level. Based on the Data Agenda, the government is mainly focusing on administrative support (a director as ambassador for data-driven work) and securing data expertise at board level (by appointing a Chief Data Officer (CDO)). A good start, but that's not all.

Because this is the level where, by definition, it is all about abstractions and the grand gesture. And often also about the (political) craze of the day. In such a changing (and sometimes treacherous) environment, you have to be strong in your shoes to make the right choices. First of all, you have the ultimate responsibility to act sensibly and ethically .