Data Democracy: The Power of Data

As you could read in the previous blog on Data Democracy, there is a lot to gain from making data freely available within your organization. The benefits of Data Democracy are a dream for any CEO. But does that mean you should simply throw your company data wide open? Data Strategy Leader Louis de Roo tells you more in this blog.

Spiderman

The Peter Parker principle, known from the Spiderman comics, says that great power must come with great responsibility ('With great power comes great responsibility'). This principle, formulated earlier during the French Revolution as a guideline for the people's representatives (Plan de travail, de surveillance et de correspondance, proposé par le Comité de Salut Public aux Représentants du Peuple, députés prés des Armées de la République, 1793), is often quoted to illustrate the importance of balancing ability and responsibility. Those who hold a lot of power must handle that power responsibly. Working with data is no different. Anyone with access to an organization's data has access to its vital information flows. In the wrong hands, this data can harm your company, but within your company too, incorrect or irresponsible use of this data can steer you toward the wrong conclusions or decisions. This raises questions about how democratic you should make your data and how to go about it.

French Revolution

Back to the French Revolution. When, after the overthrow of the monarchy in France, the people's representation was filled with new, inexperienced members of parliament, it also became clear that these people could not be expected to make the right decisions without training and prior knowledge. In our modern data democracy it is no different. The 'citizens' of a data democracy need knowledge and context to make the right decisions and draw the right conclusions from the data they can so freely access.

Responsibilities, then. Of course, as a manager you may expect something from all those employees to whom you give free access to your data. First of all, that they understand the meaning and context of the data. That they know the limitations of the data, especially when it comes to the quality and availability of the data. You may expect them to know the source of the data and how it is fed – or who is responsible for it. And, more importantly, that they have the knowledge and skills to actually interpret the data. Much has already been written about this last topic, also known as data literacy. Rightly so, because it is an important ingredient of your data democracy. But having well-trained employees in your organization does not immediately give you a functioning data democracy!

Ground rules

At least as important is following a number of ground rules. Just as in a 'real' democracy, a data democracy only works if clear agreements are made. In a data democracy it is very important that not only the source data is available to everyone, but also the transformations of it; anyone who makes an analysis also shares it with the 'community', so that duplication is prevented. For the same reason, a data democracy uses no disconnected data: exports to Excel or other ways of working on data 'detached' from the source should be avoided, so that reliability is safeguarded. In addition, there is of course confidential data. In a data democracy all participants know which data has which level of confidentiality, and act accordingly. Not only because of a possible non-disclosure agreement, but also because they know the rules on data processing inside and outside the organization. And you may expect your 'data citizens' to be willing to help each other, with insights, interpretations or analyses. Sharing knowledge is, after all, one of the founding principles of data democracy.

With all those responsibilities and ground rules, it may sound like democratizing your data is a lot of work. And perhaps it is. But we all know the alternative: endless discussions about which Excel file is the 'correct' representation of the situation, nice reports built on outdated datasets (and therefore useless), an analysis that turned out to be exactly the same as your colleague's, and heated discussions in meetings because the numbers were wrong.

Data democracy

An environment in which everyone has free access to the right data, understands and uses this data without doubting the quality of the source, the definitions or its reliability. Where everyone speaks the same 'language' when it comes to data, and where we can invest our time in gaining new insights from data instead of in making the right data available. That is a data democracy. Time to get truly innovative!