Data needs of organizations are increasing. Based on consumer behavior, social and economic trends, insight into assets and other available internal and external data, companies and their leaders want to make better decisions and respond more adequately to customer needs. Data governance can help to extract this desired added value from data.

“Leadership is a requirement to set the right things in motion,” concluded  Meindert Boorsma, data specialist with Squadra during the recent dinner discussion, in which a dozen data leaders from nationally and internationally operating organizations joined. “Later you can assign the responsibilities to people elsewhere within the organization.”

In the first place, data governance should serve a clear goal, as became clear during the meeting initiated by Squadra in restaurant De Heeren van Montfoort. What can you achieve and what do you want to achieve with it? The way in which you organize your data governance depends on the context and your own data maturity. It is in any case a shared responsibility with other functions and departments.

Two worlds

“A separate data governance organization is needed to get value out of data,” Meindert Boorsma brought the first proposition to the table. Lenno Maris, Global Director Enterprise Data & Authorizations at FrieslandCampina, had been allowed to think about this beforehand as an introductory speaker. According to him, it doesn’t necessarily have to be a separate department, but the management can also be placed in the line organization and, in part, even be taken on in a broader sense.

Maris shared his own experiences in this area: “in terms of data, there are two worlds. On the one hand, everything you standardize and centralize, and on the other hand, the things that happen locally.” According to him, they are two different dynamics that eventually have to converge somewhere.

“You can partly decentralize the responsibility and ownership in the business.”

“That cannot be done other than with a centrally operating team that has the total overview,” continued the speaker, who thereby wants to guarantee the right data quality, among other things. As far as he is concerned, this also includes the right tooling. “But the responsibility and ownership of data can be partially decentralized in the business, because that is where the interest in the accuracy and availability of data is greatest.”


This hybrid approach is endorsed by most of those present. Central and decentralized are in fact two sides of the same coin, and are no more opposites than organization and individual. The same applies to the people and departments involved. Even though blue (conscientious) and green (stable) people types are often seen as the designated data guardians, without the input of red (dominant) and yellow (interactive) people from procurement, category management, sales and marketing, no value is created. For example, ownership for product data often lies with category management while operational responsibility (accountability) is often delegated to a specialist data management department.

The success of the organization and the prevention of pain are the responsibility of all concerned. According to Squadra co-founder Jos Schreurs, how you set up data governance partly depends on the maturity in dealing with data: “You need to get things under control first. That often starts top-down, but after that you can delegate it and data governance often gets a more supporting role.”

In short, strictly speaking, there doesn’t need to be a separate data governance organization, but you do need to facilitate the necessary processes and decision-making from a central conscience. Delegate the right things to the right people and encourage the desired behavior.

“How you shape data leadership depends primarily on the maturity of the organization”

External data

Possibly the way most people interact with their personal location data on Google gives an indication of the overall attitude toward data. After all, based on each person’s own input, they end up getting better information and tips. We share our personal data so that we get something in return that fulfills our need or provides some other benefit. In a corporate environment, roughly the same dynamic is at play.

The discussion in Montfoort then turned to the way in which you deal with product and supplier data originating from chain partners, for example. You can make demands on such parties, it was argued. If necessary, you can help them on their way by providing the right tools for correct input.

Most participants are already broadly active with such external data. The necessary data is also sourced from specialized suppliers of standardized data such as Dun & Bradstreet (company data), GS1 (food products, among others), 2ba (installation industry, among others) PostNL (zip code check) and other sources. Ultimately, blockchain technology can play a role in the accessibility, transparency and quality of data.


The second statement “without data leadership, data optimization fails,” according to Mark Mescher, Head of Master Data Management at Ericsson, is more stimulating when you turn it around: without data optimization, leadership fails. Even after the tilt, the statement was considered basic in Montfoort. After all, one thing cannot happen without the other, because it is precisely a leader who must be able to show results.

“Ericsson started standardizing data twenty years ago,” Mescher told of his own practical experiences. “Master data management formed the foundation.” Since then, ownership has been vested both centrally and decentrally. “Leadership is an absolute requirement to get things going, initially mainly top-down. After that, it’s about things like behavior, culture and mindset.”

When this is taken up, ownership no longer lies with a few individuals and even data leadership belongs to everyone. Every employee then bears responsibility (consciously or unconsciously) for feeding the systems in the right way. Because this is embedded in the way of working and because in the end it gives everyone something valuable. “How you shape data governance depends primarily on the maturity of the organization.”

Why, what for?

Ultimately, everything revolves around the question of what you want to achieve with data optimization. Why do I want it? What am I doing it for? Each company, each department and perhaps even each individual involved makes his or her own choices in this regard. Whoever has a clear business motivation can start organizing, directing and implementing it. “You often hear people and companies talk about a data-driven strategy,” remarked Meindert Boorsma towards the end of the evening.

“Often it remained unclear why it is so important, and what exactly they do with it.” Squadra colleague Jos Schreurs complemented: “However, organizations increasingly understand the importance of data for the control and digitalization of their business. This is especially true for master data management, which forms the data foundation and is therefore a precondition for a lot of activities.”

So as a leader or organization, you do need to have a vision, which you can make explicit so that you can then act on it. Data governance starts with a clear goal. How exactly you organize it depends on context and your own maturity. From top-down to a broadly supported ownership and responsibility.