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In the battle to become more data-driven, all sorts of organizational issues surface that demand answers. An important aspect that we encounter a lot is how best to organize the employees working with data. Organizational structure.


Give us a “rake” is then often the question.
And this at a time when fewer and fewer people seem interested in gardening.

From strategy to organization: organizational structure follows strategy….or the other way around?

Opinions on the relationship between strategy and organizational structure are quite divided if you look at the past few decades. Although I still hear the cry “Structure follows Strategy” come along from time to time, we must remember that this is a now 57-year-old wisdom from Harvard professor Alfred Chandler. A cry that certainly doesn’t ring true everywhere anymore, to say the least….

That strategy is necessary certainly applies to the use of data as well. And with big data and artificial intelligence and other terms you hear a lot in relation to data that often make eyes glaze over. By creating a data strategy, you identify where you can use data and analytics to better fulfill business goals. Scoring with data. Next, determine how you will implement the strategy. In other words, how does the vision and direction translate to the various organizational aspects, from people to resources. In which our experience shows that organizational structure is a strong success determinant.

An organizational structure that helps score with data

Whereas in previous articles we have looked in depth at data strategy and how the people side is a success factor in it, we now look specifically at organizational structure. The organizational structure as an element that must be right in order to successfully and in balance make the transition to data deployment. Leveraging data to the level of strategic value creation and data as a director of choices.

The ‘rake’ and pressing questions around organizational design for data-driven work

Whenever we come to talk about organizational structure with clients in our consulting processes, the need to start drawing “rakes” surfaces. Sometimes with lines, spheres or other shapes. Especially to keep it from looking old-fashioned. After all, we don’t work in departments these days; we work Agile in squads and tribes and so on. But regardless of how we choose to work as an organization, there is a need to get clarity on:

  • What kind of people do I need? What roles and competencies do you need in a data & analytics team? And how many employees per competency do you need.
  • What place does it have in the organization? Where do the analysis roles fall under, do we organize this centrally or decentrally. And how do you manage deployment and capacity and also ensure good cooperation with IT and Business departments.
  • In doing so, how do I ensure engaged and inspired employees who develop to their fullest potential? So how do you bundle and develop competencies optimally: where will the roles and competencies find each other, inspire and strengthen each other, and how will you optimally captivate and bind people with these qualities.

The three-stage rocket

To answer the above questions, we use a three-step approach that addresses all of these questions.

Step 1 is to identify the required competencies and translate them into required roles/people, from ambition and current competencies present. In doing so, we bundle competencies into roles. And in order not to make the whole thing look too complex, we visualize these roles in the form of lego dolls. A great metaphor for building an organization. In larger organizations, you get asked how many of which dolls you need. In small organizations, one is often shocked by the number of people. What helps is that these are roles, where it may well be the case for smaller organizations that employees can fill more roles.

Distinguishing and naming roles and competencies helps bring into focus what you need and what you already have in place. As such, it forms the first part of the puzzle to the design of the organization.


Step 2 is to determine the possible organizational variants
In this step, we determine the most obvious organizational variants, so get to work with the rakes. What this step looks like depends on the size of the organization. And so can vary enormously. Are you talking about a company with 50 people on staff and with two analysts or an international player with hundreds of people in the data domain …
We explore and work out the variants. What do we do centrally and what do we do decentrally, who directs what, how do departments work together and so on. At this stage, limit yourself to preferably no more than three variants.

Step 3 is working out choices in a structured way…and making them!
Once we have a sharp sense of what we need and in what forms we can organize it, it’s about making choices as objectively as possible. After all, it’s about people, their job satisfaction, their attachment to the company, as well as efficiency and meeting goals. But also, unfortunately, to power and control and more such sensitivities.

In short, not something to be determined from the underbelly or based on who shouts the loudest. To make the choice so transparent, we first work out the selection criteria.

For criteria, we look at objective things like number of employees involved and resolution of concrete bottlenecks. But also to aspects such as: how independent analysts can bring their advice, how we can secure knowledge development up to and including the organizational variant that best facilitates the achievement of strategic goals.

If there is agreement on the criteria, we then determine the weights and scores of the organization variants. Scoring each organization variant on a criterion ultimately creates a winner!

The powerful thing about this approach is that because of the tiered approach, you get consensus on parts of the question each time and not immediate discussion of the final solution. The most appropriate design then follows from the sum.

Strategy and structure are intertwined…and then you have culture as a success factor!

Whether structure follows from strategy or the other way around remains an interesting question, but don’t fall into the trap of trying to think out a variant that fits everyone. Make choices for an arrangement that scores best at that moment and dare to act, then, is the best motto.
When people start taking ownership from a clear organizational establishment, things happen that mean real progress. And then it soon becomes about culture again. You can find more on that in this article.

Wondering where your organization stands?
Want to know where your organization stands with data-driven work? Do the data maturity scan!

Want to read more about data strategy?

Read how to transform data strategy into organziational design.

Peter Reddering
Principal Consultant
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