• Organisations need to rethink the way they handle and use data

  • Our model has been developed through years of collaboration

  • There are six key roles that can help organisations become more data-driven

Data coordination is a complex task

“Who’s doing what?” “Who’s accountable?” These are frequently heard questions when building a data-driven organisation. Almost every leader will have to face it at some point: it’s not that easy to coordinate all the digital transformation work that needs to be done.

This kind of challenge isn’t new. There is plenty of business literature about the best ways to coordinate work, and plenty of organisations have successfully overcome these obstacles in their Finance or Human Resources departments. However, when it comes to data, many organisations struggle. 

Often, organisations end up building large, complex structures to manage data coordination. Not only is this an expensive approach, it also takes a lot of time to implement. This can be difficult to balance with the added business value – especially as it takes a long time to realise ROI. 

To deliver value faster, organisations need a more pragmatic solution that integrates easily with their existing structure. This is where our Data Operating Model helps out. It’s a decentralised model, developed in close collaboration with our clients.

The Data Operating Model: 6 key roles

The Data Operating Model focuses on arranging six different roles in your organisation. 

In practice, we often start by allocating one or more of these roles to existing functions in our client’s organisation. This leads to smaller initial investments, making it easier to begin using the model and build the business case for full-time data roles. 

Let’s explore the roles and how each is positioned in the operating model. (Keep in mind that these don’t have to be full-time commitments for your people.)


This role is responsible for creating business value by executing a process and continuously monitoring its success, such as an operations manager who’s in charge of a manufacturing process.  

The BPO is also responsible for enhancing the business with data-driven design and digital innovations such as digital twins, IoT or advanced analytics. To achieve all this, the BPO needs to define what data they need and how it will be used.


The DOs in an organisation are accountable for ensuring data is fit for purpose in line with the business’ needs. Because this role has to oversee the execution of data-handling activities, it works best at the senior management level, but some responsibilities can then be delegated to lower levels. 

An example is a production manager who also owns product data. In this role, they have to coordinate and align with all BPOs that use product data in their processes. They’re a logical choice for DO, as they’re likely to be one of the heaviest users of product data. 


CDOs have to envision how data-driven working can generate more business value by creating and managing the data strategy, governance principles, and policies. In practice, this role is also the lead of the ‘Data Office’, a new organisational function, with a similar seniority to HR management.

The added value is to ensure data governance and management is done effectively throughout the organisation. There has to be a unified understanding of goals, guidelines and concept, so no one has to reinvent the wheel.


Stewards are the linking pin in the operating model. They’re the ones that connect data requirements to business value and data policies to execution. This requires them to work actively to align priorities between BPOs and DOs. 

This role can also be a new function, but often organisations start by allocating the data steward role to information managers or data analysts who want to take a next step in their development.

Having good data stewards is a key starting point for an effective data governance framework and data management. They understand the business and its data, and they operate strategically without being afraid to get their hands dirty. 

To help new stewards understand theory and practice for the role, we’ve created a training program for Data Stewardship. Various companies in Industry, Finance and Public Services have adopted this approach already.


Everyone in an organisation is a data user, producer or both: creating, enhancing, using or destroying data. Awareness among everyone about their role in handling data properly is vital to realise business value from data. 

Consider this: a customer service agent makes a typo when they record a new customer’s phone number. This leads to extra time in various processes when the business needs to contact that customer, and their experience is affected. 

Another example is a manager sending an updated version of a presentation back and forth. Each time, this creates new data, resulting in higher storage costs and time-consuming version control. These types of issues are directly related to data quality and are often difficult to trace.

Solving these problems doesn’t start with technology solutions. It starts with general awareness about data among employees, and how they can manage data as a valuable resource. This is key to adopting a data-driven mindset and culture.

Build your data-driven foundation

By establishing key roles and responsibilities within your organisation, the Data Operating Model helps you build out the foundations for a data-driven organisation. 

With your people taking ownership of how they handle data, and process owners making their data needs clear, you can begin continuously turning data into tangible value for your business. 

Once you’ve established the model, prioritise your data activities based on the value they’ll provide your business, focusing first on small changes and investments that will have a large impact. This will enable you to build a compelling business case to scale up based on your successes.