Over the last 20 years, the volume of data has increased significantly, establishing it as a key strategic asset for companies looking to expand their operations.

In most data teams, a project is initiated in response to a business request, with the primary objective being to deliver the final solution as quickly as possible.

However, this approach quickly reaches its limits, as it does not consider the long term or the possibility of reusing the data solution for other projects. Many things are overlooked, such as documentation and the definition of KPIs. Teams only create data solutions when required by business departments.

This can lead to frustration, as there is no common reflection on how to perpetuate the same solution. This can result in silos multiplying and inconsistent sources emerging.

Ultimately, business representatives become frustrated because accessing their data becomes more challenging. This approach is not suited to delivering data solutions.

The Product Mindset: Building Data Solutions with Purpose and Usability

Another approach should be adopted and implemented in your data governance framework. It is commonly called 'Data as a Product'.

As you might have guessed, the idea is to view data as a product. This means that the data solution is built like a product, with users, goals, and improvements. In other words, create data solutions in the same way as cars.

When a car is released to the public, it has specific targets to achieve, such as driving its users (in this case, passengers) a defined distance, with long-term improvements such as self-driving or increased autonomy.

When you buy a car, it is delivered with a manual containing instructions on how to use it and start the engine. The same applies to a data product. It has users, goals to be achieved and improvements, as well as clear rules.

User-Centric Data: Enabling Access, Understanding, and Continuous Improvement

In that way, you put the business user at the centre of your data product. In addition, you have consistent, well-documented data records that are easily accessible to these users.

Thanks to the collaboration between business and IT partners, improvements are made on an ongoing basis. Also, less time is spent trying to understand the received data.

Managing Change: Overcoming Resistance in the Shift to Data Products

Naturally, this comes with challenges, as it disrupts workers' established habits. To avoid potential resistance to change, it is recommended that workers are trained in this approach and that it is incorporated into a global data governance framework.

In summary, the data product approach makes the data more user-centric. However, it requires significant change, but also brings more value to your data patrimony.