All the building blocks at a glance

A good plan of action can only be created when you have a view of the bigger picture. Successful use of data throughout your organization requires various building blocks. First of all, you need to be convinced of the strategic importance of data. As a strategic differentiator, data also needs organizational change. A data culture, data awareness among every employee and data-driven processes are prerequisites for embedding the right data mindset in your organization. In addition to an optimized culture and processes, a cleverly thought out technological platform is also needed to facilitate everything.

Gathering inspiration and knowledge is one thing. But action is required to achieve real results. Backed by the vision we've revealed throughout the blog series, you can get started step by step in an agile way.

Get started step by step

What we describe as business understanding is an important first step. Look for an appropriate challenge within your company that is linked to your business objectives. You can do this by studying the interfaces between 'which objectives exist' and 'what is possible with new technologies'. The limited case that emerges from this can still be small as long as demonstrable value can be created. It's a good idea to describe this potential value in a business case before starting the actual project.

Once the business opportunity has been properly mapped out, the next step can be taken. How does this translate into data? First check the current status and check the quality of your data. Take a snapshot of your data, so to speak, analyze it and see which internal and external data sources are available. This is what we call data understanding. This requires an open dialogue between business and IT so that they understand each other well from the start. During these dialogue rounds, the needs of both parties are translated into specifications that determine what your data-driven platform, culture and processes will look like in order to formulate an answer to your business challenge. Once all this is clear, the dashboard, model or algorithm can be set up.

Following a successful but limited project in which the value of data-driven working has been proven, the time has come to industrialize and is a matter of embedding the way of working throughout the entire organization. After a successful project where, for example, a predictive model has emerged, many new questions arise. Will the model replace experts or will it only have a supportive function? What if the model starts to act strangely? To what extent is there still human control? Data can only be embedded in the heart of your organization by looking at the whole picture.