The path to successful digitization starts on the work floor

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In this data-driven era in which data finds new customers, binds existing customers and makes efficiency possible, everyone seems to have an idea regarding digitization and the value this offers the business. But how do you create real value with data? And where do you begin?

Traditionally, it has been the sales and marketing department that utilizes data to search for new ways of reaching customers through data. Nowadays, however, this plays an important role everywhere. Customer managers in a production environment use data to streamline production processes and to be able to produce products quicker. Data is currently indispensable in logistics processes such as planning smarter routes and knowing when customers are available for at home deliveries. For all these examples ‘data first’ is the rule. In other words every digitization process starts with a sound data strategy. But also, start small and then quickly scale up.

Find, share and collaborate 

Every organization that undergoes a data-driven digital transformation has to go through three critical phases: find, share and collaborate. First of all, it is important to determine what data you need to be able to create a use case. How do I get the best return from existing, new, internal and external data? And how do we ensure a sustainable data strategy that safely manages different types of data and integrates this data into a flexible IT architecture. This last point is essential for managing and sharing data. Compare this with a ‘traditional’ library. Each company must have an index that knows exactly where to find different data assets. The different data sets in an organization can only be managed and deployed properly when the access to all types of data (onsite, managed, in cloud, etc.) is completely transparent. We refer to this as data governance 2.0 or unified governance. Using this, we attempt to provide a catalogue to everyone in an organization who depends on data to deploy new activities and initiatives – for example data analysts, business analysts, and data scientists. With the right access to data, you also increasingly see new, cross-disciplinary collaborations arising.

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The work floor as the testing ground 

The flip side of this data-first mind set, is that organizations have never been so dependent on data and digitization. In my opinion, it is important not to take giant steps all at once. Most questions and challenges arise on the work floor – a fantastic testing ground for testing and optimizing digitization in a small environment. If you make the first project too big or too complex, you are quickly faced with more different variables than you can manage. If you keep things small you can create a valuable use case in no time; this can then be quickly scaled up and modified for other departments within the organization. Another advantage is that you can demonstrate concrete results immediately, which helps create support for the rollout of future digitization projects.

All these changes put pressure on the CIO. In addition to managing the transition to a data first business architecture, he must properly consider and integrate the issues and desires of his CDO and CFO colleagues. A CIO benefits from a stable and controlled environment with the least possible costs. A CDO will ask questions regarding flexibility and investments that can make the organization quicker and more agile. In addition, the arrival of a data first environment means that a much larger group has to deal with the organization’s IT architecture and its data infrastructure than was previously the case. This ensures that such decisions must be made by the entire management, rather than just the CIO or CDO. The CIO, CDO and CFO will have to deal with one another more and more often in order to achieve the desired solutions. Innovation and digitization involves everyone.

In short, data-driven digitization is not a point on the horizon, but rather a practical process that must be performed. Provided the right steps are followed, it can be initiated and stopped quickly. The process from a small use case to proof of technology with validated architecture should take a maximum of 12 weeks. In practice, you frequently know within three or four weeks what the outcome will be. By focusing on this collectively and working on it together, the general customer experience can quickly be brought to a higher level.

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