In addition, the purchasing trend research (Supply Value, 2017) has also shown that a high priority is given to the use of Big Data within purchasing in the coming year. Big data analyzes can improve the purchasing process and ensure better forecasting within purchasing. With such advantages, the question remains: why is Big Data analysis so little used in e-Procurement systems?

If we look at the current state of affairs within e-Procurement systems, we are not yet making full use of the possibilities that Big Data analysis entails. Not only in the area of the data about purchased items and services, but also about the underlying data about the purchasing processes and their turnaround times. The problem that this is not yet being used is twofold in my view.

Firstly, there are often no data specialists at purchasing departments who can help with setting up data collection and processing. In order for big data to succeed, not only a lot of data must be present, but often this must also be processed or otherwise collected. Only with good input good and effective output can be delivered. In order for big data to succeed in combination with e-Procurement, we have to look ahead in the purchasing department. Investments should not only be made in buyers, but also in data analysts who can support.

The second thing that is often lacking is the absence of a good connection or integration between Big Data analysis tools and e-Procurement systems. There are many e-Procurement systems in the market and perhaps even more data analysis systems, but the link between the two is often not present. This leads to a lot of data that is collected but not used within an organization.

As expected in the above two subjects, these problems reinforce each other. Without good data specialists within procurement, good tooling will not be used in e-Procurement to analyze and use large amounts of data. From the other side, however, it can also be argued that without good tooling there are no data specialists who want to start purchasing within a purchasing department. The problem must therefore be dealt with from two sides.

The big question now remains how this should be done. Unfortunately, there is still no clear answer to this. Substantial investments in the purchasing department are an option, but often this is not done because this is not a vital / primary activity of an organization. A better choice is to gradually gain more data specialism within the purchasing department, for example by purchasing buyers with a beta background or by training the fixed buyers in data analysis.

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