The Perils of Big data in Procurement

With the progress in digitalization and technology to extract data and the creation of a lot of different means to exchange it, information has never been so accessible and in so much quantity.

Bits and bytes flow from different parts of a business, covering all aspects of its ecosystem in an attempt to understand what happened, what is happening, and what will happen.

This wave of innovation is also spread in the procurement departments. Buyers and procurement managers, as they manage vendor performance, negotiate and run RFPs events, they have now available a huge and unprecedented amount of data, and by following Drucker’s words of wisdom, they start to measure everything in order to try to manage it, only to realize that is very difficult to do so if you have a universe of information at your disposable but don’t know what is the crucial data that would give you critical insights.

With this approach, several data lakes are created, feeding various dashboards, scorecards, reports, and metrics as procurement professionals try to understand spend analysis, price trends, market fluctuations, volume, cost savings, negotiation performance, and other essential factors.

However, sometimes, the data available is not only huge but also in granularity and coverage; that is very easy for a person to be lost in that sea of numbers and details and miss the big picture entirely.

It is the same as someone that enters the hospital with a broken leg but has everything else checked – brain scans, electrocardiograms, colonoscopy, diagnosis of internal organs, check for rare diseases - while, for the entire time, the big problem was right in front of the doctors at plenty sight.

I am not saying that analysis should be superficial and not deep. Procurement and Supply Chain can be very complex, and sometimes the understanding of a situation or the definition of the best negotiation strategy may require sophisticated information evaluation, but it is crucial to understand what to know and what to look after.

Through some years of experience in trying to navigate those problematic tides, I came to believe that a few things are essential when dealing with information management and big data:

- Understand what matters – make sure you know the few critical things that are very impactful and relevant.

- Start with a top-down view – focus first on measuring macro metrics of the important things and only after starting to drill down as you go after more insights. Don’t jump directly into a big amount of details before understanding the layers above.

- Good people for insights – people working with the data should be good at getting insights from what they are reading. This is different from having someone good at manipulating a large amount of information and building a database. What is valuable is someone that can read the information and identify the reality there. A person who can see patterns identifies the root cause of behaviors, asks the right questions, and confirms the fact that it may be anecdotal or “gut feeling.”

Undoubtedly, technologies and big data bring incredible potential to do things better and more intelligently. However, if there is no clarity on exactly what is important to measure, if it is not accessible in a quick and friendly way and available to the people that truly have the skills to unlock the value of it, the big leverage could become a liability at the end, bringing confusion and slowing down the organization.