The missing link in getting data-driven procurement right
Are you happy with your data foundation? Algorithms may be smart, but they are still machines. That means that if you feed them garbage (as result of a bad data foundation), they will give you garbage. As a procurement leader, you do not want that.
Innovate your procurement process, but do it right
Today’s procurement leaders already realize that the future of procurement is data-driven. But let us get specific for a minute. What is data-driven procurement exactly? What are the specific building blocks that you need to realize this? And in terms of maturity level, where are you now?
Nowadays, it is hardly thinkable to be at an event and not spot one of the following buzzwords: artificial intelligence (AI), machine learning (ML), business intelligence (BI) and many more. Does that sound familiar? It is no coincidence that these terms can be found on any banner, flyer or promo video and that it probably trigger you. They are cool, trending and the future will most definitely be full of them. Consequently, to get with the program is to get acquainted with these techniques and to be able to understand how they can profit your business and day-to-day operations. When you do, the most sensible action to start with, is to look at what is at the foundation of these innovations: easy access to usable, high quality data.
Algorithms and data – things to know if you want them to be happily married
Algorithms could provide you with actionable insights. For example, they could spot (tail) spend patterns, anticipate changes in customer demand and identify bottlenecks in procurement process before they arise. When done right, these techniques are extremely valuable and essential for an efficient procurement process.
However, we see many procurement specialists who struggle from a sub-optimal data foundation that typically contains dirty- and bad quality data that cannot simply (and fast) be accessed. Algorithms may be smart, but they are still machines. That means that if you feed them garbage (as result of a bad data foundation), they will give you garbage as output. This is called the garbage in = garbage out principle, and is a situation where you do not want to position yourself in as procurement leader. Typical symptoms of having a sub-optimal data foundation that we see, and that you might recognize, in practice are:
- It takes weeks and sometimes maybe even months to access relevant data
- Not enough data and data scarcity
- Dirty- and bad quality data, with lots of missing and incorrect values
- (Privacy) sensitive and therefore unreachable data
- Time consuming trajectories and internal processes to get access to relevant data
A sub-optimal data foundation could results in suboptimal insights
The strong foundation your procurement department needs
What does a future, efficient procurement process look like? Ideally, one would like to have a strong data foundation with easy access to usable and high quality data to be able to realize data-driven innovation with aforementioned buzzwords (e.g. AI, ML, BI etc.). With such a strong data foundation, high quality data will provide you high quality results and actionable insights that will boost your procurement department and will provide you with a huge advantage in comparison to those who still lack a proper data foundation.
So how do we do this right?
A chain is as strong as its weakest link. And in the chain of procurement, most links are already present and relatively easy to implement. However, there is one challenging link missing. How do you establish a strong data foundation and where could you start as procurement leader?
A strong data foundation results in strong and actionable insights
Depending on which challenges your procurement department struggles with, Syntho can help you to establish this strong data foundation. Some examples that Syntho supports:
- Making (privacy) sensitive data easy accessible without losing quality
- Speed up data access to (sensitive) data from weeks (and sometimes months) to hours
- Viably resolve data quality issues such as missing/incorrect values
- In case of data scarcity challenges (to train for example algorithms), we can apply sub-setting/oversampling where more high quality training data is of the essence
- Generating extra intelligent synthetic data with the same patterns, characteristics and statistical relationships as the original data you have
Do you recognize the hurdles we mentioned? And does this article give you a better sense of your journey towards data-drive procurement and your current maternity level? We would love to hear where you stand, what difficulties you face and your general feedback. Please feel free to contact us and ask us all questions you have. Contact us directly to further deep dive into the future of data-driven procurement.
Are you happy with your data foundation? Syntho was founded in 2020 with the goal of solving the privacy dilemma and enable the open data economy, where data can be used and shared freely and privacy guaranteed. This Amsterdam based startup revolutionizes how companies can access (sensitive) data with their user friendly software solution for AI generated synthetic data.
With AI generated synthetic data, Syntho allows organizations to build a strong foundation to realize innovations with easy and fast access to more high quality data. Syntho’s award winning solution (Philips Innovation Award) has enabled Global 500 companies to shorten the time to access to (sensitive) high quality data from months to hours. For more information, visit Syntho’s website at www.syntho.ai.
Watch our winning pitch at the Philips Innovation Award:
Wim Kees Janssen
Gijs Kleine Schaars