Three Days in a Supply Chain Masterclass: Here is What I Learned.

First of all, why did I do a masterclass on this topic, isn't Nemeon a tech company?

Yes, it sure is. Yet, the company wants to be market leader in its niche (developing data and AI solutions for logistics). To understand a niche, you need to submerse yourself into the debates that are held. Going about your everyday activities is fine, but we often forget the "other worlds" that contribute to our knowledge on particular topics. Academia is one of these worlds and one which is oftentimes overlooked by industry. In the following, I'll try to summarize some key points of three packed days at the Antwerp Management School.

Current trends

Some figures that rocked my boat:

• 69% of firms say they do not have full visibility into their supply chains.
• 63% of organizations do not use technology to analyze, track and monitor their supply chain performance.
• 99% of the companies have experienced a disruption in their supply chain over the past 5 years.

While I'm not an "emoji" guy, but ??♂????????? !!!

We hear this daily, "we're on it", "data has our full priority", "we got this covered."

The reality: some old SQL database and a number of spreadsheets linked to a Power BI report that was developed in overtime by the operations guy. Sorry guys, this isn't top priority, and you're not "on it."

It is time people in logistics (even more if they are in 3PL!), recognize the world post COVID. One of the professors summarized it in an acronym "VUCA", meaning that supply chains now are characterized by:

• Volatility
• Uncertainty
• Complexity
• Ambiguity

An example: the semiconductor supply chain is one of the most complex there is with easy disruptions if one of the layers in the chain experiences hickups.

Apart from volatility, with attempts at becoming more "data-driven", the industry is trying to be "greener" (albeit that this topic is a bit "on hold" as there is an economic downturn) . The costs for lowering emissions is also not offset by government subsidies. Example: cost of a classic truck stands at € 100k today where an electric truck easily exceeds € 300k.

The law of the "large numbers" is also at play. Look at this: Belgium counts about 10.000 transportation companies. As of number 200 on the list, the average number of FTEs on payroll drops to "1". So for Belgium, we're looking at 100 or so that dominate the market with the top 5 taking a lot of the business. As a result, the bigger ones buy the smaller ones or drive competition to the point where the small ones go bankrupt.

Forecasting & Demand / Inventory Theory

I must say, I was blown away by how vast some areas of expertise are. Some forecasting and demand experts take mathematics to a whole new level of complexity to get their forecasts as good as possible. It is a running joke in the industry though that these professionals are "either lucky or wrong." The learning here was that 72% accuracy is the average in the industry. I also learned that forecasts are regularly "adapted" to match reality. Experts call this "demand sensing" and it is advised to do this regularly as unforeseen events occur (example: bankruptcy of a competitor). A final interesting observation with regard to forecasting is that human planners seem to be more likely to overwrite a model when its complexity increases.

What use if your forecast is perfect but you experience a stock-out? This shouldn't occur of course. That's why demand forecasts need to be taken into account, next to lead times, review times, and excess demand cycles. The gist of the matter is that inventory theory uses complex algorithms to weigh costs (such as holding costs or stockout penalty costs) against potential gains (not missing on potential sales).

While we covered a lot of ground in a mere three days, we also just scratched the surface. It is clear that Supply Chain is a field with a lot of different "expertise domains" that warrant a lifetime of study. It was useful to get an overview so that we can understand our clients better. A "central narrative" throughout each of the session though was this: data (and mathematics) take central stage in the supply chain world. "Gut feel" and "doing stuff because we always did that" are getting punished by those who are investing (e.g.: Amazon is the "big bad beast"). Nemeon is here to help innovation-oriented 3PL companies make better use of their data and - as such - increase their competitiveness in the market.