Professor of Operations and Logistics Management | Industrial Engineer | Tilburg University | Eindhoven University of Technology | MIT | Author of "Reaching 50 Million Nanostores" | Speaker |
Debunking studies are not very common but this excellent study by my former colleague Professor Kai Hoberg and his coauthors does an excellent job reviewing expectations on #digital technologies that were present in 2014, by re-interviewing executives from the same companies that had those expectations back then. They show that focused implementation of some of the technologies was successful, but by and large the expectations at the time were very inflated. Why? The report finds that *immature technologies*, a *shortage of skilled personnel*, and *inconsistent data management* were the main impediments. Exceptions were high-clockspeed industries that had invested already in *specific* technologies and skilled people. I am very curious whether in 8 years' time we will think the same about the massive (at least: massively announced) investments in #AI in the #supplychain. I would personally think that the same three issues are still very present. Maybe the companies that have been able to ride the first wave of digitization in their supply chain can further advance, but those struggling with poor data and a lack of skilled people might better focus on repairing these issues first. Thanks Kai for sharing this important study!
Here is a nice article that summarizes our joint SAP-KLU report "What Really Works in #Digital #Supply #Chain" in German. I like the provocative title that translates as "Is the hype over". Jörg Wilke and I outline what companies should consider to be succesful in their digital #SCM transformation journey and which levers to pull. The special issue of VerkehrsRundschau is available here (p. 4-6): https://lnkd.in/dBYFrAkn The full 72 page report (in English) is available here: https://lnkd.in/dYRmGgp7 #supplychain #logistics Kuehne Logistics University #myklu
Laxman Marathe
5mo
Yes AI and supply chain too would meet the same fate after eight years. They're a nebulously good sounding idea that does not solve the basic problem all companies face. Even the report concluded that way. So what is this PROBLEM. The problem is deciding who should do what now and once it's over next at a micro level. That's micro level autonomous scheduling of the operations. We automated everything else but this primary core issue. No human can do this job. Obviously a solution exists, as I have developed it myself. It's an autonomous scheduling engine that controls operations at a micro level 25x7x365. You can ask Kai and his co-authors to review it. All information describing it is already published on my LinkedIn profile page.
Thank you for sharing this, Jan Fransoo. It’s a valuable reminder of how inflated expectations can be tempered by reality. I’m also curious about how AI investments will be judged in a few years. I agree that the same issues—data quality, skilled personnel, and mature technology—are still relevant. Focusing on these basics will be key to successful implementation.
Professor of Supply Chain and Operations Strategy at Kühne Logistics University
5moThanks a lot Jan! I think we need to educate managers what is realistic and what is not. I will never forget the discussion I had with a head of after sales - he wanted to forecast the daily demand per spare part (100,000+ SKUs) for each of his 3,500 service technicians to avoid express shipping fees and implement anticipatory shipping. Finally convinced him that big data has some limits 😉