NextGen SCM: the future of Supply Chain Management (a one-on-one interview with Dr. JT Kostman) PART 1

On November 18^th Dr. JT Kostman will take the stage at the FORGE 2021 Blue Sky Conference to talk about the future of supply chain management.

For those not yet familiar with FORGE conferences, and Blue Sky in particular, it is Procurement Foundry’s “go-to” virtual meet-up where senior leaders in sourcing and supply chain come together to benchmark their priorities and strategic objectives for the year to come. 

In the meantime, and turning our attention back to Dr. Kostman’s session—or JT as he likes to be known—our team at Procurement Foundry Press had the opportunity to talk to him and pose several interesting and provocative questions in advance of the conference. 

We are pleased to share JT’s response to these questions in this first of a two-part series of our interview.

PF Press: No one could anticipate the pandemic nor the outward ripple effect of its “unintended consequences.” Do you agree with this statement, and if not, why?

JT Kostman: Mark Twain once said, “History may not repeat itself, but it sure does rhyme.”

The COVID-19 pandemic has, to be sure, already had a more devastating impact on the global economy and supply chains than any event in our lives (with the possible exception of the few centenarians who were born before the Great Depression). But the pandemic and its consequences were not just predictable; they were inevitable.

The Spanish Flu pandemic of 1918-1920 brought the world to its knees—and the world of a century ago was not nearly as networked, interconnected, interdependent, dynamic, and complex as ours. Over the last few years alone, we have seen SARS, Ebola, and scares involving the potential weaponization of Anthrax, Ricin, and Measles. 

Bill Gates, Vaclav Smil, Laurie Garrett, and Anthony Fauci, among dozens of others, have warned us for years that it was only a matter of time before we would be confronted with another global pandemic. My wife, who has been an ICU Nurse for 40 years, has been warning me for at least that long that we could see a near Extinction Level Event (ELE) virus within our lifetimes. Her concerns are shared throughout the medical community regarding the over-prescription of antibiotics and the subsequent creation of so-called superbugs.

That governments and major corporations weren’t better prepared for and did not have contingency plans for responding to these inevitabilities is inexcusable.

Could better preparation have completely avoided the catastrophic circumstances we subsequently find ourselves in? Perhaps not. But as I reminded my students when I taught an MBA capstone course on Leadership in Times of Crisis, Chaos and Change, the time to try to kill Godzilla is not when he’s wreaking havoc in downtown Tokyo – it’s when he’s still cute and cuddly.

We have to use this experience to start preparing for the next global calamity – whether that one is due to weather, war, or another pandemic. As the old aphorism goes: When did Noah build the ark? Before the flood. 

PF Press – Many organizations who believed that they were an online business could not respond to increasing customer demands for their products. Amazon seemed to be one of the few exceptions in that they effectively met the surge in demand for products. At the same time, companies like Peloton had to scramble to address cargo shipping congestions in major California ports by shipping products by air and actively working towards repatriating some of their manufacturing to the US. Why was Amazon successful, but the majority of companies such as Peloton were not?

When I was a teenager, I had dinner one evening with the legendary founder of McDonald’s, Ray Kroc. “What business do you think I’m in?” He asked me. Hamburgers? Nope. Restaurants? No. Service? Wrong again. “I’m in the real estate business,” he told me. It’s a lesson that’s stuck with me for 50+ years: The real business of businesses may not be what you think; it’s often deeper and more complex than it appears. 

There is a misperception by most people that Amazon is a retailer. They’re not. Amazon is in the business of logistics. And (with the possible exceptions of Walmart and UPS) they do logistics better than just about anyone.

In routing their deliveries, Amazon uses some very sophisticated (and very cool) mathematics – including Nonlinear Dynamical Systems Theory, Graph Theory, and Ant Colony Optimization algorithms.

But the real secret to their success? That comes from the AI-Enabled Recommender Systems that are integral to their algorithms. These systems give them the capability, in most cases, to predict which book, bedding, or bottle of vitamins you will want days, weeks, and even months in advance. 

“JT, I see that you normally order [blah, blah] around this time every month,” Alexa said to me just this morning, “would you like me to add it to your cart?”

When you order something from Amazon, they’re often already a few steps ahead of you; they usually know what you’ll want even before you do. And knowing that you will likely want that product, Amazon has already sent it to a hub nearby. Why? Because even if they’re wrong (and they rarely are), a nearby neighbor with similar tastes will likely avail themselves of that item if you won’t. 

Amazon’s prediction capabilities have become so refined that they are currently considering simply sending what they predict you will want direct to your house, giving you the option of returning it in the (highly unlikely) event they are wrong.

So, why doesn’t Peloton do that same voodoo that Amazon do? Because Machine Learning algorithms need data to thrive. If you’re like most Americans, you get a smiley brown box on your doorstep at least once a week (for me, it’s sometimes several times a day) – and every one of those transactions is an opportunity for Amazon’s algorithms to learn more about me.

The real question to ask yourself is not why Peloton has not employed this same strategy—but rather to ask what you and your company can do to capitalize on the data you already have— and how to combine it with acquired, ambient, and exogenous data to develop AI-Enabled Recommender Systems for yourself; systems that can be incorporated into your Supply Chain to optimize efficiencies—while simultaneously substantially boosting your sales.

[Note: A McKinsey & Company report attributed 35% of Amazon’s sales to its recommendations —which accounts for $23.64B of their $67.55B in sales in 2020.]

We’re really excited to welcome JT Kostman. Join us at FORGE Blue Sky.