Zero100 Forum: AI for Supply Chain in Three Words 

Last week, Zero100 hosted 100 chief supply chain and operations officers on a two-day sprint to solve AI for supply chain. We explored diagnostic data, emerging use cases, and heard an incisive, worldly perspective on our turbulent times from former UK Prime Minister, the Rt Hon Sir Tony Blair.  

And we’ve landed on three words to sum it up. 

Science: In the Land of Anecdote, Data Is King 

Nvidia’s stock is up 191% since ChatGPT’s launch in November 2023. As the bellwether for AI stocks, this data point confirms what everyone from Mr Blair to our guest speakers, panelists, and attendees affirmed at Forum: AI for supply chain is huge. 

Zero100 data showed correlations between AI leadership (measured in job descriptions, earnings call transcripts, employee LinkedIn profiles, etc) and KPIs, including revenue growth, margins, EPS guidance accuracy, and progress on decarbonization. Plus, data describing a meta-analysis of 544 AI use cases shows progress across the end-to-end supply chain, with visible public examples of Shein, Procter & Gamble, Temu, and Lenovo achieving enormous productivity gains. 

And yet, many are still searching for a one-pager to galvanize the C-suite and mobilize resources. Some attendees saw promise in an AI Blueprinting framework Zero100 members are pioneering to choose and champion the vital few smart AI bets instead of hosting an AI science fair. 

Practical: It’s Still About People 

One of the top-scoring sessions of the show was about Andi, an imaginary supply chain team member with all the right stuff for our digital future. This was presented by Lauren Acoba, a ten-year Starbucks veteran who joined Zero100 as Principal Researcher last year. The session opened by highlighting the yawning gap between AI vision and AI results described by CEOs on Q1 2024 earnings calls – 88% talked vision, but only 25% could cite results. 

The key to closing this gap is people – a very different kind from the classical supply chain person hired over the past 20 years. Andi, our imaginary 2030 supply chain star, is intentionally in transition:

• from project manager to product manager, able to deliver and improve ops tech the way people really use it. 
• from subject matter expert to prompt engineer, able to use genAI tools to get a fast start on creative problem solving. 
• from a focus on communication to an obsession with agility, curiosity, and integration, able to lead tech and process innovation.

In fact, an analysis of 414,000 job posts from 243 companies shows just how fast the old skills are fading and how quickly the new skills are rising.  

Practical thinking about AI for supply chain certainly includes getting one’s data house in order, building trust with good tech partners, and, of course, locking in a solid ROI plan, but all of these depend on having the right team.  

People are the first ingredient. 

Leapfrog: No Longer a Game of Inches 

AI for supply chain is part of a wider moment of faith – among investors, operators, and even governments – in this tech revolution and its power to unlock massive efficiency gains. Even though most ops leaders are still working through the digital transformation of their ERP and legacy systems, it would be a mistake to sit idle as this movement gains momentum. 

The closing presentation of the event (also a huge audience favorite) was delivered by Steve Hochman, a ten-year Nike veteran and supply chain entrepreneur who joined Zero100 as a Research VP in 2022. His story described a framework, stolen in part from the great American explorers Lewis and Clark and in part from Jeff Bezos, which sets a mega-goal and works backwards through the necessary steps, solutions, and breaks that need to happen along the way. 

Using examples like Amazon vs Toys R Us ($1.6T vs $0 market cap) and iPhone vs Blackberry ($2.6T vs $0 market cap), the session crystallized three steps to attack the opportunity of AI for supply chain: 

• Set a strategy under extreme uncertainty by using Amazon’s PRFAQ and working backwards approach. 
• Organize for fast learning and scale by using the Star model of hybridized central control. 
• Deploy using an accountability framework tuned to the special needs of AI for supply chain. We call it a Fusion Workflow. 

This Is a Once in a Generation Opportunity 

Science – Lead with facts. 

Practical – Start with people. 

Leapfrog – Think and act big.