The WSJ had a super interesting piece about the impact of AI on supply chains where the authors posit that AI is going to upend Wright’s Law.
Wright’s Law states that as production number increase, costs decrease by a steady and predictable amount. For any given process it’s often stated something like ‘as production doubles, costs will decline by 20%.’ The percentage cost reduction will vary, but it’s usually steady enough to be predictive so people use Wright’s Law to model costs across multiple industries.
The authors thesis is that AI is going to create step changes in cost reductions that will cascade and continue through supply chains. Instead of learning through experience, AI will test and recommend the best paths. And because supply chains are massively interconnected systems, as each node in the network improves with AI, the costs will decrease faster.
At first blush for brands, this all sounds great. COGS go down; margins go up. Ca-ching!
But your margin is my opportunity as a famous ecomm person once said. So what happens when competitors start figuring out the efficiencies? I think we see a repeat of facebook/Meta except 10X faster. Back in the day, some founders at some brands figured out how to arb facebook ad spend to rapidly grow their brands. Then everyone jumped in and the easy wins were gone replaced by an online global brawl among advertisers eking out pennies.
As the authors note, it’s the combination of AI fed by great data and human insight that will propel the winners. So what can brand leaders do to prepare, capture the early wins and then enable sustainable advantage?
Three big things jump out:
- Get their data in shape now. This means deciding how to bring the data together and make it available. The myriad ways to do this are beyond this post’s scope, but if you are still managing all your data in google sheets with a half dozen different owners, you have some work to do.
- Bring data analytics expertise in-house. Ops is going to become very data intensive. There is value in the old hands who know the vendors and where the fat is in the logistics chains, but if your analytics consists of everyone looking at a google sheet while someone toggles year over year growth assumptions, you need a real data person.
- Assess your supply chain vendors such as manufacturers and 3PL on their ability to get you the data you need. So much of the cost savings is hidden from you on purpose or just through lousy reporting. You can’t improve what you can’t see. So either force the divulgence of the data or prioritize data availability and transparency in future relationships.