I suspect that this point of view may be somewhat against the current zeitgeist towards AI-driven productivity, but I do believe that there is such a thing as too much efficiency.
A good example of this happened in 2011 when the Tōhoku earthquake and tsunami devastated parts of Japan, and Toyota’s supply chain was hit hard. In April of that year the company’s production fell by 78% y-o-y, quarterly profits plunged 99% y-o-y, a number of their manufacturing sites were closed for almost two months, and global production was materially impacted by a shortage of over 150 different parts that were produced in the affected regions.
The disaster revealed a multitude of supply chain vulnerabilities. At the time, 45% of Toyota’s vehicles were built in Japan, and specialist suppliers in hard hit regions of Japan saw their factories destroyed, halting the supply of crucial electronic components.
The earthquake had highlighted the dangers of having too much production concentrated in one region, leading to a major overhaul of how the company managed its suppliers. But it also revealed the hidden risks of not having any spare capacity. The company that had invented Just-in-Time manufacturing, the global benchmark for lean efficiency, found itself unable to produce cars because there was no back up inventory.
So Toyota went about building more slack into the system. It required suppliers to hold months of inventory. It diversified its supplier base across multiple geographies. It invested in visibility and flexibility that, during normal operations, would look like an expensive and unnecessary luxury. In short, they built resilience into the system. The company that had taught the world to eliminate waste, had learned the hard way that some kinds of waste aren’t waste at all.
With AI, the dominant narrative right now is about eliminating friction, removing redundancy, automating anything that looks like unnecessary human effort. If we take this to its logical conclusion the hidden risk is that we’ll be using AI to the eliminate the excess capacity that allows an organisation to absorb shocks, experiment with new ideas, and respond to unexpected opportunities.
Let’s not forget that some inefficiency can be helpful.
A version of this post appeared on my weekly Substack of AI and digital trends, and transformation insights. To join our community of over thirteen thousand subscribers you can sign up to that here.
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Image: Bertel Schmitt, CC BY-SA 3.0 via Wikimedia Commons
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