THE TRANSFORMER
“bifocal” supply chain practitioners— versatilists who can manage work up close and personal day-to-day, then flip the switch after “end of quarter” and support other forward-looking projects. For inspiration, they should look at how data culture has evolved. Analysts, engineers, scientists, and translators/ journalists often double hat, flowing to work and need. Incentivizing employees to stretch roles is key. As one example, CPG manufacturer Unilever created an internal job marketplace to help individuals develop new skills. Teams in need of flexible resourcing created specific roles/tasks. Employees with extra bandwidth could apply for “gigs” and expand their developmental goals. The challenge with this type of program is administrative. Leadership needs to buy into the idea employees are not contributing 100% to one role. Similarly, key performance indicators (KPIs) have to be aligned to encourage double-hatting. And lastly, HR needs to identify ways to track and measure performance across multiple teams, projects, functions, and managers. 4. Build a community of practice around AI and innovation. Articulating the What, Why, and How is the cornerstone of any change management endeavor. Rather than hide behind guarded language (co-pilot, human-in-the-loop, hybrid intelligence) and fears of job displacement, enterprises can embrace a future with AI by creating communities of practice where employees openly learn with and educate one another. This dovetails with the bottoms-up meets top-down co-creation approach. Employee experience platforms such as Microsoft 365 and Salesforce’s Slack provide space where employees can crowdsource and chat about news and trends. Candid conversations and dialog about AI and future use cases can allay employee concerns. It similarly serves as a feedback loop for leadership and HR to better understand concerns and identify new ideas for exploration. Building social communities of
Drawing inspiration from the Toyota Production System, modern talent development embraces a demand-driven approach centered on skill set diversity and flexibility. By cross- training employees to manage multiple processes, as Taiichi Ohno pioneered, organizations can level-set demand and build an adaptable workforce.
ways of working before mainstream scaling. This follows the sequencing innovation paradigm. Again, perhaps the past portends the future. Ohno’s view of Jidoka (Autonomation) was both reactive and proactive. It’s a principle that translates to “automation with a human touch.” Sound familiar? Technology detects errors, then humans intervene and course correct before those mistakes are replicated down the line. AI will no doubt supersede Ohno’s elegantly simple ideals. But his instructions are worth reflection. Human-in-the-loop AI presents a burning platform to transform supply chain culture. What is culture? It’s the instinct to behave and act in a certain way without thinking about it. Like Jidoka, enterprises that take the time early on to learn, iterate, and recalibrate with the human at the center of their AI designs will realize sustaining value in the long run.
practice also helps underscore the importance of upskilling. Employees should be encouraged to share their experiences, helping to validate the best learning and training curricula. In a positive way, peer pressure can sway others to want to learn. Much of what Taiichi Ohno created in the Toyota Production System was inspired by others: learnings from his predecessor Sakichi Toyoda’s auto- activated textile weaving machine as well as Henry Ford’s moving assembly line. He was a bricoleur who borrowed from the past to drive a new vision for the future. The impact of AI on business culture is at the forefront of today’s corporate conundrum: Do enterprises react to how technology changes the way they do business? Or do they proactively shape new ways of working in concert with AI? It’s not a simple answer. One might argue organizations need to react first, capture learnings, then proactively rethink processes, roles, and
Footnotes 1 Gartner, Gartner Says AI Ambition and AI-Ready Scenarios Must Be a Top Priority for CIOs for Next 12-24 Months (2023) 2 Joe O’Reilly, The Evolution of Inbound Logistics (Inbound Logistics, 2008) 3 Gartner, Inside the Concept of Versatilists: What Are They and How Do CIOs Develop Them? (2008) 4 OMP, How P&G is building the supply chain of the future, one decision at a time (2026) 5 Gartner, Survey Shows Just 36% of Chief Procurement Officers Are Very Confident in Ability to Redesign Function for AI (2026)
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