This was originally posted on Logistics Viewpoints.
UPS dominated business and trade headlines for a day in late January when the world’s largest package delivery company announced plans to cut 12,000 full- and part-time management jobs as part of a new initiative called “Fit to Serve.”
What stood out even more was the “subhead” of UPS’ announcement. As reported by The Wall Street Journal, “Those jobs weren’t likely to return even when business picks up,” UPS said, adding that the reductions are part of what would be “new ways of working.” (Emphasis mine.)
Meanwhile SAP jumped to an all-time high based on a bullish forecast of double-digit growth in cloud revenue. But the good news came with a price: the company said it will spend roughly $2B restructuring “8,000 jobs to either retrain employees with AI skills or to replace them through voluntary redundancy programs.” Google, Microsoft and others have announced similar moves.
Allow me to translate: “New ways of working” and “retraining” = doing more with less.
In other words, boosting productivity has rapidly emerged as the overarching mandate in business going forward — and AI is widely seen as the rocket fuel for launching productivity into the stratosphere.
Make no mistake: AI is indeed a once-in-a-generation technological paradigm shift and a transformative force for business reinvention. But AI is no panacea. The companies who will achieve the biggest gains in productivity will implement AI through the dual lenses of business process reengineering and change management.
I’ll give you a recent example from my business, which enables real-time supply chain visibility, with AI-powered predictive insights and analytics, for the world’s largest shippers and their partners.
I was speaking with the Chief Supply Chain Officer at one of the world’s largest CPG companies. One minute, he conveyed how productive his workforce is, but a moment later, I was scratching my head when he told me that their biggest issue going forward is “ironing out scheduling issues.”
What?
It took some digging to understand that despite the substantial productivity gains we’ve enabled to-date, further gains would require additional business process reengineering. As it turns out, there are a certain number of “scheduling use cases” that require a warehouse manager to leave our system and work within another vendor’s app. That’s a drag on time and resources. To address these additional use cases, you have to deeply analyze the workflows between business functions and systems, identify the gaps, redesign the process — and then use IT (and AI) to integrate the systems and automate the process.
AI presents nearly limitless opportunities to boost the productivity of supply chain professionals across every industry, every team and every need. Take onboarding and training new employees. With tools like GenAI, new workers can get real-time answers to questions and highly-personalized training. It’s easy to imagine a faster and more efficient path to productive work.
Or consider the potential for radically more user-friendly interfaces to enterprise applications. Even today’s most simplified “single-pane-of-glass” enterprise applications require that workers are well-versed in the system’s features and functions and trained to get the data and insights they are looking for. Tomorrow’s apps promise an interface that’s as clean and simple as a Google search bar. Users will simply pose their questions and the system will do all of the hard work “under the hood” to return workflow-specific insights and recommended actions.
The race is on to harness AI to achieve quantum leaps in productivity — but success also hinges on investing time, energy and resources in change management. Without a robust commitment to managing these profound changes in how people work, technology initiatives will fall flat if not fail entirely.
So what are some of the fundamental characteristics of sound change management?
Executive sponsorship at the C-level is a pre-requisite to any significant change initiative — in part because real change invariably cuts across multiple internal organizations, leaders and teams. And if one team doesn’t cooperate or fully embrace the change, everything breaks down (not unlike supply chains during a disruption).
Similarly, creating a cross-functional governance structure is key, with representatives from every impacted department playing an active role in the rollout of new initiatives.
Metrics are critical as well. But be wary of setting “moonshot goals” that may take years to achieve. Set milestones that can be achieved in two weeks, a month, a quarter — and then go from there.
Lastly, company leaders and managers must have the courage and fortitude to accept short-term disruptions. Often, true transformation might mean that your pace temporarily slows as the organization adjusts and refines to its new methods. But this is a strategic deceleration, one that promises greater speed and accuracy in the long run as you build a more robust, resilient, and productive operation.
Real change requires more than deploying the latest technology, however powerful. It takes an organization-wide commitment, resources and time — with great care taken to redesign the old ways of doing things, and to bring the workforce along for the journey.
