MHI Solutions Improving Supply Chain Performance
Supply chains are investing heavily in AI, automation and advanced analytics, yet workforce skills are not keeping pace, limiting the return on technology spend. Leading experts from academia and research organizations share strategies for closing this gap, including designing targeted upskilling programs, avoiding common pitfalls and measuring real business impact.
BY , CHIEF MARKETING OFFICER, MHI
SUPPLY CHAINS TODAY are awash in data and technology: artificial intelligence (AI), advanced analytics, automation platforms and cloud systems promise greater visibility, responsiveness and efficiency than ever before. Yet for all the dollars flowing into these digital tools, companies are struggling to unlock their full value because workforce capabilities lag behind technological adoption.
Indeed, research from ZipDo found that 52–68% of supply chain managers report skills gaps that impede agility and digital transformation. Further, fewer than one in five organizations have a formal AI strategy in place—leaving much of the potential of modern tools untapped.
According to Gartner, 60% of digital adoption efforts in supply chain will fail to deliver promised value by 2028 due to insufficient investment in learning and development. Clearly, technology alone is no longer the bottleneck—people are, too. The central challenge for leaders, then, is not just selecting the right platform but pairing that platform with the right talent strategy.
Here, six leading experts from academia and research organizations share insights into how organizations can close the digital skills gap by better aligning their tech spend with talent investment. They discuss the most pressing skill deficiencies, how to structure upskilling initiatives, common pitfalls and the measurable outcomes that matter most.
WHERE THE DIGITAL SKILLS GAP IS MOST ACUTE
In supply chains across multiple industries, fundamental deficits persist not because companies lack tools, but because employees have not learned to use them effectively, said Kapil Dev Bansal, associate partner with McKinsey & Company.
“Companies have a lot of data, but they lack the skill sets for getting the outputs that help them move the needle,” he said, confirming that the ability to derive meaningful insights and act on them remains scarce.
This shortfall shows up in technical areas like data analytics and predictive modeling, but also in the broader way teams understand the implications of technology on real operational workflows. Bansal and his McKinsey colleague Rahul Shahani, a partner and global leader of tech enablement for McKinsey’s Manufacturing and Supply Chain Practice, grouped the gaps into three core categories: analytics and data fluency, digital risk and resilience, and practical integration of technology with supply chain processes.
“While many supply chain teams use forecasting and predictive tools, turning insights into day‑to‑day decisions remains a challenge. Through our work with frontline teams, we’ve developed a task‑goal‑orchestrator agent framework that aligns narrow automations to business outcomes and coordinates them across the supply chain. When digital tools are embedded into core processes, they become part of the workflow, rather than an add‑on,” said Shahani, who noted this uncertainty hinders adoption and undercuts the tangible return leaders expect from their digital investments.
Marin Heiskell, senior manager focused on human capital in Deloitte’s Organization, Workforce and Change Practice, identified gaps in AI deployment, automation and real‑time platform integration.
“These solutions reduce errors, lower costs and improve response speed,” she said. “Their underutilization can lead to higher operational risk and lost efficiency.”
Heiskell also highlighted the increasing importance of cybersecurity skills. “As we know, one breach can disrupt an entire supply chain,” she said. “Insufficient cybersecurity capability leaves supply chain teams vulnerable to data loss, operational downtime and reputational damage.”
DESIGNING EFFECTIVE UPSKILLING PROGRAMS
If identifying skill gaps is the starting point, the next challenge is designing upskilling programs that actually close them. Across interviews, the experts agreed that high‑impact workforce development must be anchored in business relevance, reinforced through real work and tailored to how supply chain roles actually operate.
Heiskell stressed that upskilling programs only deliver value when they are tightly aligned with business strategy. “The skills you build have to map directly to your supply chain’s digital transformation roadmap and broader organizational goals,” she said. “That starts with creating role‑based learning tracks—planners, procurement, logistics and leaders all need different levels of digital capability and different learning outcomes.”
Successful upskilling programs go beyond technical training, Heiskell added. “You have to blend digital skills with soft skills like change leadership and collaboration, because adoption is ultimately a cultural challenge,” she explained. “The most effective programs use multiple learning modalities, encourage peer learning and mentorship and put people in real scenarios where they solve actual supply chain problems using new tools.”
Further, Heiskell emphasized the importance of measuring improvement. “Companies need to track not just participation, but real performance improvements—cycle times, error rates and productivity gains—so learning is clearly tied to business impact.”
Several experts stressed that how learning happens matters as much as what is taught. Mel Mohamednur, director analyst in Gartner’s Supply Chain Practice, warned against treating upskilling as a one‑time training event.
“Upskilling isn’t just about buying off‑the‑shelf training programs. It’s about turning knowledge into practical skills. Information alone isn’t enough. Mastery comes from consistent performance, especially under pressure,” she said, adding that experiential learning—through job shadowing, project rotations or stretch assignments—builds both confidence and adaptability in real operating environments.
PITFALLS TO AVOID WHEN CONNECTING TECH INVESTMENTS TO WORKFORCE READINESS
When organizations attempt to link digital transformation efforts with workforce readiness, several recurring pitfalls can undermine even the most advanced technology investments.
Vince Castillo, Ph.D., assistant professor of logistics at The Ohio State University, stressed the importance of change management as part of an investment in digital tools.
“When companies buy new technology solutions—especially AI subscriptions—sometimes I wonder whether they fully understand why they’re making the investment,” Castillo said. “Leaders need to understand what AI can do, what it can’t do and how it actually supports the broader corporate strategy. Too often, that strategic connection is missing.”
Castillo warned that simply layering new tools onto existing workflows without clear purpose or communication is unlikely to succeed. “If the reason for the technology isn’t made clear, and if it isn’t rolled out in the right way, adoption becomes very difficult,” he observed. “With AI in particular, companies often ask employees to interact with new systems and feed them data without addressing very real concerns about job displacement.”
According to Castillo, acknowledging employee fears and clearly communicating how technology will be used are essential components of effective change management. “Understanding people’s concerns, alongside the capabilities and limitations of the technology, is paramount to improving skill development and increasing adoption.”