Talking Supply Chain: Why Automation Feasibility Should Guide Supply Chain Decisions

Talking Supply Chain: Why automation feasibility should guide supply chain decisions

TMX's Jeff Bornino and Nick de Klerk, join influential industry voice Brian Straight.

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Supply Chain Management Review

Published

8 January 2026

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LISTEN HERE: Talking Supply Chain: Why automation feasibility should guide supply chain decisions

As supply chain leaders confront rising labor costs, workforce shortages, and global uncertainty, automation is increasingly seen as both an opportunity and a risk. In this episode of Talking Supply Chain, host Brian Straight speaks with Jeff Bornino, president of North America at TMX Transform, and Nick de Klerk, senior director, about why automation decisions must start with feasibility, not enthusiasm for the latest technology. The discussion emphasizes that rushing into large capital investments without fully understanding operational needs often leads to costly mistakes that can burden organizations for decades.

Bornino stresses that automation feasibility studies help companies avoid what he calls “the modern million-dollar paperweight.” Rather than jumping straight into implementation, organizations need to evaluate their current operations, growth projections, and long-term labor realities. Automation, he notes, is no longer driven solely by cost reduction but increasingly by labor availability, service reliability, and the need to future-proof operations in an environment where finding workers for physically demanding warehouse roles is becoming harder each year.

De Klerk adds a technical perspective, outlining how feasibility studies rely on detailed operational data to determine whether automation is truly warranted. By examining what materials are handled, how much volume moves through a facility, how fast operations must run, and how work is performed, companies can match the right technology to the right problem. He cautions against assuming that a single automation solution can be replicated across an entire network, noting that differences in labor markets, real estate costs, and regional conditions can dramatically change the optimal design.

A central theme of the conversation is the growing role of digital twins and AI-driven simulation in reducing risk. By testing multiple “what-if” scenarios, companies can evaluate automation options before any equipment is installed. Both guests argue that this approach not only improves ROI but also helps executives and boards gain confidence in their decisions, shifting automation from a leap of faith to a data-backed strategic move.

This article and podcast were originally published in Supply Chain Management Review on January 8, 2026.

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