Digital Transformation That Actually Scales (And Isn’t Rocket Science)

Plenty of companies can point to a “cool pilot” that never went anywhere. 

As Robert Schoeberger reports in Control, the difference between one-off experiments and scaled digital transformation isn’t rocket science, even when the industry involves actual rocket science. Schoeberger shares a perspective from Rockwell Automation SVP Tessa Myers, who gave the keynote address at this year's Automation Fair held in Chicago.

According to Myers, successful initiatives have three things in common: they put people at the center, measure more than cost, and start with projects big enough to matter across the business. Leaders who “start with the end in mind” spell out clear business outcomes, lead with transparency about challenges, and then empower teams with tools and training.

For example, at Canadian food maker Perth County Ingredients, that meant outfitting maintenance teams with tablets so they had the right information in hand. The result: reactive maintenance and after-hours calls fell by more than 50%, and work became more predictable, less stressful, and more strategic.

Myers also argues that many promising projects die in the boardroom because they’re justified only on cost. In a world of volatility, she urges executives to value agility, uptime, and resiliency alongside lean operations. Companies that think “boldly and broadly” about digital value are already seeing faster recovery from supply chain shocks, higher first-pass yield and quality, and less unplanned downtime.

Her final rule flips the usual “start small” advice: don’t dabble in trivial use cases. Instead, pick horizontal applications that can scale, like AI vision for quality inspection, automated material handling between lines and warehouses, or in-line process optimization using sensors and AI. A frozen French fry producer did exactly that, using predictive modeling and real-time monitoring to optimize cooking conditions, standardize output, and increase plant throughput without adding new lines.

Whether you’re running a food plant, a machine shop, or a services operation, the guidance is the same: clarify the outcome, involve your people, aim tech at shared pain points, and design use cases that can repeat across sites, shifts, and teams.

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