The global chemical sector is chasing big-ticket digital projects while overlooking a lever hiding in plain sight: frontline execution. Across the industry’s largest manufacturers (>$5B revenue), annual sales exceed $1.2 trillion and maintenance averages ~3% of revenue—roughly $36 billion a year. Yet wrench time—the portion of a technician’s shift spent on value-adding work—often sits at 25–30%, while best-in-class reaches 60–65%. Even a modest improvement translates into billions in savings and immediate EBITDA impact.
As Sundeep Ravande, CEO & Co-Founder at Innovapptive, puts it, “You can’t hire your way out of this crisis—you have to execute your way out.” By 2035, roughly 30% of the chemical manufacturing workforce will retire, and projections suggest only half those roles will be refilled. Add Chinese oversupply, elevated energy costs, and constrained capital, and the old playbook of hiring or outsourcing more labor breaks down. The only scalable option is to do more with less—and do it far better.
The competitive lesson appears outside chemicals, too. In AI, challengers have beaten better-funded rivals not by buying pricier hardware, but by optimizing compute and workflow. The parallel on the plant floor is direct: the winners won’t be those with the biggest digital portfolios but those who systematically strip out wasted motion, waiting, rework, and paperwork.
At many plants, technicians turn wrenches fewer than three hours in a ten-hour shift. Time evaporates chasing permits, hunting for parts, walking between units, awaiting approvals, or deciphering unclear job plans. Double wrench time from ~30% to ~60% and the math flips: organizations can meet targets without adding 30% more headcount, and O&M costs fall materially—often up to 30%—while uptime and safety improve.
The fix isn’t another siloed app. It’s a unified execution layer that binds operations, maintenance, EHS, quality, and stores into one real-time flow: parts pre-kitted and staged before work starts; mobile and AI guidance to remove guesswork and bad handoffs; data captured once at the source and structured for KPIs, RCA, and PM optimization; closed-loop feedback that tightens plans and eliminates repeat failures. When execution is unified, wrench time climbs, labor dependency falls, and cost transformation becomes sustainable—not theoretical.
Too many digital portfolios focus on optics—digital twins, dashboards, AI pilots. Valuable, yes, but they won’t move near-term EBITDA if frontline execution remains broken. Durable gains require governance and discipline – think a Manufacturing Excellence Council, standard work, and poka-yoke data practices from work request through feedback – so technology, process, and culture reinforce each other.
For executive teams deciding where the next dollar goes, three questions cut through the noise:
- Will this materially increase wrench time and asset availability in the next 6–12 months?
- Does it reduce dependency on scarce labor instead of adding coordination burden?
- Is it eliminating waste—not just instrumenting it?
“Constraints don’t slow innovation—they force it,” Ravande said, drawing a line from benchmark-beating AI efficiency to plant-floor reality. The capital-light path to capacity is execution excellence.
Reframe wrench time as a profit lever, not a metric. A 10% maintenance-cost reduction across top players implies a $3.6B annual unlock—and at the site level, it’s common to see $50–$100M+ in EBITDA improvement across a footprint once unified execution takes hold. “Wrench time is the fastest, fairest way to buy back capacity and margin,” Ravande said. “It’s where transformation stops being theater and starts paying the bills.”
