Stop Measuring Motion: How Caterpillar, Hilti & Kaeser Escaped the Utilization Trap

In heavy industry and professional services, the metrics that run delivery—utilization, billable hours, first-time fix rates—increasingly work against the outcomes and revenue growth they were meant to produce. Here is how to tell the two apart, what the best industrial companies actually measure instead, and how to rebuild the scorecard before AI forces the issue.

The Two Families of Service Metrics

Family One: Delivery Metrics Measure Motion These answer "how efficiently are we working?" In field services: first-time fix rate, mean time to repair, response time, SLA compliance, equipment uptime. In professional services: billable utilization, rate realization, project margin, on-time delivery, revenue per consultant.

These metrics are seductive because they are easy to capture, respond quickly to management pressure, and sit entirely within the service team's control. But every one of them measures motion, not value. A technician with a 95% first-time fix rate on the wrong root cause is efficient and ineffective. A consultant billed at 90% on work the client never adopts is fully utilized and worthless.

Family Two: Outcome and Growth Metrics Measure Value These answer "did the customer get the result, and did that result grow our business?" On the customer side: value realized, adoption, time-to-value, prevented downtime value. On the growth side: net revenue retention, service attach rate, contract renewal, expansion, aftermarket customer lifetime value.

This is where the economics turn serious. McKinsey finds aftermarket services carry an average EBIT margin of about 25% versus 10% for new equipment. Deloitte puts aftermarket operating margins at roughly 2.5 times those of new-equipment sales. Yet roughly three-quarters of industrial machinery makers still earn less than 20% of revenue from service.

How AI Is Breaking Traditional Service Metrics

AI has severed the link between effort and revenue. TSIA calls it the AI Value Paradox: when AI compresses the time required to deliver a result, any business that prices and measures itself by hours watches its revenue shrink precisely as it improves. Utilization becomes a broken metric—automation strips out routine billable work, technicians log fewer hours while solving harder problems, and utilization falls even as profitability and customer outcomes rise.

The proposed replacement: measure absorption—value and revenue delivered relative to cost—instead of utilization, which only measures time spent.

What Measuring Value Actually Looks Like

Caterpillar manages to an explicit growth number: a target of $28 billion in services revenue by 2026, up from roughly $14 billion in 2016. It sells about two-thirds of new machines with Customer Value Agreements that lock in future parts and labor. Customers using its digital tools spend up to 33% more on aftermarket services and stay longer.

Hilti rebuilt its business model entirely: instead of selling tools, it manages tool fleets for a monthly fee—roughly 1.5 million tools under management, with customer retention around five times higher than in the old sales model.

Kaeser does the same with air: customers buy compressed air by the cubic meter rather than buying a compressor, and Kaeser is measured on the outcome it guarantees.

These models align provider incentives with customer outcomes. Under outcome-based models, the provider earns more the more reliably its equipment runs.

Why Growth Metrics Need Governance and Culture

Here is the danger: once "grow service revenue" becomes the goal, the easiest lever is not better outcomes—it is squeezing a captive installed base. Raise parts prices, force bundles, lock in contracts. A revenue-growth metric will happily reward that, because the number cannot tell the difference between value created and value extracted.

The evidence that greed backfires is hard to ignore. OEM parts are commonly priced 30–50% above independent alternatives, and the installed base is voting with its feet. The independent aftermarket already accounts for roughly three-quarters of US automotive parts sales. Outcome-based models are built entirely on the customer believing you are optimizing their result and not your take. That belief is produced by governance and culture.

How to Rebuild the Service Scorecard in Three Steps

1. Reclassify delivery metrics as constraints, not goals. Utilization, MTTR, fix rate become guardrails you hold above a floor—not targets you maximize.

2. Promote outcome and growth metrics to the top of the dashboard. Make net revenue retention, aftermarket lifetime value, absorption, attach rate, renewal, and prevented-downtime value the numbers leadership manages to.

3. Move up the maturity curve deliberately, and give service its own P&L. Top-maturity service organizations show dramatically higher revenue growth and profit margins—differences measured in multiples, not points.

What Service Leaders Should Measure Instead

Pull up your service dashboard and count. How many metrics measure motion—how busy the team was, how fast it closed, how utilized it stayed? And how many measure value—what the customer achieved, and how much the service business grew as a result?

For most organizations the ratio is embarrassing. The service department is no longer the cost of having sold a machine; it is the highest-margin, most defensible engine the company owns—and you cannot run that engine on a dashboard built for a repair shop.

AI is about to make this unavoidable. The organizations still measuring motion will watch their numbers deteriorate while doing everything "right." The ones measuring value—outcomes delivered and growth generated, honestly, the way Caterpillar, Hilti, and Rolls-Royce already do—will finally see what their service work was worth all along.