Editorial
Research Report
Building the Case for Modern Public Sector Messaging
The Gist
- What's the difference between delivery metrics and outcome/growth metrics? Delivery metrics measure motion — utilization, fix rates — while outcome and growth metrics measure value, like net revenue retention and lifetime value.
- Why is AI breaking traditional service metrics? AI decouples effort from revenue, so utilization falls even as automation increases profitability and customer outcomes.
- How are leading industrial companies rebuilding their scorecards? Caterpillar, Hilti and Kaeser subordinate delivery metrics to growth metrics like retention, recurring revenue and prevented downtime value.
In heavy industry and professional services alike, 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.
Every service organization I work with can tell me its billable utilization to the decimal point. Very few can tell me what a customer relationship is worth over its lifetime, or how much revenue growth their service work actually generated last year. That asymmetry is not an accident. It is the result of measuring what is easy to count instead of what is hard to create — and it is quietly costing the industry a fortune.
We are living through the proof. According to SPI Research's Professional Services Maturity Benchmark, billable utilization has fallen to record lows around 66%, well under the 70–75 % healthy range, while EBITDA margins have slid into single digits. Firms are managing their delivery dashboards harder than ever, and the dashboards are getting worse. When the metrics you worship stop moving in your favor no matter how hard you push, the problem is rarely effort. It is that you are measuring the wrong things.
There are two fundamentally different families of service metrics, and most organizations have built their entire management system on the first while neglecting the seccond.
Family One: Delivery Metrics Measure Motion
Delivery metrics answer the question how efficiently are we working? In field and industrial services that means first-time fix rate, mean time to repair, response time, SLA compliance and equipment uptime. In professional services it means billable utilization, rate realization, project margin, on-time delivery and revenue per consultant.
These are good metrics, and they are seductive for three reasons: they are easy to capture, they respond quickly to management pressure and they sit entirely within the service team's control. A manager can move fix rate or utilization this quarter through scheduling and discipline. That controllability is exactly why they dominate the scorecard — and exactly why they mislead.
Because every one of these metrics 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. SPI's data makes the point at industry scale: project overruns have risen even as firms chase efficiency, because efficiency pressure breeds scope creep, burnout and rushed delivery — the very things that destroy the outcome. Motion and value are not the same, and maximizing one can actively erode the other.
Family Two: Outcome and Growth Metrics Measure Value
The second family answers a different question: did the customer get the result, and did that result grow our business? On the customer side sit measures like value realized, adoption, time-to-value and — in industrial settings — prevented downtime value, the financial worth of failures caught before they happen. On the growth side sit net revenue retention, service attach rate, contract renewal, expansion and aftermarket customer lifetime value: the total revenue earned from servicing an installed asset across its life.
This is where the economics turn serious. McKinsey finds aftermarket services carry an average EBIT margin of about 25% versus 10% for new equipment, with parts gross margins routinely above 30%. Deloitte puts aftermarket operating margins at roughly 2.5 times those of new-equipment sales. And BCG frames the aftermarket as one of manufacturing's most reliable growth engines — precisely because it compounds off the installed base rather than the order book.
Yet, tellingly, industry research suggests roughly three-quarters of industrial machinery makers still earn less than 20% of revenue from service, even though service revenue tends to grow far faster than new-equipment sales. The gap between what service is worth and what firms measure is the largest untapped lever in industry.
Related Article: What Separates the Best and Worst Customer Service
Rebuilding the Service Scorecard: Key Shifts and Actions
Editor's note: The following table highlights the most important lessons, actions and strategic considerations emerging from the shift from delivery-based to outcome-based service metrics.
| Key Area | What Happened | Why It Matters | Recommended Action |
|---|---|---|---|
| Delivery Metrics | Billable utilization has fallen to record lows (~66%) even as firms manage it harder than ever | Efficiency metrics measure motion, not value, and are now diverging from profitability | Reclassify delivery metrics as guardrails, not targets |
| AI Impact | AI decouples effort from revenue by automating routine billable work | Time-based metrics like utilization break down as hours fall while outcomes improve | Adopt absorption (value/revenue relative to cost) instead of utilization |
| Growth Metrics | Aftermarket service carries roughly 2–2.5x the margin of new equipment sales | Most industrial companies still under-measure and under-monetize the installed base | Promote net revenue retention and aftermarket lifetime value to top-line KPIs |
| Governance Risk | OEMs pricing parts 30–50% above independents are losing share to third-party providers | Growth metrics alone can reward value extraction instead of value creation | Pair growth targets with pricing transparency and customer-outcome governance |
How AI Is Breaking Traditional Service Metrics
For most of the industry's history, the tension between motion and value stayed hidden, because effort and revenue were loosely correlated: more billable hours, more fix visits, generally meant more money. AI has severed that link, and the severing is the most important measurement story of the decade.
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. In their field-services analysis, TSIA is blunt that utilization is becoming 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.
Their proposed replacement captures this whole argument: measure absorption — value and revenue delivered relative to cost — instead of utilization, which only measures time spent. One counts whether people were busy. The other counts whether the work was worth doing.
What Measuring Value Actually Looks Like — the Industrial Evidence
This is not theory. The heavy-industry companies pulling ahead are the ones that stopped scoring service by motion and started scoring it by outcomes and growth.
Caterpillar is the clearest example. Rather than measuring dealer service by activity, 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 now sells about two-thirds of new machines with Customer Value Agreements that lock in future parts and labor, converting one-off sales into measured, recurring service relationships. And Caterpillar reports that customers using its digital tools spend up to 33 percent more on aftermarket services and stay longer — an outcome-and-growth metric, not a fix-rate.
Hilti went further and rebuilt the business model itself. Instead of selling tools, it manages tool fleets for a monthly fee — roughly 1.5 million tools under management, on three-to-five-year contracts, with customer retention around five times higher than in the old sales model. Hilti stopped measuring tools shipped and started measuring retention and recurring revenue; the shift took more than fifteen years of change management and carried the company through the 2008 construction collapse.
Kaeser did the same with air: through its SIGMA Air Utility model, customers buy compressed air by the cubic meter rather than buying a compressor, and Kaeser is measured on the outcome it guarantees, not the hardware it ships. Both echo the archetype — Rolls-Royce's "Power by the Hour" / TotalCare, where airlines pay per flight hour and the manufacturer earns more the more reliably its engines run. Under these models, provider incentives and customer outcomes finally point the same direction.
The lifetime-value logic shows up on the balance sheet, too. Industry analysis documents that Baker Hughes earns one to two times the original-equipment revenue over a machine's life through service contracts, and Chart Industries runs repair-and-service margins near double its equipment margins — while countercyclical aftermarket exposure keeps revenue steady when orders stall. These are companies measuring the annuity, not the transaction.
Packaging and filling machinery shows the same divide. Tetra Pak frames its predictive-maintenance service around uptime protected rather than visits performed, reporting roughly 130 additional production hours a year for an average plant: a prevented-downtime-value metric, not a visit count. Krones organizes its offer around Lifecycle Service and its KRONES.digital line-performance software — the language of the machine's whole life and the customer's output, not the individual repair. In a sector where a high-speed filling line can lose hundreds of thousands of dollars for every hour it stands still, the installed base is a decades-long annuity that a delivery dashboard renders invisible and a growth dashboard makes central.
Why Growth Metrics Need Governance and Culture
Here is the danger buried inside everything above. Once "grow service revenue" becomes the goal, the easiest lever is not better outcomes — it is squeezing a captive installed base. Raise the parts price list, force the bundle, lock in the contract, and the margin lands this quarter. A revenue-growth metric will happily reward that, because the number cannot tell the difference between value created and value extracted; it only counts the money. That is why metrics alone are not a strategy, and why governance and culture are not soft accompaniments to measurement but the thing that keeps measurement honest.
The evidence that greed backfires is now 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, a majority of Western buyers now choose independent parts over OEM, and a large share of aftermarket executives expect margin compression ahead.
The pattern is seductive and self-destructive — pull the pricing lever, book the margin, report the result and watch customer defection, dealer workarounds and independent-channel share gain show up one to three years later, by which point the decision that caused them is forgotten. Consultancies describe the same slow bleed as aftermarket "leakage": decades of OEMs treating the installed base as a margin faucet while independents — cheaper, faster, easier to deal with — quietly took the relationship. Even McKinsey, the loudest voice on aftermarket profitability, is explicit that OEMs routinely lose ground to third-party providers despite owning the product knowledge and the data.
Why Trust, Not Just Metrics, Determines Whether Growth Metrics Work
So the annuity you were measuring evaporates precisely because you optimized the number instead of the relationship. This is where measurement meets trust — the same relationship integrity that determines whether a customer will keep letting you service their machines at all. Outcome-based models, the highest-value endpoint of the whole framework, are built entirely on the customer believing you are optimizing their result and not your take. That belief is not produced by a metric. It is produced by governance and culture:
- Governance means a clear owner for the question are we growing by creating value or by extracting it? — plus fair, transparent, defensible pricing, auditable service standards and someone accountable for the customer's outcome, not just the quarter's margin.
- Culture means the operating instinct that the customer's outcome comes before the quarterly take — because leaders who chase the extraction number always find it and always pay for it later.
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The practical implication is that a mature service scorecard needs a third layer sitting above delivery and growth: guardrails that keep the growth metrics from curdling into greed. Fair-pricing discipline, transparency and customer-outcome ownership are not constraints on the growth engine. They are what stops the growth engine from consuming the installed base it runs on.
Related Article: Customer Health Scores Are the New CX Metrics That Matter
How to Rebuild the Service Scorecard in Three Steps
None of this means throwing out delivery metrics. A service organization that ignores fix rate, utilization and project margin will go broke feeling virtuous. TSIA's own guidance is to run "bridging metrics" — funding the present with efficiency measures while steering the future with value measures. The point is to subordinate family one, not delete it. Three concrete moves:
-
Reclassify delivery metrics as constraints, not goals. Utilization, MTTR, fix rate and on-time delivery become guardrails you hold above a floor — the discipline that keeps you solvent — not targets you maximize. Maximizing a floor is precisely how you manufacture scope creep and burnout.
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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. Caterpillar's Customer Value Agreements and Hilti's retention multiple work because those are the metrics the executive team actually watches. Follow the money into the installed base: BCG notes that ecommerce's share of parts sales, still only 5–10%, is expected to at least double by 2030 as aggregators steer demand to whoever makes buying easiest — a growth pool that only shows up if you are measuring it.
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Move up the maturity curve deliberately, and give service its own P&L. SPI Research finds top-maturity service organizations show dramatically higher revenue growth and profit margins than the least mature — differences measured in multiples, not points. The companies that made the leap — Hilti, Kaeser, Caterpillar — did it by treating service as a business with its own economics and its own scorecard, not as a cost tail on the product.
The endpoint is outcome-based commercial models, where the measurement question and the commercial question become one: the provider earns only when the customer's result is real. For a mid-sized packaging or filling-machinery OEM, the practical first step is smaller and immediate — calculate aftermarket lifetime value per machine line, measure attach and renewal across the installed base, and put a prevented-downtime-value figure next to every fix rate on the dashboard.
Common Questions About Service Metrics and AI's Impact on Utilization
Editor's note: The following answers common reader questions about the shift from delivery metrics to outcome-based service metrics.
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, and it explains why their delivery has never been tighter and their growth has never been slower. In heavy industry and professional services alike, 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. As effort decouples from revenue for good, 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. The metrics you choose are not a reporting decision. They are a decision about what kind of business you intend to become.
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