The performance test grades the operator on RevPAR Index. The operator doesn’t control RevPAR Index.
RevPAR Index is a relative measure — the property’s revenue per available room against its comp set’s average, as a percentage. Most performance tests require the operator to hold that number above a threshold — 85%, 90%, 92%, depending on the deal — or the owner gets termination rights.
The metric exists for a good reason. A market-relative benchmark is meant to separate the operator’s skill from the market’s luck: reward the operator for beating the comp set, not for riding a rising market, and don’t punish the operator when the whole market softens. That design is sound. The problem is narrower. Some of the biggest forces that move the index aren’t operator skill and aren’t the market’s tide. They’re specific decisions — a competitor’s, the owner’s — that the operator can’t touch.
A performance test is a fair measure only when the operator controls the inputs. When the number is driven by forces the operator can’t move, the test turns into a termination risk the operator carries but can’t manage. That’s the controllability principle: hold someone accountable only for what they can move. Tie termination to a number the operator can’t move, and the test stops disciplining performance. It starts allocating luck.
The operator is measured on a metric it doesn’t control, and carries that risk across the whole term.
Why RevPAR Index Puts Termination Risk on Forces the Operator Doesn’t Control
Two failure modes make it concrete. Both are mid-market realities — the daily experience of operators running 120- to 300-room select-service and regional hotels. Both show the index failing as a measure even when the operator runs the property well.
A New Competitor Opens Into the Comp Set
A new hotel opens down the block. New supply, rate compression, and the comp set’s average shifts. The property’s own RevPAR might hold steady or even grow in absolute dollars — but the index falls, because the baseline it’s measured against moved.
The operator’s number drops on someone else’s construction schedule. The operator didn’t choose the competitor’s opening, its rate positioning, or its ramp. Often the operator didn’t even choose whether the new hotel enters the comp set — that’s an owner decision, or a definition locked at signing. The index slides from 95% to 88% over eighteen months, and a prong that was clearing comfortably now fails.
Absolute performance didn’t change. Execution didn’t degrade. The comp set changed, and the index changed with it.
This isn’t hypothetical. New supply enters markets constantly. A secondary-market select-service hotel watches a 150-room competitor open two blocks away. An airport full-service hotel watches the market add 400 keys in a year. The set absorbs the supply, the average resets, and the operator carries the risk. The operator can respond — sharpen rate strategy, push occupancy, protect margin — but the response is reactive. The index moved on someone else’s decision.
The Owner Won’t Fund the Capex
The renovation that keeps the hotel rate-competitive is the owner’s call. The operator recommends it, builds the plan, shows the ROI — but the owner controls the budget and the timing. Defer it, and the property’s rate position erodes.
Meanwhile the comp set refreshes on its owners’ schedules. One property finishes a $3 million renovation. Another replaces case goods and soft goods. A third adds a lobby bar. The subject ages against the set. ADR slips, occupancy follows, the index declines.
The index falls on a budget the operator doesn’t control. A tertiary-market full-service hotel defers a refresh the operator has requested for two years. The ADR premium erodes, the index drops from 92% to 84%, and a comfortable prong now fails.
This is predictable, and it isn’t irrational on the owner’s side. Owners defer capex for cash flow, for portfolio-level capital allocation, for timing unrelated to this property’s competitive position. The operator can push, build the business case, and escalate through asset management — but the decision, and the consequence, sit on opposite sides of the table.
The owner can also define the comp set to include hotels punching above the subject’s weight — properties with more recent renovations, stronger brand positioning, better locations — setting the bar on a number the operator can’t reach. That’s a negotiable lever at bid stage. Once the HMA is signed, the definition is locked.
The Extreme Case: Convention Headquarters Asymmetry
The convention headquarters structure shows the same pattern at its most dramatic. Every operator sits somewhere on this spectrum; this is the far end.
Picture a convention headquarters hotel whose owner also controls the convention center’s booking calendar. The owner steers the citywide business that sets the hotel’s demand — the large conventions, trade shows, and association meetings that drive compression across the market and lift every hotel’s RevPAR in the busy periods.
The asymmetry is clean. The operator is graded on RevPAR Index. The owner controls the demand that drives RevPAR. The operator manages the property and delivers service, but doesn’t control the calendar — which events book, when, how many room nights they generate, how the demand spreads across the market. The owner controls the calendar, and the calendar controls the demand.
Here’s the sharp turn: owner-steered citywide business can actually depress the subject’s index.
The headquarters hotel commits room blocks at contracted rates, locked in months or years ahead of the compression. The comp set sells into that same compression at rack rate. So in the busy periods — the periods the owner controls — the headquarters hotel’s RevPAR lags the comp set’s, because it’s selling contracted blocks while the comp set sells transient at peak.
The index can fall in the busy periods. The periods the owner controls.
This is a recognized convention headquarters dynamic. The headquarters hotel absorbs the contracted business that anchors the event; the comp set captures the transient overflow at higher rates. The headquarters hotel’s RevPAR grows in absolute dollars — the compression lifts everyone — but the index can decline because the comp set’s RevPAR grows faster. The test measures the operator on a number that moves inversely to the owner’s decision to commit blocks at contracted rates.
And that decision is rational for the owner. Anchoring citywide events is the headquarters hotel’s whole strategic purpose; the contracted blocks are how the owner secures the calendar that fills the market. The owner is doing exactly what the asset is for. The operator just happens to be graded on a metric that dips when the owner does it.
The convention case is the extreme, but the pattern holds across the industry. Wherever the test grades the operator on a metric shaped by forces outside the operator’s control, the measure gets unfair. Here the owner’s control over demand is explicit; elsewhere it’s quieter. The comp set changes. The owner defers capex. Demand shifts on macro forces, airline route decisions, corporate relocations the operator doesn’t steer. The index moves, and the operator carries the termination risk.
The Operator’s Control Surface
The operator isn’t powerless. Two remedies matter.
Build the Prong the Operator Does Control
GOP margin is the operator’s own cost discipline — labor productivity, F&B cost ratios, energy, controllable expense. The operator moves these directly. Lifting the GOP margin prong into passing range gives the test a second, independent prong the market and the owner can’t steer.
Most HMA tests run two prongs: RevPAR Index and GOP margin. Both have to fail before termination rights trigger. So if the operator clears the margin prong, the test passes even when the index prong fails. The pass no longer rests entirely on a number the operator can’t control. That’s the multitasking insight in practice: when one measure is noisy and beyond the agent’s control and another is clean and controllable, put the operative weight on the controllable one (Holmström & Milgrom, 1991).
It’s not a complete fix — the operator still carries index risk, and a sustained index failure still hands the owner leverage even short of termination — but it’s a real risk reduction. It builds a second line of defense on a number the operator actually controls.
The work is backward-solving. How far does GOP margin have to move to clear the threshold? What mix of labor productivity, F&B cost, and controllable-expense cuts gets the prong into passing range?
Negotiate the Test Mechanics at Bid Stage
The time to fix an unfair measure is before signing. After that, the mechanics are locked.
Comp-set definition is negotiable — which hotels are in, which are out, and what happens if the set changes materially during the term. An operator facing a set stacked with properties above its weight can negotiate exclusions, adjustment mechanisms, or a definition that reflects realistic competitive positioning rather than an aspirational one.
Carve-outs for demand the operator demonstrably doesn’t control are negotiable. Citywide compression periods where the hotel absorbs contracted blocks. Owner-deferred capex periods where rate position erodes on the owner’s budget call. Force majeure that disrupts demand across the market. These are established practitioner asks — control carve-outs and force-majeure adjustments that put the risk back on the party that actually holds it (JMBM; ISHC). They don’t erase the asymmetry, but they cut the operator’s exposure to termination on forces it can’t move.
Measurement mechanics are negotiable too. Annual versus rolling measurement. Cure rights — how many consecutive failures trigger termination. Cure windows — how long the operator has to fix a failure before termination rights vest. Longer cure windows buy the operator time to respond to index moves driven from outside.
All of it happens at bid stage. The operator prices the deal, finds the structural risks, and builds the negotiation around the ones that matter most. If RevPAR Index is the dominant termination risk — if the operator is being graded on a number it doesn’t control — the negotiation should concentrate there: comp-set definition, adjustment mechanisms, and cure windows.
When the Test Stops Measuring Performance
The test is supposed to measure the operator’s performance. Run it on RevPAR Index — a comp-set-relative, demand-driven number — and the operator gets graded partly on forces outside its control.
A competitor opens. The owner defers capex. The comp set refreshes on someone else’s schedule. The index moves, and the operator carries the risk.
The remedies exist. Build the prong the operator controls. Negotiate the mechanics before signing. Both cut the exposure, and both belong in the standard playbook.
But the structure underneath stays. A performance test is a fair measure only when the operator controls the inputs. When the inputs sit outside the operator’s hands, the test stops measuring performance and starts measuring luck. So it’s worth asking of any deal on the table: how much of the operator’s termination risk rides on the prong it controls — and how much on the one the market and the owner move?
Dash Decisions provides vendor-side financial deal desk services for hotel operators bidding on HMAs.