Every store already has a gold standard hidden inside its own history — its own best days. The Bench measures the distance from the average day to that ceiling — then climbs one layer up to benchmark every store against your network's best.
46 live stores · 19,210 store-days · Jan 2024 → Jun 2026 · names anonymised
$84.1M
Revenue analyzed
across 46 stores
$33.3M
Recoverable vs own best
39.6% of actual
$19.4M/yr
Lift to network gold
everyone to your best store
70→39%
Gap trend (4-wk avg)
closing over the window
The idea
One bench, two layers
Operational performance lives at two altitudes. Tactix Bench measures both — and you can't have the second without the first.
Layer 1 · Micro
Each store vs its own best
For every store and weekday, the 90th-percentile day is the proven ceiling. The distance from an ordinary day to that ceiling is recoverable revenue — performance the store has already hit.
Layer 2 · Macro
Every store vs the network's gold standard
Your best-run store sets the bar. The Bench shows where every other store sits on the climb to that gold standard — and what reaching it is worth across the whole system.
Layer 1 · the finding
A store's best week isn't luck. It's the bar.
Summed across 46 stores and Jan 2024–Jun 2026, the gap to each store's own best is $33,261,448 — 39.6% of the $84,054,230 actually rung up. Annualised, that's roughly $29,080,385 against proven ceilings.
Read this as opportunity sizing from history — not attribution to Tactix.It's the ceiling each store has already touched; Tactix's job is to help it get there more often. The Explorer applies a realistic smart-action adherence rate.
Layer 2 · the ladder
Benchmark every store against your best
Operational consistency is the share of its own ceiling a store actually delivers. Your gold standard — Brand B · 01 — runs at 85.1%. The network average is 60.5%. Closing that climb across every store is worth about $19,352,185/yr — more conservative than each store hitting 100% of its own ceiling, and a clearer target: get everyone to your best.
Operational consistency — climb to gold
▲ gold standard 85.1%
Brand B · 01★ gold
85.1%
Brand B · 02
84.6%
Brand B · 05
83.3%
Brand B · 03
82.1%
Brand B · 10
81.9%
Brand B · 04
81.8%
Brand B · 09
81.4%
Independent · 12
80.5%
Brand B · 06
79.9%
Brand B · 08
77.0%
Independent · 30
76.2%
Brand B · 07
76.2%
The dataset
Real registers. No synthetic demand.
19,210 store-days of operating data, Jan 2024–Jun 2026. Two national QSR chains (anonymised here as Brand A and Brand B) anchor it alongside independents — and they tell opposite stories.
Independent
30 stores
39.9%
recoverable gap
$24,206,454 recoverable · ~$24.1M/yr
Brand A
6 stores
65.0%
recoverable gap
$6,672,321 recoverable · ~$6.4M/yr
Brand B
10 stores
18.1%
recoverable gap
$2,382,673 recoverable · ~$2.1M/yr
Leaderboard
Where the money is
Top 12 stores by recoverable revenue over the window. Bars sized to dollars; brand colour-coded.
Independent · 0468.1%
$2.7M
Independent · 0159.3%
$1.8M
Independent · 0935.6%
$1.7M
Brand A · 0561.9%
$1.6M
Independent · 0370.1%
$1.6M
Brand A · 0462.9%
$1.4M
Independent · 0270.4%
$1.4M
Independent · 0824.8%
$1.4M
Independent · 2738.6%
$1.3M
Independent · 0560.8%
$1.2M
Brand A · 0363.8%
$1M
Independent · 1729.7%
$1M
IndependentBrand ABrand B
The trajectory
The gap is closing
Network-average recoverable gap by week, with a 4-week rolling average — falling from 70.3% to 38.5% across the window.
Weekly network avg gap %4-week rolling avg
The taxonomy
Every day is a situation — every situation, a smart action
Each store-day is classified against that store's own baselines, and every situation triggers its own smart action — the specific move that closes the gap. Across 19,204store-days, here's the mix. (See how a smart action is made.)
Capacity management — staffing and throughput review
Normal 21%
Smart action ↓
Maintenance — sustain current performance
How it becomes a smart action
From clean signals to one clear move
The agent doesn't hold the data — it holds a question and a map of tools, and fetches clean signals from purpose-built gold marts. That's how a store-day turns into a real, priced play.
The system has already written 649 dated smart actions across 17 stores in this snapshot — each with a priority, a confidence, an expected dollar impact, and the reasoning behind it. Two, verbatim:
✦
Tuesday May 12 — Soft Day Ahead
$1.7K–$2.3K
↓ softer day
highLabor optimizationhigh confidence
Tuesdays at this location consistently run 30-36% below daily average revenue ($4394 vs $6550 overall) based on 13 observations with a tight range.
→Move: Right-size labour for the softer day
✓Evidence: 13 comparable days, high confidence
Why this — the full reasoning
Tuesdays at this location consistently run 30-36% below daily average revenue ($4394 vs $6550 overall) based on 13 observations with a tight range. Confidence: high given repeated, recent samples. With Tue May 12 in next week's window, it's worth reviewing whether your current plans align with the expected lower volume that day. Expected impact: $1,700-$2,300 13 DOW observations; Tue avg revenue 4394 vs overall 6550.
✦
Tuesday May 5 — Softer Day Expected
$2K–$2.3K
↓ softer day
highLabor optimizationhigh confidence
Tuesdays at this location historically run about $2000-$2250 below the overall daily average (avg $4,281 vs.
→Move: Right-size labour for the softer day
Why this — the full reasoning
Tuesdays at this location historically run about $2000-$2250 below the overall daily average (avg $4,281 vs. $6,409), based on 13 past Tuesdays with a tight range. As you finalize next week's plans, May 5 is worth a closer look given this pattern. It's worth reviewing whether your current plans align with the expected softer volume that day. Expected impact: $2,000-$2,250 Tuesday avg revenue $4,281.05 vs overall $6,409.22 (sample 13).
How each one is made — clean signals, narrow tools, one clear move → Smart actions
No black box
The math
The first question every operator asks: how is the gap determined? Here it is, in full — follow one Tuesday through all four steps.
ⓘ Hover or tap any coloured termfor a plain-language definition.
01
Own-best baseline
P90s,dThe 90th-percentile day from this store's own history for that weekday — a genuinely good day it has already hit, not a target we invent. = 90th percentile of revenueWhat the store actually rang up that day. for store s, weekday d
A genuinely good Tuesday or Saturday for that store — drawn from its own history, not a target we invent.
examplebest Tuesday for this store ≈ $4,200
02
Recoverable — per day
recoverables,tThe shortfall versus the own-best day. Floored at zero, so strong days never count against the store. = max( 0 , P90s,dThe 90th-percentile day from this store's own history for that weekday — a genuinely good day it has already hit, not a target we invent. − revenues,tWhat the store actually rang up that day. )
How far a given day fell short of its own comparable best. Great days never count against you.
example$4,200 − $3,100 = $1,100 recoverable
03
Recoverable gap %
gap%Total recoverable as a share of revenue — the headline opportunity number. = Σ recoverableThe shortfall versus the own-best day. Floored at zero, so strong days never count against the store. ⁄ Σ revenueWhat the store actually rang up that day.
The store's (or the network's) total shortfall as a share of what it actually earned.
example$1.6M ⁄ $5.7M ≈ 28%
04
Consistency & gold standard
consistency100 − gap%. How close a store runs to its own proven ceiling. = 100 − gap%Total recoverable as a share of revenue — the headline opportunity number. ; goldThe highest consistency in the network — your best-run store sets the bar everyone else climbs toward. = max( consistency100 − gap%. How close a store runs to its own proven ceiling. )
Your best-run store sets the bar; every other store is measured against it.
example72% here · network gold standard 85%
Where it's going
From hindsight to real time
The Bench sizes what's on the table from history. The next layer captures it in the moment: anomaly scans every 15 minutes instead of once a day, a morning health-check against the day's dollar target, and smart actions specific enough to name who to send home when labour is running hot.
Bench (today)
Sizes the recoverable gap against your own best and your network's gold standard.
Real-time scan (next)
15-minute anomaly checks: off-pace, running hot/cold, a day's forecast at risk — flagged as it happens.
Smart actions (next)
Specific moves to close the gap — down to staff and skill set — so adherence turns the gap into captured revenue.
See how a smart action is made — clean signals, narrow tools, one clear move → Smart actions
Go deeper
Put your own numbers on it
Pick stores, set a smart-action adherence rate, and watch the estimated impact move — or walk a single store's worst days and the plays that would have closed the gap.