Finding the real capacity bottleneck
Separate building, checkout, product-fixture and staffing capacity before adding equipment.
Decision first
The lowest useful capacity layer is the one to improve; everything above it is idle investment.
Building limit, equipment capacity, staffed throughput, and realized customers are related but distinct quantities.
Capture all four quantities.
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Capacity terminology
Building limit, equipment capacity, staffed throughput, and realized customers are related but distinct quantities.
The developer explicitly separates the hard building ceiling from equipment totals and the multi-factor flow of actual customers.
Procedure: record the building limit; open every capacity row; identify installed totals; map staff coverage; compare hourly completed customers
Example: A thirty-limit store has forty register capacity, twenty display capacity, and twelve realized customers. The structural bottleneck is twenty, while demand or execution explains the gap from twelve.
Never use one number labeled capacity to answer all four questions. Inspect building limit, minimum equipment capacity, staffed service capacity, and realized customers before choosing the more expensive branch.
Record each quantity with its source screen and measurement period in BizMan. Use building limit, minimum equipment capacity, staffed service capacity, and realized customers only when its controls remain comparable.
Interface labels can evolve, so preserve the meaning rather than relying on old screenshots. Confirm the current F1 requirement again after a relevant patch.
Test reproducibility from the record alone. If each quantity with its source screen and measurement period omits the neighborhood, hours, stock state, staffing, price, or costs needed to recreate the observation, add the missing field. More decimal places cannot compensate for missing operating conditions.
Write four labels before diagnosing throughput: property building limit, minimum installed equipment capacity, staffed capacity during the hour, and completed customers. Each belongs to a different branch and demands a different remedy.
Action checklist
- Capture all four quantities.
- Identify their source.
- Compare in order.
- Locate the first gap.
- Choose a targeted test.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| capture all four quantities | building limit, minimum equipment capacity, staffed service capacity, and realized customers supports the intended condition under the recorded controls. | identify their source |
| compare in order | each quantity with its source screen and measurement period is complete and the comparison has no unexplained outage. | locate the first gap |
| choose a targeted test | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in capacity terminology. |
Developer-confirmed structural formula
The structural customer ceiling is the minimum of the building limit and every relevant equipment-category total. The remaining uncertainty should appear in the record attached to minimum category total relative to building limit.
Developer examples show that two twenty-cap registers provide forty register capacity in a thirty-limit building, but one twenty-cap required station still limits the store to twenty.
Procedure: list required categories; sum identical items within each; cap category totals at the building limit for planning; select the minimum; verify BizMan
Example: Building thirty, registers forty, baskets thirty, product A thirty, product B ten yields effective structural capacity ten until Product B fixtures are expanded.
If displayed effective capacity differs, inspect for an overlooked product or station row. Inspect minimum category total relative to building limit before choosing the more expensive branch.
Record category, capacity each, count, total, staff need, and live displayed effective capacity in BizMan. Use minimum category total relative to building limit only when its controls remain comparable.
This is a boundary, not a formula for guaranteed customer arrivals. Confirm the current F1 requirement again after a relevant patch.
Apply enumerate all categories, observe minimum category total relative to building limit, and reverse the change when its predicted mechanism does not appear. Scaling a weak signal multiplies uncertainty and cost together.
For a thirty-limit store with category totals of forty, thirty, and ten, structural capacity is ten. Raising the ten-cap category to thirty changes it to thirty; adding units to the forty-cap category changes nothing.
Action checklist
- Enumerate all categories.
- Sum correctly.
- Take the minimum.
- Verify in BizMan.
- Fix the limiting row.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| enumerate all categories | minimum category total relative to building limit supports the intended condition under the recorded controls. | sum correctly |
| take the minimum | category, capacity each, count, total, staff need, and live displayed effective capacity is complete and the comparison has no unexplained outage. | verify in BizMan |
| fix the limiting row | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in developer-confirmed structural formula. |
Building limit
The property imposes a hard maximum customers per hour that equipment and marketing cannot exceed.
The developer states the building maximum cannot be surpassed even when installed equipment totals are higher.
Procedure: record the limit before leasing; estimate demand; cost the equipment to approach it; monitor peak customers; expand property only when headroom has value
Example: Extra registers raise their category to sixty in a thirty-limit property, but maximum structural throughput remains thirty.
When all categories exceed the building limit and peaks repeatedly hit it, the site rather than furniture becomes the structural constraint. Inspect building limit and frequency of hourly saturation before choosing the more expensive branch.
Record limit, peak hours, customers, queues, demand, contribution, and relocation cost in BizMan. Use building limit and frequency of hourly saturation only when its controls remain comparable.
A bigger limit does not guarantee more customers because product type, demand, competition, traffic, promotion, and satisfaction still matter. Confirm the current F1 requirement again after a relevant patch.
End with a pre-mortem. Assume the choice failed, then rank count saturated hours, estimate lost contribution, and cost relocation by how quickly each would explain the loss.
Count how often Yesterday equals the property limit while stock, staffing, and satisfaction remain intact. Repeated profitable saturation supports relocation; a single peak does not justify a larger site.
Action checklist
- Verify the property limit.
- Count saturated hours.
- Estimate lost contribution.
- Cost relocation.
- Expand only with evidence.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| verify the property limit | building limit and frequency of hourly saturation supports the intended condition under the recorded controls. | count saturated hours |
| estimate lost contribution | limit, peak hours, customers, queues, demand, contribution, and relocation cost is complete and the comparison has no unexplained outage. | cost relocation |
| expand only with evidence | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in building limit. |
Product-display capacity
Each active product or relevant display category may need enough fixture capacity to avoid constraining the entire store. That distinction determines which screen can verify product-display capacity.
Developer examples use clothing racks to show that capacity must be supplied for each type, not merely by placing many unrelated racks.
Procedure: inventory active SKUs; map each to displays; total capacity per SKU or category; identify the smallest; remove or expand weak lines deliberately
Example: Twenty-three well-supplied clothing racks do not compensate for one clothing type with only ten capacity in a thirty-cap plan.
If adding a product lowers effective capacity, inspect the new product's fixtures. Inspect capacity for every active product line before choosing the more expensive branch.
Record SKU, fixture type, capacity each, count, stock, units sold, and minimum row in BizMan. Use capacity for every active product line only when its controls remain comparable.
The exact grouping of products follows the live capacity panel; do not guess from visual similarity. Confirm the current F1 requirement again after a relevant patch.
Try to disprove the working assumption before funding it. For Product-display capacity, hold capacity for every active product line steady while testing map SKUs to fixtures. If the predicted signal does not move, return to calculate each total and record the contradiction instead of adding another purchase to save the theory.
Audit product fixtures by active SKU. Three racks of one clothing type cannot compensate for one rack of another if the panel treats each as required; expand or remove the underbuilt line.
Action checklist
- Map SKUs to fixtures.
- Calculate each total.
- Identify weak additions.
- Expand or remove them.
- Confirm the new minimum.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| map SKUs to fixtures | capacity for every active product line supports the intended condition under the recorded controls. | calculate each total |
| identify weak additions | SKU, fixture type, capacity each, count, stock, units sold, and minimum row is complete and the comparison has no unexplained outage. | expand or remove them |
| confirm the new minimum | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in product-display capacity. |
Checkout and staffed throughput
Physical checkout capacity and actual staffed checkout throughput can diverge. The next decision should therefore be tied to installed checkout capacity, staffed registers, queue complaints, and completed customers, not to visual activity.
Developer examples quantify register capacity, while schedule and queue behavior determine whether installed stations serve customers.
Procedure: record register capacity; map employee coverage; inspect queues; compare served customers; add staff or equipment only where the pattern requires
Example: Two registers satisfy a forty-cap structural row, but one is unstaffed during peak demand. The interface may show installed headroom while customers still abandon queues.
If queue complaints appear below structural capacity, inspect simultaneous staffing and pathing. Inspect installed checkout capacity, staffed registers, queue complaints, and completed customers before choosing the more expensive branch.
Record hourly station assignments, worker skill, arrivals, completed sales, and abandoned transactions in BizMan. Use installed checkout capacity, staffed registers, queue complaints, and completed customers only when its controls remain comparable.
Do not infer staffed throughput solely from the number of objects on the floor. Confirm the current F1 requirement again after a relevant patch.
Build a two-column ledger. Put installed checkout capacity, staffed registers, queue complaints, and completed customers under results and hourly station assignments, worker skill, arrivals, completed sales, and abandoned transactions under controls. Credit map checkout objects only when the controls describe the same operating conditions; otherwise a delivery, staffing change, or unusually busy day can receive credit for an effect it did not cause.
Observe checkout capacity and staffing separately. Two registers may satisfy the installed row, yet one staffed lane can create queues; add labor when schedule binds and furniture when equipment binds.
Action checklist
- Map checkout objects.
- Map workers by hour.
- Observe queues.
- Compare completed sales.
- Add only needed coverage.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| map checkout objects | installed checkout capacity, staffed registers, queue complaints, and completed customers supports the intended condition under the recorded controls. | map workers by hour |
| observe queues | hourly station assignments, worker skill, arrivals, completed sales, and abandoned transactions is complete and the comparison has no unexplained outage. | compare completed sales |
| add only needed coverage | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in checkout and staffed throughput. |
Production and service stations
Coffee, food, salon, and other service formats can be limited by a required production or service station even when checkout is ample. Treat the live requirement as the gate for production and service stations.
The minimum-category rule applies to all required equipment, not only cash registers and shelves.
Procedure: list every production stage; capture station capacity; verify assigned roles; inspect the minimum; test one added station
Example: A restaurant has checkout capacity thirty but one grill supporting twenty. A second grill may remove the structural bottleneck if staff and other menu stations also support the target.
If new menu equipment lowers capacity, inspect whether that newly active category is underprovisioned. Inspect capacity and staffing for every production or service stage before choosing the more expensive branch.
Record station, product served, capacity, count, employee, hours, and queue signal in BizMan. Use capacity and staffing for every production or service stage only when its controls remain comparable.
A station with spare theoretical capacity does not create demand for its product. Confirm the current F1 requirement again after a relevant patch.
Set a stopping rule before the experiment. Redesign the plan when capacity and staffing for every production or service stage remains unfavorable after map every service stage and find the slowest both pass.
Map every production stage for coffee, food, and service businesses. A grill, machine, display, or chair with the lowest throughput can cap the store even when payment equipment and property permit more.
Action checklist
- Map every service stage.
- Find the slowest.
- Verify staffing.
- Add one unit.
- Remeasure.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| map every service stage | capacity and staffing for every production or service stage supports the intended condition under the recorded controls. | find the slowest |
| verify staffing | station, product served, capacity, count, employee, hours, and queue signal is complete and the comparison has no unexplained outage. | add one unit |
| remeasure | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in production and service stations. |
Actual customers are not capacity
Realized customer count can remain far below structural capacity without indicating a bug. This turns actual customers are not capacity into a measurable commitment rather than a guess.
The developer lists business type, demand, competition, promotion, traffic, and satisfaction as customer-volume inputs; expensive discretionary businesses naturally see fewer customers.
Procedure: confirm structure; confirm open hours and stock; inspect demand and rivals; inspect price and satisfaction; test marketing only with remaining headroom
Example: A seventy-five-cap electronics store serving twenty customers may still be healthy because the category has lower natural frequency and high contribution per sale.
If realized customers are low, do not add fixtures until the existing minimum is approached. Inspect hourly completed customers as a fraction of effective structural capacity before choosing the more expensive branch.
Record customers, capacity, demand, providers, promotion, satisfaction, price, and contribution in BizMan. Use hourly completed customers as a fraction of effective structural capacity only when its controls remain comparable.
Low utilization is not automatically bad when contribution per customer is high. Confirm the current F1 requirement again after a relevant patch.
Cross-check the management screens. BizMan should explain hourly completed customers as a fraction of effective structural capacity, while Market Insider or EconoView supplies the market or cost context contained in customers, capacity, demand, providers, promotion, satisfaction, price, and contribution.
Calculate utilization as completed hourly customers divided by effective structural capacity. Low utilization directs attention toward demand, competition, traffic, promotion, price, satisfaction, hours, or stock rather than another fixture.
Action checklist
- Verify structural readiness.
- Measure utilization.
- Inspect market factors.
- Calculate contribution.
- Avoid premature equipment.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| verify structural readiness | hourly completed customers as a fraction of effective structural capacity supports the intended condition under the recorded controls. | measure utilization |
| inspect market factors | customers, capacity, demand, providers, promotion, satisfaction, price, and contribution is complete and the comparison has no unexplained outage. | calculate contribution |
| avoid premature equipment | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in actual customers are not capacity. |
Traffic and promotion boundary
Traffic and marketing influence flow toward the store but neither changes the building's hard capacity. The dated observation becomes the baseline for traffic, promotion, peak customers, effective capacity, and campaign cost.
Developer responses identify promotion as a combination of natural traffic and marketing while warning that campaigns are wasted at the ceiling.
Procedure: record traffic; record promotion; compare peaks with capacity; test a campaign if headroom exists; stop when incremental profit disappears
Example: A store at ten of thirty customers may benefit from promotion if demand and operations are sound. A store already at thirty cannot use more arrivals that hour.
When marketing fails, compare customers to the minimum structural capacity before declaring the campaign broken. Inspect traffic, promotion, peak customers, effective capacity, and campaign cost before choosing the more expensive branch.
Record baseline and campaign periods with all capacity and market controls in BizMan. Use traffic, promotion, peak customers, effective capacity, and campaign cost only when its controls remain comparable.
No complete official traffic-to-customer equation is published. Confirm the current F1 requirement again after a relevant patch.
Ask a counterfactual question: if separate flow from ceiling were not the constraint, what different result should appear in traffic, promotion, peak customers, effective capacity, and campaign cost? A useful intervention produces distinguishable success and failure signals.
Record traffic and promotion beside capacity without combining them into an invented equation. They influence attempted flow; they do not alter the property ceiling or repair an underbuilt category.
Action checklist
- Separate flow from ceiling.
- Verify headroom.
- Test one campaign.
- Measure incremental customers.
- Stop at saturation.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| separate flow from ceiling | traffic, promotion, peak customers, effective capacity, and campaign cost supports the intended condition under the recorded controls. | verify headroom |
| test one campaign | baseline and campaign periods with all capacity and market controls is complete and the comparison has no unexplained outage. | measure incremental customers |
| stop at saturation | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in traffic and promotion boundary. |
Use the Yesterday hourly graph
BizMan Insights can show the previous day's served customers hour by hour.
The developer directly recommends switching the customer graph to Yesterday to diagnose capacity and opening hours.
Procedure: select Yesterday; transcribe every open hour; mark staff and stock anomalies; compare with effective capacity; repeat across representative days
Example: A daily total of one hundred forty could mean seven hours at a twenty cap and one empty hour, or eight moderate hours. The hourly graph distinguishes them.
Do not infer saturation from daily total alone. Inspect hour-by-hour served customers and repeated flat peaks before choosing the more expensive branch.
Record date, hour, customers, capacity, staff, stock, price, campaign, and anomaly in BizMan. Use hour-by-hour served customers and repeated flat peaks only when its controls remain comparable.
Weekday patterns differ, and the previous day may contain a closure or stockout. Confirm the current F1 requirement again after a relevant patch.
Price the opportunity cost. Cash or time committed to switch to Yesterday cannot also fund compare repeated days.
Transcribe Yesterday hour by hour and mark stockouts, employee changes, closures, and queues on the same rows. Repeated flat peaks under clean conditions beat daily totals as saturation evidence.
Action checklist
- Switch to Yesterday.
- Capture each hour.
- Mark anomalies.
- Compare repeated days.
- Identify true plateaus.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| switch to Yesterday | hour-by-hour served customers and repeated flat peaks supports the intended condition under the recorded controls. | capture each hour |
| mark anomalies | date, hour, customers, capacity, staff, stock, price, campaign, and anomaly is complete and the comparison has no unexplained outage. | compare repeated days |
| identify true plateaus | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in use the yesterday hourly graph. |
When to add equipment
Additional capacity creates value only when profitable demand is being lost at the current bottleneck.
The hard-minimum rule explains what equipment can remove; customer-flow evidence shows whether removal is economically useful.
Procedure: identify the minimum row; confirm saturated hours; estimate lost transactions; calculate added contribution; compare with equipment and labor cost
Example: Adding a fixture costs two thousand and enables five extra customers per day at twelve contribution each. The simple payback is about thirty-four operating days before other costs.
If customers never approach the bottleneck, investigate demand and execution first. Inspect saturated hours, estimated lost customers, contribution per customer, and upgrade cost before choosing the more expensive branch.
Record before-after capacity, customers, queues, units, equipment cost, added labor, and contribution in BizMan. Use saturated hours, estimated lost customers, contribution per customer, and upgrade cost only when its controls remain comparable.
Payback ignores risk and future demand changes; use it as one decision aid. Confirm the current F1 requirement again after a relevant patch.
Follow the cheap branch first: establish prove saturation, read saturated hours, estimated lost customers, contribution per customer, and upgrade cost, and commit to run a only when both support the same explanation.
For equipment, estimate recoverable customers per day and multiply by average contribution. Divide equipment plus added labor cost by that daily increment to estimate simple payback before purchasing.
Action checklist
- Prove saturation.
- Estimate recoverable demand.
- Cost the upgrade.
- Calculate payback.
- Run a.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| prove saturation | saturated hours, estimated lost customers, contribution per customer, and upgrade cost supports the intended condition under the recorded controls. | estimate recoverable demand |
| cost the upgrade | before-after capacity, customers, queues, units, equipment cost, added labor, and contribution is complete and the comparison has no unexplained outage. | calculate payback |
| run a | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in when to add equipment. |
When to move buildings
Relocation is justified when the property limit repeatedly blocks profitable demand and expansion economics exceed moving costs. The chosen target must remain serviceable through the next replenishment opportunity.
Equipment cannot lift a hard building ceiling, so site change is the available structural response once all lower categories are adequate.
Procedure: verify all categories meet the limit; count saturated hours; estimate lost contribution; cost new rent and refit; compare a conservative payback
Example: A fifteen-cap store reaches fifteen through several profitable hours with queues and stable stock. A thirty-cap site may be justified if demand persists after accounting for higher rent and fixtures.
Do not relocate a ten-utilization shop from a thirty-cap property because the problem is not the ceiling. Inspect hours at building limit, lost-demand estimate, incremental occupancy cost, and moving cost before choosing the more expensive branch.
Record current and target site data, refit items, downtime, expected customers, and downside case in BizMan. Use hours at building limit, lost-demand estimate, incremental occupancy cost, and moving cost only when its controls remain comparable.
Demand can fall after entry or rival response, so include a downside. Confirm the current F1 requirement again after a relevant patch.
Exclude contaminated comparisons. An uncovered shift, closure, stockout, supplier arrival, rival move, hype period, shortage, backorder, or game patch can change the result independently of quantify blocked demand.
A relocation model includes higher rent, duplicated or replaced fixtures, moving cost, downtime, and conservative demand. Compare them with contribution from customers blocked specifically by the building ceiling.
Action checklist
- Prove the building ceiling.
- Quantify blocked demand.
- Cost complete relocation.
- Stress-test demand.
- Move only on positive economics.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| prove the building ceiling | hours at building limit, lost-demand estimate, incremental occupancy cost, and moving cost supports the intended condition under the recorded controls. | quantify blocked demand |
| cost complete relocation | current and target site data, refit items, downtime, expected customers, and downside case is complete and the comparison has no unexplained outage. | stress-test demand |
| move only on positive economics | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in when to move buildings. |
Capacity and product breadth
Adding an active SKU can reduce total effective capacity if its display category is underbuilt.
The minimum-category formula makes assortment a structural decision, not merely an inventory choice.
Procedure: calculate current minimum; model the new SKU fixture requirement; estimate its contribution; compare floor and stock cost; add only with full capacity support
Example: A new accessory promises small sales but activates a ten-cap display row in a thirty-cap store. Its incremental margin may not offset reduced throughput across the existing basket.
If customer capacity falls immediately after assortment expansion, inspect the new row. Inspect effective capacity before and after SKU addition plus incremental product contribution before choosing the more expensive branch.
Record new fixture count, floor use, stock cash, units, and effect on all-store throughput in BizMan. Use effective capacity before and after SKU addition plus incremental product contribution only when its controls remain comparable.
The live capacity panel determines whether a product creates a separate row. Confirm the current F1 requirement again after a relevant patch.
Turn the observation into a trigger. Continue while effective capacity before and after SKU addition plus incremental product contribution stays inside the chosen range, invoke estimate product value at the boundary, and reconsider the larger plan only after compare whole-store effect fails. Written triggers make repeated decisions consistent across in-game weeks.
Before adding a product, inspect whether it creates a capacity row. Model the fixture quantity and stock needed for the current target; a weak accessory can lower throughput for established goods.
Action checklist
- Model the new row.
- Cost full support.
- Estimate product value.
- Compare whole-store effect.
- Reverse harmful additions.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| model the new row | effective capacity before and after SKU addition plus incremental product contribution supports the intended condition under the recorded controls. | cost full support |
| estimate product value | new fixture count, floor use, stock cash, units, and effect on all-store throughput is complete and the comparison has no unexplained outage. | compare whole-store effect |
| reverse harmful additions | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in capacity and product breadth. |
Capacity diagnostic decision tree
Capacity problems are solved by identifying whether the binding constraint is property, equipment category, staffing, market flow, or economics.
Developer explanations provide the hierarchy needed for a deterministic diagnosis.
Procedure: record building limit; find minimum equipment row; verify staff; inspect Yesterday peaks; inspect demand and satisfaction; calculate upgrade value
Example: Ten customers in a thirty building can mean ten structural capacity or thirty structural capacity with weak flow. The first requires fixtures; the second requires market or execution analysis.
At each node, stop when observed evidence is below the next ceiling. Inspect first binding constraint in the ordered hierarchy before choosing the more expensive branch.
Record value and evidence source for every node in BizMan. Use first binding constraint in the ordered hierarchy only when its controls remain comparable.
More than one constraint may bind sequentially. Confirm the current F1 requirement again after a relevant patch.
Compare a survival case with an upside case, keeping value and evidence source for every node explicit in both. The first asks whether the operation remains solvent after identify the property ceiling; the second asks whether test economic value has room to add value. A plan that works only under upside assumptions is not ready.
Diagnose in this order: property ceiling, installed-category minimum, staffed throughput, actual customers, market factors, then economics. Stop at the first binding value and do not solve later branches first.
Action checklist
- Identify the property ceiling.
- Identify the equipment minimum.
- Verify staffed throughput.
- Measure actual flow.
- Test economic value.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| identify the property ceiling | first binding constraint in the ordered hierarchy supports the intended condition under the recorded controls. | identify the equipment minimum |
| verify staffed throughput | value and evidence source for every node is complete and the comparison has no unexplained outage. | measure actual flow |
| test economic value | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in capacity diagnostic decision tree. |
Capacity testing protocol
A valid before-after capacity test changes the bottleneck while holding demand-generating conditions stable. Keeping the sequence intact gives each change one plausible explanation.
Because actual customers use many factors, uncontrolled tests cannot attribute a change to equipment.
Procedure: select comparable days; maintain price and campaigns; guarantee stock and staff; add one bottleneck item; compare hourly completed customers
Example: After adding a rack, customers rise, but a new billboard also began. The test cannot tell whether structure or promotion caused the lift.
Invalidate runs with stockouts, closures, rival events, major price changes, or schedule differences. Inspect hourly customers and contribution before and after one capacity change before choosing the more expensive branch.
Record control conditions, capacity row, intervention cost, results, and anomalies in BizMan. Use hourly customers and contribution before and after one capacity change only when its controls remain comparable.
The goal is decision-grade evidence, not laboratory perfection. Confirm the current F1 requirement again after a relevant patch.
Resolve reversible uncertainty before irreversible cost. freeze market levers can be tested for a short period, while a lease, broad fit-out, specialized hire, or large inventory position persists.
Run before-and-after tests on matching weekdays with identical prices, campaigns, hours, and staff. Guarantee stock, change the identified low category, then compare hourly customers and contribution.
Action checklist
- Freeze market levers.
- Guarantee operations.
- Change one bottleneck.
- Compare matched hours.
- Repeat if contaminated.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| freeze market levers | hourly customers and contribution before and after one capacity change supports the intended condition under the recorded controls. | guarantee operations |
| change one bottleneck | control conditions, capacity row, intervention cost, results, and anomalies is complete and the comparison has no unexplained outage. | compare matched hours |
| repeat if contaminated | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in capacity testing protocol. |
Final capacity audit
A well-sized store has no accidental low row, enough staffed throughput for observed demand, and no unjustified excess equipment. Reconciliation decides whether the apparent gain survives all recorded costs.
This standard respects both the hard capacity formula and the difference between potential and realized customers.
Procedure: verify building limit; verify every category; verify schedule; compare hourly utilization; review upgrade economics
Example: The audit may conclude that a ten-of-thirty store is correctly equipped because demand is only ten, or that it is structurally broken because one row is ten. Evidence distinguishes them.
Any unexplained difference among property, equipment, staff, and realized flow remains unresolved. Inspect complete reconciled capacity chain and economic justification before choosing the more expensive branch.
Record current limits, utilization, bottlenecks, unused equipment, next review trigger, and supporting dates in BizMan. Use complete reconciled capacity chain and economic justification only when its controls remain comparable.
Repeat after adding SKUs, changing stations, moving, repricing, marketing, or major patches. Confirm the current F1 requirement again after a relevant patch.
Audit every denominator. Write the denominator beside complete reconciled capacity chain and economic justification; otherwise a changing scale can masquerade as improvement.
Capacity auditing ends when every row is intentional. Some may equal the property limit; others may stay lower because measured demand cannot repay expansion. Document either choice with utilization and payback.
Action checklist
- Reconcile every layer.
- Remove accidental bottlenecks.
- Test staffed throughput.
- Value headroom.
- Document the final state.
| Checkpoint | Evidence of a pass | Response to failure |
|---|---|---|
| reconcile every layer | complete reconciled capacity chain and economic justification supports the intended condition under the recorded controls. | remove accidental bottlenecks |
| test staffed throughput | current limits, utilization, bottlenecks, unused equipment, next review trigger, and supporting dates is complete and the comparison has no unexplained outage. | value headroom |
| document the final state | The downside is affordable and a review trigger is recorded. | Pause and repeat the smallest disputed test in final capacity audit. |
Research ledger
These links establish mechanics or provide a reproducible lead. Any balance-sensitive number still has to be checked in the current save.
Questions answered
What is the customer-capacity formula?
For structural planning, take the minimum of the building limit and the total capacity of every relevant equipment or display category. This defines a ceiling, not guaranteed customers.
Why do I have fewer customers than my capacity?
Actual customers also depend on business type, demand, competition, traffic, promotion, price, satisfaction, hours, staffing, and stock. Capacity only says how many the setup could support.
Do two twenty-cap registers give forty capacity?
They give forty within the register category, but the building limit and every other required category still apply. In a thirty-limit building the structural ceiling remains at most thirty.
Should every fixture category equal the building limit?
That prevents accidental structural bottlenecks, but it may be uneconomic when realized demand is far below the limit. Size deliberately and verify the live capacity panel.
How do I know I am capacity constrained?
Use BizMan Insights on Yesterday. Repeated hourly peaks exactly at the effective capacity, with stock and staffing intact, are strong evidence. One daily total or a busy-looking queue is not enough.