Problems › Where Should We Invest Next? › Retail
Capital allocation goes wrong when the stores whose operators argue hardest keep their leases rather than the ones with the best four-wall margin on the next dollar of occupancy cost. For retailers, this shows up in a particular place. The numbers that carry the answer are four-wall margin and sales per square foot, and the complication specific to this industry is that 22 leases expire within 24 months and nobody can say which stores are actually profitable. The general version of this problem and the one you are actually in have different first moves.
Capital allocation goes wrong when the stores whose operators argue hardest keep their leases rather than the ones with the best four-wall margin on the next dollar of occupancy cost. For retailers, this shows up in a particular place. The numbers that carry the answer are four-wall margin and sales per square foot, and the complication specific to this industry is that 22 leases expire within 24 months and nobody can say which stores are actually profitable. The general version of this problem and the one you are actually in have different first moves.
Retailers renew leases by history and by advocacy: the locations that were funded last year get renewed again, and the person who argues best for their store gets the increment. Neither has anything to do with where the next dollar of occupancy earns most in four-wall margin.
The analysis that helps ranks each store on two things — its four-wall margin on incremental occupancy and how durable that margin is given sales per square foot and traffic density. A store that returns well but loses co-tenancy in eighteen months is a different proposition from one that returns modestly for a decade, and treating them as comparable is how retailers end up funding decline.
The output should be a sequence with a stopping rule, not a budget split across the 22 leases. Which store first, what occupancy cost it funds next, and the observation on sales per square foot that would say the sequence is wrong.
These three together are the signature. One on its own usually points somewhere else.
✓ Leases are renewed because they existed last year without recalculation of four-wall margin
✓ Nobody can rank the stores by four-wall margin on incremental occupancy
✓ Lease decisions are defended by strategic importance of the location rather than by occupancy cost ratio
The move that usually makes it worse. Renewing leases across all locations to keep the peace, which underfunds the stores that would have compounded through higher sales per square foot.
It is for you if you run or finance a retailer and budgets are set by last year plus a percentage. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.
It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
Below is an excerpt from a real run of this analysis on a retailer. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.
The subject is Marlin & Crowe, a sample company profile used for testing rather than a customer — $95M revenue, 40 stores.
Excerpt from a real Percision run · Cost Reduction & Efficiency · sample company profile
The move. Turn 410k loyalty profiles into a self-funding personalization engine that lifts margin $2.1–3.4M within 18 months.
The leak it closes. Reduced markdown depth on excess inventory via targeted offers
The assumption it rests on. 410k loyalty file remains active at ≥55 % of sales throughout rollout — the engine put the probability at 0.75.
| Investment required | $1.5M total ($0.6M Phase 1, $0.5M Phase 2, $0.4M Phase 3) |
| Expected return | 140–227 % over 18 months on $215M revenue base |
| Revenue, year 1 | $1.1–1.7M incremental margin |
| Revenue, year 2 | $2.1–3.4M incremental margin |
| Revenue, year 3 | $3.5–4.8M incremental margin |
| Exit criteria | Discontinue investment if conversion lift remains below 2 pp after Month 9 OR if privacy regulation reduces usable profiles by >30 % |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Growth Portfolio Framework, one of 29 engagements the platform runs. For retailers it works through four-wall margin, sales per square foot, occupancy cost ratio and traffic density, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.
You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.
Price the durability explicitly. A return that decays needs a stated half-life; once each option carries one, options with different horizons become comparable rather than a matter of taste.
Usually the strongest, because that is where a marginal dollar compounds. Fixing the weakest is worth doing when it is a constraint on the strongest, and not otherwise.
Then decide on reversibility. When two options return similarly, take the one you can stop, because the value of the information you buy exceeds the difference in the estimates.
Materially, yes. 22 leases expire within 24 months and nobody can say which stores are actually profitable — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are four-wall margin, sales per square foot, occupancy cost ratio, and an answer built on industry-general benchmarks will usually point at the wrong one first.
Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on four-wall margin and sales per square foot. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.
Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
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