Community supermarket franchisee - payback calculator tool; feed in the investment, three daily-sales scenarios, margin, and monthly fixed costs, and out come the break-even daily sales and the payback months per scenario, side by side, with the worst case's survivability in plain view

You are a coding agent. Build a single-file
HTML "franchise payback calculator" for
someone about to take over or renew a
community supermarket franchise: between
the recruiting brochure's numbers and the
real numbers sits a three-scenario spread.
Runs locally, no network, no external
dependencies.

Positioning (design to this; it is not an
investment decision system): the recruiter's
math always runs on ideal daily sales, and
the listener cannot argue because they have
never computed their own. This tool's single
job is letting the franchisee's own numbers
speak: how much in, what each of three
sales tiers produces, and whether the worst
case is survivable. It deliberately renders
no verdict on "should I sign" - judgment
stays human; the tool guarantees the human
sees complete arithmetic.

Three blocks:

1. Investment entry
- One-time: franchise fee / deposit
  (labeled "refundability per contract;
  excluded from payback math") / transfer
  fee / buildout and equipment / opening
  stock
- Each line can opt into amortization by
  year, default off
- Monthly fixed costs: rent / labor
  (including the owner's own opportunity
  cost, as a toggle) / utilities and
  misc / headquarters fees (monthly
  franchise fee, POS license, marketing
  levy - as the contract lists; zero
  where none)

2. Three-tier computation
- Three daily-sales tiers: conservative /
  expected / optimistic, each with its
  own daily sales and blended margin
  (margins may differ per tier - ramp-up
  months run heavy promos and thinner
  margins)
- Per tier output: monthly sales / monthly
  gross / monthly net (gross minus
  fixed) / break-even daily sales (fixed
  costs / margin / 30, marked against
  the tiers for where it lands) /
  payback months (one-time investment /
  monthly net; a negative net shows
  "this tier never pays back")
- All three tiers in one table, no
  weighted average - averaging conceals;
  side-by-side is honest

3. Ramp and cash
- Ramp-up: the first [ramp months]
  months computed at the conservative
  tier (or a custom discount); output
  "the tightest cash month" - which
  month cumulative net outflow peaks,
  and by how much
- One conclusion line: under the worst
  case (conservative), how many months
  cash holds, and whether it survives
  the ramp, yes/no - the single number
  most people never compute before
  signing

Hard constraints:
- Every formula displays beside its
  result (payback = investment / monthly
  net); every figure hand-checkable
- The three tiers always share one
  screen; never show the best tier alone
- Beside break-even daily sales, one
  reference input: "actual daily sales
  of a comparable store nearby (as
  asked around)" - the tool prints it
  on the same row as the tiers; a
  number overheard in the neighborhood
  beats any tier
- Data in localStorage, exportable as
  JSON
- Preloaded sample data (including a
  "conservative tier never pays back"
  case) so the full picture shows on
  first open

You shall not:
- No network, no external data
- No "suggested daily sales," no
  "projected growth rate" - the tool
  predicts nothing it was not told
- No "should you take this store"
  score or verdict; output stops at
  numbers
- No accounts, no external libraries

Why it is written this way

Between recruiting math and real operations sits exactly one tier of daily sales: the brochure's optimistic tier pays back in eight months; the franchisee lives between conservative and expected for two years. Nobody is wronged here - the franchisee simply never ran their own numbers before signing. The three-tier design (conservative / expected / optimistic side by side, weighted averages banned) exists for this: an average blends the tiers into one "looks viable" middle number, while side-by-side forces a stare at the conservative tier - if that tier never pays back, then there is genuinely a probability it never pays back.

"Does the owner's own labor count as cost" is a toggle because it is the most honest question in this kind of math: a couple-run store pays no wages and shows a decent monthly net that is really unpaid labor exchanged for the figure. The toggle defaults to on (opportunity cost), letting the franchisee see both readings - most people discover, the first time they switch it, that half the "profit" is their own salary. Similarly the deposit is excluded from payback with a note: whether and when it refunds is contract language, not arithmetic.

The ramp block and "tightest cash month" are the most practical part of the tool: payback math assumes full sales from day one, while reality climbs for months with the deepest net outflow early - franchises rarely die from never paying back; they die from the cash breaking during the ramp. The tool marks the peak month and amount of cumulative outflow, then answers one binary question - does conservative-tier cash survive the ramp - the line most worth reading before signing and least often read.

Banning every prediction and score is defenses against the tool's most common decay: becoming a reassurance machine. Add one "assumed 10% annual growth" and the payback months instantly flatter, and decisions get made on it. The tool's stance is fixed: output stops at numbers, judgment belongs to the human - and its greatest service to the franchisee is precisely refusing to decide for them.

Variables