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How it works

No black box. Here is the arithmetic.

Every figure HDHICT shows is produced by ordinary, testable code, the same methods taught in hospitality finance and used by chains with analysts on staff. This page is the whole method, so you can check our working.

Cash forecast

Holt smoothing, then the things you already know.

A baseline is projected from your trailing twelve weeks using Holt’s linear exponential smoothing. It tracks both a level and a trend, so a business that is growing forecasts as growing. Then the certainties are layered on top.

How one forecast week is built Three inputs stack into one weekly figure: a smoothed baseline from the trailing twelve weeks, plus recurring bills dated to the week they fall, plus open invoices dated to when they are due. The result is a projected closing cash balance for each of thirteen weeks. Trailing 12 weeks Your own takings, smoothed (Holt exponential smoothing) Recurring bills Rent, insurance, loan payments placed on the week they land Open invoices Money owed to you, dated to when it is actually due + Closing cash, 13 weeks zero week 12: short The forecast names the week you run short, not just that risk exists. Nine weeks of warning is enough time to collect, delay, or renegotiate.
Nothing here is an industry average. The baseline is your own trailing twelve weeks; the spikes are your bills and your invoices, on the dates they actually fall.

Why smoothing, not an average

A plain average of twelve weeks ignores direction. Holt carries a trend term, so a steady 2% weekly climb keeps climbing in the forecast rather than flattening out.

Why thirteen weeks

One quarter is the standard treasury horizon: long enough to see a problem coming, short enough that the numbers still mean something.

What it will not do

It cannot know about a booking you have not entered or a supplier rise you have not recorded. It forecasts the business as you have described it.

Customer segments

Three scores, eight segments.

RFM scoring is the oldest reliable idea in retail analytics. Each customer gets three scores from 1 to 5: how recently they bought, how often, and how much, and the combination places them in a segment.

Customer segments by recency and frequency A grid with how recently a customer bought on the horizontal axis and how often on the vertical. Champions and Loyal sit top right; New and Potential Loyalist bottom right; At Risk and Needs Attention in the middle left; Hibernating and Lost bottom left. Bought more recently Buys more often At Risk Used to be regulars. Reach out this week. Loyal Steady and dependable. Ask them to refer. Champions Recent, frequent, high spend. Protect these people. Hibernating Long gone, low value. One cheap win-back. Needs Attention Slipping. Still winnable with a timely nudge. Potential Loyalist Coming back already. Give them a reason to stay. Lost Do not spend real money chasing these. New First visit was recent. The second visit decides it.
Monetary value is the third axis, and it decides ties, a lapsed big spender is At Risk rather than Hibernating, because they are worth the phone call.

Break-even

The sales figure that pays for the doors being open.

Break-even is fixed costs divided by gross margin. For the demo restaurant, $17,388 a month of rent, insurance and other fixed costs against a 74% gross margin gives a break-even of $23,499, and the last thirty days came in $26,966 above it.

The formula

fixed costs
÷ gross margin %
= break-even sales

Gross margin comes from your own ledger, sales less the costs that scale with them, so the answer reflects how you actually trade.

Break-even for the demo restaurant Monthly sales of $50,465 against a break-even point of $23,499. Fixed costs and variable costs are covered, leaving $26,966 of headroom above break-even. Last 30 days Sales $50,465 everything that came in Break-even $23,499 the point the doors pay for themselves Headroom above break-even $26,966 what is left to cover profit and reinvestment break-even crossed here A restaurant trading below this line is losing money every day it opens, however busy it feels.
The scale is real: the break-even block is 47% of the bar because $23,499 is 47% of $50,465.

Health score

Four components, no mystery index.

The letter grade on the dashboard is the average of four scores, and each one names the figure that produced it. You can always see why it moved.

Profitability
Net margin over the last 30 days.
Revenue trend
Weekly direction over twelve weeks, discounted by how well the line actually fits.
Cash position
Months of runway at your current burn, or cash-flow positive.
Receivables
The share of open invoice value that is overdue.

Why no AI

Arithmetic first, always.

This ordering is the whole design. A language model is good at explaining and prioritising, and bad at arithmetic, so it is never allowed to do any. Today no AI feature is switched on at all.

  1. Step one

    You record

    Sales, costs, recipes and customers, typed in or imported.

  2. Step two

    Code computes

    Forecast, margins, segments and scores, from unit-tested functions.

  3. Step three

    A digest is built

    The finished figures are packaged as ground truth. Nothing raw, nothing invented.

  4. Step four

    The model explains

    It reads that digest and tells you what to do. It cannot reach the underlying data.

The practical consequence: no AI feature is switched on in HDHICT today, and every number on every screen is exactly what it would be if one were. The analysis has never depended on a model.

Check the working yourself.

Load the demo restaurant, no account needed, and every figure on this page is reproduced in front of you.

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