Daily Covers Served · 28 Days
28 days. One metric. One turn.
The turn was clear in Week 3.
Week 4 was already too late.
Read the turn. Not the crash.
67Mean
3Signal pts
↓ 44%MA drop
Metriq.OneDoes it matter? — Measure it‼️
Demo Stack · Neighborhood Vendor · Base Configuration
Running a Neighborhood Vendor Operation — and Knowing If It Is Actually Working
A plain language deployment guide for any small vendor selling goods to the immediate community — a corner store, a market stall, a home-based shop, or a mobile cart. One operation. One chain. Three questions. Everything collected in one notebook by one person.
The Idea
Every neighborhood vendor runs the same operation, regardless of what is sold or what the store is called. The chain is always the same. When it holds, the vendor survives. When it breaks — even quietly, even slowly — the vendor does not.
1
Buy at a known costEvery purchase recorded. The cost per unit is known before anything is sold.
2
Sell at a price that covers every cost — not just the purchase priceTransport, storage, spoilage, packaging — all included. The margin is calculated, not guessed.
3
Collect the cash — including credit given to community membersCash sales and credit sales are both recorded. Credit is not income until it is collected.
4
Cash in hand at day's end exceeds cash spent that morningThe difference — however small — is real income. It must exist. Every day.
5
Restock from today's earnings — never from a loanThe moment restocking requires borrowing, the chain has already broken. The operation is funding debt, not trade.
A vendor with full shelves and no cash has not been selling — they have been lending goods to the community at zero interest. The goods left. The cash did not return. The chain is broken and the shelves will empty for the last time soon.
MCA — Context (Fill in for your operation)
| What is sold | Category of goods. Format of sale — by unit, by weight, by portion. Fixed location or mobile. Operating hours and days. |
| Who operates it | Number of people involved. Who buys stock, who sells, who records transactions, who manages credit accounts. |
| Who are the customers | Immediate community — households within walking distance. Regular buyers. Credit customers. Occasional buyers. |
| What resources it has | Current cash reserve. Storage space. Equipment. Existing supplier relationships. Credit accounts with suppliers. |
| What has gone wrong before | Credit not collected. Stock expired before sale. Supplier price increase not passed on. Ran out of a critical item. Borrowed to restock. |
| The main challenge right now | State as something observable — an amount, a count, a frequency. Not a feeling. |
| What the operation is working toward | A measurable target connected to one of the three survival questions below. |
The Stack — 3 CSI · 9 Modules · 27 PI · 3 CRI
DESIGNATION BRIDGE
Every item sold generates cash that returns before the next restock — at a margin that covers all costs — and the credit given to the community never exceeds the cash available to fund it.
PI
What to count
How to collect it — who, when
CSI-1
Stability
Is more cash coming in than going out — every day, not just in a good week?
A vendor can be busy and still be losing money. The only way to know is to count what came in, count what went out, and compare them — every day. Not at the end of the month when the damage is already done and the restock money is gone.
MOD-1.1
Daily Cash Position
Does cash return every day?
PI-1.1.1
Cash collected today vs cash spent today on stock, transport, and operating costs
End-of-day cash count — operator records both figures before closing each day
PI-1.1.2
Number of days this period when cash collected was less than cash spent
Daily cash log — any negative day marked with reason noted on the day
PI-1.1.3
Number of times this period borrowing was required to fund a restock purchase
Operator records each borrowing event on the day it happens — amount and source noted
MOD-1.2
Margin and Stock Control
Is the selling price actually covering all costs?
PI-1.2.1
Selling price vs total cost per unit for the three best-selling items — is the margin positive on each?
Operator price list — cost and selling price recorded per item, updated when supplier price changes
PI-1.2.2
Units or quantity purchased this period vs units or quantity sold — how much is sitting unsold?
Stock log — purchases recorded at time of purchase, remaining stock counted weekly
PI-1.2.3
Number of items sold below cost this period to clear slow-moving or expiring stock
Operator marks below-cost sales at point of sale — item and actual price recorded
MOD-1.3
Supply and Restocking
Can stock be replaced reliably at a predictable cost?
PI-1.3.1
Number of times this period a high-demand item ran out before the end of the trading day
Operator records each stockout on the day — item name and estimated lost sales noted
PI-1.3.2
Number of available suppliers for the operation's three most critical items
Operator supplier list — updated when a new supply source is identified or lost
PI-1.3.3
Number of supplier price increases this period that were not yet reflected in the selling price
Purchase receipts compared to previous purchase — price gap noted at time of purchase
CRI-1
Is cash collected exceeding cash spent every day — with no borrowing required to restock and no items being sold below their full cost?
CSI-2
Safety
Is the operation protected from the risks that drain it quietly — credit, shrinkage, and price exposure?
Neighborhood vendor operations rarely fail dramatically. They drain. Credit extended to community members accumulates unpaid. Goods disappear in small amounts that seem insignificant individually. Supplier prices rise while selling prices stay the same. Each of these is manageable when caught early. Together, undetected, they are fatal.
MOD-2.1
Credit Control
Is the amount owed by community credit customers under control?
PI-2.1.1
Total amount owed by credit customers at end of this period vs total at end of last period
Credit ledger total — all outstanding balances summed and compared at end of each week
PI-2.1.2
Number of credit customers who have not made any payment in more than 14 days
Credit ledger review — last payment date checked for each account every week
PI-2.1.3
Amount collected from credit customers this period vs amount extended on credit this period
Credit ledger — new credit and payments both recorded on the day of each transaction
MOD-2.2
Shrinkage and Loss
Are goods leaving the operation without generating cash?
PI-2.2.1
Number of items unaccounted for at end-of-day stock check this period
Daily spot-check on fast-moving items — count compared to expected based on recorded sales
PI-2.2.2
Number of expired, damaged, or unsellable items disposed of this period
Disposal log — item, quantity, and purchase cost recorded each time goods cannot be sold
PI-2.2.3
Estimated value of stock lost to shrinkage and disposal this period
Calculated from disposal log and stock check discrepancies — recorded at end of each week
MOD-2.3
Operating Conditions
What disrupted the operation this period — and was it documented?
PI-2.3.1
Number of trading days lost this period due to weather, access, power, or location disruption
Operator log — each missed trading day recorded with cause on the day it occurs
PI-2.3.2
Number of days this period a critical item was unavailable from all known suppliers
Operator notes on the day — item and all suppliers contacted recorded
PI-2.3.3
Number of competitor operations that opened or closed within the immediate trading area this period
Operator observation — noted at start of each week
CRI-2
Is total credit owed declining or stable, are shrinkage losses within a documented acceptable range, and are all operating disruptions recorded with their cause?
CSI-3
Continuity
Are community members still choosing this operation — and is it improving based on what the numbers show?
A neighborhood vendor runs on proximity and trust. Customers leave quietly. They do not announce that they found a better price or a more reliable stock somewhere else. By the time the drop in daily sales is noticeable, the departure is already weeks old. These indicators catch the drift early enough to reverse it.
MOD-3.1
Customer Return
Are the same customers coming back?
PI-3.1.1
Number of regular customers served this week vs the same count last week
Operator estimate at end of each trading day — count of familiar returning buyers
PI-3.1.2
Number of regular customers not seen this week who were seen the previous week
Operator notes absent regulars at end of week — pattern tracked across periods
PI-3.1.3
Number of first-time buyers this period who mentioned how they found the operation
Operator asks or notes when a new buyer mentions a referral or passes a competitor to get here
MOD-3.2
Product and Service Fit
Is the operation stocking and selling what the community actually needs?
PI-3.2.1
Number of customer requests for items not currently stocked this period
Operator notes each request on the day — item name recorded
PI-3.2.2
Number of items consistently purchased elsewhere that this operation does not carry
Operator notes when customers mention buying something from a competitor — item recorded
PI-3.2.3
Number of items added to stock this period in direct response to a recorded customer request
Operator records each new item added — linked to the request or observation that prompted it
MOD-3.3
Learning and Improvement
Is the operation getting better based on its own recorded data?
PI-3.3.1
Average daily revenue this period vs average daily revenue last period
Weekly total divided by trading days — compared period to period in the cash log
PI-3.3.2
Number of deliberate changes made this period based on a pattern observed in last period's records
Operator notes each intentional change — the observation that prompted it recorded alongside
PI-3.3.3
Number of days this period revenue exceeded the upper operating target
Daily cash log compared to target — days above upper threshold noted at close
CRI-3
Are regular community members continuing to return, is the product range responding to what they need, and is the operation making deliberate improvements based on its own recorded data?
When You Present This — What to Say
1
One notebook. Ten minutes a day. That is the entire system.
Every indicator is collected at a natural point in the trading day — before opening, at closing, or when something happens. No computer. No spreadsheet. No dedicated staff member.
2
The credit warning appears weeks before the restock money runs out.
PI-2.1.1 tracks total credit outstanding each week. A rising trend over four consecutive weeks is a signal — not a crisis yet, but the direction is already visible. That is the moment to act.
3
When a lender asks for evidence — it exists.
Four weeks of daily cash records, a credit ledger, and a stock log tell a lender more than any application form. It shows the operation knows its own numbers. That is the first thing any lender or programme officer needs to see.
4
Environmental conditions are recorded — not blamed on anyone.
A week of bad weather, a supplier price spike, a local event that changed foot traffic — all go into MOD-2.3. They explain unusual readings without assigning fault. The record stands on its own as evidence.