Supplier Lead Time Calculation From Your Own POs

Why the rep's "two days" doesn't hold

The distributor's rep says "order by Monday, you'll have it Wednesday." You plan around that. Then the truck turns up Friday, the shelf has been empty since Thursday morning, and a customer walks out to the shop down the road.

Nobody lied, exactly. The rep is quoting the best case: stock in the warehouse, the van on its usual route, no festival rush. But your reorder timing should run on what actually happens. And that's already written down in your own purchase records.

This post is about pulling that number out of your own records: order date to received date, per supplier, over the last few months. Then turning it into an average and a worst case you can plan around.

How the gap between promise and dock opens up

Lead time isn't one thing. It's the time it takes the distributor to see your order, check stock, pick it, wait for a van with space and drive your route. Each of those steps can slip on its own.

When the warehouse is out of one SKU, your order can sit until the next inward shipment. When your shop is the last stop on a route, a full van means you get pushed to tomorrow. When the salesman takes the order on WhatsApp and only keys it in the next evening, a day goes missing before anyone at the warehouse knows about it.

None of that shows up in the promise. All of it shows up in the gap between the date on your PO and the date the goods hit your counter. So that gap is the number you want, and it's different for every supplier.

The two dates you need per order

For each purchase order you need just two dates:

• Order date: the day you actually placed the order. Not the day you thought about it, and not the day the rep visited.
• Received date: the day the goods were checked in at your shop or godown.

Lead time for that order is received date minus order date, counted in days.

Partial deliveries need a rule, so decide one and stick to it. The simple version: use the date the order arrived complete enough to sell from. Note short-shipped lines in a separate column, because a supplier who's always on time but short is a different problem from one who's late.

Pulling the dates from purchase records or a CSV

You've probably got both dates already. They're just sitting in two different places.

• Your billing or inventory system: purchase orders carry the order date, and the purchase entry or inward entry carries the received date. Export both to Excel and match them on PO number or supplier invoice number.
• Tally: purchase vouchers have a date, but that's often the bill date, not the day you placed the order. If you raise purchase orders in Tally, export the order register and the purchase register and match them. If you don't, the order date has to come from somewhere else.
• WhatsApp or a notebook: plenty of orders go out as a message to the rep. The message timestamp is your order date. Pulling it is tedious, but a few months' worth for your top suppliers is an evening's work.

Put it all in one sheet with five columns: supplier, PO number, order date, received date, lead time (days). Sort by supplier. That sheet is the whole method.

Worked example: three suppliers, one quarter

Suppose a mid-sized grocery store pulls one quarter of purchase records for three suppliers. Here's what the lead time column shows:

• Supplier A (staples distributor), eight orders: 2, 2, 3, 2, 4, 2, 3, 2 days. Total 20, average 2.5 days, worst 4.
• Supplier B (personal care distributor), six orders: 1, 1, 1, 5, 1, 6 days. Total 15, average 2.5 days, worst 6.
• Supplier C (local dairy), twelve orders, all 1 or 2 days. Average about 1.5, worst 2.

Look at A and B. Same average, but B's worst case is six days. Two of its six orders came in very late, probably stockouts at their warehouse. If you only track the average, you'd treat A and B the same and get caught out by B again and again.

Average, worst case and the spread

From each supplier's column you want three things:

• Average lead time: what you plan around on a normal week.
• Worst case: the longest gap in the period. This is what empties your shelf.
• Spread: worst minus best. A small spread means the supplier is predictable. A big one means you need more buffer, or a frank conversation with them.

Use at least a few months of orders so one bad week doesn't skew things. And redo it after anything that changes the route: a new distributor, a depot move, a festival season. Tracking delivery times like this matters even more when one category comes from several sources, a mess we cover in handling multiple suppliers with different expiry patterns.

The spread is also useful when you talk to the supplier. "Your last six orders took between one and six days" lands much harder than "you're always late."

Feeding lead time into reorder timing

Lead time matters because it tells you how much stock you burn through between placing an order and having it on the shelf. The reorder point is basically daily sales multiplied by lead time, plus a buffer. We walk through it step by step in the sell-through method for reorder points.

For example, take a shampoo SKU from Supplier B above that sells 6 units a day:

• Planning on the average of 2.5 days, you need 15 units on hand when you order.
• Planning on the worst case of 6 days, you need 36 units.
• The rep's promise of 1 day would have said 6 units. That's how the shelf ends up bare by Thursday.

The gap between 15 and 36 is your safety buffer, and it costs money to carry. For a slow, cheap, long-life item, covering the worst case is cheap insurance. For perishables, carrying the worst-case buffer means overstock that expires, so you might cover something between the average and the worst and accept the odd stockout. Both ways of losing money are laid out in the hidden cost of out-of-stocks versus perishable waste.

The point is that it's now a decision you make with real numbers in front of you, instead of the rep making it for you without either of you noticing.

Keeping the log alive after the first pull

The first pull is the hard part. After that, keeping it going comes down to one habit: write the received date on the PO or bill the moment goods are checked in. Whoever does receiving owns that step.

Then once a month, add the new rows and recompute each supplier's average and worst case. A spreadsheet handles this fine for a handful of suppliers. Where it gets hard is linking it all up: the sheet knows lead times, but it doesn't know what's selling today, what's sitting near expiry, or which reorder point should move because a supplier slowed down. Someone has to cross-check those by hand, and in a busy week nobody does.

Where ShelfSense fits

That cross-checking is what ShelfSense by ShelfLifePro is built for. It's a daily inventory agent that works alongside the system you already use. Once a day it reads your stock, batch, cost and expiry records. It sizes reorders from sell-through and cost basis, with a safety buffer and a lead time it learns from your own orders. It recommends, a human approves, and it never places an order by itself. You can read how it reasons through a call.

You can start with a CSV export of your stock and expiry dates. If you're on Tally, export to CSV today; a direct connection is on request. ShelfSense's free audit reads one CSV export, no account needed. If you want to try it, start free on the ShelfSense page. And either way, go pull those two dates for your top three suppliers this week.