An advantage in one category says nothing about the next

The same factory, twice

Halbrent is a serious outerwear maker. On ALD-2210 it quoted USD 24.80 against a spread of USD 3.70 and delivered the cheapest jacket of the four. It has made padded outerwear for eleven years.

In the same week it quoted Aldermist for ALD-4400, a single-jersey short-sleeve tee, 120,000 units. Halbrent quoted USD 4.35. The order went elsewhere at USD 3.42.

Halbrent is 27.4% above the winner on a garment made of one fabric with four seams. Nothing about the factory changed between the two quotes: the same origin, the same wage, the same building, the same management, the same currency, the same duty preference. Whatever makes an origin competitive, it is not a property of the origin.

Where the tee gap actually is

The gap is USD 0.94, and it splits almost exactly in half: 49.1% of it is fabric and 50.9% is sewing. Neither half is a wage.

The sewing half is a method fact, not a labour fact. Halbrent's cost per standard minute is 42.4% above the winner's — which is lesson 2's number and reflects a plant tooled and staffed for 42-minute outerwear. But its standard minutes on a tee are 36.1% above the winner's as well, and that is worse, because it means the plant is slow at this garment in a way that a cheaper minute would not fix. A line balanced for a padded jacket has the wrong section lengths, the wrong machine mix and operators whose speed lives in a different set of operations.

The fabric half is an ecosystem fact. The winner buys knitted, dyed and finished single jersey from a mill forty minutes away, in a market where a dozen knitters compete for its business. Halbrent imports jersey, pays an input duty on it, and waits three weeks longer for it. No amount of factory improvement touches that line.

Which produces the most useful number in this lesson. Suppose Halbrent fixed the whole of the making side — a dedicated jersey line, a proper method study, a cost per standard minute and a standard minute value matching the winner exactly:

winner's FOB                       3.42
plus Halbrent's fabric disadvantage 0.46
best Halbrent could ever quote     3.88
still above the winner by          13.5%

A perfect making operation still leaves Halbrent 13.5% off, because the gap is in a fabric it cannot buy at that price. So the answer is not get better at tees. The answer is stop quoting tees, and the next section is how an owner decides that with evidence instead of instinct.

The four things that make a category advantage

Category advantage accumulates, which is why it is slow to build and slow to lose. Four ingredients, and an origin can be rich in one category and empty in the next.

1. Installed machine mix. Down filling, seam taping, bar tacking, flatlock, linking, laundry capacity. Machines are bought for a category and then decide which categories are cheap.
2. Accumulated method. The four-hundredth time a line makes a style, its standard minute value is genuinely lower. Experience shows up as a real, measurable reduction in the minutes a garment needs, and it is specific to the garment.
3. Inputs within reach. Fabric is the largest line on most quotes, as lesson 1 showed. Whether the mill is forty minutes away or six weeks away is the biggest single category fact about an origin, and it is rarely what people mean when they name one.
4. Quantity economics. A tee programme is a large-volume, thin-margin business with its own minimums; a padded jacket programme is not. A factory whose overhead is sized for one is wrong for the other.

The sheet almost no factory keeps

Halbrent's owner believes the factory is competitive. Two years of quotes say something more precise.

The overall win rate is 37.9%, and it is the least informative number on the page. Read by category it says four things the owner did not know.

Two categories are a rounding error in wins and a third of the workload. Jersey and woven shirts are 20 quotes — 34.5% of everything the costing desk did — for 4.5% of the wins. At Halbrent's own figure of USD 340 of merchandiser, costing and sampling time per quote, that is USD 6,800 spent to win a single order.

The gap sizes say which losses are worth fighting. A loss at 2.1% is a negotiation, a specification detail, a payment term. A loss at 19.8% is a structure, and no amount of sharpening the pencil closes it. Sort your losses by gap, and only the small ones are a sales problem.

Where the factory wins, it wins on things it built. Padded outerwear, soft shell and fleece share the same machines, the same operators and the same fabric suppliers. The advantage is real and it is narrow, and narrow is fine.

Leaving a category is not free, and should still be priced. Halbrent's jersey quoting keeps it on two buyers' lists for the whole range. If it stops, it may be dropped from both. That is a genuine cost, and it is a smaller number than the USD 6,800 those twenty quotes cost — so the answer here is to stop, and to say so to the buyers rather than quoting badly and letting them work it out.

Act as a commercial director reviewing a factory's quoting record. I will paste my quote history: one row per quote with date, buyer, product category, quantity, my FOB, the winning FOB where I learned it, won or lost, and the reason the buyer gave. My cost of preparing one quote, including merchandiser time, costing time and sampling, is [AMOUNT]. Here is the data: [PASTE]. Do the following. First, a table by category: quotes, wins, win rate, average percentage gap on the losses where I know the winning price, and how many losses have no reason recorded. Second, tell me which categories are structural losses and which are negotiable ones, using the gap size as the test, and say what gap you would treat as the dividing line and why. Third, calculate what I spent quoting in the categories where I win least, and what that bought. Fourth, for my two worst categories, ask me which of the four category ingredients is missing — machines, accumulated method, inputs within reach, or quantity economics — and, if I tell you my fabric cost disadvantage in that category, calculate the best price I could ever quote assuming my making became identical to the winner's, so I can see whether the gap is closable at all. Fifth, name the categories I should stop quoting, and draft the short message I should send to the buyers concerned so that stopping does not read as walking away. Sixth, list the columns missing from my sheet that would have made this analysis better, so I can start collecting them now. Use only my data; do not compare me with any published industry figure.