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Evidence Review

What the published research
actually says about planning.

An evidence review collects what has actually been measured about a subject, names who measured it, and states the limits of each finding. This one covers apparel merchandising planning — markdown optimisation, demand-supply mismatch, and where merchandising time goes.

There is no RetailNorthstar research on this page. We have not run a planning survey. Every figure below belongs to someone else, is linked to its primary source, and carries the population it was measured on — because most planning statistics in circulation have lost theirs somewhere along the way.

Six sources · re-traced to primary in August 2026 · no gate, no download · how we source what we publish

The evidence

01

Optimised markdown pricing raised clearance revenue about 6% — in one controlled test

A controlled field experiment run across all Zara stores in Belgium and Ireland during the 2008 autumn-winter clearance season found that replacing a manual markdown process with a forecasting-and-optimisation model increased clearance revenue by roughly 6%.

Population
One fast-fashion retailer, two countries, one clearance season. Zara operates a deliberately low-promotion, fast-turn model that most brands do not.
What was measured
Clearance revenue. Not gross margin, and not total-season revenue.
Read it with
The comparison is optimised pricing against a manual process at the same company, so it measures the value of the method — not a gap between two vendors.
Caro & Gallien, Operations Research (2012) →

Primary confirmed — published abstract read directly.

02

Reacting to early-season sales cut demand-supply mismatch cost enough to raise profit 60%

Applying a two-stage production model that updates forecasts from early sales, the authors reported that cost "relative to the current informal response system was reduced by enough to increase profits by 60%." Against a no-response baseline, the same paper puts the effect at roughly quadrupled profit.

Population
A single firm — described in the abstract only as "a major fashion skiwear firm" — under early-1990s conditions. n = 1.
What was measured
A model-estimated reduction in expected mismatch cost, re-expressed as a profit equivalent. Not an audited profit increase from company accounts.
Read it with
The 60% baseline is the firm’s existing informal quick-response practice, not doing nothing — which is why the second figure in the same abstract is so much larger. A figure quoted without its baseline is not quoting this paper.
Fisher & Raman, Operations Research 44(1) (1996), 87–99 →

Primary confirmed. Note the widely repeated "halved the cost of over- and underproduction" phrasing does not appear in this paper, and the Harvard Business School faculty page miscites the issue number.

03

Retail merchants spent about two-thirds of their time on low-value-added work

In a McKinsey survey of more than 30 retailers, merchants spent "approximately two-thirds of their time gathering data, managing exceptions, “firefighting,” and participating in meetings to syndicate with colleagues and only one-third of their time working on critical strategy and analytics or insights."

Population
Merchants at retailers generally. Not apparel specifically, and not merchandise planners, allocators or buyers. Treating this as a statistic about planners would change what it measured.
What was measured
Self-reported share of working time, split across two buckets. "Approximately" and "only" are the source’s own hedges.
Read it with
Eight years old, drawn from an unpublished internal consulting survey with no methodology, response rate or exact sample published — "more than 30" is all that is disclosed. McKinsey also sells the transformation the article recommends.
Begley, Fox, Lunawat & MacKenzie, McKinsey & Company (21 August 2018) →

Primary confirmed — article read in full, sentence matched character for character.

04

The industry has not quantified how much merchant time is wasted

Deloitte surveyed 570 merchandising executives and professionals across US mass, grocery and apparel, and concluded that retailers are "still not aggressive enough at eliminating the non-value-add work that consumes merchants’ time" — while publishing no figure for how much time that is.

Population
570 merchandising executives and professionals, US mass, grocery and apparel.
What was measured
None. The absence is the point: the largest recent survey in this area describes the problem qualitatively and declines to size it.
Read it with
If a vendor quotes you a precise percentage for planner time wasted, this is the study it is not coming from.
Deloitte, "Future of Merchandising" (14 May 2026) →

Primary confirmed — article read directly, sample and wording verified.

05

Most brands do not publish the data an inventory benchmark would need

The eighth edition of the index, covering the 250 largest fashion brands and retailers, found that 88% do not disclose their annual production volumes — up from 85% the year before.

Population
The 250 largest global fashion brands and retailers.
What was measured
Share of ranked brands publishing annual production volume.
Read it with
This is the structural reason to distrust any "X% of apparel inventory goes unsold" figure. The denominator is not public for roughly nine brands in ten, so an industry-wide rate cannot be computed from disclosure — whoever quotes one is estimating, whether or not they say so.
Fashion Revolution, Fashion Transparency Index 2023 →

Primary confirmed — index page read directly, figure and prior-year comparison verified.

06

The most-quoted excess-inventory number describes small general-retail stores

A vendor-commissioned survey of 500 US retailers reported that the average US small store held about $48,000 of excess stock, equal to roughly 22% of its total inventory. Within the same survey, 44% of apparel respondents reported excess stock after the holiday period.

Population
Small US retail stores across general retail, with roughly $218,000 of total inventory. That is neither apparel-specific nor mid-market.
What was measured
Self-reported excess stock as a share of total inventory.
Read it with
The 22% is widely recycled as an apparel figure. It is not one. We include it to mark the population gap, not to endorse the number — and the survey was commissioned by a vendor selling inventory software.
Inventory Planner, survey of 500 US retailers (February 2023) →

Verified — survey reporting read; population confirmed as small US general-retail stores.

How to use this

The useful pattern across these six is not any single number. It is that the measured gains come from reacting faster to real demand signal, not from planning harder up front. Caro and Gallien changed when and how markdowns were decided. Fisher and Raman changed how much of the buy was committed before the season told them anything. Neither improved a forecast; both shortened the distance between a signal and a decision.

The second pattern is an absence. Nobody has credibly measured how much planner time disconnected systems cost, and the largest recent survey of merchandising professionals declined to put a number on it. Any vendor quoting you a precise figure — including us — is estimating. Ask which population it was measured on, and you will usually find the answer is nobody's.

If you want a number for your own business, the honest route is to measure your own: reconciliation hours per planning cycle, days between a sell-through signal and a buy decision, and in-season markdown taken against plan. Our retail maths formulas and the planning maturity assessment are built for exactly that, and the spreadsheet risk whitepaper gives you a cost model to run the arithmetic on.

Questions

Did RetailNorthstar run this research?

No. We have not run an apparel planning survey, and nothing on this page is first-party research. This is a review of studies published by other people, each named and linked so you can check it yourself. If you have seen a RetailNorthstar benchmark report quoted anywhere, it should not be relied on — an earlier version of this page presented a survey that was never conducted, and this page replaced it.

Why are there so few numbers here?

Because there are few that survive checking. Most figures circulating about apparel planning trace back to vendor marketing, a conference footnote, or a restatement of a restatement. We publish the ones with a named primary and a stated population, and we say plainly where the research does not exist — Deloitte surveyed 570 merchandising professionals in 2026 and deliberately published no number for wasted merchant time, which tells you the industry has not measured it.

Can I cite these figures in an internal business case?

Cite the original sources, not this page, and carry the population with the number. The most common error is a population swap — McKinsey measured retail merchants, not apparel planners, and Inventory Planner measured small general-retail stores, not mid-market apparel brands. A figure detached from the group it was measured on is no longer evidence.

Why is there no downloadable report?

There is nothing to download that is not on this page. The page is ungated and complete, and the PDF that used to sit behind an email form was retired because its contents were not sourced.

What if one of these citations is wrong?

Tell us and we will correct it. Two figures on this page were previously repeated incorrectly in our own notes and were fixed when we re-traced them to the primary sources in August 2026. Our editorial standard sets out how corrections are handled.

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