{"id":6434,"date":"2026-02-16T15:41:08","date_gmt":"2026-02-16T15:41:08","guid":{"rendered":"https:\/\/newtonimpact.com\/?post_type=content_library&p=6434"},"modified":"2026-02-26T09:53:06","modified_gmt":"2026-02-26T09:53:06","slug":"dont-trust-the-tills","status":"publish","type":"content_library","link":"https:\/\/newtonimpact.com\/en-us\/content-library\/blog\/dont-trust-the-tills\/","title":{"rendered":"Don’t trust the tills – How to fix the self perpetuating cycle of size ratio errors"},"content":{"rendered":"\n
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\n Take Me Back<\/a>\n\n

Don’t trust the tills – How to fix the self perpetuating cycle of size ratio errors<\/h1>\n

By Imogen Hardcastle-Kidd, Retail Director at Newton & Belinda Earl Senior Advisor at Newton and Non-Executive Director <\/p>\n\n

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Blog<\/p>\n <\/span>\n \n

8 min<\/p>\n <\/span>\n \n

16th February 2026<\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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Outdated data and spreadsheet analysis can’t predict true customer demand, leaving many brands with a hidden – and growing – size availability problem. The cost is both custom and margin. But new tools and approaches are an easy lever to course correct.<\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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Introduction<\/p>\n

Imogen Hardcastle-Kidd, Retail Director, Newton<\/h2>\n <\/hgroup>\n \n
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I love shopping so I understand how frustrating it is for customers when they spend an evening browsing, finally spotting the perfect item, only to see their size crossed out \u2013 because that\u2019s me! Before my career partnering with fashion retailers, my data-loving brain wondered: how could this happen so often?\u00a0<\/span><\/p>\n

Now, I know the incredible complexity of managing sizes. Not only does every brand have a different customer profile, size ratio curves vary by country, region, in-store and online. Ratios can change quickly, responding to sudden consumer shifts, innovations like GLP-1 weight loss drugs along with design trends (like oversize) influencing fit. Then there\u2019s the fact that many decisions are made nine to 18 months in advance. Making predictions in such a complex, moving set of variables is a science. Size ratio inaccuracies create some of the most visible gaps for customers, with retailers getting hammered on viral social media posts for running out of fringe sizes regularly.<\/span><\/p>\n

Stocking the wrong sizes leads to lost sales, excess markdowns and customer complaints, but also <\/span>the fundamental problem flourishes unseen<\/b>. Without stock available, sales data moves even further from the true picture, and with no corrective feedback loop, the problem gets worse. No visible signs of trouble means no reason to adapt.<\/span><\/p>\n

But that is exciting too. Most brands don\u2019t realise the opportunity of updating their approach to size ratios, <\/span>there is\u00a0 an early mover advantage to secure sales and customer loyalty<\/b>.\u00a0<\/span><\/p>\n

To help retailers and merchandisers in this group, this report outlines the financial case for adaptation and practical steps to maximising full price sales \u2013 by having the right sizes available in the right place at the right time. This is the moment to act as new solutions make current analytics look as outdated as flipping through line sheets in plastic folders.<\/span><\/p>\n

I hope retailers and merchandisers find this report useful to re-evaluate whether your size ratios are working for your customers. Please contact me if you have any questions. It\u2019s a topic I could happily talk about all day. <\/span><\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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New Data: Size Ratio Perpetuation<\/h2>\n <\/hgroup>\n \n
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In January 2026, Newton\u2019s proprietary web scraping tool, Observatory, investigated current availability across clothing retailers. We combined this data with real world experience gained delivering effective size ratio improvement projects within leading UK retailers. <\/span><\/p>\n

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What we found is that there is a hidden issue affecting profitability in all major retailers.<\/p>\n <\/hgroup>\n

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60 to 75% demand weighted availability on average<\/h3>\n

All retailers have an availability gap when accounting for lost sales adjusted demand.<\/p>\n <\/div>\n

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15% to 20% of total availability losses can be attributed to inaccurate size ratios<\/h3>\n

Size ratio errors lead to customers not buying. <\/p>\n <\/div>\n

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1 to 2.5% like-for-like sales uplift <\/h3>\n

Get it right, and there are significant financial benefits. <\/p>\n <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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Small changes, big gains Up to 20% of total availability losses are due to inaccurate size ratios (with other issues including allocation and replenishment issues, trapped stock, depth of buy and supply chain disruption). The impact of size ratios on margins is significant. Solutions available today matched with a strategic approach can reduce size ratio errors by 30 to 50% \u2013 leading to the equivalent of a <\/span>1 to 2.5% like-for-like sales uplift.<\/b><\/p>\n

Availability reality check <\/b>While our experience shows that most retailers believe they have approximately 80% availability (binary measure), our figures suggest the reality ranges from 60% to 75%, when you take customer demand into account. Size ratio inaccuracies create some of the most visible and frustrating gaps for customers, so size ratio improvements offer a financial, customer and sustainability opportunity that other retailers may not even realise exists.\u00a0<\/span><\/p>\n

Data corruption derails decision making <\/b>The rewards of rectifying size ratio data compound over time. Every time stock is too low, customers are prevented from buying what they want, and sales data moves further from the demand. Speed is key to a full overview too. Purchasing patterns can change fast, so even the first two weeks of sales doesn\u2019t necessarily provide an accurate forecast, particularly when availability dips below 100%. <\/span><\/p>\n

The right size ratio approach unlocks lasting advantage. Better data enables better benchmarking against past styles, identifies trends in-the-moment and supports intelligent stock, range and assortment decisions.\u00a0<\/b><\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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Issue: An ever-evolving environment <\/h2>\n <\/hgroup>\n \n
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Does this sound familiar? Every time you design a new fashion line or rebuy a core staple, a new order is placed with the same size distribution calculated months \u2013 sometimes years \u2013\u00a0before. The result is that there is plenty of stock for some sizes, but none at all for others. The size ratio error is perpetuating the problem.\u00a0<\/span><\/p>\n

We\u2019ve seen issues like this time and again because size ratio calculations are:<\/span><\/p>\n

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  1. Hugely complex – Location, channel, season and range of size are just some of the factors affecting size ratio curves.<\/li>\n
  2. Vast – Hundreds, sometimes thousands of SKUs are in play daily<\/li>\n
  3. Ever-evolving – Customers and trends change fast, with what happened even last week not always being true today<\/li>\n<\/ol>\n

    Often, to stay on top of size ratio decisions, retailers rely on merchandisers who manually update static spreadsheets based on what has been sold, rather than demand.<\/p>\n

    But what if retailers could automate the analysis of sales at a daily SKU-location level, adjusting for continuity and seasons? It’s more than possible with technology matched with brilliant thinking.<\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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    Opportunity: Estimate today’s true demand<\/h2>\n <\/hgroup>\n \n
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    Estimating true demand that drives profitability is achieved by empowering merchandisers to combine their expertise with near real-time AI and data analytics. This means they can make both automated and autonomous decisions.<\/span><\/p>\n

    What does that approach look like at key retail moments?\u00a0<\/b><\/p>\n

    For continuity items, <\/b>retailers get as close as possible to a perfect size ratio by examining historical stock and sales, calculating lost-sales adjusted demand, and correcting orders based on known seasonal trends, while timing orders to minimise stockholding without risking availability gaps.<\/span><\/p>\n

    For seasonal launches<\/b>, <\/span>match to similar products from past seasons with compatible attributes, e.g. shape, design, prices and materials. From there, lost sales demand can adjust for patterns in size ratio, buy volumes, launch volumes and trapped stock, to get a best estimate for the right size ratio to buy this product in. Even if not all attributes have historically been recorded, AI can extract key attributes from product images, reducing manual input and improving data quality.\u00a0<\/span><\/p>\n

    For fashion lines, <\/b>automation reduces the time required for size ratio analysis: we\u2019ve seen two week processes cut to 30 minutes. With merchandiser time freed up, they can focus on the areas where merchandiser intervention is most valuable.\u00a0<\/span><\/p>\n

    For complex category size decisions, <\/b>such as bras or ranges covering any or all of a combination of babies, small children, teenagers and adults, again, granular data matched with merchandiser experience comes into its own. We\u2019ve helped global retailers by quantifying their specific cannibalisation and cross selling patterns, to make strategic decisions where to extend and shrink range.<\/span><\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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    Conclusion<\/p>\n

    Belinda Earl, Senior Adviser at Newton and Non-Executive Director <\/h2>\n <\/hgroup>\n \n
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    Fit and availability have always been central to earning trust for your brand. It’s the basic fundamentals of merchandising and the pressure to get it right will only increase as customers get ever more discerning, and are happy to shop elsewhere at the touch of a button. Equally overstock and you\u2019re left wondering whether to discount, impacting both margins and brand (not to mention the sustainability implications of producing and storing mountains of unsold clothing and cash tied up in inventory).\u00a0<\/span><\/p>\n

    This is the all-too-fine balance between providing what customers want and managing profitability \u2013 a balance that feels especially important to achieve as business costs rise and margins tighten in a challenging retail environment.\u00a0<\/span><\/p>\n

    So why, in many categories, are decisions on size ratios not revisited for years? Should you really buy in a one-two-two-one ratio just because that is what you did last time \u2013 and the time before? History is repeating itself again and again. And as this report shows, even retailers that review their data regularly and are confident in their sizing strategy may be unknowingly off the mark.\u00a0<\/span><\/p>\n

    With all the technology available to us today, it\u2019s time for us all to re-look at size ratios and build a crystal clear, granular profile of demand and availability. It is constantly-evolving, customer-focused work that merchandisers excel at and that leading retailers are turning into competitive advantage.<\/span><\/p>\n <\/div>\n<\/div>\n\n <\/div>\n <\/div>\n <\/section>\n\n \n\n\n

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    Contact<\/p>\n

    Want to continue the conversation? <\/h2>\n <\/hgroup>\n \n\n Email Imogen now<\/span>\n \n \n <\/svg>\n
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