Published: ETRetail.com, May 8, 2017. The fashion industry has a holy grail of 'size sets' or 'ratio packs'. The standard predefined assortments of goods that are used for production and logistics. To understand this: when an article is conceived for the range of the company, considering that the customers require a size that fits them, the same article (design, colour) is manufactured in all the size options (XS, S, M, L, XL and so on, or sizes – 28, 30, 32, 34 and so on). Since the distribution of the human population is not equal across physical attributes, the industry cannot manufacture the same quantities of each size (the number of XS, S, M, L, and XL people is not equal!). This is the 'etymology' of the size set. The set is supposed to be designed after careful analysis of population distribution. It is almost a normal curve distribution with many quantities of some regular sizes and very few of the extreme sizes (too big or too small). For example, a single garment design set might have a high volume for sizes M or L and low volume for sizes XS on one side and size XXL on the other extreme. This distribution supposedly reflects the overall population distribution of the sizes. So, a typical ratio pack of, say, a t-shirt design may have 1 x XS, 2 x S, 3 x M, 3 x L, 2 x XL and 1 x XXL. So far so good?Now let us look at the problem:A visit to any retail outlet will tell us that stock-outs at size level are significant. It is not surprising to find out that the size for a specific design you chose is unavailable. Of course, the salesperson tries his/her best to shift your interest to a different design. Many times, the customer shifts and many times does not. So, at the end of the season what is left over is not only odd designs but also odd sizes. Why do you think this happens?There are two factors at play here. One is the fact that though overall population distribution may follow the normal distribution curve for variation sizes, the sales of a particular design/garment do not necessarily follow the distribution! After all, consumer choice is an enigmatic subject. The assumption that for 3 medium sized people who buy the Pink chest print t-shirt with a white collar, there will be two XL people and 1 XXL person buying is not true. Reality tells us that at a shop and at a day-to-day level, the arrival can be very erratic. The fluctuations at a shop level are much more than what is seen at a large population level. We can suddenly have too many people of a specific size walk in, causing a stock out while the other sizes lie as inventory. But that still does not explain stock-outs and surpluses, right? The second factor at play here is the practice of the fashion industry to produce and supply only in size sets or multiples thereof. This means that the plants will produce in multiples of size sets and if a retailer has to buy, his minimum lot of buying is one full size set. The combination of these two factors creates problems for the entire supply chain. What prevents a retailer from ordering fast-selling designs? It is the fear of getting stuck with the odds. So even when a design is selling fast, and some sizes are stocked-out, the retailer may not re-order out of the fear that when he gets a full-size set, he will be saddled with more of the sizes which are not selling currently. The damages of lost sales, high inventory and discounted sales look significant. Then why is the industry stuck in the inertia of selling in fixed lots? Maybe it has to do with internal production considerations. While most machines need a setup change for a design change, they invariably do not need a set up change for a size change. For example, if we take the case of fabric weaving, the setup is high between design changes but not much for colour changes within a design. Similarly, for garment making, the setups are high for moving over from one design to another. The same is the case of shoemaking. So, for machine efficiency considerations, it is better to take a design and complete all the sizes in one go. The strategy of selling to distribution points in pre-defined sets is not only due to an erroneous statistical assumption that a smaller sample will exactly mimic the distribution of a large sample but is further reinforced due to internal efficiency considerations. But if we look at the end-of-season sales – we see odd sizes of designs left behind while there is a stock out of running sizes. What if the production capacity was used up to produce more of the running sizes instead of it being wasted for making the non-running sizes? Yes, it may increase the setups as the manufacturing planning has to focus on design and size instead of just designs. But is setup time a waste? Well, by not manufacturing as per the selling sizes and forcing design sets in the supply chain, we are actually increasing the wastages of the system (more inventory and loss sales). So it seems that selling as per pre-defined sets is not only statistically erroneous but also bad for internal efficiencies. The solution? Extremely simple now!While the first lot of goods that arrive in stores must be for each size (or one full-size set if you will), the subsequent supplies should be strictly as per consumption. The replenishment (whether it is from production or warehouses) should be at a size level and not a size set level. This will ensure that sales loss is eliminated by always having all the sizes in stock, and at the same time, the surplus inventory is limited by not supplying those sizes that are not selling. A true win-win! Of course, it will call for changes in the ERP system, policies that govern production and shipping and full detailing and buy-in of this solution by all stakeholders of the company, but the results are dramatic.Some of Vector’s clients have seen stock-outs reduce from a typical 25%-30% to less than 5%, a sales growth of about 25% and, at the same time reduction in 'end of range’ and discounts at the end of the seasons. The key insight that these companies have realised is that it is not the manufacturer but the market which decides the size set and the size set for each variant could be different (depending on how the customers take to the product). So, instead of guessing or force-fitting a pre-conceived offering to the market, if the company subordinates to the customer choice, it can capture full sales potential and yet not suffer the ills of high inventory.

Key Takeaways

The practice of producing 'fixed size sets' in the fashion industry is a big reason for stock-outs and sales losses. A change in the manufacturing and ordering process can solve this.

Size does matter!

Published: ETRetail.com, May 8, 2017. The fashion industry has a holy grail of 'size sets' or 'ratio packs'. The standard predefined assortments of goods that are used for production and logistics. To understand this: when an article is conceived for the range of the company, considering that the customers require a size that fits them, the same article (design, colour) is manufactured in all the size options (XS, S, M, L, XL and so on, or sizes – 28, 30, 32, 34 and so on). Since the distribution of the human population is not equal across physical attributes, the industry cannot manufacture the same quantities of each size (the number of XS, S, M, L, and XL people is not equal!). This is the 'etymology' of the size set. The set is supposed to be designed after careful analysis of population distribution. It is almost a normal curve distribution with many quantities of some regular sizes and very few of the extreme sizes (too big or too small). For example, a single garment design set might have a high volume for sizes M or L and low volume for sizes XS on one side and size XXL on the other extreme. This distribution supposedly reflects the overall population distribution of the sizes. So, a typical ratio pack of, say, a t-shirt design may have 1 x XS, 2 x S, 3 x M, 3 x L, 2 x XL and 1 x XXL. So far so good?Now let us look at the problem:A visit to any retail outlet will tell us that stock-outs at size level are significant. It is not surprising to find out that the size for a specific design you chose is unavailable. Of course, the salesperson tries his/her best to shift your interest to a different design. Many times, the customer shifts and many times does not. So, at the end of the season what is left over is not only odd designs but also odd sizes. Why do you think this happens?There are two factors at play here. One is the fact that though overall population distribution may follow the normal distribution curve for variation sizes, the sales of a particular design/garment do not necessarily follow the distribution! After all, consumer choice is an enigmatic subject. The assumption that for 3 medium sized people who buy the Pink chest print t-shirt with a white collar, there will be two XL people and 1 XXL person buying is not true. Reality tells us that at a shop and at a day-to-day level, the arrival can be very erratic. The fluctuations at a shop level are much more than what is seen at a large population level. We can suddenly have too many people of a specific size walk in, causing a stock out while the other sizes lie as inventory. But that still does not explain stock-outs and surpluses, right? The second factor at play here is the practice of the <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/textile-garments/">fashion</a> industry to produce and supply only in size sets or multiples thereof. This means that the plants will produce in multiples of size sets and if a retailer has to buy, his minimum lot of buying is one full size set. The combination of these two factors creates problems for the entire supply chain. What prevents a retailer from ordering fast-selling designs? It is the fear of getting stuck with the odds. So even when a design is selling fast, and some sizes are stocked-out, the retailer may not re-order out of the fear that when he gets a full-size set, he will be saddled with more of the sizes which are not selling currently. The damages of lost sales, high inventory and discounted sales look significant. Then why is the industry stuck in the inertia of selling in fixed lots? Maybe it has to do with internal production considerations. While most machines need a setup change for a design change, they invariably do not need a set up change for a size change. For example, if we take the case of fabric weaving, the setup is high between design changes but not much for colour changes within a design. Similarly, for garment making, the setups are high for moving over from one design to another. The same is the case of shoemaking. So, for machine efficiency considerations, it is better to take a design and complete all the sizes in one go. The strategy of selling to distribution points in pre-defined sets is not only due to an erroneous statistical assumption that a smaller sample will exactly mimic the distribution of a large sample but is further reinforced due to internal efficiency considerations. But if we look at the end-of-season sales – we see odd sizes of designs left behind while there is a stock out of running sizes. What if the production capacity was used up to produce more of the running sizes instead of it being wasted for making the non-running sizes? Yes, it may increase the setups as the manufacturing planning has to focus on design and size instead of just designs. But is setup time a waste? Well, by not manufacturing as per the selling sizes and forcing design sets in the <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/research-and-publication/articles/fashion-forward-navigating-supply-chain-challenges-in-apparel-retail/">supply chain</a>, we are actually increasing the wastages of the system (more inventory and loss sales). So it seems that selling as per pre-defined sets is not only statistically erroneous but also bad for internal efficiencies. The solution? Extremely simple now!While the first lot of goods that arrive in stores must be for each size (or one full-size set if you will), the subsequent supplies should be strictly as per consumption. The replenishment (whether it is from production or warehouses) should be at a size level and not a size set level. This will ensure that sales loss is eliminated by always having all the sizes in stock, and at the same time, the surplus inventory is limited by not supplying those sizes that are not selling. A true win-win! Of course, it will call for changes in the ERP system, policies that govern production and shipping and full detailing and buy-in of this solution by all stakeholders of the company, but the results are dramatic.Some of Vector’s clients have seen stock-outs reduce from a typical 25%-30% to less than 5%, a sales growth of about 25% and, at the same time reduction in 'end of range’ and discounts at the end of the seasons. The key insight that these companies have realised is that it is not the manufacturer but the market which decides the size set and the size set for each variant could be different (depending on how the customers take to the product). So, instead of guessing or force-fitting a pre-conceived offering to the market, if the company subordinates to the customer choice, it can capture full sales potential and yet not suffer the ills of high inventory.

<h5>Size does matter!</h5>

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Often fashion retailers simultaneously face the problem of stock-outs of some fast moving SKUs while there is excess stock of others. Read to know how this can be prevented.