An article in the Wall Street Journal (November 27,2016) titled “The Next Fashion Trend:Weather Forecasting” describes the impact of weather on fashion sales and thus the need for the fashion industry to learn about weather forecasting. It claims that the average temperature last winter was 4.6 degrees above average and thus decreased demand for heavy coats and impacted J.C.Penney’s apparel sales. In response, designer Michael Kors includes a range of fabric weights to cover the possible clothing types that may be demanded in response to weather. Others choose layered options that can adjust to the weather. Which of these options i.e., offer a broader range of weights or offer a layered solution is likely to be the best for the retailer ? Should domestic, quick response yet higher cost sourcing be included as a way to compete ? How might forecasting be linked to product uptake over smaller intervals to ensure profitability ?
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In offering a wider selection, the company may be able to capture a wider market. However, this may also increase costs because there is not an ability to standardize product creation. If a layered solution is provided, this may need coordination amongst multiple suppliers for the materials which could also potentially drive up costs. In order to determine which solution is better, the company needs to compare the profit associated with layers versus heavier coats/lighter coats. If it would cost more to do a layered solution than to not sell a heavy or light coat then a layered solution should be further investigated. However, if the company sees the opposite is true, it may be better to have a wider product array. Though, if the company can forecast the weather and has designed ready for both paths, it can create designs more quickly; this would essentially require a lot of coordination to have materials in place for creation.
Generally, the creation of clothes has a long lead time from sourcing to manufacturing and then shipping. A reduction in forecasting errors would definitely impact the profitability of the company by having lesser occurrences in shortage or overage. Also, in a review by the International Journal of Business and Management, 80% of the manufacturing cost of the product is determined by the design or the process. One suggestion to improve on forecasting would be through “postponement”, similar to the case of Benetton in their manufacturing of a sweater. By delaying the final manufacturing, companies can modify their “basic” design to address the change in weather.
The inculcation of changes in weather change to fashion trends is a pretty old fashioned technique. This was mostly due to the various seasons experienced by the country. But as each season itself changes over a certain number of years in terms of duration and range of temperature, the demands of the customer as well change. By offering a layered solution the retailer is giving a long term option to the customer in terms of higher return/use for the same investment. But on the other hand in areas of fast fashion offering a broad range of weights might work better for the customer as one would not want to stick to the same pair of clothes for a longer period of time. This also has another advantage of higher returns and repeated customers for the same brand. By anticipating the trend in weather the fashion brands can come up with innovative solutions by offering one stop shop for a range of weather patterns and leave the final decision to the customer as per their requirements. At the end of the day, customer loyalty would play a key factor as the cost of acquisition of a customer is rather small compared to a lost customer.
It’s hard to put all categories of fashion in two categories, heavy and layered. Some trendy fashion producers will not risk changing their brand image to adapt to new ways of forecasting or changes in the weather. However, other fashion producers have already been doing it, let alone some producers who use the layered approach as one of their core designs, but those are the more trendy practical fashion brands.
High end fashion producers will most likely use a closer and more expensive suppliers to respond faster, but that is a horizontal competition between fashion producers on the same level.
I would say it depends on the position of the clothes retailer in the market to decide whether a range of weights or layered design is better. For high end clothes retailers, it’s better for them to develop clothes based on different weights because only these branded retailers will be able to spend money on this particular detail. For mid priced clothes retailers, their clothes are much more affordable than those from high end retailers for customers and thus, acceptable to buy multiple clothes. Layered option suits for mid priced apparel retailers. Sourcing domestically should only be applicable for high end clothes retailers because of the higher production cost it leads to.
Layered option is a good solution and will go a long way to go towards demand consolidation and hence more accurate forecasting. But unlike normal commodity products, apparel industry (winter clothes) is mostly dominated by designs, and customers will certainly buy a good design product even if it serves a weather few degrees above or below the requirement. The use of layered design have to carefully coordinated across multiple sources which may tend to increase costs. And even then customers might not approve the layered design and sales will plummet.
There might be many other reason because of which sales may have dipped that winter:
1. Excess stock in customer’s house due to high sales promotions last year.
2. No new design in the market.
I always think the fashion industry is not related with weather, especially high-end fashion. Those fashion people do only consider the design. What’s the weather outside does not matter to them. Low-end clothe industry would be more reactive to the weather, while price is another important factor to them. Thus, high cost-quick response supplier would not be the best choice for them.
There are too many variables to justify using quick response sourcing to respond to the weather. With the relatively long lead times in the industry, the company would have to start relying on external weather forecasting. This would be another forecasting area that is prone to inaccuracies. This multiplied with the companies own forecasting inaccuracies could exacerbate problems. Offering layered options would be a more viable solution and reduce overall forecasting inaccuracies. The company could effectively reduce the variations in their product offerings, which would allow them to forecast more accurately.
If the retailer choose layered option, it can be benefited by satisfying a broader range of customer need. By choosing different combination of layered, customer can assemble the best combination of layers to best fit their need. However, the weight option might not being able to satisfy that broad of customer need. In the clothing market, majority of the sales occur before the season actually begin, thus even though the quick response can manufacture the one that customer need, it won’t be able to catch up the sales. While the forecasting will not be that accurate, it should help the company to have a preliminary picture of the market demand and plan for it which could reduced the left overs.
Clothes that are not sold during the season will be salvage after the season end, so retailer are looking for the option that could satisfy customer the most and left the lowest inventory. If retailer choose the weight option, the temperature fluctuation will lead to large sale of certain type of cloth, but others may remain huge inventory left. On the contrary, the layered option provide customer different kind of choices to satisfy their need, and different types of layer can be combine together and have the same warming effect to accommodate large quantity of customer with the same need.
If the estimation of the total left over cost is greater than the high sourcing cost for the quick response option, then the quick response option should be considered. Since it can satisfy the need for the customer while lower the inventory cost for the retailer.
With the forecasting, clothing industry can produce the right type of clothes that customer needs and reduce the cost of left over.
It is definitely for fashion supplier’s benefit to incorporate weather indicators into their predictive models if the current weather forecast technology is able to capture the overall temperature trend over the next season within an acceptable tolerance. However, the cost of forecasting error can be rather high, since it will be affecting the product characteristic of the entire season, especially given the perishable nature of fashion products. A reasonable alternative should be introducing local, responsive suppliers in preparation for unexpected change in macro conditions instead of manufacturing a vast number inventory in advance.
Looking at how the weather affects demand of winter clothing, having less SKUs (less inventory) would be an ideal situation. In this case, the layered options for winter clothing would be the better option than carrying a broader range of weights which make the retailer have to hold significantly more inventory of winter clothing. It seems that it would be wise for domestic, quick response sourcing to be used as an ideal way to compete if the designer is choosing a range of weights for their clothing so that the designer could allow the retailer to keep less SKU and less inventory but still be responsive to demand. Furthermore, accurate weather forecasting would allow the retailers to hold less inventory if the designers utilized different weight options and correlated their weight options with the weather forecasts, colder forecasts=heavier weight options. Of course, this scenario would require quick response sourcing so that the correct SKUs could be quickly transported to the retailer as the temperatures trended colder. Now the layered options for clothing could avoid the need to accurately forecast the weather and potentially not utilize the higher priced quick response sourcing since there would be 1 SKU that can adjust to the weather. But, the real question is will the customer like these layered options instead of traditional coats? That question remains to be answered.
The weather forecasting will have higher uncertainty and error if the lead time is great. Hence, if there is a relatively long lead time about 12 months in apparel supply chain, forecasting can’t work as a guidance of manufacturing and sourcing. Additionally, the taste of customers changes dramatically these years that they care more about fashion but functionality. Building up quick responsive system will benefit the retailer of having a more accurate forecast of fashion trend but not the weather. High-end retailers who try to lead the trend but not to follow would focus on innovative designs. While for retailers who try to follow the newest trend, due to the intense competition in this segment, the benefit they get from quick response supply chain may outweigh the higher sourcing cost.
I agree with you. Longer lead time, larger forecast error, especially in apparel supply chain. The trends of fashion are changing quickly. The quick responsive system can reduce forecast error and reduce the lead time.
Offering a layered solution is likely to be best for the retailer. Having a broader range of weights will require a much higher inventory and more risk of forecasting error. The layered solution will allow for much less inventory and can help reduce their costs. Quick response sourcing can be considered, however, designs and planning will need to be incorporated prior to the season. The retailer will still need to plan for the production of heavier garments, but give it a go/no-go decision based on early weather forecasts.
The fashion market can change almost everyday, thus the less forecasting error will definitely brought higher profit. The choose of having a brand range of weighted options sounds like would provide better options when facing the weather changing, however, this will incur a huge material and inventory cost to keep those material on hand. The best choice for quick fashion would be having the quick response system. With the quick response to dealing with the customer’s taste, quick response will better deal with a serious of changes to better meet the demand even there is a demand fluctuation occur. Instead of having too much material inventory on hand, quick response will lower the inventory cost plus give better demand satisfaction.
Using a layered solution seems preferable for the retailer because it can utilize standardization to mitigate what would be complex guesswork to produce the different weights needed to suit every customer’s taste, thereby also decreasing the per-unit cost of the winter wear.
As others mentioned, adding weather forecasting would include another very unpredictable variable for the forecasting process, probably leading to a worse result.
If one has the opportunity to use the layered solution, it is not only better for the retailer and producer, because they would be covering a wider range of specifications with a single product, reducing the number of needed SKUs and thus, inventory level, but also better for customers, for acquiring a more versatile product, with a longer life and that can be used in more situations.
I agree with Emily’s point that weather has no influence on high-end fashion. But most people in real life care about the weather. So the weather does a lot of influence on clothing demand. Quick response means higher cost. So for the small retailers, I would recommend having a broader range of clothing to satisfy the demand with variation.
I agree with Adam’s point in that a layered solution allows standardization. The final product can be postponed essentially at the retail store which will help with a more accurate forecast. I don’t think a higher costing quick sourcing strategy would be useful for most retailers. Most clothes bought at retail stores like H&M, JC Penney, Macy’s, etc. are made at low cost overseas, so having a safety stock for a higher service level would not be as costly as relying on quick domestic sourcing to cover stockout.
No company is good at forecasting and adding another variable might just complicate things even further. But then companies have been performing by managing risks associated with forecasting inaccuracies till now.
From a company perspective the question that needs to be asked is what are their core competencies.
Is it an optimized supply chain? Is it variety of SKUs? Or is it a fashion trend setter? Based on that it would depend for the company to choose between a layered option or having a range of fabric weights. From a supply chain perspective having less SKUs looks to be the solution but the industry that we are talking about is fashion and having a variety is an important factor.
The other question that needs to be asked is does domestic sourcing, which would reduce lead time by multiples, help in increasing the market share to such an extent that the extra cost associated with it is balanced or not. Being quick and responsive is something that helps apparel companies’ top line.
Forecasting weather is another variable but if it can incorporated into optimizing the supply chain function for apparel companies then it could improve profitability.
Current day business is becoming data driven in every possible way, new technological advancements are enabling that drive in effective manner. Weather Forecasting is not a new thing and today’s technologies have enabled firms to get reliable forecasts for longer time period of time but despite all these accurate forecasts, fashion firms can only be successful when customer is given an option to choose form and i believe layered clothing with a fashionable design really gives customer a choice not only when buying but also when he is using it if companies are able educate the consumer of the same it would be a real seller.
Layered products also gives the fashion industries a degree of advantage in postponed production and multi-season sale, retailers can themselves restructure the layers based on season if the products are designed with right material that could be across seasons.
The layered option will be a better option obviously because the retailer has to keep less inventory which means lesser inventory holding costs not particularly because of lesser SKU’s but because the product can be more saleable because it eliminates the dependency on weather fluctuations.
Fashion apparels involve innovative and high margin products which requires a responsive supply chain. A responsive supply chain may incur higher costs but the higher margin should more than offset the costs involved.
Accurate weather forecasting can help retailers to stock up only on apparel which will be on demand just because the apparel is the right fit for a particular Fahrenheit range.(We are assuming that the apparel has variety in terms of sizes and colors).Because we are stocking up keeping the weather in mind we will have less holding costs, lesser cost of lost sales and hence greater profitability.
One of the major challenges that the fashion industry is facing is forecasting. Fashion industry is characterized by higher forecasting errors which is a result of higher number of new SKU’s that contribute to 85% of the sales while other regular SKU’s contribute to balance 15% of sales. New SKU’s replace the older stocks on shelves much faster. Fashion apparel companies such as Lululemon Athletica, Under Armour, Zella etc focus on low volume, high price sector. Most of these companies procure products from outsourced manufacturing facilities in Asia (due to low cost) and sell them in USA, Europe, Australia, Hong Kong etc. Any company that has a responsive supply chain would maximize its profits. Responsive supply chains can be designed by using information from the retailers about customer’s feedback during early days of the season (or from sales figures of similar products in previous season) and thus revise production quantities accordingly.
Offering clothing options closer to weather conditions would definitely enhance sales volume, but matching weather forecasts is more difficult especially in cases where lead times are higher. Hence, domestic production with a lesser lead time even at a higher cost would be the best way to maximize sales volumes. I suggest that these companies should maintain contracts with at least two manufacturers (one with lesser lead time but with higher cost, other with higher lead time but with lower cost). If during the season, weather conditions are not matched with clothing options then domestic manufacturer with lesser lead time can be utilized to respond faster. Production quantities of manufacturer with longer lead time can be altered accordingly. Weather forecasts are more accurate for shorter time horizon. Hence, responsive supply chain is a certain need for fashion industry.
If apparel stores choose a range of clothes with different weights, they have to maintain inventory for each of them. Given a season, based on the weather only few cloth types will have good sales and considering how quickly clothes go out of fashion these days, keeping a lot of inventory may not be profitable. Cycle time from design to retail stores for most apparel will range from three to eight months and predicting weather much before the actual season will not be accurate and any decisions based on weather predictions may not work. I think a layered solution is more appropriate to adapt to the uncertain weather changes. Retail stores should find suppliers who can respond quickly to the dynamic requirements of customers through buyback agreements and moving inventory to more favorable weather destinations.
For retailers, offering the layered option is best choice because the layered coats can be adjusted to any weather conditions and will have less forecasting errors. It is easy to procure from suppliers and reduces the number of different product types. However, customer preferences about the layered options should be considered while making the demand forecasting. Most of the people prefer to have two or three different weight of coats to adapt to different winter temperatures. So, these customer category would not buy layered coat. They will be looking for a particular fabric weight coats.
The apparel industry has to consider the weather forecasting while deciding fashion clothes for the season. Because, customer preferences change according to the weather conditions experienced. So, apparel companies should include weather forecast insights in their decision making process and manufacture a range of fabric weights coats to include possible product types that are expected for the upcoming season. To do so, consider outsourcing to domestic suppliers. They will have low lead time and more information can be obtained about next season if we order near to the season to a domestic supplier. This will reduce salvage products and stock outs, thereby improves the competitiveness of an apparel manufacturer.
I would like to weigh the pros and cons of both options: range of fabric weights and layered options. Given the high volatility of the fashion industry, for the layered options solution, the customers would benefit by being able to use the product for a longer term which would give them a higher return on the purchase. It also gives the retailer the benefit of holding lesser inventory and a reduced forecasting error. However, in this case, coordination between different suppliers for materials could be complex and much more important than the other case and hence increase the overall costs. Looking at the range of fabric weights, this would work better, especially for the high-end products as customers generally do not want to keep the same clothes for a long time. This results in higher turns and repeat-customers along with higher brand loyalty. Thus, a financial analysis comparing the two options would need to be done in order to determine which gives the highest ROI. Regarding forecasting, even though adding a new variable of “weather changes” increases the complexity of forecasting, it needs to be done as the preferences of this industry is highly correlated to weather conditions. I agree that the lead time of this industry is quite long and thus forecasting errors can be very high, especially if the weather factor is introduced. However, the domestic sourcing option would make this easier as that improves the flexibility of the system while reducing lead time and improving the forecasting accuracy. Thus, benefit from the quick response could outweigh the higher cost. Customer loyalty is key in this business and if the customers’ preferences are not met, it can destroy the brand and make it very hard to recover from. The cost of customer acquisition in this case has to be compared to the cost of losing a customer which would help make the final decision.
From my point of view, I think offering a broader range of weights would be a better choice. Since fashion industry is a high-paced industry and the life cycle of products are generally shorter, offering a broader range of weights would give the customers more options. It would also be a long-term strategy because it is less dependent on the weather. However, this would be a even better strategy if the company is doing weather forecasting. With weather forecasting, the company has a better understanding of what kinds of clothes the customers are less likely be interested in. As a result, the company can reduce the production of those kinds of clothes to reduce the inventory. This will save the company’s cost and increase the profitability.
Would you agree that by offering different weights of products could extend the product life cycle. Now a fall jacket may be heavy enough for most of winter and maybe even spring. So if designers could use a material and design that transcends seasons. This would reduce the risk of keeping the multiple weights while keeping the unique jackets over a single multi-layered jacket. What are your thoughts? Do you think customers would be willing to wear materials like wool in fall and spring?
I feel retailers must offer different options to customers so that the customers don’t go to other retailers as switching cost for them is very low. To evaluate the better options among layered or broader range of weight must be carried out. Further response from both options from the customers must also be evaluated. Broader range of weights increases the inventory at the retailers end whereas layered helps them to save shelf space. They also should focus on local customers in case of high demand of a particular type of fabric as cost of customer acquisition is very high, The factor of weather should definitely be given some weight while making forecast for future demand as it has become very volatile in the recent years and with the increased global warming and other natural factors it will continue to be the same.
I believe that offering a layered solution would be best for the retailer. Although going with this solution will involve increased coordinating complexity amongst suppliers, demand forecasting inaccuracies would be minimized, and the retailer would not have to order as much and incur such a large inventory holding cost as they would with the other option. However, I do not think that quick response would be appropriate for the layered solution. One of the purposes of quick response is to decrease inventory holding cost, and quick response would be more appropriate to implement if the retailer chose to offer a broad range of weights, where holding costs would be more of an issue. Additionally, weather forecasting is more accurate in relation to shorter time horizons. Thus, in the case where a broad range of weights is chosen, having quick response will allow the retailer to have more appropriate inventory on hand and increase profits.
In my opinion, i feel that keeping layered options would best benefit the customer as he/she is more likely to mix and match various options and would even last long for certain customers in other seasons as well. However, keeping layered options would lead to a lot of coordination issues as Derek has suggested above. Restricting certain items as quick response clothing with respect to the fashion trends would best benefit the retailer in terms of cost. However, having said that it is crucial to consider weather forecasting in demand planning for the broad range of weights as the customer is more likely to go for heavier clothing during really cold seasons than layering options. In this case, the retailer benefits in terms of inventory planning but has to account for the holding costs during that period. I believe that a trade off has to be made in terms of costs and profitability when it comes to choose between layering or broad range of weights option. The former can be attributed to quick response sourcing for select products based on latest fashion trends and other materials under this category could be sourced normally based on the demand forecast. During cold, snowy or windy seasons, having a broad range of weights could go up in priority based on recent shopping trends and competitor analysis of selling similar products.
A retailer will be obviously better off by having a broad range of products to offer to the customer so he/she might select what best suit for the occasion. This might hurt the retailer by the large amount of stock from a specific garment that was too “heavy” or one that was to light for this winter. Layered products might be a better idea to retailers at this moment were global warming is hitting hard and unexpected changes in temperature happen.
Forecast should be implemented by this brands so they might have an idea of whats coming and what should they be prepared too. Cities like Miami or Chicago will know that they’ll need swimsuits or big coats respectively at some point of the year so for some cities like these ones forecast are easier to produce. Layered products might help this retailers in the sense they could be used in different range temperatures but they might also have an impact on fashion. Lets remember designing garments that are layered might look weird at some point and some big efforts should be done there. Again, forecast can help retailers by showing them what is expected but they also should be ready for this sudden temperature changes and have a responsive supply chain that could help them mitigate those extra costs incurred by the postponement of products or lead times.
Even though this is an interesting way to tackle the issue of forecasting clothing trends and supply requirements, manufacturers and designers would most likely be best suited with the second option of offering clothing that comes in a layered design. This allows them the flexibility if weather forecasts are wildly inaccurate. If they plan on an extremely cold winter and plan on producing their garments with heavy and warm material they could be setting themselves up for failure if it ends up being a mild winter. However, if they plan their designs around a layered, modular approach to clothing where layers can easily be added/removed then regardless if it ends up being a cold or mild season they will be set up for success.
I agree with your statement that layered designs will be better for retailers in these times of weather changes. In my personal opinion this type of layered fashion might also affect the industry due to its constraints by having to add layers. I agree that forecasting will be easier but how much will the retailer or designer will be giving up by doing all or most of its garments like that? Success in forecasting can be achieved, but popularity and fashion designs could be dropped and retailers might lose customers.
From my perspective, layered strategy is a better choice. First, changing fabric means that manufacturers need to procure new various fabrics, this process will increase all holding cost, procurement costs and operation costs, and the complexity of production can increase quite a lot in this process. On the other hand, if the manufacturer choose layered ones, they can make the different layers can be reversed based on various weather. As for respond to sudden weather change, I think forecast for a period of time is important, if the forecast shows that the weather change won’t be a temporary one, then it is important to order more stock before the demand change really happens.
Do you think that customers would be willing to purchase one more expensive jacket (the layered option) over a cheaper single layered jacket for the current weather conditions? Because it is fashion, do you think customers would be concerned with committing to a more costly option that may be “out of style” next season?
Weather forecasting do play an important part in improving fashion product profitability. Thus, suppliers should pay more attention to Weather forecasting and figure out the correlation between weather and sales. For retailer, it is very reasonable to choose some stable suppliers and retain some safety stock to react to uncertain weather. What’s more, quick response yet higher cost souring should be included because higher cost also brings retailers a good profit only if they can find out an optimal trade-off. There are many new technologies to help us forecast weather such as machine learning and artificial intelligence, we can take advantages of these tools and develop some model to gain more profits.
I think the importance of weather forecasting goes beyond just the retail cloths industry. It seems that a layer approach could be beneficial for retailers, but I think there is also a benefit to avoid a jacket for all weather variants. Reading the WSJ article, it seems that the designer is trying to use materials from traditional seasons in other seasons, specifically wool in spring. This approach would increase the selling season and allow for retailers to buy lighter weight products in winter and heavier weight products in fall. By breaking down these traditional selling seasons, the designers/manufactures can blur the retailers fears of having excess inventory.
I think that a more responsive approach to weather changes could assist with demand changes. If designers try to forecast the weather for the entire US versus a single state, aggregation should decrease the error. While this error could also be reduced by limiting the number of products through more flexible products, this option would limit the number of products a customer purchases. But, if the manufacturer or retailer can move the inventory as weather develops and changes, it could take advantage of sharp changes in demand. Of course an umbrella is worth more during a rain storm, so jackets are worth more during their designed temperature range. This means the weather forecasting and tracking doesn’t stop at design but continues through distribution.
I think first we need to consider that there are different customer segments in the market and that Michael Kors targets the high-end consumers. High-end consumers can afford to buy different clothing for one single season whereas consumers with lower income group would buy only one cloth fits the full season type of a product. So I think that both the options are equally attractive and that the retailers should keep the kind of possibilities considering the nature of consumers the retailer caters to. It all depends on the consumer segment which you are targetting that can decide which type of a response and sourcing option to use. If the retailer is targeting high-end consumers, quick response is a key irrespective of a higher cost, whereas if the retailer is targeting the low-end consumer, efficiency and lower cost per unit is the key. Better forecast of weather conditions help the company plan the quick responsiveness along with efficiency making it a win-win situation for all the stakeholders and thus the better the forecast accuracy, the lower the costs regarding variety, stock-outs, higher inventory, etc. Therefore, improve the forecast accuracy to enhance the revenues & profits.
The layered option definitely seems to offer a better solution but in the apparel industry, I think ‘fashion’ might be a key determinant of customer preferences and will play a critical role in influencing customers’ choices.
Often, the competitiveness of a company is measured by the competitiveness of its supply chain and those companies which develop Hau L. Lee’s ‘Triple-A Supply Chain’ will have an edge in the market. A supply chain’s agility, adaptability and alignment provide a competitive advantage, the benefits of which outweigh the cost of maintaining such a chain.
The short lifecycle of apparel products makes it imperative that forecasts for these products be accurate. But going a step further, we need to examine ways to improve the accuracy of the forecast. As mentioned in the article, one way is to analyze demand in the context of changing weather conditions. Another way is to see how we can leverage product adoption/uptake rate as a way to improve the forecast. There are mathematical techniques which can be used to model a product’s lifecycle and its uptake rate at specific points of time after launch. I believe if we’re able to estimate the adoption rate, it’ll go a long way towards improving forecast accuracy and thereby the profitability.
Firstly we need to understand the difference in both the type of apparels. A layered option is one which could be used in various levels of weather while a single heavy option is only usable in very cold weather so consumer might have to get multiple warm clothes for various weathers. But on the other hand, a person buying Michael Kors would not be wearing a same apparel in all the weathers conditions and can afford to buy different warm apparels for various level of cold weathers. So, clearly there is difference in the segments targeted by both the options. Talking about the weather forecast, yes the apparel industry should consider doing that but the thing to consider is how long before they have to see the forecast so that they can design a new product for that weather, produce it and make it available in the market for the consumer. And the consumer should get enough time to realize that he/she is going to need that product and should buy one. Can the weather forecast of such a later date be so accurate?
A dual sourcing strategy can be used here in an attempt to minimize the impact of weather variation on the sales volumes. The initial weather forecast can be used to predict the average seasonal demand for each type of apparel. The manufacturing for this forecast volume of apparel can be outsourced to get high profit margins. At the same time arrangements can be made for sourcing domestically at higher costs to fulfill the additional apparel demand, which depends on the weather. The apparel not in demand can be sold at promotional rates to ensure that the company does not have to hold any inventory until the next season.
I consider that offering the layered solution is likely to be the best for the retailer. Within ten years, weather changes dramatically, and it’s dynamic every day. Moreover, the most important thing is whatever retailers forecast, the forecasting will never be accurate. The layered solution offers higher profit margin than a broader range of weights does. Retailers provide more options, meaning that they carry higher cost and risk. Besides, the layered solution is a kind of risk pooling method. The layered solution gives retailers buffer reacting the weather changing and ensure the essential profitability. Of course, retailers need to provide a proper response to weather changes. How not to be over respond is another issues retailers need to deal with.
Weather forecasting is sure important for the fashion industry, it will secure the design of each season could meet customers’ need and sell more products, therefore gain more profit. However, due to the unique seasonality of the fashion industry, the products usually could not sell again next year after it launched to the market. So the accuracy of weather forecasting and flexibility of manufacturing play a significant role. The company could collaborate with weather forecasting company to build a system or get a continuously accurate trend of weather for the upcoming season before or during the production of next season products. And also provide an alternate design for unexpected extreme forecasting error, and make sure the manufacturer could have enough reaction time and capacity facing the emergency change.
Weather forecasting has become an important resource for forecasting demand for retailers. For example, Japanese convenience stores use daily weather forecast to determine the order quantity of foods and beverages.
In the same way, amusement park such as Universal Studio also uses weather forecasting for estimating the number of visitors. Precise demand forecasting allows retailers to moderate the inventory level and cut huge cost. The problem with this case is that the lead-time of the apparel industry is much longer than convenience stores and amusement park. Thus, the variety of layers strategy might work because the company can adjust the product for meeting the demand.
Providing a tiered solution should be a better option for retailers. Due to the high uncertainty of the weather, even the most advanced weather forecasting system still has a large error, so the offering a wider range of weights cannot be used as a good choice. With a tiered solution, you can have a lot of flexibility, customers can choose by themselves, and retailers are more targeted. Domestic, fast-response and higher-cost purchases should be the focus of retailers’ attention, and the difference between domestic and international environment and consumer habits will have an impact on retailer decisions. The quick response tests the retailer’s mobility and is able to make timely adjustments to the market environment. If the capital conditions are sufficient, a higher-cost procurement plan will certainly have a greater advantage in the market, because it can allow suppliers to obtain more profits, so these are competitive means. If it is necessary to predict the product absorption rate in a short time interval, the corresponding laws can only be studied through historical data, especially in years with similar weather conditions, which give greater sensitivity to data analysis.
While this is a interesting take to try and predict sales it is notoriously hard to predict the weather as well. So if this is to be taken seriously then they should start hedging there bets against every outcome. With that in mind i would just try and figure our weather layering or different SKU’s will make me the most money. This is also assuming that all customers are willing to take the fashion of layering or heavier products without that changing what they are normally going to buy. Assuming all of this i would chose the layering option. This seams like a form of delayed manufacturing and as we know this can drastically reduce costs. This also decrease the possibility of missing the market and therefore is less risky then trying to guess what the weather is going to be like a year from now.
In my opinion, it can’t be asserted that which choice is better for retailers, since revenues or sales volume of retailers depend on various factors, including clothes characteristics, forecast errors, etc. To be more concise, if I am a big fan of Michael Kors, I’d like to choose the coat of it no matter what the style is. Moreover, to some customers, they aren’t concerned the warmness of the coat and what they are concerned is only the style, then it’s not easy to say which choice is better for retailers. Therefore, to determine which choice is better, factors above need to be taken into consideration. In fact, I think that adjusting the designation of clothes based on the weather forecasting may not generate as much profits as expected for two reasons. First, the forecast errors which may be quite big can’t be avoided. Then, delays exist, since both the designation and manufacturing need time. Therefore, the finishing of new style coats may exceed the weather fluctuation periods.
This new forecast impact on the fashion industry will heavily depend on the forecast error to the weather. Even though it does not seem to work for the current weather forecast technology, however, as the fashion industry becomes more and more competitive and the weather change becomes massive, it may be the new way to rethink the logistics in fashion. Comfortableness is a big part of for consumers while considering a brand. In terms of design, thinking from customers’ perspective would be the core competitiveness for companies that it can provide the high-quality product that suits customers under the weather they forecast. Logistics will become highly unstable if companies are trying to catch up with the weather. Therefore, they should provide more flexibility for the products that fit the forecast. Eventually, I think, it is not only about the cost or logistics or the forecast accuracy, but more about the product itself that create higher customer satisfaction.
I believe that Michael Kors’s choice of offering a broader range of weights is the best for the retailer. As the apparel industry is facing a long lead time and high forecasting error. Actually it is difficult to forecast accurately for the demand of the coming winter. Therefore, if the wide range of weight is offered, the retailer can make choice according to both the weather and the preference of consumers. In this way, orders can be made ahead of time and help with cost saving.
As for the domestic, quick response sourcing, it is based on the high margin. If the margin is high enough, we of course can choose the domestic sourcing instead of the imported sourcing.
It will come down to analyzing the costs associated with each option. A wider product array has the ability to catch a wider market of individuals and increase the overall amount of goods sold. While a layered solution can lead to higher sales for an individual purchase because consumers will want the matching outfit. One of the main factors will come down to longevity of the outfit in terms of fashion style for the consumer. The advantage of offering a wide product array is that the consumer has the opportunity to easily mix and match and create new outfits over time, while with layered solutions may make it difficult to match and consumers could be stuck buying a complete layered outfit to complete the work. In terms of utilizing domestic, quick sourcing methods, I believe it is something the company should keep on the table. If after their initial production is delivered and consumer demand is well above the anticipated demand, then it could make sense to incur the higher cost of the faster sourced product at a higher cost. When it comes to having an efficient supply chain, it is important to always consider all the options available.
One thing is definitely correct is that weather would have an impact to the style of apparel. However, how much it can influence the sales is still hard to say. But as an rigid demand, it is worth to change. A range of fabric weights could definitely cover different types and may easier to design or manufacture, but it inevitable will cause surplus clothes which in final get a big discount due to the fast-changing style. For layered option, it could be more flexible and better adapt the changeable weather. Nevertheless, it may cause extra cost and stress the design and manufacture. In final, quick response means higher cost but in turn decrease the inventory which could improve the company’s competitive.
Choosing between two options is based on what the company is trying to achieve. If company focuses more on reducing risks, inventory costs and increasing flexibility, then it should choose layered option. However, layered option is more costly and easily outdated. If the company can come up with a creative design solution, like a jacket with multiple wearing ways and looks, then it would be the optimal choice. If company focuses more on satisfying customers and reducing production costs, then it should choose a broader range of weights. Customers will have various styles of clothes to choose and get more satisfied. However, this option will incur high inventory costs. If the company have the ability to redesign the outdated clothes letting them adapt to the trend. Then it would be the optimal choice.
To improve the forecasting accuracy we should look for out of the box variables like weather forecast, which always helps. The strategy one can follow in this scenario can be to have two order up to policies, one for outsourcing products and other for sourcing from domestic.
The strategy suggested by Micheal Kors is synonymous to assembly postponement. But instead of people’s interest in buying the product being the sole factor, the weather is also a deciding factor which can be readily forecasted. Including a range of fabric-weights will give a sense of wide variety to the consumers is critical in the fashion industry. Having fabric that adjusts to weather can be adopted for designs where demand forecasting is widespread. Quick response at a higher cost is still better than understocking because even at the higher cost, the profit margins can be 100% in the apparel industry.
In my view a wide variety would be beneficial for the over all supply chain as there will be individual demand for each variety. Further, even a customer would get bored in case of layered clothing. Firms should take this decision based on their brand positioning strategy. Having said that, predictability of weather should not be discounted. Firms should deploy predictive analytics to forecast weather and in turn forecast when to bring out the products in the markets.
Apparel sector has been plagued by Fashion for centuries. To rightly predict the Fashion is like hitting the jackpot. No one can truly know what all factors govern the forecast. Adding to the misery the climate shift and weather change has also started to play crucial role in apparel type.
One who can better forecast can play with large inventory of less SKUs. However others have to make a trade-off between greater range of SKUs or quick response delivery from domestic at higher price.
This is more towards a permanent shift, where apparel industry can take this as a indication to the market shift. However, adapting the 8 months lead time with weather forecast is not an easy bet and relies heavily on the forecast accuracy. The layered option may reduce the forecast error due to aggregation. But this will drastically reduce the expected profit margin.
It is for sure that the impact of weather is significant on Fashion/Apparel industry and this should definitely be included while making the forecast for the next season. The question here can be asked that how drastically the weather would change the on-going trend in the fashion industry.The layered options seems to be more safe since, customers would have the option to change whenever they require and it won’t assess vast range of suppliers, whereas different fabrics would increase the coordination issue. Here, it’s also important to understand the brand of the respective companies. Michael Kors is an high end brand, which definitely would like to satisfy their customer with vast range of SKUs where as the companies opting for layered clothing would suffice the generic demand of the population.
While the range of fabric weights have higher profit margins attached to it, the layered options would sell in larger volumes throughout the year. Comparing the overall profitability of both the options would be a good way to decide the best solution for the retailer. The retailer needs to evaluate the impact of lost sales and goodwill cost to develop its sourcing strategy. If the trends can be forecasted in advance and sales can be estimated well, lost cost sourcing would be profitable. However, if it is difficult to evaluate the trends and a quick response is needed to fulfill the demand, high-cost sourcing would be a better way to compete. The sales of a related product in the recent past can be used to understand the demand. This recent history of product uptake can then be used for better forecasting of consumer choices.
With estimates of forecast errors ranging between 100%-300% in the fashion industry, the effect of a huge reduction in the forecast error cannot be overemphasized. One way to improve on the forecasts is to forecast using data from sales of similar products at points closer to the upcoming season before placing the order. The most effective sourcing strategy in this regard would be the domestic, quick response sourcing.
Though sourcing domestically would imply higher costs, the retail gross margins of 200%-250% would be more than enough to cover the costs. There would also be the need for an agreement for the fashion company to commit to a 100% service level to ensure a higher expected profitability for both the supplier and the fashion company.
The first question that came to my mind when I read this, is the explanatory power for this regression model. Assuming the model is robust, I would recommend a layered approach for segments that are price-sensitive and more customized heavy option for customers who have a greater willingness to pay. This is because customers who are price-sensitive when given a layered option, can customize their outfit depending on the weather every season instead of having to purchase a new outfit. Thus, a layered approach will give customers an option to build their own outfit that matches the season. However, shoppers with higher disposable income may not face concerns in purchasing new outfits to match every season. I realize that in my argument above, I have viewed this through the lens of a marketer and hence only considered demand side. Viewing this from the supply side, i.e. costs optimization standpoint, it boils down to analyzing the total costs incurred with each alternative. The point where these two factors meet would be my solution to this issue.
Offering a wide range of weights and Offering layered solutions have their own positives and negatives respectively. Merits of the former include capturing a wider market while de-merits include increased holding cost. Merits of the latter include lesser holding cost while an inability to cover a diversified market would be one of the major drawbacks. In such a case, it becomes important to look at the influence of sales by the change in weather pattern. The fact that the average temperature last winter was 4.6 degrees above average meant a reduced demand for heavy coats. Since the demand is planned in the fashion industry at least half a year in advance, If a company following former policy wasn’t following at the weather forecast/weather forecast being inaccurate would affect their sales drastically. In such a case, retail stores offering layered solutions would do good in terms of sales.
To counter this problem, we can adopt a quick response, 100% customer service level agreement between retailers and manufacturers which will see both retailers and manufactures ending up with profits.
The lead time in fashion industry is too long which makes future demand prediction difficult. there is high risk of trends changing for various reasons including weather. It cannot be completely avoided but the risk can be reduced by the assembly postponement strategy. The final products can be assembled much closer to the actual demand date when demands/trends can be better forecasted. Layering can also be an option. However, the customers who are accustomed to buying high-end winter jackets might not necessarily conform to layering options. To target such customers, having a wider range of options available is a better strategy.
Having a range of fabrics of different thicknesses seems innovative but it does not necessarily resolve the demand forecasting problem. Michael Kors will face issues while trying to source the fabric. They will not be able to gain the same economies of scale that they would if they chose a single fabric. However, were they to choose a layered option, they could pick a single fabric that is slightly thinner and make a whole range of apparel. The beauty of this variant is that the layered option will appeal to customer owing to its practicality. A layered option will definitely be more economical for the end customer compared to two or three coats of different thicknesses. The fashion business, especially seasonal clothing relies heavily on the ability to respond to changes in demand promptly. While Michael Kors should focus on cheap sourcing for the bulk of the their manufacturing, they should have an alternative supplier in close proximity to react to any spike in demand. Forecasting can definitely be linked to profitability over small intervals. For example, weather adversities such as snow storms are not typically known by the average customer until that week or that month. This pressurizes the customer to react to such weather conditions by stocking up on warm clothes. Companies can take advantage of this to change their stock to cater to changing weather conditions.
Multiple questions need to be answered to decide on what to would trend:
1. The unpredictability of the nature of customers’ behavior, trends can be on either side.
2. The fluctuation in weather, which has become imminent in recent years.
3. The cost of forecast error vs the cost of sourcing various materials, and many more.
I would think of this as new product development because weather fluctuation has started impacting sales now, but was not a concern few years back.
It is important to understand the customer’s reaction and costing for changes to develop strategies to check what works out: Local sourcing may help if weather forecasting is as error prone as apparel industry forecasting is, as it would hamper sales and brand image both.
The same concern is for whether to use weighted clothing or layered clothing.
The idea of product uptake over smaller intervals becomes important during periods of higher uncertainty. If the fashion is trending so quickly or the weather is changing so quickly or both,the ideas would be beneficial. Zara and H&M has worked on similar models to benefit in fashion industry. The different version of it, i.e. predictive analytics for short version would work to control the cost and ensure a better service level for the customers.
We have two strategies to choose from. Offering wide varieties or Layered solution. Adopting just one of the two strategies might or might not be profitable depending on the accuracy of the weather forecasting. So, a wise solution might be to have a mix of both the above said strategies. In case, the winter is not as harsh as it was predicted to be, layered jackets might be the most sought after by the customers. Also, to capture a wider market it is always better to have more options at the store. In case, a fashion company has not been doing at par in the recent years mainly because of poor forecasting it would make sense for them to adopt a quick response with a higher cost sourcing to compete in the market. Postponed production can be adopted and the final product can be built closer to the start of the season depending the updated forecasts. This could lead to product uptake over smaller intervals to ensure profitability.
The primary rule of forecasting says “Forecasts are always wrong” although, this is not to be taken literally. That being said, in a highly dynamic industry such as the apparel industry with high lead times of 90+ days, I don’t think companies investing into weather forecasting is a strategic decision. Layering is definitely a better option to adopt because this gives the customer more options to play with, making them feel more in control of their purchase decisions. This is also beneficial to the retailers, as now they need to keep a lesser inventory and have a reduced error in forecasting.
The inculcation of changes in weather change to fashion trends is a pretty old fashioned technique. This was mostly due to the various seasons experienced by the country. For mid priced clothes retailers, their clothes are much more affordable than those from high end retailers for customers and thus, acceptable to buy multiple clothes. Layered option suits for mid priced apparel retailers. The factor of weather should definitely be given some weight while making forecast for future demand as it has become very volatile in the recent years and with the increased global warming and other natural factors it will continue to be the same. In the end, retailers need to provide a proper response to weather changes. How not to be over respond is another issues retailers need to deal with.
Technological advancement has always facilitated businesses by providing them more accurate information about the something that they needed to forecast before. The scenario above is a perfect example of this.Each solution here would have its own pros and cons. Offering a layered solution would make manufacturing more standardized and hence reduce production costs. However, offering broader range of options would give customer more range to choose from, thereby targeting all consumer segments. What should be the strategy for JC Penney or any player in the winter apparel industry should depend upon who are their target consumers.Forecasting in short term would allow retailers to coordinate and display the right assortment of apparels in their store to completely meet consumer demands.
Fashion retailers often struggle to address seasonal fluctuations and capitalize on unexpected opportunities quickly. Predictive analytics for planning and forecasting to provide real-time insights, retailers can shorten seasonal cycles to meet changing customer preferences. More flexibility in the supply chain responsiveness can enable higher cost sourcing. The ability to combine internal and external data resources which lead to greater precision of in-season control. It can help in deriving insights and optimize product, promotion, pricing, placement and people.
Michael Kors range of fabric is a better option; there are no leftover inventories in the market. The inventories can be used during Black Friday or Christmas holidays.
I think it definitely depends on the geographic region that you live and the impact of small temperature changes. Living in Michigan, I would be surprised if 4.6 degree difference in the temperature would change purchase trends of outdoor gear. In other areas that have a more moderate climate, a mild change in temperature would have a greater impact.
That being said, I think it also depends on your target customer. Vendors such as Michael Kors can easily pass on that cost if you are in New York City. In rural Michigan, an increase in cost due to decreased lead times, would like affect sales.
I also agree with Neha’s comment that the idea of selling options for layering leaves you less likely to have leftover inventory that doesn’t have any salvage value. Hopefully you could at least place the item on sale and still break even.
The seasons have seemed to changed considerably from year to year which certainly has impacted the types of clothing people are wearing and purchasing. From a retailer perspective, it would seem much more logical to offer a layered solution to clothing given the high level of uncertainty in predicting weather far in advance. The main issue with having a wide range of offerings to cover all potential spectrum is the high likelihood of significant left-over inventories at the end of the season. Particularly in the areas where the weather didn’t “hit”. Left over Inventory in the retail space is clearly a major source of waste, keeping clearance stores such as TJ Maxx fully stocked. In order to account for this significant left over inventories in these typical department stores, they need to have pretty high profit margins on their products. One way to improve this process is have a shorter forecasting model (more accurate) using quick response/higher cost sourcing. The profit margins would not be as significant, yet left over inventories would inevitably reduce. A win for all involved.
Companies should use a broader range of indicators to predict demand and improve forecasts for their winter solutions. With changing climates and more unpredictability in seasons, offering layered solutions is likely to be the key for the retailers. They can offer smaller quantities of certain items and sell more items to maintain the same level of warmth. According to companies like Patagonia, higher cost more environmentally responsible sourcing is the responsible choice for the environment while still providing a quality product. I think it depends on the companies business model and what they value. Higher cost sourcing will lead to higher costs for consumers. Some consumers will not make these type of investments.
Forecasting will assist by taking into account seasonality of the product as well as the right size to buy in inventory to maximize profits. Over-buying to obtain better CPU’s on the goods it takes to make your finished product do not make sense if they are going to turn into waste. In this scenario manufacturing the traditional amount of really warm coats to be sold would not make sense. Knowing that the end consumers will not be purchasing them because of climate changes should cause a different production decision.
I would expect that retailers would prefer the layered option, as it would likely mean less inventory remaining at the end of a season. The Michael Kors strategy of offering multiple items would most likely result in higher inventory levels at a retailer at the end of each season. Mild winter equals left-over heavy coats while cold winter equals left-over lightweight jackets. The layering option should allow for more predictability.
Quick response domestic sourcing may be beneficial to employ the strategy explained in the HBR article Making Supply Meet Demand in an Uncertain World. Utilize domestic sourcing for reactive products that are more susceptible to weather (heavy coats), and utilize overseas sourcing for products that tend to be consistent and more predictable year-over-year (lighter coats). This would be more applicable to the Michael Kors line of covering a range of fabric weights.
Fashion and weather are both unpredictable in their own right and I’m not sure of the value in using one unknown to predict another. Customers and therefore retailers would definitely appreciate the option to dress for the weather. I believe that the layered option would be better for the retailer because they would be able to could offer the product in many ways with different pricing options. Additionally, for retailers with national presence, they may be able to order in bulk and offer them selectively based on the weather in the location. The broader range of weights could have greater cost especially for the heavy-weight fabric and retailers would have to be selective about the locations where they could offer them.
If holding costs are minimal, and it is the same product that is being ordered, domestic, quick response may not be a big factor. Unlike perishables, retailers can choose to order in advance based on predicted demand without having to write off inventory because it went bad.
All retailers use historical sales to predict demand – forecasting for smaller intervals might be useful for seasonal items. Based on product uptake the corresponding forecast can be altered.
When comparing the choices of multiple weight fabric offerings vs a layered solutions, I think that the layered clothing choice would provide less risk to the retailer. If selling clothing choices in multiple fabric weights, it would seem there is higher opportunity to be left with inventory as some selections would only be appropriate seasonally. Demand variability due to impacts such as weather in addition to style preference would both be in play. With a layered clothing line, as many have stated, there is more flexibility for the consumer, and this should enable improved (lower) product mix to manage in their forecast. From a forecasting perspective, applying processes as described in the HBR article on accurate response may be appropriate. One of the methods mentioned in the article of manufacturing items that are common early to provide a stock level and leave more manufacturing open for non-standard items may be an approach to take. High runner clothing choices, or base layers could be more predictable and enable building ahead, or level loading demand, to allow for a buffer when other more unpredictable demand needs arrive.
A broader range of options with different fabric weights appeals to a larger group of consumers. When you have a layered design you limit selection and may lose customers. I personally don’t like layered jackets so I know I wouldn’t buy one. The downside to this is you hold more inventory with multiple options of fabric weights and you have higher holding costs. With that said the broader range of weights should appeal to a larger group and result in less undersold inventory.
Domestic higher cost sourcing can be an option to buy inventory at a shorter lead time to allow for additional time and data to forecast weather patterns and translate that to customer needs. Retailers and fashion designers can blend domestic and Rest Of World (ROW) sourcing to gain the benefits of each path (lower costs versus speed).
Forecasting at smaller intervals can improve accuracy of demand versus supply and allow designers and retailers to proactively adjust orders before and during seasons. Perhaps they can even implement a Just In Time (JIT) type of push manufacturing model if the manufacturing and delivery times are acceptable. This will ultimately lead to less probability of unsold inventory and less holding costs… a win-win.
Personally, I believe that the retailers have already aligned themselves towards the layered option. When purchasing clothing in colder climates, one will see the options of purchasing a coat that may be used for multiple seasons via removing layers. It all depends on the market – I have multiple winter coats and just plan accordingly as to which I will wear per the weather outside. Domestic, quick response sourcing will not effect the clothing industry. As retailers tend to plan for seasons one year in advance – creating a fast TAT on more clothing will not be an option.
Forecasting in this industry has to be very difficult as they place orders at least a years in advance. They must evaluate demands and create forecasts based on past history. One benefit to online shopping is that the company can quickly get an item to a customer if it is not available in a particular market.
I believe the layered solution gives people more options therefore will be the most popular choice.
Fast fashion is the practice of rapidly translating high fashion design trends into low-priced garments and accessories by mass-market retailers at low costs. There are a number of elements that are key to the fast fashion process, namely: the price of the garments and accessories; and the method and timeline of manufacturing.
Accurately forecasting your sales and building a sales plan can help you to avoid unforeseen cash flow problems and manage your production, staff and financing needs more effectively. A sales forecast is an essential tool for managing a business of any size. It is a month-by-month forecast of the level of sales you expect to achieve. Most businesses draw up a sales forecast once a year. With this information you can rapidly identify problems and opportunities – and do something about them.
I would argue that marketing outerwear with layered options would be the best for the retailer. Based on the geographic location, the retailer should obviously focus on options that fit its local area’s weather the most. I think having a layered approach would allow the retailer to sell its offering for longer periods throughout the year. These layered options could really appeal to the market base because while customers may have to invest more initially, they could use their layered outerwear throughout the year to meet the needs of fluctuating heavier and lighter weather based on the seasons.
The downside to having a layered approach is that customers may not make purchases as often. So I would assume that a quick response approach would be ideal to maximize profitability in the short-term. Meanwhile, forecasting would be necessary for understanding the variance of weather changes throughout the year. But I would encourage the retailer to also focus on demographics in their forecast. For layered outerwear that may not sell as frequent because it could be used year-round, understanding area turnover will help in forecasting (e.g. college town, military, etc.).
Retailers that want to maximize profits from unexpected market changes influenced by weather in this case would do better if they opted for the layered solution in my opinion. With a layered solution a retailer may be better able to match supply with demand. Depending on the overall deviation from “normal” in the weather patterns it could assist in forecasting to order more heaver layers or more lighter layer items. It could also provide opportunities for up-selling customers on layers that are not moving as well. By mixing and matching it could reduce unwanted inventory.
Because there are a lot of people that don’t plan and purchase winter jackets or clothing until it starts hitting uncomfortable temperatures I would say yes that quick response at higher cost should be included. For a purchase like a coat or jacket I know that if I find one I like, and it is cold outside I’m willing to pay more.
I think the layered option would be great for retailers because they will make more profits. Additionally, reviewing their past forecasting processes and adjusting what has or has not worked in the past would be critical for success. The idea of “upsells” really works in that the business creates a solution to a problem for the consumer. Thus, higher profit margins for the business with additional upsells. We see this all the time driving up to a fast food restaurant. Would you like to a package of cookies or drink to go with your entree?
That being said, profits will only go up during winter months so we are discussing seasonal profitability. Companies that invest in online marketing professionals will also increase their chances for higher profit margins in regards to clothing. These specialists know how to create sales funnels and one click upsells that increase purchase amounts. Amazon being a perfect example. I think the layered approach would work best for the company for the long-term.
I believe consumers prefer layering in clothing as it is more about versatility and efficiency over weighted garments. Instead of dressing in heavy items, layering helps to quickly add or remove as conditions change. If the weather is fluctuating and becoming unpredictable, then retailers shall choose clothing that helps consumers to adapt to varying conditions and fluctuating levels of activity. Choosing from a higher cost sourcing is an option only if the supplier lead time is short and they will turn the inventory around fast.
Though higher cost sourcing helps on customer satisfaction that would result in leftover inventory and possible shelf space constraints unless order quantities are small batches and the turn the inventory around is fast. Product uptake over smaller batches and small intervals of time would be a better solution, in which case the demand forecasting and order process has to be balanced. Collecting and retaining historic demand forecast, actual demand, A/F ratios, and analyzing forecast errors correlated to weather forecast/errors is critical for creating profitable models.
For certain winter brands like Canada Goose/ Patagonia – changes in weather prediction will have no affect. These brands are positioned in the market as multi year extreme weather clothing and do not even offer deep discounts
For fashion brands, i had an opportunity to work with designers for Nordstrom to create an application that helped them in creating their seasonal product line. Work on Fall/Winter collection actually starts way back in April/May and it is hard to predict the weather at that time even with best statistical tools therefore the go to strategy would be to create a wider set of clothes.
I would assume that the short term operation planning would be to regulate the supply of heavier or lighter clothes depending on weather. One would start with the lighter fall collection but if it starts getting cold, supply of heavier clothes would be increased. The production could be delayed incase weather stays warm. So I would suggest that newspaper model alone would not be sufficient as the fluctuation in weather patterns would instrumentally affect the production capacities and supply chains
Adopting weather forecasts into a integral component of launching a broader range of weighted clothing or different layered solutions will reduce waste in manufacturing. Demand forecasting in retail is key and without demand forecasting it is difficult to have the right amount of stock on hand. Company’s stand the potential threat of losing customers to competitors. The addition of weather forecasts can play a major role in meeting the demands of consumers in diverse regions.
In my opinion, offering a layered solution is the better option for the retailer. Consumers will have the option to purchase multiple items for their wardrobe and plan accordingly to any weather forecast in their region. This is turn will allow the volumes for production to be more accurate and retailers will generate more revenue within the company, while reducing inventory.
One of the major factors that should be considered regarding the question of additional layer options versus broader range of weights comes down to inventory. In my opinion you would only have to increase your inventory slightly with broader range of weights (one or two new options) as opposed to the layering strategy which could require many new garments for layering. Additionally, it seems as though some sort of customer preference study would be needed prior to making this decision. With regards to quick response supply chain, I don’t believe this is necessary. We have significant data regarding global warming and the impact on weather. Year over year forecast are fairly reliable and this data should be leveraged. Weather forecasts should be evaluated on a quarterly intervals to determine the needs for garments.
It’s interesting to read that weather forecasting could be to blame for a decrease in sales of winter clothing. I believe that this could influence the purchasing trends of some heavier winter wear. When we lived in the Southwestern region of the US, we certainly didn’t purchase nearly as much heavy winter clothing. I think that it is important to understand the implications of weather on fashion and I could see it being a positive move looking more towards the layering approach of fashion design. This way it would be more suitable for more geographical areas of the country and it seems in its self to be a much trendier way to go with the lighter is better approach. I like the quick response at higher cost option to domestic sourcing. If it were anything other than fashion I might not agree. When it comes to winter outer wear, anything goes. People not only like to have the right coat, but they want to look right for the season. Over all I think the layered options will outperform the fabric weight design. This gives the consumer more flexibility when it comes to winter outerwear. It will be interesting to watch how the clothing designers keep pace with the changing weather forecast.
It all depends what kind of brand recognition each of these retailers have on coats and on layered clothing. In general retailers should have a mix of broader range of fabric coats. A conservative manager would factor in layered option in the product mix. Splitting the winter demand into heavy coats and layered while using the newsvendor model would give two different inventory choice for both the options. This way we can cover the loss of one mix to another. Another 4 degrees increase from last winter would result in drastic reduction of heavy coats sales and on contrary if there were a decrease in temperature there would be a spike in heavy coats sales. Since there is no technology available to predict weather this far, the best is to rely on historical data and make a projection. Forecasting linked to smaller interval is good idea only if there is a good cancelation policy.
Technically, you can only know what the average temperature is after the fact (then you sum up and calculate the average). Which means you cannot really predict the strategy to adopt if your main data is obtained post-ante.From the customer point of view, the layered strategy would be more advantageous, although it is down to the manufacturing strategy to determine the more suitable pricing. Let say that you can split in two the production (fabric weigh and layered options), the demand can be more accurately measured and a trend of the cloths ordered definitely gives a better base for future orders. Domestic sourcing only makes sense if the NPV of the project is positive, the advantage of such a technique should be the time to availability, but the problem is definitely the quantity (how much should we order and in turn how soon would the clothes be there?). Only after can we compute the logistic of the firm. Forecasting helps (with a margin of error) to establish an estimation of what will be needed. It can help in a certain measure.
We cannot depend on one strategy on this competitive and high demanding volatility of the current market. I believe of offering warm winter cloths and a combination of Layered ones. As the weather forecasting may vary its better to adopt more than one strategy to make the firm profitable. Ina nutshell it should be a mixture of warm and layered cloths based on the market demands. If the winter is not as harsh as it was predicted to be, layered jackets might should be more applicable to the customers comparing the warmer ones. Also, to capture a wider market it is always better to have more options at the store. In recent times fashion company has not been doing mainly because of poor forecasting and competition from different online stores like Amazon. Again the cost factor is another hindrance for the fashion company because they are not able to compete with other online companies. Overall to be profitable its better to follow the market trend and should strategize taking all the factors including weather. You have to be the game changer by introducing innovative ideas in the clothing section with affordable pricing to the customers which can increase your sales and stay in the competition.
It is worth noting that the accuracy of the weather forecast is strongly related to the lead time, and a longer forecast period will result in higher uncertainty. Similarly, if the lead time in the apparel supply chain is longer than acceptable predictive accuracy, the forecast cannot be used as a guide for manufacturing and purchasing. Rather than investing in weather forecasting, it is better to build a rapid response system that benefits fashion retailers.
Logically, weather forecast can be a key break point to lots of industries, but, in my own opinion, not to fashion industry. On the one hand, set a broader range of different weights layers can extramely extend the lead time of the whole season’s products or increase overhead cost due to an insufficient response time. On the other hand, weather impact would not became the key critiria for the fashion industry customers. Increase the R&D cost for new functional matrial would be a more reasonable choice for the company and a more possiable to attract their target customers.
Impact of the weather on fashion is very common and forecasting this seasonal impact prior and accommodating for it can have huge potential for profits. Particular weather not only affects the type of clothes or materials of fashion season but also the colors trending for that season.
In the discussion above, offering a broad range of fabric weight can cause lot of variation in demand for each type and can be a huge task dealing with the amount of inventory of each type. Whereas, offering a layered material is an engineered solution which not only simplifies the product variations but can also have economies of scale that help with the fluctuating demand.
In saying so, there might be lot of other factors that cannot be proactively figured out and if not acted upon quicker might lead to loss of margin and sales for the season. Hence apart from having low cost, and high lead time sourcing for stable demand, we must also be ready with a domestic, quick response yet higher cost sourcing as a way to compete with fluctuating demand.
I feel that we can learn from Zara, the fashion supply chain leader. Having a responsive chain pays off big time in the apparel industry. Weather predictions can give a very small idea about demand, but I seriously doubt fashion companies will be able to place their forecasts solely on the weather forecasts.
It’s the customer who decides against what fabric he/she wants this season, and fashion houses have no choice but to follow a reactive approach to meet demands. If we can have a nearby local supplier, which has good turn around time, we can meet customer demands based on the season as it progresses.
One other thing companies can do is to have their products in a more modular form, which can later be fully customized as and when the demand is more predictable.
The choice between broader range of weights and layered options is dependent on the customer segments being served by the respective retailers. The layered option gives more flexibility to the customers and is more suited for the mass market whereas a broader range of weights is more apt for customers with deeper pockets who can afford mutliple winter coats. Domestic quick response sourcing options may be more suited for dynamic demand marred by fluctuating weather conditions, but comes with the trade-off of high costs. So again, this is a matter of choice based on the customer segment being served. If weather forecasting can truly be a part of demand forecasting it can determine demand patterns over shorter periods of time. However, the shorter the period of forecast, the more inaccurate it is.
Offering a layered solution is likely to involve higher manufacturing costs and would require a lot of coordination between raw material suppliers to ensure the final product is as per specifications. Due to this, the product may be sold in the market at a higher cost which would serve the needs of only a specific segment and would not necessarily increase competitiveness against other retailers. Offering a broader range of weights would seem as the better option, preferably postponement in the manufacturing of the final product until the demand forecast is more clear. In my opinion, when customers visit retail stores they would also like to view a higher variety of any item, this would also help cater to the requirements of all market segments.
Given the fact that apparel industry already has such a high level of forecast error in nature, including weather forecast will make the overall demand forecast even a lot more difficult. In addition, considering that the weather forecast itself also has very high risk that the initial forecast is actually not correct, I think offering a broader range of weights concerning weather changes has significant possibility for retailers to end up with high level of inventory at the end of the season otherwise backorder costs. Therefore, for the retailers, providing customers with a layered solution is more likely to be the best option. Retailers may include domestic sources to meet unexpected high increase in demand, but I don’t think this should be a “must” option to take assuming such an expensive cost for sourcing. The quick response strategy could be applied to specific, certain competitive items which have enough profitability to cover the additional costs of domestic sourcing.
The choice between the two options is based on the company’s target market. If the company is focused on the high-end market for luxury goods, then layered option may be the best solution for retailers. Although it can also result in additional costs in design and manufacturing, it can increase the flexibility to adapt to the weather and reduce risk. Customers of these companies are paying attention to specificity. They have enough wealth to buy different types of clothes and don’t care about the price. Conversely, if companies are more concerned with meeting the public needs in the market, they will choose to provide a broader range of weights. It has a high profit margin and, because of its simple design, can cover different types of clothing, so it is easier for most people to afford based on the lower price.
In my opinion, customers would prefer layering in clothing as it is more about versatility and efficiency over weighted attributes. Layered clothing could cover a wider range of weather conditions than single heavy cloths, which could attract consumers to buy.
Unpredictable weather patterns are posing a challenge for fashion designers. Some of the biggest retailers have started hiring climatologists to help them predict what the seasons might have in store. I thinks it’s a good way for biggest retailers to take similar actions, but for smaller retailers, layered solutions would be a better way to deal with the uncertain climate change.
Also, choosing from a higher cost sourcing is an option only if the supplier lead time is short and they will turn the inventory around fast.
I believe that having layered options like the designer label “Vince” would be ideal because historical data cannot be accurately used for weather forecasting. Having a variety of layered clothes may persuade consumers to stock up on the layered clothes rather than look at the single non-layered product and decide if the weather permits the purchase. There would also be less inventory selection for consumers when picking non-layered clothing. Domestic, quick response should not be considered because the layering effect would cover the situation adequately. The domestic quick response is only warranted for heavy winter coats when the weather doesn’t warrant the heavy winter but milder ones. Forecasting may be linked to better profitability in short intervals because if a retailer were to stock up on heavy winter coats too late, they may lose out on potential sales. This would also help layering because they would add the heavier ones when they are forecasted correctly.
Actually weather might be a factor which can influence sale, but whether this is really important or not is not clear. If we have investigated deeper, we may know how much weight we should put it into our forecast. However, supporting such investigation needs funding, instead of doing that, if we use this cash flow to find faster response supplier, the risk should be lower while we still are capable for adjusting. What’s more, clother industry still need to be seperated by fashion or normal use. Perhaps people would prefer follow the fashion trend rather than follow weather.
Considering this reasons, making a more accurate forecast and finding faster response supplier are more practical methods for clothes companies to adopt.
The layers options is better for the retailer because it will not build a huge inventory in the retailer’s inventory. Large inventory means large cost. It is better to include a higher cost sourcing method because fashion industry is a high margin market. Customer service level is very important and also the critical ratio. The more product retailers sale, the more profit retailers get. If the company can not provide an accurate forecast, it is better to increase inventory when the target service level is high. For the smaller intervals, I’ m not very clear what is it. But as a guess, profitability will has a strong relationship with sales.
If we are strictly analyzing JC Penny, I do not see any issue which would cause them to change their sourcing for seasonal clothes. I take this stance because I understand the typical JC Penny shopper. The demographic is price sensitive as seen from the typical JCP coupons and seasonal sales (for example, a previous CEO once eliminated the coupons and the shoppers voiced their displeasure). JCP, however, has some selected name brands that are exempt from these price cuts (ex Michael Kors). If you start passing the increased prices (for different material based on recent weather) to the JCP customers, I believe they will see a drop in revenue. Lastly, I see the weather as too risky to make sourcing decisions. Even if most predict it will be warm weather for example, there is still good likelihood that it won’t come true. I believe that certain stand alone, fashion-focused brands should play to their audience and take this approach but for the typical JCP shopper, I don’t believe this is a good idea.
For sure, the apparel sales can be greatly impacted by the weathers to an extent, but since long-term weather forecasting today is still unreliable, whether including weather forecasts would improve fashion product profitability or decrease product profitability is still a question. Relying on long-term weather forecast to do business and make decisions is more like gambling. Thus, to counterfeit the changeable weather, the key is to improve the flexibility to meet the demand and offering layered solutions would be a great way to do so without severely add complexity to the product line. However, this doesn’t mean there is no role for forecasting to play in the fashion industry weather forecasting still can be utilized at a smaller scale. For example, retailers may be able to use short-term weather forecasting to consolidate their regional stock in order to minimize the chance of having a stock out, manage their floor plans more effectively and even to plan promotions accordingly.
Offer a layered solution is likely to be the best for the retailers, because this option can satisfy a broader range of customer need and has more accurate forecasting. On the other hand, the weight option might lead to huge inventory left duo to the temperature fluctuation. Also, I think domestic, quick response yet higher cost sourcing should not be included as a way to compete for most of the retailers. Because though now is quick fashion on trend, except for the large apparel company like Zara, H&M, most of the retailers will still keep the lower cost with lower risk of inventory.
From the real demand of the market, the weather should be an important factor need to be taken into the industrial’s consideration. But here comes a question, do customers buying new clothes are triggered by the weather fluctuations?
I cannot agree with this theory since at least myself is not doing like that.
Here will be multiple reasons illustrated that the weather could not be the main incentive to push those brand to do some modification on their own strategy or to say those couldn’t be the first priority to optimize.
Firstly, the forecast of the weather couldn’t provide solid reference for the design. Not all the apparel producer can forecast these complicated weather conditions since so many scientists over the world have worked for years to try to figure it out.
Moreover, it is so hard to do a marketing event around the “new designs” since they are based on the weather change. For example, many brands will use the picture or concept to express their design language, like “soft, comfortable or beautiful and warm”, but you can’t just say that “it is getting colder or warmer, so we design it for you” which is very implicit and confusing for customers.
For retailers, offering a layered solution is better. The customers can purchase clothes based on their demands, and the felt air temperatures. Conversely, providing too many fabric weights always lead to a great number of unpopular items, which needed to salvage.
I agree with introducing the quick response element to the retailers. Even the cost of sourcing is higher, it helps retailers to be more sensitive to future weather, enabling them to rapidly determine the styles, fabric weights for the next season. If unsold items decrease, retailers can benefit from overage costs. And Indeed, the weather now is more and more volatile, the accuracy of the weather forecast has become a must for each retailer. Being responsive to the weather and selling the right clothes, retailers can avoid costs for unsold products, which is the key to profitability.
Personally, I think which options (multi-layer or wide range of weight) retail should go for coping with sales issue resulting from the weather change really depends on customers preference. I think retail should go both ways to cover as many customer base as possible. From my own experience, young generation may prefer the single layer clothes while old generation don’t care that much about how clothes look. if retails target old generation who care more about functionality of the product than the outlook of it, then, multi-layer option may be the best to consider. On the other hand, for those retails that mainly target young generation, they should place more focus on the single layer with different weight options. I don’t think sourcing from domestic will be the long-term solution for solving the problem. It could be done for the short term. However, from long term perspective, better forecast with sufficient possible demand coverage is the way to go for companies in the States. The forcasting accuracy is important regarding how much to order and how much safety stock need to be in place. In clothing industry, outsourcing is way more cost-efficient than local sourcing for companies in the states. The accurate forecasting is the only way the companies can use to leverage this cost-efficient option. Personally, I think two drivers that will cause demand on clothing to spike in smaller time-interval. One is the fashion trend and the other one is the weather. With those two drivers in mind and other strategic plan in place, companies would be more ready for uncertain demand volume going forward.
With the apparel supply chain becoming more responsive and companies focusing on increasing their inventory turns every year, it is imperative to have a local supply base to respond to demand. Such fluctuations in demand could easily be seen in situations such as extreme weather – where customers inevitably purchase apparel. In order to keep up with the demand, it becomes important for fashion retailers to keep a tab on the weather. Having a high cost local supplier would easily be able to help sales in case of higher demand due to weather fluctuations.
Weight vs layer depends on the customer base. Customers with lower spending power might buy multiple layers over a course of time – and might use them well into spring, whereas customers with a high spending power and would go for weights. The example in the article does not address this question well – given that Michael Kors caters to the high spend customer base, whereas J.C. Penney responds to the other. Stores should stock apparel that cater to their customer base.
From a practical point of view, we dress according to the weather. In terms of if retailers should offer a broader range of weights or offer a layered solution is not so important. As long as clothes can match well and fit the weather, people will have them. However, quick response to the market is another story. It is necessary for retailers to have a quick response regarding to the fashion trend. Especially in apparel industry, the first mover advantage is tremendous, and that will be magnified once the retailers have a great reputation. Therefore, even if higher cost sourcing is needed, it is necessary. Since fashion trend is harder to predict compared to that of traditional industry, knowing the trend as well as reducing forecasting error are important. To do this, I suggest hire a third party player who does the fashion trend prediction or improve the efficiency along the supply chain in apparel industry to make sure retailers can catch up the time to sell their clothes.
First of all, it is interesting to see that global warming or climate change is directly affecting the profits in the fashion industry too. I mean the erratic deviation of average temperatures is a result of the climate change. With respect to what benefits the retailer – a broader range or a layered solution – really depends on their brand image and type of Supply Chain. Quick response – higher cost sourcing will be an option that retailers will have to depend on if they do not start accounting for weather changes in their demand predictions. This not only helps reduce their overage costs but also prevents redundant units from being manufactured and thus avoiding wastage of resources.Better forecasting will definitely increase their profits in the long run.
I think weather definitely is an important factor to be considered for both manufacturers and retailers in apparel industry. Obviously, people tend to purchase warm clothes during cold days while purchase light clothes during hot days. However, long-term weather forecasting has high uncertainty, and forecasting error would cost a lot. Thus, offering layered option would be a good solution for retailers since this would increase the flexibility to meet the unpredictable demand fluctuation without holding much inventory. In addition, for manufacturers, layered option also is a good choice because this would not increase production complexity too much. They can use same raw materials and similar design to accomplish layered clothes.
Sourcing domestically would lower the lead time and response time, which indicates customer satisfaction would increase. So, for some companies that go after high customer satisfaction, such as luxury company, domestic sourcing should be considered.
I think weather definitely is an important factor to be considered for both manufacturers and retailers in apparel industry. Obviously, people tend to purchase warm clothes during cold days while purchase light clothes during hot days. However, long-term weather forecasting has high uncertainty, and forecasting error would cost a lot. Thus, offering layered option would be a good solution for retailers since this would increase the flexibility to meet unpredictable demand fluctuation without holding much inventory. In addition, for manufacturers, layered option also is a good choice because this would not increase too much production complexity. They can use same raw materials and similar design to accomplish layered clothes.
Sourcing domestically would lower the lead time and response time, which indicates customer satisfaction would increase. So, for some companies that go after high customer satisfaction, such as luxury company, domestic sourcing should be considered.
Layered options may be more preferable to both the apparel companies as well as consumers.
From apparel companies’ perspective –
Layer clothing have longer shelf-life per year, customer can purchase different layered products and wear it all throughout autumn and winter, decreasing the demand variation. Less responsive supply chain would be needed, creating more cost saving opportunity.
Broader range of weights clothing that could only be worn in specific weather condition decreases each SKU’s shelf-life and hence demand a more responsive supply chain and could cost more to the company.
From consumers’ perspective –
Layer clothing in terms of functionality and product’s useful life on yearly bases and convenience of immediately clothing adjustment corresponding to weather is more attractive to consumers.
Broader range of weights clothing creates difficulty for consumer in dressing option that they have to purchase specific clothing for specific weather condition, dressing up every day would be a gamble as weather forecast may be inaccurate and wearing a too light or too thick clothing could be a disaster.
Including weather forecasting as an additional factor while predicting demand introduces wild variations in the system already inherent with variable production and supply lead times. Weather forecasts are notoriously unpredictable, and often times restrictively reliable. Focusing on weather forecasts also could be considered opportunity cost for lost resources.
Instead working on an efficient quick response system with suppliers will help in reducing inventories, and preventing supply-demand mismatch. Placing orders closer to the seasons, with efficient material and information sharing systems with suppliers can reduce forecast errors and lower inventories.
A quick response supply chain has become prevalent in the apparel supply chain due to increasingly responsive players like Zara. Since apparel supply chains traditionally have a higher lead time, fashion retailers face difficulties while predicting demand, resulting in either SKU stock outs or excess inventory in case of a out of trend estimation. A way to offset these risks and to compete in an increasing competitive environment is having a local supplier who can help during unpredictable demand increase.
Customer base matters in case of comparing layers vs weights by spending power. Customers with a higher spending power might be willing to pay a higher price for a broad range of weights at a Michael Kors store. Customers with low spending power would probably invest in layers, buying items as the weather progresses.
In my opinion, layered solution and delayed differentiation can be an optimal solution regarding the product design, but they can still plenty of approaches to lower or even take advantage of the weather impact. For example, redesign forecasting model with additional weather index that will increase the accuracy toward weather fluctuation, in other words, lowering the inventory level as well as inventory cost. Domestic sourcing can also be a solution but considering the high labor cost in the United States, the price increment cannot be ignored for low-end products with respectively thin margin.
I would say layered option is the best choice.
If retailers choose to provide multiple weights clothes, it is very possible that a big portion of them will eventually go to outlet stores or just stay in the warehouse for a long time. Using layered design, customers will have the flexibility. Thus the sales won’t be influenced by weather condition,
Another reason is that weather is not easy to be predicted in advance. The lead time for clothing industry is usually several months. It is almost impossible to have accurate weather forecast. One possible option would be using local supplier with quick response. However, the cost might increase dramatically. It is also possible that local suppliers don’t have the availability. Given these, layered option would be the best.
In my opinion, layered solution and delayed differentiation can be an optimal solution regarding the product design, but they can still plenty of approaches to lower or even take advantage of the weather impact. For example, redesign forecasting model with additional weather index that will increase the accuracy toward weather fluctuation, in other words, lowering the inventory level as well as inventory cost. Domestic sourcing can also be a solution but considering the high labor cost in the United States, the price increment cannot be ignored for low-end products with relatively thin margin. However, considering the profits of high-end products, its definitely worth trying to do local sourcing as fashion products has shorter life cycle and the value will perish with a incredible speed over time.
Clothing stores generally order clothes months before based on the predicted weather condition in the future. Thus if the weather forecast is not accurate clothing loses money as they have to have sold the stock at a discounted price. People won’t buy anything that they do not require. Thus companies should strive to better plan their order point of clothes for the upcoming season. Predictive analytics can improve the odds of predicting the actual weather and using big data to determine optimum order point shall help clothing stores to better protect them from losing the sales.
I believe the layered option is a better choice for the retailer. With this option, they will have to carry lesser inventory. Weather forecasting is not a reliable method of forecasting demand. Taking decision about capacity and inventory to hold solely on it will be a bad idea for the apparel manufacturers. In response to a sudden demand due to change in weather, domestic production should be considered to meet the demand. As there is a higher demand, the price of the apparel can be increased to justify the increased costs. Forecasting can help improve profitability by controlling the demand. If one takes into account the weather forecast, it can help make more informed decision about production of apparels specific to a particular season and reduce the chances of a product getting sold to the outlet store because it runs out of fashion
The success of either of the options (i.e. broad range of fabric weights or layered) for the retailer will be gauged by the degree to which the option is useful to customers and the ability of the option to recover the lost sales. The layered clothing will serve the customer even in other seasons and the sales for this option will not drop and may even constantly increase throughout the year thereby offsetting the lost sales. On the other hand, the fabric weight option does not guarantee customer satisfaction and a stable/high demand in the given weather. Moreover, higher costs will be required to create a range of fabric weights that covers all the clothing types asked for a particular weather condition as compared to the costs for generating a clothing solution in high volume that sustains all weather conditions. Thus, the layered clothing option is the best for the retailer.
Due to volatility in demand in the apparel industry any edge over competition needs to be considered. Domestic, quick response options should be considered despite the higher costs as the margins in the apparel industry are extremely high during season and drop to bare minimums, off season. Quick response sourcing ensures that the retailer doesn’t lose it’s competitive edge. That being said, weather forecast as a means to determine demand seems a very risky proposition. While the average weather could be gauged, the mindset of the customer may not linearly be impacted by the weather. Hence, in my opinion broader range of weights would be the ideal method to maximize profit. The range ensures they aren’t eliminated from competing in any situation and the sourcing strategy can help reduce inventory carrying costs, which eat into a lot of profits within the apparel industry.
Leftovers of the season will be salvaged after the season end, so retailer will try to optimise the service level and keep inventory low. With weight option huge inventory is going to be there. On the contrary, the layered option provide customer different kind of choices to satisfy their need, and different types of layer can be combine together and have the same warming effect to accommodate large quantity of customer with the same need.
If total left over cost is greater than the sourcing cost for the quick response option, then the quick response option should be considered. Since it can satisfy the need for the customer while lower the inventory cost for the retailer.
With the forecasting, clothing industry can produce the right type of clothes that customer needs and reduce the cost of left over.
In the apparel industry, the lead times are very long and thus responding to quick changes in conditions and trends very difficult. I believe the layered option is the correct one based on practicality and feasibility. The consumer is provided with additional flexibility and this reduces risk for the apparel firm. In theory, relying on weather forecasts would be useful as it would allow additional information to enhance forecasting but unfortunately, weather forecasting is not accurate enough to predict the conditions months in advance accurately enough to base inventory decisions on.
Offering a layered solution would be a better choice, since if the company choose to purchase a range of fabrics weight to adjust the weather, the variety of inventory would increase. The increasing of variety would impact the inventory management and make it harder to manage and forecast, which means the inventory holding cost would increase. On another side, only change the layered of clothes wouldn’t impact the performance of the company and also wouldn’t impact the inventory that much. If the company does run out all the fabrics at the end of the season, that is also easier to outlet the rest part with large volume instead of many catalogs of fabrics with small volume.
The climate has changed significantly over the past few decades and has become erratic in many countries. This change makes it difficult to predict exact seasons since we have rain during summer and even during winters now. I would believe that having a layered cloth would help in this situation, however, fashion tastes also change thereby leading to obsolete inventory. Having a responsive supply chain might really help in this situation or a made to order model where people can choose their colours and the dress is delivered in just a day could really help the industry compete.
Whether a retailer should choose to offer broader range of weights option or to choose to offer a layering solution also depends on the customer demographic that the retailer wants to address, so the question whether a retailer should choose one over the other would depend on what their target audience would be, as both models are more or less similar. Weather forecasts are rarely accurate, as we can see in recent times due to climate change and global warming. To factor in the risk that climate change brings, it would be a safer option to place an order much closer to the weeks the clothes hit the shelves. This quick response – high cost model, even though incurs higher costs could help the retailer save on inventory. Not only does placing orders in small intervals, helps reduce inventory costs, it may also go a long way to help retailers increase their profitability.
Quick, domestic but more expensive response may not be a solution for most fashion businesses, especially those fast fashion or middle-end brands. Price is one of most important factor for profits in non-luxury apparel. More expensive sourcing will affect profits margin. I think a layered solution is better than a broader range of weights. Because a broader range will increase volarity and safety stock, Hence, this solution will increase inventory cost and risk.
I think that offering a broader range of weights would give the stores greater flexibility in offering without needing to carry additional SKU’s for layers. Domestic sourcing should also be used. The greater cost partially pays for itself because of the improved forecasting with a reduced lead time. It allows you to have that flexibility needed. If we were to model this out I am sure that this would yield the highest returns, flexibility almost always yields higher returns. Additionally, apparel retailers might push back on suppliers and negotiate revenue sharing contracts to keep sales and profits as high as possible.
Fashion industry highly depends on consumer’s preference of clothes, the current trend in the market, the style, the color, etc. As weather impacts the choice of clothes for consumers, apparel industry should really consider the impact of temperature of clothes choice. However, we can not predict whether retailer should go for range of fabric weights or layered options as choosing and wearing a dress is highly subjective. In my opinion, the retailers should carry inventory of both types in less amount, and then as per demand may choose to let go one type, or both types, or use both based on their profitability. Therefore, quick response yet higher cost sourcing should be included as a way to compete. Excess inventory runs a risk of product becoming obsolete, while less inventory leads to loss of customer goodwill. Products should be forecast based on previous demand of similar products.
Offering layered options would be a more viable solution since it can reduce overall forecasting inaccuracies (which are caused due to inaccuracies in weather forecasting, change in fashion trends which are attimes not captured by retailers, internal forecasting inaccuracies, etc). It can also give a higher ROI as layering options would give the customer the opportunity to use the products more, rather than only having to buy clothes with heavy fabric, which would be used only limited number of times. They can also use the concept of “postponement” to further reduce the risks caused due to forecasting inaccuracies. That is, keeping the basic materials and designs same, and changing them into the final product when the order is realized. Many retailers are already doing this. In case of brands that are considered fast fashion, layering would be a better option as it would mean lower costs for them as well as the customers, which is basically their USP. For the luxury brands, it might be feasible to have different range of fabrics as their customers do not mind spending on a number of items and both the brands and it’s customers are capable of absorbing the costs.
Offering a layered solution seems best for retailers instead of carrying an inventory of the broader range for certain weather types. Depending on the demographics of the region and the spending power of the customers, one can choose to respond quickly to the change in demand by paying a higher cost for local sourcing. Forecasting can be used to plan short term inventory/demand requirements, but it will be difficult to implement it through the supply chain when it’s not sourced locally, and thus the stocking can be done choosing certain SKU’s among those available at the distribution center. Although to get a forecast of demand by forecasting weather would not help much as weather forecasting is not yet accurate and accuracy of weather over a week or a month is usually incorrect. So it’s difficult to utilize or take advantage of weather forecast.
In the fashion industry, far away suppliers are engaged to ensure low-cost production of garments. The garments, with a markup of 120-300%, which are not sold during the season, are sold at a discount or to other markets in the world. Overall, the system is working well and is earning profit for all entities involved in the supply chain.
Weather is highly unpredictable, a modular way to go about fashion with layers may result in a higher sales level. And with “the climate change”, predicting the weather is highly impossible as the trends change from year to year.
Unless the weather forecast prediction improves, predicting the right weight of the garment would have a low probability. Even a quick domestic response of a month may still not correct the problems being faced by the industry.
The choice between the options for the customer is driven by the severity of the weather more than the length of the severe weather conditions. Erratic weather patterns are affecting the length and time of these weather conditions effectively the quantity of each category, so balancing the forecasts of quantity for both accurately will be beneficial to firms.
The cost of excess for heavy coats is higher compared to layers as layers can have separate markets in other parts of the world as seasons shift. So retailers can over forecast for layers accordingly if the consumer chooses the layers they will not stock-out as and if consumers choose weights for protection they will reduce their total loss of customers and cover the risks of excess layer inventory in alternative markets.
No matter the accuracy levels of the weather forecasting technologies, weather has never been mastered and understood accurately ever. Thus, it will be a waste for fashion apparel companies to try to predict weather and thus base products on them. The Michael Kors approach seems more sensible which places eggs in different baskets and hence, minimized risk of loss. But the layered clothing idea seems to be the most appealing, both to the manufacturers and the consumers. Manufactures can place price on each layer and the consumer, understanding the versatility of all the layers, would be more willing to own a customizable piece of clothing.
From a customer perspective, a layered option would be more flexible to endure the unpredictable weather. From a supplier perspective, why would I add weather uncertainty to the already difficult demand forecast of apparel? I think the experiment is costly, highly risky and requires a lot of technical knowledge to forecast based on weather behavior.
Increasing demand uncertainty is moving the apparel industry towards responsive supply chain. The layered options provide more flexibility to the customers .The profit margin in the apparel industry is 200%-300% ,so when any one of the designs is a hit, the retailers generate profits that can cover their costs. Sourcing domestically can help the companies to reduce lead time and be more responsive to demand but at the same time might increase the cost. The companies need to strategically decide and consider the factors such has target customer segment, product quality, regulations, capability ,responsiveness and value added services before deciding to source domestically. Forecasting at smaller intervals will help to reduce forecast errors by analysing the trends efficiently.
The clothing industry needs to know the factors that affect the dynamic nature of demand into its formula to come up with better product offerings. Any production house would be able to have extract profits out of this opportunity by having an agile and flexible supply chain enabled through technology and sound logistics planning.
With the kind of uncertainty we see in weather nowadays, a layered solution would be better for both consumers as well as producers as the per-unit cost would be lower for both.
A quicker domestic production would help in cutting the time to market and beat competitors.
With fields like Predictive and Advanced Analytics being used in so many different fields so effectively, fashion industry should also accommodate the same in their planning for the year. Because if there are leftovers from a certain year it would be very costly as fashion industry is a fast moving industry and trends may not be the same the coming year. Also, offering layered options would be a more doable solution as it would help to reduce forecasting errors. Also, layering options would give the customer the opportunity to use the products in more than one way. Also, it depends on the brands customer base. Fast moving fashion brands should consider layering options whereas luxury brands customers do not mind spending on more than one type of apparel.