From luxury e-tailers to the high street – fashion brands around the globe face the same challenge season after season: minimizing end-of-season leftover stock while optimizing sales throughout the season. This is a recurring challenge for all retailers, especially during times of economic decline. With possibly the worst health crisis in modern times, where shops worldwide were shuttered, Product Lifecycle Management has become more important than ever.

Predicting demand in the fashion industry

Product Lifecycle Management (PLM); the handling of a good as it moves through the typical stages of its product life, is more challenging in the fashion industry compared to other industries, this is for two reasons. First of all, predicting demand is more complex when there is a high number of SKUs involved due to having multiple sizes per style. Secondly, there is a higher amount of uncertainty with high fashion collections since they are heavily influenced by trends and therefore more difficult to predict with historic data. Both reasons make best in class lifecycle management in the fashion industry highly complex.

Despite its complexity, it is important for every organization to design a good PLM. A strategic and well-designed PLM system can lead, amongst other things, to more efficient and profitable distribution channels, higher return on investment from promotional campaigns and reduced market entry costs. In addition, the high pressure on margins in the fashion industry creates an increased need to optimize PLM. At BearingPoint, we helped a global fashion brand to improve their PLM by focusing on two areas: data-driven buying and in-season stock management.

Data-driven buying

Some retailers strategically over-order seasonal collections to minimize lost sales and attract new customers during sales. In this scenario, retailers are betting on achieving higher sales by selling a higher volume at a lower average margin. A disadvantage of this approach is that long sale periods and heavy discounts do have an impact on the consumer's perception of the brand's superiority.

A more sustainable solution – with less impact on brand equity – is data-driven buying. Fashion brands and retailers can leverage data to make more strategic decisions related to pricing, product development and customer interaction. Data driven fashion brands have a distinct advantage over their competitors as they can deliver a more personalized customer experience, can better predict future customer behaviour and optimize in-store product display.  When executed properly, this results in a higher sell-through rate and average margin.

In-season stock management

As fashion heavily relies on trends, data-driven predictions may turn out differently due to external factors. In-season stock management is a powerful tool to manage underperforming products and minimize leftover stock. Retailers that make use of in-season stock management are focusing more on specific products (or products categories) and on their profitability throughout the value chain, not only per channel. This results in smaller amounts of leftover stock at the end of the season. In-season stock management creates incentives for buying products throughout the whole product lifecycle because underperforming products are sold earlier in the season with a discount. In-season stock management thereby contributes towards optimizing the forecast and can be achieved in several ways. 

One of the trends in the fashion industry is that more and more brands sell their stock with a discount via, for example, a section on their website which always contains discounted items. This tab is open throughout the season and not only at the end of a season. A solution which directly influences the life cycle of the fashion items.

Another solution is the possibility of early flash sales. An early attack during the season with higher discounts could really pay off which also causes a big contribution towards lowering your leftover stock at the end of the season. Organizing such flash sales is a clever way of discounting with almost no effect on detracting from the full price merchandise and cannibalizing the ‘normal’ business.


At BearingPoint we help organizations with Product Lifecycle Management challenges, especially in the fashion industry.  We develop a tailored Product Lifecycle Management program, including Data-driven buying and In-season stock management. As a result, organizations are able to enhance purchase management, improve the ecological footprint and achieve better margins.



Michael van der Wielen

Business Analyst

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