Merchandising Revolution

Until now, merchandising and retail have been reliant on tradition-based and outdated practices, resulting in common industry failures, and being unable to adopt new processes and ideas. While many companies acknowledge the need for change, they don’t know where to start. All of this points towards a merchandising revolution.

 

The first area where change is needed is a calendar or season-based merchandise planning. Merchandise financial planning is a pre-season process, where a financial framework is prepared on what and when to buy, usually based on a category level, driven by seasonal trends and tradition. During this process, retailers and brands need to make many decisions before knowing anything about sales or product performance. One of the faults of this process is that all products are handled within the same pipeline, not considering the rapidly changing market trends or the everchanging consumer demand.

 

At the same time, human error is a factor, as it depends on the experience of the merchandisers or buyers in the field to make these decisions. Although retailers might save costs, the dynamic nature of the market isn’t considered alongside what and where the consumer wants to shop.

 

Inventory management and supply chain decisions

Merchandising is connected to supply chain decisions, where although many of the transactions happen in an online environment, the products are still physical. It’s also worth mentioning that the choice of what, where, and how to buy has exponentially increased, yet technology has not done enough to speed up the sorting and logistics processes. Supply chains need to become faster and more agile, so companies can meet the unpredictable consumer demand and changing market trends.

 

Stockouts are another issue, where retailers buy without knowing what they are going to sell, in which case, lead times need to be shortened to get the product to market. A mindset shift needs to happen where companies focus less on ‘buy to budget’, and rather think about a more unconstrained view of what the consumer needs and going to buy.

 

Many companies within the fashion industry aren’t prepared or built for fast-changing realities, where supply chain decisions are based on past experiences and facilitated with outdated tools. Innovation and retooling of the supply chain are necessary and retail businesses should consider new practices, such as sourcing closer to home. 

 

As we have seen during the pandemic, sourcing from countries in the far east meant struggles with transportation and longer lead times. A possible solution to this could be the implementation of AI and technology with automated production and better supply forecast models.

Digitalization and data

Covid helped accelerate the thought process of how organizations can ensure that consumers can shop regardless of the method or platform for shopping. Digitalization is an opportunity for brands and retailers to generate more traffic, and increase conversion using new marketing instruments. Assortments are not limited by space anymore, as retailers can see their offers to consumers as an investment portfolio rather than just a place where they offer products to consumers.

 

Another essential resource is data. Most companies still rely on legacy systems with data sitting in various sources, poorly connected; consumer data isn’t directly linked with production data to optimize sorting. Good data administration is no longer optional, yet not many companies have put effort into it. This is concerning as companies that do take advantage of the data available are more profitable and successful.

 

Therefore, a merchandising revolution is inevitable, where data will fundamentally disrupt how we know merchandising, and the way we engage with the consumer and sell to the consumer will be fundamentally different. But is this digitalized and revamped market ethical and sustainable?

 

Ethics and sustainability

A Chinese fashion company called Shein became a competitor of big global fashion brands with cheap and globally available clothing, yet their business model raises ethical questions regarding sustainability and fast fashion.

 

The mindset of “the more stock you have for customers to buy, the more success you have” has pushed back innovation and changes in the supply chain. With the current state of merchandising, there is a huge risk in buying cycle, waste, and supply chain in general. These businesses have brought back practices such as batching and long lead times to minimize costs and decrease prices. 

Adopting such practices comes with consequences on the environment and raises ethical questions about low prices and how these items have been produced.

Merchandising with the help of technology and AI

How can you leverage technology to ensure that your brand can sell the right product, at the right location and time? Technology and machine learning can enable you to “learn” consumer behavior on a granular level and respond in a better way to consumer demand. This also presents the opportunity to have product assortment recommendations for stores such as media streaming sites that have personalized recommendations, all with the help of artificial intelligence. According to recent research, many jobs will be replaced by machines in the upcoming decades; the planning side of merchandising is part of that too. Design and trend forecasting is the questionable part of merchandising where human input is still essential, yet AI has the potential to facilitate those aspects as well in the future.

 

Therefore, data and technology will help brands and retailers to provide insights on consumer behavior and supply chain decisions and ensure to couple physical products with where they can be sold and make sure that those two are always optimized.

Conclusion

We can conclude that the merchandising evolution has been slow, and Covid has accelerated change and forced us to revisit our merchandising processes, leading industry decision-makers to the conclusion that a merchandising revolution is inevitable and necessary. There is a need to postpone decision-making to understand true sales potential and use a consensus process to establish the final commitments of what to buy, make, order or ship. Businesses can do this by sourcing closer to home and implementing data tools such as AI and machine learning. 

 

To meet consumer demand in an increasingly unpredictable and fragmented omnichannel retail landscape requires a change in the way we think and work.

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