Fashion moves at an incredible pace. New trends appear out of nowhere, whether for a specific kind of patterned shirt or an innovative new backpack, and suddenly everybody wants one. For retailers, it becomes a rush to stock these items before fashion moves on. Many have invested in Product Lifecycle Management (PLM) to get products in store faster and more efficiently. PLM is a systematic approach to managing the people, processes and data associated with the iterations a product goes through, from its inception, design and development to its ultimate retirement or disposal.
But getting a product on the shelf is only half of the battle. There is a fine line between a style that is fully on trend and one that just doesn’t ‘work’ for fashion-conscious consumers. We see a significant proportion of new product introductions failing to resonate with the market, leading to markdowns, wastage in the system and a brand that is considered out of touch.
The problem is made worse for traditional retailers by the growing popularity of niche brands and online-only platforms that can be more flexible about the products they sell. Many executives worry about losing market share and being displaced. They know they can innovate and get new products to market at pace, but they want greater assurance that the finished product will be a success.
Understanding what works
For many leading brands, the answer is in advanced market research and predictive analytics. By polling consumers about their preferences upfront and applying rigorous analysis to the findings, they are in a stronger position to understand what will work and what needs to be ‘fast-failed’.
In turn, predictive analytics leads to smarter, faster and more efficient product development and introduction. Accenture sees this happening in three main ways.
Leading retailers and consumer goods companies are implementing solutions that enable them to poll tens of thousands of consumers for their immediate feedback on individual designs and materials. Through predictive analytics, they can segment respondents according to precise nuances in taste, preference and the likelihood of predicting product success. Equipped with this new information and research, companies are finding a significant improvement in designing and developing winners in the marketplace. Taking it even further, they can also determine how much consumers are willing to pay for a specific product or line which means they are less likely to have to apply discounts or markdowns at a later date. By applying this methodology to their product development pipeline, fashion retailers can rank items on a scale from ‘likely winner’ to ‘definite loser’ and anticipate and improve overall line appeal, impact and product success.
Inspired tweaks: speeding up the flow of new products
In recent years, technology has been successful in helping retailers develop products and styles more efficiently. There have been significant reductions in cycle time from over a year to often under six months.
Yet some retailers recognise that they could move even more quickly. They are developing different speed models for different classes of products. An expedited model might be reserved for the most fashion forward or trend injected styles to ensure that you capturing or even leading consumers to their next purchase. Aspects of this include abbreviated processes around concept development, design and approvals, supply chain and material considerations and expedited shipping. Getting to market first, could be well worth the extra expenses or resources to make this a reality.
New horizons in the supply chain: lean, cost-efficient operations
After decades of offshoring, there has been a trend in recent years for retailers and consumer goods businesses to explore near-short options for manufacturing. UK retailers might use facilities in Eastern Europe to carry out the ‘last mile’ of design to a product, giving them extra room to finish a product that will arrive in time to meet consumer demand. Again, predictive analytics will help them understand exactly what changes they need to make here, helping contribute to supply chain efficiency. Furthermore, leading retailers can use analytics to get better at predicting likely bottlenecks in the supply chain, depending on where trends are going, and working out in advance how they should respond.
There is no denying that predictive analytics is making a material contribution to success in the market. One leading brand has increased its ability to pick winning products from one in four to 70 percent. In our experience, brands can cut low-performing products by as much as one fifth. If retailers want to move at the speed of fashion, they should prepare for analytics to play a growing role in their business.