The recent admission by Mickey Drexler to making “mistakes” while explaining the results of two J.Crew sweaters – one successful, one not – shined a bright light on the importance of each new product decision and the consequences of getting it wrong. In the grand scheme of things, one or two bad decisions do not always make or break a company. But when you string multiple bad decisions together, the stakes are much higher. Just ask the 175 people laid off after J.Crew’s earnings report, including its head of women’s design, Tom Mora, who was blamed for the company’s product misses.
In today’s digital age, where consumers are so closely connected and already sharing their thoughts and preferences on new products, why aren’t more companies actively leveraging consumer analytics to add science to the “art” of merchandising?
The need to mitigate the risk of new product decisions
Greater than 50% of new products fail, according to MIT Sloan and Gartner, and retail CEOs typically tell me their failure rates are even 60 to 70%. Whether from making a product “mistake” or underestimating the success of another product, IHL Group has estimated that both sides of this “inventory distortion” problem add up to $818 billion globally each year in the retail industry.
Left to their intuition, merchants are betting millions of dollars on new products, and their results are worse than the flip of a coin. Just look at J. Crew’s recent “mistakes,” which resulted in the loss of millions of dollars of investor value and hundreds of jobs. I would argue this all could have been avoided.
From the runway to the rack, consumers are the new fashion critics today. They have more say and power than ever before, and the world of big data and predictive analytics can easily bring their voice to the brand. As a retail insider, I am in disbelief that so many companies squander investor capital by failing to embrace the data, tools and technology that is so easily available to help merchants and designers understand what their customers want.
Historical data should be left in the past
Drexler has been a stalwart in the retail and fashion industry for more than 40 years. He has been referred to as a “merchant prince” and “The man who dressed America.” But early on in his career, he earned the nickname “Stubs” while at Bloomingdale’s due to his habit of collecting sales tags from the store’s merchandise to keep track of daily turnover. His penchant to look at past success to anticipate future success was buoyed by his relationship with Steve Jobs. Both utilized this method, whether for t-shirts and jeans or iPods and iPhones.
When you garner the level of success both Drexler and Jobs achieved, your mistakes are often forgiven. Both have seen their share of failures, but they took their lumps for all to see and moved on. However, it is Drexler’s recent product “misses” that expose the flaws in using historical data, or “stubs,” to predict the future.
If the road is perfectly straight, you can drive looking backwards and still be relatively safe. But you and I know the road is rarely straight, and in order to stay on the road and move safely forward, your vision and focus must be set on the future, not the past.
Consumer knows best
For the five decades since the 1970s, the fashion critics and “gurus” held sway over the public’s attraction to and demand for the latest fashions and styles. But this is 2015, and fashion, like many other industries, has been democratized. Consumers are the critics, and they are driving retail.
As J.Crew leads all apparel retail companies when it comes to brand loyalty (according to Brand Keys, a world leader in customer loyalty and engagement metrics), I wonder if those loyal customers were given a voice before J.Crew launched the Tilly, its big product “miss?” The recent earnings report showing a 10% comp sales decline would seem to indicate that the answer is a resounding “no.”
The truth, however inconvenient, is that the days of relying on historical data to make new product decisions have come to pass. So has the argument that customers don’t know what they want and can’t help in the process.
Rather than blaming bad decisions on the designer or merchant, why don’t retailers better leverage the strongest voice that matters – the consumer’s?
Greg Petro is CEO of First Insight, which gathers real-time consumer data and applies predictive analytic models to create actionable insights, which drive measurable value.