Analysis Of A New Approach To Product Development – ‘Product 3.0’

Amidst declining sales and lot of media speculation, in 2015, Peck made the bold decision of eliminating the position of Creative Director at Gap Inc. and instead focused on driving sales with the help of a highly collaborative team of designers who were informed of the latest season’s trends by hard data. When we analyze Peck’s move, it becomes evident that Big data has immense potential in predicting consumer tastes and enhancing inventory management by demand-driven merchandizing. However, it is also true that a distinct creative vision is imperative for Gap to regain a strong market presence after years of declining sales. By entirely dismissing creative directors and relying entirely on fast-fashion trends generated by data, Gap runs the risk of being a trend-follower rather than a trend setter. While on the short term, this approach may bring some respite to their diminishing topline, on the long run a complete lack of unique design identity may lead to Gap failing to stand up to competition in the mid-market segment. Moreover, it is also necessary to outline a specific data analytics strategy for each of Gap’s primary brands so as to have some sort of differentiation among them, since each of them have a different positioning in the apparel landscape and appeal to different customers.

Product 3.0 was developed in the wake of numerous impending problems at Gap Inc. such as:

• Gap’s slow growth in core markets
• Better product assortment and a more agile supply chain of competitors
• Rise of e-commerce and Gap’s delay in tapping into its potential
• Rise of fast-fashion and Gap’s failure to adapt to the model
• Heavy and frequent discounting that ate into the company’s sales
• Lack of unique identity in the brand’s clothing.

In order to address the aforementioned problems, Peck launched his new brand vision Product 3.0 which would govern decisions in design, merchandizing, inventory and manufacturing so that retailers could identify trends and make them relevant to customers, test out their designs in stores and respond to the demand- restocking on products that sell and avoiding the ones that don’t. This predictive and demand driven approach enabled more successful products to move up the curve and removed ones that customers didn’t prefer. While this strategy has proved its worth by increasing Old Navy sales, Gap is yet to attain social business maturity for all of its brands. It needs to employ better and faster forecasting with all the information collected from different sources such as social media, its CRM system etc. In order to assess whether Product 3.0 was a worthy investment, it is important to assess the costs associated with its implementation. A few areas of investments would be:

1. Technology:

a. Google analytics and social media platforms (e.g.: Facebook, Instagram etc.) are treasure-trove of data, available free of cost.

b. RFID tags (to be fitted to the clothes), at least 1-2 RFID readers/ portals in every Gap store

c. Sales and customer databases.

2. Labor cost: highly trained analytics consultant and/or analytics professional who can derive insights from the data collected by employing advanced analytics skills to understand the fashion trends

a. Training: training store staff to collect customer feedback and communicate the same to the store manager in a streamlined manner. Also, train store managers and upper management professional to read business intelligence dashboards appropriately.

In addition to launching Product 3.0, there’s also mention of the company rethinking its manufacturing strategy by shifting to the “fabric platforming” strategy. This essentially means, reversing the traditional manufacturing process by buying large volumes of fabric and creating different designs in response to the trends observed in the market. Gap envisions that this strategy will enable them to respond quickly once a key trend is identified and drive their average unit cost (AUC) savings.

Ultimately, it is intuitive that employing predictive analytics to better understand customer’s tastes and improve inventory management, will only be constructive when Gap garners a strong foothold of the quality and fit of the clothes that it produces.