While It Last: Retail Industry Amidst Digital Transformation

The perfect storm of cost pressures, rising inflation and slowing wage growth is impacting consumer confidence and dampening demand according to Deloitte’s Retail Trends.

Many retailers have embraced agile working in specific areas of their business – the challenge is how can retailers now scale this across their business. All retailers have to respond faster and faster to rapid changing customer demand. The promise of emerging technology has never been greater. Ever-evolving enabling technologies including AI, social commerce, the Internet of Things (IoT) and virtual reality all have the potential to transform the customer retail experience and day-to-day operations like never before. However, retailers, especially in the US, are on pace to close more stores in 2017 than in the 2008 Great Recession.​

Markedly, 2017 is shaping up to be a new digital tipping point for retail as ecommerce continues on its relentless growth trajectory. This is being driven by the ambitious growth agenda of the leading pure-players who have now also taken on an omnichannel retailing approach and as for the rest, online is continuing to rise in importance. This is having a massive impact on the store estate in the US with 8,600 stores estimated to close in 2017.​

RETAILERS SHAPING OF TECHNOLOGY ​

According Zebra’s 2017 Retail Vision Study, retailers cite the technology trend shaping future percentage of respondents planning investments by 2021: Internet of things (IoT), machine learning or cognitive computing, and automation technology. Giving a digital voice to people, processes and things to improve the customer experience enhance supply chain visibility and expand revenue opportunities. Analytics and predictive models to help retailers personalize customer experiences and enhance inventory demand, forecasting and visibility. Automation is deployed for packing and shipping orders, inventory tracking, checking in-store inventory levels and assisting customers in finding items.​

BALANCING FOR CUSTOMER EXPERIENCE​

Although online and mobile commerce have transformed the shopping experience, 91% of all retail sales are still generated in brick-and-mortar stores. As a result, merchants are investing in improving the customer journey via the digitization of the in-store experience, getting “physical.” Retailers are on a mission to streamline the shopping journey for consumers, and mitigate shopping pain points that have long bedeviled store associates, like tracking down inventory. To that end, retailers surveyed are placing a premium on implementing in-store IoT solutions such as sensors on shelves, automated inventory verification, as well as cameras and video analytics. Stores are backing on the shift to these “phygital” upgrades to provide an unprecedented, real-time picture of actual inventory in the store.​  ​

THE INVENTORY MAKEOVER​

The incentive for this the makeover lies in the technology’s potential ROI. As an industry, retail inventory accuracy hovers at about 65%, studies show. By contrast, RFID platforms can boost inventory accuracy to 95%, while out-of-stocks can be reduced by 60% to 80% with item-level RFID tagging. Other payoffs for retailers include reduced inventory related costs. For example, apparel and footwear retailers have reported inventory labor reductions of over 75% by moving from manual to RFID automated item counting. Moreover, item-level RFID has generated increases in the number of sale items per transaction by as much as 19%, and a rise in the number of transaction by much as 6%.​

HARVESTING THE DATA

To-date, consumer information generated in the ear of digital shopping, along with the rise of technology equipped to handle and analyze the surge, is recasting how retailers determine what to sell, how to sell, what’s selling, what’s not and why. Market-basket analysis, for an example, is a timeworn modeling technique used by merchandisers to decipher which types of products shoppers are more apt to purchase together. It’s a wide-ranging tool, as basket analysis offers insight into consumer patterns, preferences and shopping behavior, regional trends, as well as reveals the relationship between products for sale. Combined these insights inform factors from store layout to marketing. Therefore, the modeling technique is being automated by big data. Sophisticated analytics platforms are transforming reams of market-basket data into insight ripe for actionable merchandising strategies like supermarket placing snacks next to baby wipes during the football season,  for instance, when daddy are shopping for both their kids and their couch-potato stash for the game.​