Inventory intelligence key to omnichannel retailing

Following the NRF 2012 Annual Convention and Expo in January, retail analysts from IDC Retail Insights cited omnichannel as one of the top trends for the year ahead.

Debra Weinswig of Citi agreed, noting: "Retailers need to approach omnichannel execution in a manner unlike any previous retailing innovation."

The goal of omnichannel retailing is to combine the benefit of cross-channel and mobile shopping with the unique revenue and loyalty building capabilities of the in-store retail experience. It offers apparel retailers opportunities to build deeper shopper relationships - or risk ending them, when availability promises go unmet.

But to successfully execute omnichannel retailing, apparel companies need to do more than just determine availability. They need to be armed with data that spans the boundaries of physical locations and technologies, and data that addresses both the short and long term need.

To do that, retailers need to build a foundation of integrated inventory intelligence.

According to recent research at the RFID Research Center at the University of Arkansas, the current inventory accuracy rate for apparel stores in the US averages only 65%. Understandably, with trending statistics such as this, retailers are scrambling to understand their inventory inaccuracies to the penny.

Further compounding the path to omnichannel success and inventory accuracy is the mistrust by retail sales associates of the in-store "system." Staff mistrust causes hesitant selling, wastes time double-checking inventory, and communicates lack of confidence to the shopper. Refunds and returns - essential to recovering trust - are often the weakest link.

The industry at large has been working on cross-channel technologies, but IT integration alone can't provide the intelligence that omnichannel retail requires.

Quality information depends on trustworthy, up-to-date inputs and outputs. That data needs to be organised into actionable information and integrated across silos spanning physical locations, technologies, and time.

Consider for example the vast complexity of retail supply chains. Even the most sophisticated, most accurate supply chain is at the mercy of poor-quality information from retail endpoints. Information risk begins to leak into the system from inputs and outputs outside integrated supply chains - especially where the operation is most vulnerable - inside the store.

At the back door of the store, inputs must document a complex array of sizes, styles, colours, and options, and outputs must reflect the same information on returned items. On the items themselves, inputs and outputs are coded in tags that must be compact, detailed, and tamper-resistant yet easy for store associates to remove.

At the point of sale, systems must capture transaction, loyalty-programme, gift card, and coupon data, and help detect, remove, and re-circulate anti-theft tags. And at the front door, inputs and outputs should show real-time store traffic and intercept shoplifters without intruding on the legitimate shopper's experience.

Effective omnichannel retailing needs to overcome suppliers' attempts to keep their solutions exclusive and integrate core functions such as execution, task management, and workflow as well as user interfaces and reports from sensors with high-fidelity data.

It also needs to support data integration over three key points in time - instantaneous, short-term and long-term. For example, shoppers want item- and location-specific information right now while retail executives want to track seasonality (short-term) and keep an eye towards long-term trends across regions or market segments.

Over any time period, inputs should offer end-to-end visibility across stores, distribution centres, and manufacturers as well as top-to-bottom visibility from the retail floor through regional sales and distribution centres, to the executive suite. More importantly, the information collected should be actionable and make those activities both effective and profitable.

By successfully managing these data points across systems and processes, retailers can begin to improve inventory tracking and help stores reorganise stock to maximise floor-space utilisation and sales per square foot.

More accurate forecasting, ordering, allocation, and replenishment intelligence helps stores tune their product portfolios, and make better use of fixtures, displays and other capital assets.

Data-based collaboration with supply-chain partners also raises compliance with order cycles and delivery requirements, and opens opportunities for closed-loop end-to-end collaboration with tag reclamation programs for example.