/ The 3 Last Miles of Retail Analytics

As a veteran of the hyper-competitive retail space, I can tell you that every serious retailer in the world has a major interest in getting the most out of its data. From the boardroom to the checkout aisle, razor-thin margins favor companies that can be smarter, faster, and nimbler with innovative information strategies.

But with so much data at their fingertips, where should retailers look to find competitive advantages with analytics?

Often, getting analytics-fueled insights out to where an actual business decision can be made is the main challenge. McKinsey & Company and others often talk about this unlocking of data as the last mile of the analytics journey. I’ve talked about it too, as this video attests.

The way I see it, however, is that there are three last miles in retail analytics, and a strategic approach to all of them will make data a game-changer for anyone in the industry.

Last Mile #1: Headquarters.

Most examples of last-mile analytics involve a top-down approach, where you optimize operations from a centralized headquarters that is making decisions for an entire retail operation.

But the real power comes when, rather than having to rely on a central team for insights and data, people making actual decisions around marketing, finance, and many other functions can control their own last mile and respond to changing business needs. Because if there’s one thing we all know with certainty, it’s that business needs will constantly change.

Undoubtedly, a great deal of business value comes from crossing this last mile at headquarters. McKinsey recently estimated that unlocking advanced analytics capabilities across retail could produce over $15 trillion in added value, as the move makes for more efficient advertising targeting, an enhanced ability to determine prime locations for new stores, and the capacity to aggregate all customer data into one central system.

The full value is only realized, however, when we think beyond the last mile that happens at headquarters and look to the last mile in physical stores and upstream with product vendors. Combining these three last miles of retail analytics is key to the future of retailers.

Last Mile #2: Brick and mortar stores.

Even in the age of e-commerce, there are still millions of people interacting in physical retail locations. Getting useful and timely data to the people working in these stores can make an immediate impact on business performance.

To get there, retail IT systems need mobile capabilities, helpful insights for workers, and full access to individual store data (in order to power the entire retail network).

Anyone who has worked in retail knows that the analytics need to be easily accessible from a mobile device. Team members do not have time to run back to a laptop to pull up data or print out reports that are already out of date. Mobile phones provide the perfect platform to deliver these insights directly to the front lines of retail.

Of course, delivering the data in an easy manner does not always make the data useful. It is imperative to deliver insights that are relevant and helpful. I’ve seen it firsthand, with sales data creating a sense of excitement among in-store teams while providing important information on which new products are resonating with customers.  

Good retail data also allows stores to compare themselves with others in the same market and/or region. Are we behind in electronics sales? If so, we can now compare data to create the best shopping environment in each location. And even better, when stores receive real-time data and enable communication around this data, conversations don’t need to be put off until the next field review meeting; they can happen immediately.

There is also a gamification and psychological aspect here. People are motivated to outperform their peers, so making data available to everyone in real time can help drive teams to higher levels of performance.

Beyond traditional sales metrics, retailers that have successfully transformed into omnichannel organizations no longer rely on store locations. They have fulfillment hubs, which can serve customer demand whether someone is walking into the store, picking up an online order, shipping an order from the local store location, or driving up for delivery right into their car.

This changes the job of a retail worker, and changes the kind of information that is needed. A store manager needs to understand what new digital orders are in the pipeline and if their team is working through the orders quickly enough. It’s not just about the sales occurring at the cash registers in that store; it’s the total customer base engaging across digital and physical.

Each store is a treasure trove of information to share, including assortment whitespace (are customers asking for something you’re not carrying?), location-specific disruption (is there a highway construction project that is impacting sales?), and voice-of-the-customer data (feedback, complaints, and trends). So the “it” is not just about getting data to the stores. The stores themselves become an important and real-time source of information and data.

Retailers nowadays need to know within days—if not hours—where, say, a dip in sales is coming from. If you don’t, you risk losing a lot of business, because you’re unable to correct for it in a timely manner. When retailers can create a two-way conversation about data in their retail locations, they have truly started to cross that last mile in retail analytics.

Last Mile #3: Product vendors and suppliers.

The third analytics opportunity for retail is with vendors and suppliers, who are key parts of any retail organization. Just like headquarters and individual store locations, vendors play an important role in making retail operations successful. And as with store locations, data must flow both ways with vendors and suppliers to get the most from the retail analytics opportunity.

Data sharing presents a new challenge for vendors, as it pushes them to think more broadly about how they can leverage data provided to them. The first step is looking to automate and increase the frequency of data coming from retailers. The days of having a full-time employee (or third-party service) spending hours prepping and massaging data need to end. Most retailers now provide APIs or other automated access to their data, and vendors need to start thinking about data arriving in real time from their retail partners.

With new and more frequent data points in hand, vendors need to up their games in terms of forecasting and other retail analytics functions. The types of data will also continue to expand with use cases around inventory data, retailer forecast data, customer sentiment data, digital search, and more.

It’s easy to imagine a day when a product complaint is logged in-store or online and suppliers are immediately alerted to the problem. This type of information will help adjust future forecasts and help suppliers with long-term product planning and strategy.

As the retailer is collecting and serving data to the field, it can also provide relevant data back to its customers. There is no reason retailers shouldn’t be able to see vendors sending real-time information to stores about product recalls or what’s selling fast. The possibilities are endless.

Last Miles are all about execution.

It can seem overwhelming to look at a journey like the one outlined above, and it’s normal to feel hesitant. With all the legacy systems at every retailer, linking data sources and getting information into the hands of every worker can feel like an impossible task.

The key is to find technology that can be a capstone on existing infrastructure, even as some of that infrastructure is starting to modernize. These new parts of the “Last Miles” can be achieved by extending and enhancing the infrastructure you already have in place.

It will take leadership and vision, but retail analytics’ three last miles can be crossed. And for those willing to make the leap, the benefits of being a modern, data-fueled retailer should more than outweigh the effort.