Robots and Retail Go Together Like Zeros and Ones

Robot Jingoism, i.e., the propaganda that robots are coming to take retail jobs, is out there. Unfortunately, nothing could be further from the truth. There are simply hundreds, if not thousands, of tasks that go undone every day inside every retail store. No retailer can monitor price accuracy, inventory accuracy, or, heck, even floor cleanliness across an entire store, multiple times per day, even if it wanted to do so. It is an untenable proposition.

Which is exactly where robots come in.

But, stopping the robot-and-retail marriage story there also misses an even greater point. Not only are robots key to doing the jobs that do not get done today, they are even more importantly, an easy-to-implement first step to help retailers operationalize their data on the road to creating better omnichannel customer experiences.

Omnichannel retail, or New Retail, as some like to call it, is all about the relationship between data and customer experience. It is the philosophy of knowing, in real-time, everything happening in and around the customer. At the simplest level, it is about turning zeros and ones into actions that excite and delight modern consumers.

As easy as it is to say, however, putting New Retail into practice is harder than it looks. Doing it well requires three essential ingredients: 1) Real-time computing power 2) Data capture 3) Grade-A analytics. 

Real-time computing power is about having POS, OMS and ERP systems capable of handling and processing data as well as communicating with each other in real-time. Data capture is about having a system of recording devices to understand everything happening in a store against a backdrop of transaction data, e.g., where a customer is, what the inventory levels are or even which prices or promotions are visible at shelf. And, no surprise here, analytics is about taking all this recorded data and being able to understand the observed correlations in space and time against customer behavior.

Sounds simple, right?

Wrong. 

It is incredibly complicated to put into practice because the whole system design puts a tremendous data load on retailers, a data load so intense that few even know what the final load looks like at this point. 

Hence, the rub. 

Every retailer wants to get to this new world, but the path is fraught with peril, especially in light of the second required element: The system of recording devices. All kinds of options, from employee tablets to customers’ mobile phones, can record activity inside stores, but many of these options also share one big problem: They require either employee or customer adoption and significant behavior changes.

Robots, on the other hand, don’t. 

Robots are possibly the most minimally invasive way to start recording data at scale. This is true because they don’t require any major changes in how customers shop or employees work. Yes, humans have to get comfortable with robots roaming the aisles, but that is a one-time event. All other customer and employee behavior remains unchanged. And, honestly, how much is there to get used to if one robot roams a 30,000-square-foot grocery store? It’s like worrying about the mechanical window washer on the outside of a skyscraper. It is just something to which people will get accustomed, something that will become blasé.

That’s the beauty of it, too. 

Retailers can start small with robot implementations. Start with simple tasks, like monitoring floor spills, then move up in complexity over time. Such an approach gives them the room to acculturate store employees and customers to robots being in their stores and then quickly lets everyone go back to their lives as usual. 

From there, the real magic happens.

Then, retailers can (and again, without asking employees or customers to do anything differently!) slowly start to assign new tasks to their robots, like inventory counting, price sign auditing and temperature checking, as part of their single robot, roam-around-the-store routines. Retailers can start to collect and learn how to operationalize all the data that could and should matter in the background, with little to no operational impact. 

Said another way, retailers can start to understand just how big the data load is without it becoming too much for employees, customers and, as importantly, the CFO and CIO to handle. This type of approach means no large capital installs, no change in customer behavior and no 17th different process that store employees have to learn for yet another technology rollout.

Just one robot. That is all it takes. 

Just one robot to help retailers learn which zeros and ones matter the most for the future.

Chris Walton is a leading expert and influencer in omnichannel retailing. An accomplished Senior Executive, with nearly 20 years of success within the retail and retail technology industries, Chris has high-level executive experience across nearly every discipline within retail. Currently he is the CEO and Founder of Omni Talk  one of the fastest growing blogs in retail, and Third Haus, a retail technology lab and coworking space in Minneapolis. He is a regular keynote speaker, a Senior Contributor for Forbes, and he also sits on the Advisory Board for Delivery Solutions and Xenia Retail. Previously, Chris worked for Target, where he was the Vice President of the retailer’s Store of the Future project and also the Vice President of Merchandising for Home Furnishings on Target.com. Chris began his career at Gap, Inc. and holds a BA in Economics and History from Stanford University, and an MBA from the Harvard Business School.