Automating data collection in the brick and mortar space continues to be an elusive goal and remains the target to chase to bring in the highest level of efficiencies and automation to the whole supply chain. Understandably this is a solution that will ultimately be hardware and software-based, that ranges from fixed cameras, smart shelves, push carts, and drones to the most conceivable option now; robots.

Although form factor is important, and yes, it is remarkable to have a robot in the store and no matter how quickly it can traverse the aisles, questions remain:

•   What kind of problems can it accurately, repeatedly, and autonomously solve at scale?

•   Can it identify out of stock products?

•   Can it recognize what products are on the shelf?

•   Can it validate pricing?

•   Are all data points localized on the store map?

Can it generate a realogram (actual product position and facings in a store level schematic) that can be compared to a planogram (planned product position and facings in a schematic) for compliance?

How will we best leverage this technology for improved shopper satisfaction (or experiences) and make positive changes to our business overall?

Some startups decided to tackle the problem head-on, some chose a gradual approach by solving less complicated problems and building a sound platform as a base to launch incremental capabilities.

Companies like RFspot, Bossa Nova Robotics, Simbe, and Zippedi, to name a few, have built their solutions with the hope of quickly capturing majority market share and setting the standard for the industry. Some started with RFID, some with toys, others with fixed cameras… some are still shifting and pivoting to identify their long-term strategy and focus. One thing for sure, the solution will have a technology component like a robot or fixed camera to collect the data and an AI element to process the data to provide real-time insights and analytics. Consolidation will happen (e.g. Softbank investments in Brain Corp, Simbe, etc.) and ultimately the market will settle with 2-3 top players that can deliver data accurately, repeatedly, and autonomously at the needed scale and cost. Observing the latest announcements around funding and partnerships, we can see how these players and major investors could be involved in various discussions for collaboration.

Who Is Playing The Chasing Game?

RFspot, was possibly the first to pilot in a live retail setting, having a robotic solution for RFID and optical data collection before running out of funding. Others followed or continue, trying to fill the gap, chasing this solution. Bossa Nova Robotics seemingly in the lead with a 50 Walmart store implementation, Simbe rolling its solution to 15 Schnucks stores and Zippedi which started rollout in Chile and is now introducing their solution in North America. The essential questions are still there… how accurately, repeatedly, and autonomously can their robot perform? And how fast can they scale?

In 2018, we had yet to witness reliable scaling of robots in retail to a large enough sample (beyond the few stores mentioned above) so retailers and CPG's could really start reaping the benefits of the data collected and provide meaningful insights. There are newcomers surfacing on a regular basis from stealth mode, claiming success with more cost-effective solutions that are slowly getting noticed. While it is impressive to have a robot move around a store, the major hurdle is not how to navigate in a store, it's the challenge of whether it can process accurately, repeatedly and autonomously the data it collects at scale – an important factor that many seem to prioritize too late in their development cycle. The company to crack the solution of processing the data to report accurately and repeatedly on the 4P's (place, product, price, and promotion) will be destined to outlive the robots to whatever other mechanism it is replaced with in the future. Even further, solution providers that can envision how the applied technology could intersect and interface with existing devices, business tools, data sets, communications, vendors, and supply chain will end up being the elite few that provide integrated solutions that will truly transform retail. This is a critical component in ensuring shopper satisfaction when brick and mortar intersect with ecommerce with buy online and pickup in store (BOPIS). Providing visibility to shelf inventory will drive traffic.

So, Who Knew Johnny Come Lately Was Such A Multi-Tasker?

An advent of late, whether by design or force of nature, are two companies that might have just touched on a sustainable approach to incrementally bring an automated data collection solution to bare. This should get everyone's attention and they deserve a mention.

Brain Corp announced an agreement with Walmart to roll out their autonomous aisle cleaning robots to 360 Walmart stores in January 2019. This is a great dispersion, it shows scale capabilities and revenue model to build the costly stack of optical data collection. A genius approach by introducing autonomous ability to current floor sweeper equipment in stores of a major retailer like Walmart.

Another mastermind approach was introduced at NRF 2019 by Badger Technologies solving one safety need, while building and enhancing the capabilities into the future to solve the larger data collection problem. They are rolling out spill detection robots to 500 Giant Martin's and Stop and Shop stores, immediately, this is dramatic improvement vs the minimal scaling we saw in 2018. Badger's platform can also serve as the base for a future optical shelf data collection solution.

Before You Marry Into One Solution, Be Sure To Pop The Big Questions?

Back to those essential questions… Can it accurately, repeatedly, and autonomously, at scale, function in retail stores processing collected data and solve real business problems?

One thing is for sure, more and more automation innovation will continue to arrive. Retailers should stay engaged and partner with these companies to help optimize their operations to carry on their quest of meeting their shopper's needs.

There is more to discuss on the challenges of processing collected data. Looking to the future and what's next and who is working on that solution? Certainly, technologies will continue to evolve in retail, it is worthy of our time to monitor the level of efficiencies and impact on improving shopper satisfaction.

About the Author

Georges Mirza has been ahead of trends developing retail/CPG market leading industry changing solutions. He led the charge and established the roadmap for robotic indoor data collection, image recognition and analytics for retail to address out of stock, inventory levels and compliance. Georges currently advises companies on how to strategize and prioritize their roadmaps for growth. Follow him on LinkedIn, Twitter or email.