Walmart’s decision to end its five year experiment with Bossa Nova Robotics and their in-store robot program was unexpected, but upon further analysis not without merit, at least in the short term. Other robotics companies servicing the retail sector are progressing, but they must continue to innovate to be successful.
Listen to this article
Sometimes the worst thing to say is “I told you so,” so I will avoid further mention of Walmart’s decision to end its five year experiment with Bossa Nova Robotics and its in-store robot program. If you have been following my writing (here and here, for example), you have probably connected the dots.
My e-mail inbox has been flooded with messages and questions about the Walmart stoppage announcement and the impact on other robotics companies providing solutions to the retail sector. Here are my thoughts on where we stand.
The Walmart risk
Many were surprised when the news broke that Walmart was ending its contract with Bossa Nova Robotics for robotic shelf scanning and inventory operations in favor of human workers and software solutions. Early this year, Walmart had announced expanding the rollout of Bossa Nova systems to 1,000 stores.
Walmart claimed that humans can do just as good a job as robots performing inventory checks, especially as an increased number of workers were hired to fulfill online orders. This might be true during the unusual times of COVID-19 as online orders spiked, although perhaps not long term. I think the view is shortsighted and might be clouded by other factors that are beyond the scope for this article.
For Bossa Nova, robot testing program at Walmart, the world’s largest retailer, was always a risk. The company could succeed hugely, or fail in a very public way.
The decision to focus on a retail giant can prove to be the path to dominance. It can also result in entanglement into a never-ending list of requirements and trials that consumes resources and drains investment. I believe that those automation and robotics firms who focus on the smaller, regional retailers have the winning strategy.
The essential questions remain the same… can robotics systems accurately, repeatedly, and autonomously (at scale) function in retail stores collecting and processing shelf data to solve real business problems? These are now table stakes – the keys to measure the success of the robots. Anything less is a nonstarter.
Larger retailers should now be looked at as technology companies. They must rapidly innovate if they are to stay competitive. They incubate solutions in their own labs which often compete with all the dreamy startups that are working on the same problems. By partnering with start-ups, large retailers position themselves to have the best of both worlds.
While Bossa Nova Robotics regroups and strategizes on life after Walmart, other providers of retail robotics solutions will continue with their pilot projects and expanding their roll-outs, but with an emphasis on lowering costs and business models prioritizing data monetization.
There is no question of the business value of automating data collection in retail. They include:
- Reducing the amount of out-of-stock items, a challenge that the retail sector has struggled over decades to achieve.
- Automation can also reduce labor costs, a critical benefit especially as labor costs continue to rise and the number of workers available to perform mundane tasks become scarcer. Even the current higher level of unemployment will not diminish the value of automation.
- Another automation advantage is the ecosystem efficiencies gained when near real-time shelf data is made available and shared with supply chain partners.
Other retail robotics players
While Bossa Nova Robotics regroups and strategizes on life after Walmart, other providers of retail robotics solutions will continue with their pilot projects and expanding their rollouts, but with an emphasis on lowering costs and business models prioritizing data monetization. This is the winning model, and one which robotics solution providers did not realize initially. Example companies include:
- Badger Technologies – Early on, Badger proved to be nimble and scaled quickly. Their retail robotics solution has been functionally expanded from spill detection to include shelf scanning. The company is scaling up operations, expanding at several grocery retailers with a shelf insights robot. The backing of Jabil, a large electronics manufacturing company, might prove to be the key to the company’s overall success.
- Simbe Robotics – Simbe began testing their solution with several retailers globally early on. The company is expanding rollouts, including the September announcement of increasing deployment at Schnucks from 16 to 62 stores. Closing their last investment round in 2019 prior to Covid19 was very timely.
- Zebra Technologies – Zebra is expediting the maturity of their robots, and leveraging their wide retail solution portfolio and business know how to move fast. The company has an established client base to whom it can offer a compelling solution.
- Zippedi – Zippedi has expanded from its sizeable presence in South America, and is now operating in the US, testing at several retailers and expanding deployment at a tier one retailer as well. By leveraging their deep retail store experience, and focusing on scaling early on, they were able to learn and adopt quickly, proving their supplier rollout model in the process, and methodically expand.
What does it take to succeed?
Walmart decision aside, the progress these companies have made is good news, and critical to their future success. Still, they must be laser focused on maturing their solutions and scaling fast. It is too late for beginner mistakes as everything is on the line.
Retailers are less forgiving now, especially given the early hype about the technology and rollout delays. Scanning at scale with high accuracy must be demonstrated quickly.
Companies must also have a solid response to the question all retailers will be asking, namely “What are you working on next?” Demonstrated capability has to be in tandem with a healthy dose of four key traits of successful start-ups – maturity, modesty, courage, and vision.
Four critical capabilities
Although adoption of robotics technologies in the retail sector is sluggish, the slow pace is understandable. Autonomous, robotic shelf scanning is one of the most complex solutions to make its way into crowded retail stores. Shelf scanning is required, and automated solutions will shine a bright light on decades of hidden deficiencies servicing the retail shelf.
The retail sector will not get there if robots are not able to deliver on the four critical capabilities of automation, scale, accuracy and repeatability during shelf scanning operations.
Collecting shelf inventory data is not the be-all, end-all capability for mobile robotics systems for retail applications. Eventually robots will add the capability to pick products and restock shelves.
If Walmart’s decision to cancel its agreement with Bossa Nova Robotics was due to an increased labor presence for fulfillment work, their change in strategy makes sense short term. That and investment in fixed cameras technologies, and the fast growing popularity of micro fulfillment centers, also imperils the value proposition of robotics shelf scanning solutions.
With the passing of the pandemic, the number of online shoppers will eventually retract, but will continue to be above pre-pandemic levels. We will have to wait and see what will be the long term impact on the retail robotics market.
Collecting shelf inventory data is not the be all end all capability for mobile robotics systems for retail applications. Eventually robots will add the capability to pick products and restock shelves. That will be the next game changer and differentiator, although it is certainly much more difficult than autonomous navigation and scanning. Some companies have started experimenting with mobile manipulation, but to attract retailers, they must prioritize it on their roadmaps and demonstrate serious progress.
About the author
Georges Mirza is vice president for platform product management at 1010data, a provider of analytical intelligence to the financial, retail and consumer markets. 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, and has been ahead of the trends that have produced industry changing solutions. He currently advises companies on how to strategize and prioritize their roadmaps for growth. Follow him on LinkedIn or Twitter.