On The Digital Life podcast this week, we chat with guest Mary Ellen Sparrow, CEO of NextShift Robotics, about collaborative robotics and automation. NextShift focuses on developing robots that work in concert with people on the warehouse floor for e-commerce operations. Unlike other automation systems, the company’s technology works within a warehouse’s existing infrastructure, rather than requiring a massive overhaul and build out. Its robots are designed to work in complex and variable environments. For example, they can avoid obstacles, navigating around objects in their path. Join us as we discuss robotic automation, misconceptions people may have about the relationship between jobs, workers, and robots, and the potential of this technology to transform industry in the near future.
Jon: Welcome to episode 245 of The Digital Life, a show about our insights into the future of design and technology. I’m your host, Jon
Follett, and with me is founder and co-host, Dirk Knemeyer.
Dirk: Greetings, listeners.
Jon: Our special guest this week is Mary Ellen Sparrow. She’s the CEO of Next Shift Robotics, right here in Massachusetts. Mary Ellen, welcome to the show.
Mary Ellen: Hi. Nice to be here.
Jon: Today, we’re gonna chat about people working alongside robots and all of the advancements that are being made in that field. Mary Ellen is gonna tell us a little bit about the great work they’re doing over at Next Shift. Mary Ellen, could we start by you telling us how Next Shift was founded as a company? What’s the story behind Next Shift?
Mary Ellen: So basically, my partner Steve Kubis and I, saw a hole in the e-commerce market in warehousing or getting goods from the warehouse over to a consumer who has been ordering something online. And in seeing that hole, what we did was decided to start Next Shift to actually help warehouses get their product to market for shipping quicker.
Jon: I think I read that Next Shift had the origins of your technology in another company called Harvest. Is that correct? How did that come to be?
Mary Ellen: That is true. Steve and I and a small team of engineers worked at Harvest Automation, and Harvest decided to divest and downsize. And in doing so, we bought the assets from Harvest and started Next Shift. So, these were assets that Steve and I had worked on in the previous year while employed at Harvest.
Jon: So the focus of Next Shift was really to take these robotic assets that you acquired from Harvest and to focus on this e-commerce niche because I think you had said on your site that Kiva Systems, when they were acquired by Amazon, left a big hole in this e-commerce warehousing, picking and shipping area. Is that pretty much … Is that summation correct?
Mary Ellen: That is true, but we kind of took it a different direction. The Kiva System is a very large ASRS system. What they do is when they go into a warehouse, and they’re fully owned by Amazon, and no one else can use them but Amazon. But what they do is they take down the infrastructure, all the shelving, all the product shelves, and they put in their whole system. What we did was design a robot that could work collaboratively with people and that could actually work in the existing shelving and the existing inventory. We wanted to go in very quickly, very cleanly and very simply. So we’re much different from lativas and the other types of automated storage and retrieval systems that you’ll see in the market today.
Dirk: So our listeners may not be familiar with those technologies and how they manifest. Could you talk a little bit more about the differences between the things that you are doing and the things that a company like Kiva’s doing?
Mary Ellen: Yeah. What happens with Kiva is Kiva goes into a warehouse, they take down all of the shelves, and then they put the goods into their mobile shelves that move to a picker. The shelves weigh about 1200 pounds, and a robot would come in, lift it up, and bring it over to a picker. A picker would pick one or two items, and then a robot would bring the shelf back to a shelving area. What we did was we left the shelves alone, so there’s still warehouse shelving like there was before. And what we do is we put a fleet of mobile autonomous robots that go into the system and actually work alongside the picker, so that the picker isn’t lifting 40 pounds. They’re not lifting heavy totes. What the picker’s doing is simply picking from the shelving at any time, and the shelving isn’t disturbed as it was with the large ASRS systems.
Jon: That’s really interesting. I think that speaks to really a different type of design approach. In other words, I’ve heard the term collaborative robotics used in a variety of contexts, just talking more about humans and robots complimenting each other. Mary Ellen, could you talk a little bit about collaborative robotics and what makes that mindset of people working with robots a unique and important approach for the future of this kind of automation?
Mary Ellen: I think it’s the future of any type of automation at this point. In the past, we’d have robots behind a fence and they’d be doing some type of work where that if anything came in, the robot would immediately stop because the robot didn’t have a suite of senses to know that there was something within the area that it needed to avoid. The robot wasn’t given design techniques so that it could work among people and actually help to make them more productive and to make the job more scalable. What we’re shooting for is basically an augmented workforce. What you’re seeing is things like AI and things like robotics and things like crowdsourcing are now adding to the workforce in place, and enhancing their productivity, and making them more effective by adding in not just the particular person worker, but adding more attributes to them so they can get their job done easier and quicker.
In doing that, what you’re seeing is by augmenting the workforce, the workforce can be scalable and it can be more productive. We’re making people start to focus more on people tasks, the tasks that they do better. So they’re better at problem-solving. They’re better at strategic thinking. They’re better at working with other people. And we’re making robots and these types of devices work on things that are rote, that are boring, that are heavy lifting, that are pushing, that are pulling, and things that people don’t enjoy as much and that stress a person’s body.
Dirk: Automation in general, and robotics in particular, have really advanced in industrial applications, far more quickly than they have in consumer applications. And a lot of our listeners are probably thinking more about robotics from the consumer side. Can you talk a little bit about both why in your opinion the advances have been more on the industrial side, and what are some advances in technology, maybe similar to the ones you mentioned before, that you think might help to accelerate robotics and automation on the consumer side?
Mary Ellen: Basically we’ve had a lot of advances on the industrial side because industry has been used to working with robots way back into the ’50’s with car manufacturers. It’s been a constant piece in our manufacturing history. So, we are familiar with robotics. We may not be familiar with collaborative robots. We may be familiar more with robots behind a fence, but robots are not unheard of in industry. So they’re very common in industrial applications, especially ones where you have a safety feature that you don’t want a human doing. So, if you don’t want a human touching a dangerous chemical or you’re trying to do something that’s very minute work that basically you need a lot of repetition for, a robot is better suited for those kinds of things.
And consumers, we’re just starting to see a lot of advancements in consumers, and we’re just starting to see, it’s actually coming forward with navigation for the robot. So now what you’re seeing is that a robot’s able to actually move around a space that isn’t a space that it had planned before. For example, we can look at iRobot’s Roomba, where it actually moves around the home without having the route to be predetermined. So, there’s a lot of navigation systems that are now using a suite of different sensor fusion to be able to move in different areas. And that’s why you’re starting to see more of your consumer goods because the technology has actually gotten better.
You’re also seeing that people are finding needs or niches for consumer robotics that we might not have had before or thought of before. The whole advancement with iRobot and the Roomba, or all the little Jibo and the different robots that you’re starting to see in the consumer industry are just starting to really come into play and not be … and start to be used in a daily fashion.
Jon: Yeah, I think we’re … You mentioned two other Massachusetts-based companies with iRobot and Jibo’s out of Massachusetts, is that right?
Mary Ellen: Yeah, it is.
Jon: I guess there’s a lot of robot talent here in the Boston general area. And of course, when people leave companies they go and form new ones, and so the ecosystem can be growing. I wanted to turn the conversation a little bit to some of the misconceptions that people might have between that relationship between jobs, workers, doing those jobs, and then robots doing similar work or even potentially, I put this in quotes, taking those jobs. Clearly, that’s got to be a theme that you deal with when you’re talking to folks at Next Shift. How do you address these misconceptions? How do you address this issue when people ask you about it?
Mary Ellen: It is a question that we see all the time. As a matter of fact, I was just doing research and if you look at the Wall Street Journal, you’ll see that they have articles that are like iRobot’s Taking My Job, and then they have articles about well why hasn’t the robot taken this job away and why is the robot gonna create so many other jobs. What we’ve found in looking at different surveys and at different academic articles is that companies would rather actually retrain their worker than reduce their labor force. 70% of companies said that they’d rather retrain than reduce. So, you’re not seeing that they’re getting rid of their workers, but they’re trying to have their workers understand that as we grow and as we grow in technology and as we move forward with things like AI and cognitive computing, that you’re seeing basically a retraining or a redefining of what the job could be and what the job should be.
With that redefinement, you’re also gonna be retraining your workforce and moving them forward, so they’re not doing jobs that are maybe unrewarding to them. They start to use more of their people skills and they start to use more of the aspects that are important in being a human, for example in problem solving and in dealing with customer issues and in increasing a company’s value proposition, as opposed to just trying to get stuff out the door. In doing that, what you are seeing is there’s a whole direction in this company, in this country, in this world that’s actually gonna redefine our jobs and our workforce, as technology becomes more and more involved. And in redefining it, what you’re seeing is that people have to be valued for their people skills and technology, robots, or whatever have you, would be valued for its more repetitive unlabored skills.
Jon: That sounds, to me, like how I imagine automation could happen, and then there’s, I think that’s a really positive and hopeful message, as opposed to the more dystopian, “Hey there’s gonna be lots of people out of work because they’re just not going to be needed anymore.”
Mary Ellen: Actually, I’m gonna give you a point of fact. When ATMs came out in the banking industry and they thought that every teller would be let go, today they have more tellers than they had before they invented ATMs. Okay. There are so many examples like that where technology has come in, and it hasn’t destroyed the infrastructure, it hasn’t destroyed the jobs, but it shifted the jobs so that jobs are a little more rewarding.
Jon: Tell us a little bit about what’s coming at Next Shift. What are you excited about? What new features and functions are you rolling out next as you develop your collaborative robotics platform?
Mary Ellen: Well, as you know, Next Shift’s a young company, so we have a very, very large technology roadmap. But with that in mind, we basically designed our system for the warehouse space, so we’ve done a lot of work around having the robot work with people. For example, when a robot goes near a person, it reduces itself to half speed to make that person more comfortable, or when a robot sees an object in the aisle, instead of just stopping there and waiting, it goes around the object if it can. We also have a robot that deals with things like an uneven floor or breaks in the floor, because we work in a warehouse and there’s a lot of concrete around. And then we’ve also tried to do our tasks for green. So for example if a warehouse has motion detection lighting in it, we have our own self-lighting around our cameras, so that we can see where we’re going even if it does get dark.
And then besides that, there’s just a lot of different structures that we’re working with, both in the collaborative and in the automatic space moving forward.
Jon: Terrific. I’m gonna wind up our interview today with you, Mary Ellen, asking to look a little bit ahead into the future, which can require a little bit of guess work, but how do you think robotic automation is going to be changing things for industry, both say in the next three to five years, then possibly further out? What do you imagine is coming for industry as robotic automation really starts taking hold?
Mary Ellen: Okay, so here’s my dreams. What I’m hoping is that you’re gonna stop seeing robotics automation tethered to the floor. You’re gonna be able to have robots on mobile platforms and they can move from one location to another. Everything is not gonna be fixed inside of a warehouse or inside of a manufacturing floor. It’s gonna be able to move. The other dream that I have, of course, is for driverless vehicles. I would love to see driverless vehicles, hopefully in my lifetime, where we get rid of a lot of our road congestion. We basically, as you well know, in traffic accidents, 90% are caused by operator error, and I’d love to see that part go away because we actually have infrastructure that can support driverless cars. Not that we do yet, but hopefully we will.
Jon: Yeah, I could see driverless cars really changing the landscape, especially around here in the Boston area where traffic is legendary.
Mary Ellen: Yeah, we know.
Jon: So, Mary Ellen, thanks so much for coming on The Digital Life and talking with us today.
Mary Ellen: Well, thanks for having me. It was great to talk to you guys and I really enjoyed it.
Dirk: It was our pleasure.
Jon: Listeners, remember that while you’re listening to this show, you can follow along with the things that we’re mentioning here in real time. Just head over to TheDigitaLife.com, that’s just one L in TheDigitaLife, and go to the page for this episode. We’ve included links to pretty much everything mentioned by everybody, so it’s a rich information resource to take advantage of while you’re listening or afterward, if you’re trying to remember something that you liked. You can find The Digital Life on iTunes, Sound Cloud, Stitcher, Player FM, and Google Play, and if you want to follow us outside of the show, you can follow me on Twitter at John Follett, that’s J-O-N F-O-L-L-E-T-T. And of course, the whole show is brought to you by Go Invo, a studio designing the future of healthcare and emerging tech, which you can check out at GoInvo.com. That’s G-O-I-N-V-O.com. Dirk?
Dirk: You can follow me on Twitter at D Knemeyer. That’s at D-K-N-E-M-E-Y-E-R. And thanks so much for listening. Mary Ellen, how about you?
Mary Ellen: We have a website. It’s called www.NextShiftRobotics.com. And we’d love to hear from you on our website. We have a contact sheet if you’d like to send us a note or drop us a line.
Jon: That’s it for episode 245 of The Digital Life. For Dirk Knemeyer, I’m Jon Follett and we’ll see you next time.