How Simbe Robotics is Impacting Grocery Stores with Automated Intelligence Gathering | FMI 2025
🎙 Omni Talk Retail Live at FMI 2025: Benjamin Bond on Retail Automation with Simbe Robotics 🎙
Join Chris Walton & Anne Mezzenga as they speak with Benjamin Bond, VP of Strategy & Business Development at Simbe Robotics, about how automation and AI are transforming grocery retail.
⏳ Key Moments:
00:00 - Introduction: Live from FMI 2025 with Simbe Robotics
01:30 - Benjamin’s Background and Role at Simbe
03:20 - The Impact of AI & Automation on Retail
06:00 - Key Benefits of Using Tally for Inventory Management
09:15 - Understanding T-Spot and Multi-Modal Data Capture
11:30 - Best Practices for Implementing Robotics in Stores
14:00 - Future Trends in Retail Automation and Technology
17:50 - How Simbe Supports Retailers with Accurate Data & Insights
💡 Explore how Simbe Robotics is leading the charge in retail innovation—Subscribe now!
#grocery #robotics #fmi #retailtrends #retailstrategy
This podcast uses the following third-party services for analysis:
Podcorn - https://podcorn.com/privacy
Transcript
Hello, everyone, this is Omnitalk Retail.
Speaker A:I'm Chris Walton.
Speaker B:And I'm Anne Mazinga.
Speaker A:And we are coming to you live once again from fmi from the Symbi booth, where Symbi and Omnitok are retail's single source of truth.
Speaker A:And standing between us, Ann is Benjamin Bond.
Speaker A:Ben is the VP of Strategy and Business Development at Symbi.
Speaker A:Ben, welcome to omnitalk and thanks for joining us at fmi.
Speaker C:Thank you for having me, Chris.
Speaker B:It's taking everything in Chris's power right now not to call you bond or 007.
Speaker B:Look at his face.
Speaker B:Look, look at.
Speaker B:Have you seen anyone, any human being so happy in the Podcast ain't over.
Speaker A:Yet and Podcast ain't over yet.
Speaker B:Well, Ben, let's start by getting a little bit of your background and your role at symby.
Speaker C:Yeah, absolutely.
Speaker C:So I lead strategy for Simbi, which is really focused on where is Symby going as a company and how are we going to get there, but then also, and more importantly, working really closely with our clients to make sure that they're getting the maximum value out of.
Speaker B:Our technology and quickly.
Speaker B:I think we've heard that a lot today about how people are thinking about, you know, it's kind of been reversed where now it's thinking about, you know, the technology and how you're going to bring people into that, like focus on the technology to help solve the problem and then how you bring the people into that.
Speaker B:Is that something that you work with partners on too in your day to day conversations?
Speaker C:Absolutely.
Speaker C:We, we pride ourselves on being the industry leader in cutting edge technology and retail, particularly in store.
Speaker C:Right.
Speaker C:But we are also very mindful of the balance between product and process and really thinking about how people are working in collaboration with our technology.
Speaker C:And oftentimes there's very specific business nuances with our clients where we have to also meet them where they are.
Speaker C:And so we're thinking about how can we help them evolve in their processes, but also do so in a very manageable way where they're going to be able to get the maximum value as quickly as possible and.
Speaker A:Oh no, go ahead.
Speaker B:I was going to say, what's your background?
Speaker B:How did you get into this?
Speaker B:How did you get into this whole Simbi lifestyle?
Speaker C:Yes, yes.
Speaker C:So I spent my entire career in retail.
Speaker C:I've always been very passionate about the space.
Speaker C:I started in fashion and have worked at this point across basically every retail sector.
Speaker C:I spent the majority of that time working for global consultancies like Accenture and Carney and during that time I was really focused on how do retailers create growth and giving them guidance on growth strategy, which would often go into the conversation of well, how do you then achieve that growth?
Speaker C:What is the type of company that can get there?
Speaker B:Right.
Speaker C:And you're thinking about growth enablement, growth led transformations and oftentimes digitally enabled business models and thinking really, how are individuals within the company going to be able to leverage that technology to create that growth?
Speaker C:Right.
Speaker A:So Ben, I'm curious because I imagine you sit across the table from a lot of retail executives in your role.
Speaker A:How would you sum up what you're hearing from them in terms of how they're thinking about both AI and particularly automation in store, both in the short term and in the long term?
Speaker C:Yeah, yeah.
Speaker C:I mean everybody's so focused on AI these days and you know, the conversation around AI, I think often drifts towards gen AI.
Speaker A:Yeah, right.
Speaker C:Which is a very important.
Speaker A:I'm glad you're making that designation.
Speaker C:Yes, it's a very important part of it.
Speaker C:And when that's the conversation, it's all about quick wins.
Speaker C:And I think there's this as they should be really thinking about experimentation and learning, but there's also a little bit of fear of not getting left behind now when the conversation shifts into automation.
Speaker C:I don't know if all executives necessarily appreciate the linkage between the two and how much potential is being unlocked in automation because of all the progress in Genai.
Speaker C:And so when we shift it to the in store context, we are working at the forefront of automation in store and in particular we're looking at all of those tasks which are incredibly monotonous when we're almost asking the store team to perform machine like tasks.
Speaker C:And so we're taking that burden off of those team members and there's so much opportunity for those stores to not only execute better but also be more accurate.
Speaker C:And that's the space that we're supporting them with.
Speaker B:And Ben, what are some of those best practices?
Speaker B:Because I think it's easy to see say those things.
Speaker B:But what do retailers really need to be doing when they start a pilot or when they even further back, like in the strategy phase of like how are we going to measure this successfully?
Speaker C:Yes, yes.
Speaker C:Well, so what's been interesting over the last year, particularly in the store intelligence arena, particularly leveraging computer vision, there's been this shift from is there value here to there is value.
Speaker C:Now I need to figure out how am I going to get that value and when am I going to pursue it.
Speaker A:Okay.
Speaker C:And so what?
Speaker C:Something that's really important in those early days is to engage with partners that you trust and to go through the exercise of thinking about, based on my unique business construct, where is that value going to be and how big is it?
Speaker C:And that's going to flow directly into, really, a prioritization element.
Speaker C:And so a really common mistake is, you know, that the potential is so massive and this data can be used in so many different ways that you.
Speaker C:You get really big eyes.
Speaker C:And actually, for the pilot to be a success, you need to really hone in on those two or three most important things.
Speaker B:Okay.
Speaker C:Nail those really well.
Speaker C:And then you're going to build confidence and momentum to move forward.
Speaker B:Got it.
Speaker A:And what.
Speaker A:What is the value?
Speaker A:So if you were to.
Speaker A:If I was to hold a gun to your head, so to speak.
Speaker A:Not that I would, Ben, but are.
Speaker B:You continuing on this bond theme?
Speaker A:But maybe if you're the bond, maybe you would to me.
Speaker A:But depends on the next question I'm gonna ask you.
Speaker A:But no.
Speaker A:If I held your feet to the fire, what is the value?
Speaker A:And if you were to outline maybe one or two or three things that the retailer should.
Speaker A:If they're thinking about automation in store for the first time, this is what you should go after.
Speaker A:This is probably where I'd start kind of question.
Speaker C:Yeah, well, I mentioned the piece on execution and accuracy.
Speaker C:I'll explain both.
Speaker C:But we always start with execution.
Speaker C:There's so many instances, particularly execution at the shop.
Speaker A:You're doing your job, basically.
Speaker C:And particularly, how are we executing at the shelf?
Speaker C:We want to make sure we have the right product in the right place at the right time.
Speaker C:And that's something that is really basic that retailers are doing every day, all day.
Speaker C:But it's not always efficient.
Speaker C:And there's often a time gap and a very slight execution gap.
Speaker C:So we help to close that gap in a really easy and effective way.
Speaker A:Got it.
Speaker A:So that's really important.
Speaker A:I never thought about that, actually.
Speaker A:So that's really important.
Speaker A:So you're basically saying, like, let's just first come in and just understand how you're doing, what you're doing.
Speaker A:Like, how well are you getting products to shelf?
Speaker C:Right.
Speaker A:How often are they on shelf?
Speaker A:And that doesn't impact the work you're doing as an employee in the store.
Speaker A:Anything.
Speaker A:You're just putting the robot in, it's scanning the store, and you're getting a report card of performance.
Speaker A:That's essentially what you're saying.
Speaker A:It's a good way to think about it.
Speaker C:Yeah, we get that baseline.
Speaker C:And then oftentimes the next step is actually taking activities that the store team is already doing.
Speaker C:And we're just giving them better understanding as to when and how they should be doing those activities.
Speaker C:And, and sometimes maybe changing the timing or exactly like the optimal routing of those activities.
Speaker B:Right.
Speaker B:Well, Ben, we've talked to some of your clients, we've talked to industry experts the last couple of days to really understand exactly what you're talking about, the case for deploying robotics in store and the benefits that come from it.
Speaker B:But I'm curious, like, where is it going next?
Speaker B:What are the next things that once somebody has built the road already with in store robotics, how do they get more cars on that road and how do they get more throughput, more scale once they've deployed something like this?
Speaker C:Yeah.
Speaker C:So it's really present in our value case.
Speaker C:About half the value is going to come from benefits in store.
Speaker C:What is a little bit next in the sequencing is everything else that can be unlocked upstream outside of the store.
Speaker C:And so then you're thinking about how is this data going to feed into various optimization engines and decisioning that we have across the business relating to merchandising, planograms, forecasting, allocation.
Speaker C:All of these are things that are going to.
Speaker C:Absolutely.
Speaker C:That's all going to benefit and that's sort of what comes next.
Speaker B:Okay.
Speaker B:And then Tally, Spot was recently introduced, adding a computer vision element into that.
Speaker B:We heard from one retailer, they're starting to use this in the back of house.
Speaker B:Have you have heard of any other use cases or any other scenarios that you're like, oh, we didn't.
Speaker B:That wasn't like on our initial roadmap.
Speaker B:But this is working for them and they like it for this reason.
Speaker C:This data is so transformational that that almost happens to us daily.
Speaker B:Okay.
Speaker C:In the case of Spot, what we're really excited about is it's kind of intuitive.
Speaker C:Yeah.
Speaker A:Explain what Talispot is too robot as well, if you don't mind.
Speaker C:So Talispot is a fixed camera solution.
Speaker C:So it's basically a different type of sensor in the store.
Speaker C:It's different from tally, our core robotics platform.
Speaker C:And so what's really intuitive for most retailers is that when they think about where is this technology going Long term, it's ubiquitous.
Speaker C:You kind of have whatever you want.
Speaker C:It's all over the store.
Speaker C:You're going to have a robot.
Speaker C:That's the most important piece for sort of the foundation and frequent high quality data.
Speaker C:But then you're going to layer on other sorts of capture modalities around the store, for example, a fixed camera or maybe a mobile handheld, et cetera, et cetera.
Speaker C:So this is where we know the industry is going, and we're choosing to lead in that journey, and that's why we're excited to say we're the only platform that is out there with multiple modalities.
Speaker B:Right.
Speaker B:They all got to work together.
Speaker A:They do.
Speaker A:They do.
Speaker A:All right, man.
Speaker A:Well, thanks for joining us today.
Speaker A:That was great, great conversation.
Speaker A: ow, we're on record as saying: Speaker A:I'm still here.
Speaker A:I think the robot is going to leave the industry.
Speaker A:Not just stirred up and.
Speaker A:But shaken, too.
Speaker B:Oh, my God.
Speaker A:All right, we'll be here.
Speaker A:All.
Speaker A:We'll be here.
Speaker A:We got one more interview coming your way.
Speaker B:One more left.
Speaker A:One more interview coming your way from fmi.
Speaker A:Thank you to Simbi for sponsoring our coverage here at the show.
Speaker A:And until that interview, Anne.
Speaker B:Oh, be careful out there.
