[0:00:05.8] EMILY: Hello, and welcome back to Happy Porch Radio, Season five, where we are looking at digital solutions in the circular economy. Today, we have the pleasure of being joined by Michael Groves, who is the CEO and founder of Topolytics, a leading data insights business that uses machine learning and geospatial analytics to make the world’s waste visible, verifiable, and valuable.
We had a very interesting conversation with Mike. We’ve actually spoken a lot about waste and data over the course of this season, it was really interesting to get his perspectives. He has got big ambitions for mapping the world’s waste and he’s really enthusiastic about taking on that challenge. I really feel that came across in this conversation, Barry.
[0:00:59.0] BOK: Yeah, definitely, I’m also glad that I didn’t have to say geospatial too much. We’ve talked about data and waste quite a lot but I really enjoyed I think this conversation was different in multiple ways and, apart from the, as you say, Mike’s passion and he talked a little bit about at the end of the interview about why that, is or where that comes from, and his desire to see or importance of geography and geospatial data analytics and solving some of these tough problems.
But all the way through, we’re talking about, I guess, the importance of data, not just for its own sake, but just speaking about that quite a lot or feel like we have throughout this season. It’s more than just the tools.
[0:01:40.0] EMILY: Yeah, definitely and I think that it’s interesting to think about this solution in terms of the bigger picture of circular economy, as Mike himself mentions, the waste is kind of a part of that, and the data is really important to gather, so that we can design for circular economy. But just how important all of this data and understanding and the interpretation of it and cleaning it up and making it available to everyone, just how important that all is, I think it’s really represented in how successful Topolytics is becoming and everything that Mike is doing.
[0:02:13.5] BOK: Absolutely. I especially, for anybody listening who is interested in data or works and data I think and a little taster here and how important your role is with the data of person’s role is, in the circular economy and then making meeting some of these top challenges.
[0:02:29.7] EMILY: Definitely.
[0:02:31.1] BOK: Without any further ado, let’s meet Mike.
[0:02:37.1] MG: Hi, my name is Mike Groves. I’m the founder and Chief Exec of Topolytics, and we’re a data aggregation and analytics business that’s making the world’s waste visible, verifiable, and valuable.
[0:02:52.0] BOK: Awesome, I really like how really simple and clear that is, because waste is a big, complex, and very fascinating topic. Mike, welcome to Happy Porch Radio and I’m really excited about this conversation. I think, as regular listeners who will know, we’ve covered multiple different things, multiple different angles of the circular economy, and waste has been something that’s come up a few times before. I think it would still be interesting to kind of get your view on, I guess, waste in terms of the circular economy, and how and why Topalytics is kind of working on that problem?
[0:03:23.6] MG: I don’t know why you want to talk about waste because it’s such a rubbish subject. We’ll maybe skip that and move on. Waste in circular economy. I mean, actually, there are sort of awkward bedfellows in some ways. I mean, we’re – there is this organisation called the Ellen MacArthur Foundation, which is the sort of the blue ball think tank, doing a lot of sort of pioneering work around circular economy, and we’re a member of that, we’re a C100 company.
What are the kind of questions you know, I get a lot is, “But Mike, the circular economy isn’t about waste. It’s about, obviously, designing waste out of the system. It’s about making products, and reducing use of those products, or making them so that they can be remanufactured, or reused, or kept in use, rather than those materials and products going into the waste stream.” But, my answer to that, and the reason we focus on the waste bit, which is almost like the end of the pipe is that, if you look at the numbers, they’re huge.
If you look at world bank numbers in terms of global volumes of what they call urban waste, just like the kind of city type waste, going from two billion tons up to over about three and a half billion tons over the next sort of 10 to 20 years. We got this massive amount of material, this massive problem that we need to deal with. Still, to this day, more than 60% of that material globally is still going into a landfill or is going to a waste dump or, obviously, at worst, is leaking into the environment. Hence, we have people like David Attenborough highlighting the issue of ocean plastics, for example.
We sort of think, the circular economy, yes, we need to sort of work to that ideal where we’re designing the wastage out of the system but, in the meantime, we got to deal with that problem as we see it. That’s why we’re trying to make that system of materials movement, on a global basis, much more visible so that you can build trust in the data and, ultimately, if there’s trust in the data, then all the players in that system can then start to build better business cases to improve the outcomes of that too.
[0:05:26.1] BOK: Yeah, that makes complete sense, and I think you just said that in a much better way than I could have. Pulling out a word you used there a couple of times: data. You’re approaching – there’s a quote from somebody at Google who says that waste is a data problem, which I think is quite interesting and I think in my mind, that’s exactly where Topolytics are. Is that fair?
[0:05:45.9] MG: Data is a waste problem, yeah, because there’s a lot of it out there and not a lot of it is being used effectively, I suppose. Yes, there’s another quote actually, which I quite like, which is from the World Economic Forum years back. I think it was from Accenture, and it basically said that, if the circular economy is going to be any kind of revolution, it will be a digital revolution.
I think by that, we clearly need digital tools to design better products, and design better packaging, and design waste out of the system but, by the same token, in terms of what we’re doing, we think that there’s an opportunity to drive digitisation into the waste industry and the waste system, because it’s a very traditional industry that has been sort of moving waste and disposing of waste for 150 years or so. There is definitely, we see an opportunity to use data in a better way.
I mean, clearly, having data is one thing but then, as everybody says, it’s what you can get out of the data, it’s the insights that you can get from that data. A lot of what we do is really just focusing on the quality of data because there is a lot of rubbish data out there. We have said, “Look, there isn’t a single source of the truth.” I think this is true about most things in life, there’s no single source of the truth, you know, everyone has a slightly different perspective, everyone has a slightly different take on a subject, and waste is no different.
There is a single perfect, beautiful, digital footprint or data set for all of that material. Whether it be plastics, paper, metals, chemicals, whatever it might be, food. What our view is, in that scenario, what we’ve got to do is we’ve got to – this is why we aggregate data, we got to be able to pull data and for many different sources and many different forms. What we’re good at doing is basically breaking it down, cleaning it, normalising it, so that you can then build it up again, and actually start to make decisions based on what you’re seeing, but what you’ve done is you’ve built a level of quality and trust into the data.
We think actually, if we’re going to get new business models, new ways of recovering material, new ways of recycling, new ways of reducing waste in the first place, I think digital technologies and tools are going to play a big part.
[0:07:59.4] EMILY: That’s really interesting Mike. I think, especially talking about that trust in the data, that’s something that’s come up quite a lot over the course of this season. As you said, it’s kind of impossible to design waste out of the system if we don’t know everything there is to know about waste and where it’s going currently.
That’s definitely the first maybe also the second, third, and fourth steps in this process, is data is so vital. Can you tell us a bit more about the digital tools that you use at Topolytics?
[0:08:30.1] MG: Yeah, we’re a pure sort of data business. We’re not – what we’re not doing is we’re not, if you like, creating data from, for example, sensors. Sometimes people say to me, “Well, you know, how do you put sensors into all this waste and measure it?” But we don’t do that. What we really good at doing is extracting that kind of data and working with that kind of data, and then understanding the sort of fundamentals of that data, and the structure, and the quality, and everything else that’s attached to it.
You know, there are sort of multiple ways in which some of this data within the waste sector is being acquired. It could be acquired through apps, it could be acquired through sensors, it could be acquired through honest-to-goodness sort of database and software, or whatever you might be, it could be acquired on a piece of paper and then put into a spreadsheet.
In terms of a sort of tools that we’re using, it’s all in the back end, it’s all in the way you process that data, the way you ingest that data, the way you clean that data, the way you analyse that data. We won a competition, for example, we won a competition last year that Google Cloud and the big software company SAP ran, which was to find a commercial technology that enabled the circular economy at scale. 250 companies applied globally and we won that competition. It was quite a privilege for us, but obviously, if you think about Google Cloud, I mean, it’s one of the fastest growing bits of Google or alphabet, so it’s a kind of cloud hosting, data processing, bit off the bigger business.
There’s some really fantastic tools within that for new machine learning, you know, for looking at patents in the data, for cleaning and processing that data. A lot of the tools we use are really in the back end, in the guts of the system where we’re – it’s almost like the trenches, it’s the really unglamorous bit. But it’s the bit that’s really important because, if we’re going to present information to our customers, and we’re going to present it in a way that we can stand behind and we have confidence in, we can create a fantastic kind of view of into that data through the dashboard or maps or whatever it might be. We really have to be sure that whatever data sits behind those kinds of views into it is as good as it possibly can be. We’ve also got to be very good at being able to pull that data into our platform we call WasteMap, as easy as possible, because we’re trying to do this at scale.
We’re sort of trying to – with pulling in data, significant quantities use of data. I think a lot of what we use is in that sort of the back end and then we’re using obviously various tools to visualise and to analyse it and kind of generate the use of the data as well.
[0:11:12.3] EMILY: First of all, congratulations on winning that competition, it sounds fantastic. I look forward to seeing how things pie out with it. Am I right in thinking that the – just so I’ve got a clear picture. Data is out there and being collected by other people, who are not you, and then Topolytics is gathering all of this data into one place, is that right?
[0:11:35.1] MG: That’s a pretty good summary, I mean, we’re an aggregator, so we aggregate at scale, because we think that, again, coming back to that sort of mission statement, if you like, about making this system or visible. It is a system, you know? We see as global system of interconnected materials movements, you know, many thousands of different sort of companies and organisations involved in that system, many thousands of different materials, and many millions of movements of that material.
That’s the way we view it. In order to make sense of that, we have to be able to work with many different types of data sets for many different sources. Yeah, we’re aggregating from those different sources.
[0:12:20.7] EMILY: Yeah, can you give us some examples of what your clients do with that data specifically?
[0:12:25.7] MG: Well, a big question for a lot of people is, and this is really something that’s sort of really come to the fore of the last few years I would say, is that fundamental question about what has happened to that material? Where does that material go? Because I think, traditionally, because it’s waste, it’s kind of being out of sight, out of mind. Whilst certainly in Europe and US and elsewhere, there is what you might call a duty of care, if you're a waste producer, to dispose of that material correctly, there is still an element of opaqueness in the system and not – those companies and organisations that are producing the waste, somebody else deals with that material.
You know, they have a contract of somebody who takes that material away and they dispose of the problem. You know, it’s removed from their sight. Traditionally I think that’s been sort of the way we’ve pretty well all viewed waste, is it not? Is that we put it in a bin, somebody else removes the bin, and does something with it. I think that is definitely changing and clearly, God bless David Attenborough, you know, environmental communicator bar none. Some of the work that he’s done around, particularly around the ocean plastics and Blue Planet et cetera, I think opened people’s eyes to the stuff that’s kind of leaking out of the system and obviously plastics as had the most attention there. I think that’s a big question that we’re helping. No, you think it would be easy to answer that question but, because of the nature of the system, and the nature of waste, and the way it’s handled, that is quite difficult. That’s why, as a team, we have people that work – our teams sort of really triangulates on three things. Waste industry and circular economy, so we’ve got people that run waste management companies, we know the way the waste industry works, we’ve got software development team, and then we got a data science team. Really, we’re using data science as trying out to some of these questions. That’s a kind of key question, we’re currently also working with the UK environmental regulators, so DEFRA and the various national regulators, who have set a challenge to create what they call a smart waste tracking system for the UK.
This, in essence, is a digital system that can assist, can digitally track all waste movements across the UK. We are building a sort of prototype version of that system at the moment. The challenge I think for the regulator is much better oversight, and much better visibility of the waste movements, and one of the kind of key things there is to try and address quite a big problem of waste crime.
You know, fly tipping material that’s being disposed of incorrectly or improperly, material is being exported when it shouldn’t be exported, or the wrong type of material is being exported, et cetera. There’s a huge problem with waste crime. They’re the kind of answers that you know, the kind of questions that the regulators have.
Then I think, if you think about the industry itself, you know, the recycling industry, the waste management industry, there’s a lot of new technologies that are being developed to recycle what were previously difficult materials to recycle, but what they need to understand is where is that material? What does that look like? What does that sort of map of materials look like? Where could they best invest in capacity to effectively recover that material?
There’s a whole range of different questions that we are answering for those different types of organisations.
[0:15:46.4] BOK: There’s something though which really appeals to the engineer in me, to the coder in me, all through that, you used the generic term waste, and yet in each of those scenarios, there’s multiple, that covers – I noticed on your website there’s an example of a gas, basically gas leaks, and then you're talking about plastics, and then you're talking about all the waste in the UK and with [inaudible 0:16:05].
Is that what or how you're approaching that problem? You know, you’re looking at these waste streams, is part of that analysis and data then and, maybe in certain cases, breaking that down into types? How granular are you able to go in some of these scenarios?
[0:16:23.9] MG: Addressing that first point about the use case around gas census, I mean, as Topolytics, we’re focused on, what you might call solid waste. That will be your commercial, industrial waste streams, that will be household and domestic waste streams, and hazardous waste, which tends to be a solid or a sludge or liquid. The gas leaking is interesting because we knew that, at some point, there’s going to be much more, if you like – this whole piece about industry 4.0, you know, sort of internet of things, census, machine to machine, you know, sort to data acquisition, et cetera, that was a sort of coming wave, or it is a coming wave, and that’s going to hit the wastes industry as much as it hits any other industry.
But this is a few years ago, we thought, well actually, we need to understand how that kind of data works. You know, we need to understand quality of the data, we understand how those sensors work, how that data is acquired, some of the shortcomings, some of the opportunities, and actually, the idea of having sensors on bins is certainly a sort of – that’s a sort of growing area and growing fast but, at that point, we thought, actually, we can get sensors that are gas sensors, so we can at least understand how those kind of realtime kind of sensors work and we could take that experience back into the waste sector.
That, I guess, is the first to say around that. You're right, I mean, this is one of the real – I get asked this question a lot, it’s like, “Why don’t you just look at the particular material? Why don’t you just look at particular type of plastic, or look through at food?” We have deliberately set out to look at all of those types of material because what happens is, that material might be picked up in a mixed load. It might be plastics, card, and paper mixed in the same container.
It then gets taken somewhere where it’s separated, but your card is mixed with card from other sources, and it then gets bailed, and it then gets sold, and moved on. It’s all an interconnected system that’s handled by the same types of companies, passes through the same sites, but then it might get separated and moved on to other sites. We think, if we only look at one material, we’d only see one small part of that system, so we have to look at it on a systemic basis.
In terms of the granularity, I’m a geographer so I see the world through those eyes, if you like. In terms of what we’re doing, if you think about the geospatial or the geographical piece around waste, it’s really crucial to understanding, number one, what happens to it, and number two, what could happen to it.
There’s a piece around the relationship between where waste begins and where waste ends. There’s this sort of spatial relationship thing there. But also, if you think about geography and maps, there is a scale thing as well. You could look at an atlas, and what you see as sort of an aggregated view of the United Kingdom on an Atlas. It doesn’t give you all of the detail, but they just show you the main roads, they show this main features, but what you can do, obviously, is you could zoom into a very detailed, ordinate serving map that shows an individual building, so you’ve got a large scale view.
So that’s what we’re trying to do with our platform, is to be able to zoom in right in, down to the level of an individual bin or an individual container. You can have data attached to that or you can zoom out and see thousands or millions of containers, and what you do is you aggregate the view or aggregate the data. You aggregate and desegregate as you go, but our starting point is to say the more granular the data that we work with, the more accurate, if you like, the atlas view will be. If that makes any kind of sense?
[0:19:57.8] BOK: It does. It makes complete sense. Well, there is quite a lot there but also it gives a real inside into the complexity of the problem. You might just say it’s really hardcore data science, never mind the gathering and further validating of that data. Something you said earlier about there being no single source, I was almost a very relieved to hear somebody say that, because I feel often in the digital space we always were too structured, we’re too linear.
We are kind of different, we’re sort of separate from the real world. We are trying to force binary logic onto what is not a binary system at all. It is really interesting when you said that and then about sourcing data from multiple places and then trying to aggregate it and understand it, in a way that is very real-world, I think that is what I heard from what you are describing there.
[0:20:45.2] MG: Yeah, I think that is a pretty good summary, yeah. I mean, the phrase I always use is, “There is no single source of the truth.” You are absolutely right. The other phrase that is a favourite of my chief of technology officer is, “Even messy data is useful data.” So, of course we see a lot of data that, you know, we see some very good data, and then we see less good data, but actually even the less good data can be useful to us.
Real life is messy, is it not? Whatever you’re looking at, whatever aspect of real life and waste is no different. You’ve got multiple organisations, you’ve got multiple materials, you’ve got different ways of describing that material, you’ve got different ways of classifying that material, you’ve got different ways of measuring that material, people take a slightly different approaches, even though there are weather regulations in place and there might be some schemes in place, but yes,you’ve got these multiple players who are all describing and measuring in slightly different ways, and waste might be taken to a weight bridge, but how do you know the weight bridge has been calibrated properly? There are all sorts of subtle and not so subtle variations in the system. These are the kind of things that we are trying to pick up and analyse, so that we can build up this, try and build to a better version of the truth, even if it isn’t a perfect view, it’s still better than having no real idea at all about what’s going on.
[0:22:07.0] EMILY: Yeah that is a lot of variation in the data. I can imagine that that is the magic, when you can pull it together and make it in some way uniform and usable. I imagine that’s especially difficult in terms of working around the world, and in different regions, and across different continents. What happens on the other side when instead of too much messy data, there is actually a hole in the data, and it’s not even out there to be found?
[0:22:35.3] MG: Yeah, I mean even in what you might call data-rich environments, there is always holes. So, that’s the first thing to say on it. I think part of the messiness might be lots of holes. We are used to that. As you say, in certain different countries, you’ve got different regulations, you’ve got different levels of sophistication around how information is being captured, if any information is being captured at all.
That’s where we’ll try to bring in data that maybe comes from certain – you know, maybe comes from large companies that might have a footprint in that country. It gives us something that we can work with. Again, our approach to this is almost like a crime scene procedure, where you start with a set of known connections. You just gradually build up a picture, or you model it as you go, and that’s basically our approach where we don’t have – We normally have something but it might be very limited and we just sort of build from there.
It is a challenge but, to be perfectly honest, you know that’s the challenge we’ve set ourselves because we think actually that is where an opportunity but I do get, you know, lots of people say to me, “Mike, it’s just so – why do you do this? It’s just so difficult,” you know?
Also I do get various trips to Silicon Valley and I set up, and I pitch, “We are building this meta map of the world’s waste etcetera, etcetera.” In Silicon Valley, you get, “Oh Mike that’s awesome,” and you get that reaction, but you know I do also get the reaction, but, “Oh but Mike you’ll never do that.” My view is, well, you know building up that perfect 100% view of all of that material, yes it is very challenging, but we’re giving it our best shot.
Also, the more we see, the more we can model, and the more we can improve the modelling. Even when we do have limited data, we can still infer things, and we can still draw conclusions. You’re right, it is a real challenge, but fundamentally our approach is to say, whatever we do in the UK or the US or whatever it might be, we say, "This has to work across all countries.”
It is a constant challenge that one, but something that we’re well used to, and a challenge that we happily accept.
[0:24:51.1] EMILY: Why do you do it?
[0:24:54.3] MG: Hey, yeah there you go. The six million dollar question.
[0:24:57.9] EMILY: In the face of all that challenge, as you described ,and also in the face of that – not necessarily push back from people saying it can’t be done or you won’t do it, but just kind of that reality that it is a really huge undertaking. What is it that kind of keeps you going on a day-to-day basis?
[0:25:16.4] MG: I love the challenge. I guess that is the first thing, and I love it when people tell me I can’t do something. That is the red rag to a bull, isn’t it? So the whole race thing is going, I mean it is the entrepreneur thing. I mean, I guess I am an entrepreneur and what do entrepreneurs do? They love to service, they have an appetite for risk. They love a challenge, they love creating value from where there was no value, where there was nothing.
I love that aspect of it. I am trying to build – this isn’t my first company. A number of startups and sold one company and etcetera, etcetera, but I am really trying to build something that’s scalable and significant. That is something I am trying to do as well. By the same token, why waste? I sometimes tell a story, I used to work – I was involved in the very early days of for Forest Stewardship Council. This is in the very early days, in the late 90s, where we were trying to certify sustainable forest management. We were trying to sort of – you know, Forest Stewardship Council was one of the first independent certification schemes for sustainable forest management.
I worked for a company that was one of the auditors against that kind of standard. I basically ran around Southeast Asia, I was based in Jakarta, and ran around Southeast Asia, going into all of these remote forest in Borneo and Malaysia, or in Indonesia, or in Papua New Guinea, etcetera, and trying to check if the forests were being managed against these kind of standards. I spend a lot of time in the forests, and at logging camps, and bumping around in ancient Toyota Land Cruisers, but occasionally, of course, one would have a day off, and occasionally one would go to the beach, being in Southeast Asia. Of course, many a time I’d come across a tide line full of flip-flops or plastic bottles, and this was the best part of 25 years ago.
I thought to myself then, “How on earth did that material end up in this remote, pristine location?" There’s an element that, if you think about the why, you know, that was that first bit where I thought, "This is really strange that this shouldn’t be happening.” Then, you know, I always worked in and around environmental management, sustainability, etcetera, etcetera. To a certain extent that bit, in terms of actually trying to do something that has an environmental benefit whilst also makes money – I don’t think the two are mutually exclusive – is something that motivates me.
[0:27:42.9] EMILY: Thanks for sharing that story, that’s cool. I am very glad that the world has people like you with an entrepreneurial spirit to take on these challenges, because I imagine it is not easy, day in, day out.
[0:27:59.4] MG: Yeah. It has its moments, let’s put it that way.
[0:28:03.0] EMILY: We started this conversation talking about circular economy and the idea of designing waste out of the system. You’ve talked about kind of big plans for mapping the whole world and waste but, in terms of the big picture, what do you see as the future of waste?
[0:28:23.2] MG: Initially, at least, I think what we need to be doing is reducing the volume of material that enters the system. Waste material is clearly the bigger aim, but where that material is being disposed of in some way, or put into a bin, or whether it be production waste from a factory, or whether it be from a retail operation, or whether it be our own bins at home. Making sure that that material isn’t just disappearing into a hole in the ground, or disappearing into rivers, I think that is the initial clear and present danger that we have to try and address.
That’s the first thing, but then, in parallel with that, it is, I think, about clearly looking at substitute materials, looking at reducing the amount of raw material that we use in products and/or packaging. Moving into that position where, in essence, we are trying to design both products and associated packaging but also the commercial systems whereby that product is kept in use, or the utility of that product is maximised.
That is clearly what – the circular economy, clearly there’s a piece there about materials, but there is a whole piece around, if you like, the financial and the business models attached to how we access those products. Do we just rent or lease something as opposed to buy something? You know, those kinds of the servitisation type models so there is a whole piece of work around that as well. But purely in terms of this materials piece, clearly is about ultimately reducing that which goes in the waste stream, but that which goes into the waste stream making sure that isn’t just being lost and we at least trying to capture, to its highest possible degree, the value in that material.
Now maybe it’s that some of that material does end up being converse it into energy, but obviously, what we are trying to do is actually recover as much of it, and reuse as much of it, or recycle as much of it.
[0:30:21.0] BOK: What's your next level of Topolytics, what’s the vision aligned to that, as you just described? Are you able to air the impact you would like to? You said you were looking to build a scalable impact for business.
[0:30:34.3] MG: Well, I guess to a certain – I mean if you are looking for a parallel, you know somebody – so, these aren’t my words, somebody likened us to the Bloomberg for waste on that way, that’s the sort of ambition, is that we become this global trusted source of insights, from which people are then able to make these better commercial and environmental, or get these better commercial and environmental outcomes.
Some of the work that we are doing with, for example, having won that competition with SAP, for example. You know if you look at SAP, they have set very, very ambitious goals around addressing some of these big problems, for example the ocean plastics problem, carbon emissions, and, as a big enterprise software company, what they see a lot of data on in terms of raw materials. They see lots of data on production, if you loss the supply chain data, and they work with some of the world’s biggest consumer product companies for example.
Where they have these ambitions around driving waste reduction, driving circular economy goals, we can directly feed into that through some of those relationships. In terms of what we are doing, linking the insights that we are able to provide about what happens to that material once it goes into that waste system, linking that back into the purchasing and supply chain systems, because it is a supply chain issue. It is really interesting to us.
That starts to really try and close the loop, you know, that is where you really close the loop, in terms of the circular economy and materials. It is really, really interesting work in that regard as well. I think fundamentally, yeah, you know, this idea of this global, trusted insights that people can access on a live basis is the ambition.
[0:32:24.3] BOK: That is really interesting and inspiring, I can’t – the example, it took me a moment to connect the Bloomberg example, but then that doesn’t make complete sense. It is like the real-time and deep market insights that somebody like that provides. You are looking at that in the real world waste and the people who need to make business in terms of hygiene and circular decisions.That is really interesting and, as you say, has the potential to really scale and have that huge impact.
I’d love to go into all of that on more detail but as we are running out of time but I can finish on a slightly different question. For those listening, particularly those who are maybe interested in things like data science, or there’s this sort of geography geospatial, or machine learning, that they’re the kind of tools that you are using to reach that big vision you just laid out.
For those people listening who might be interested in working out how they can get involved perhaps in contributing to that kind of vision, or to the problems that they care about, and this is maybe a tough question, but what advice would you give them?
[0:33:21.1] MG: I did a TEDx a few years ago, called Why Geography is Going to Save the World, or Saving the World with Geography I think it’s called. I am passionate about geography and geospatial science and how it can absolutely play a leading role in actually trying to achieve some of these ambitious goals that we have, or these challenges that we have globally, not at least of which is climate change. I would say to anybody who is thinking about where they might go, both the geospatial science bit and then pure data science and data analytics – I mean, you can’t get a data scientist or a data analyst for love or money at the moment because there is such demand.
I would say to anybody who is looking at that, I think there is lots of opportunity out there. Professionally, I think there is this growing demand. Clearly build that better, you know post-COVID and all of these stuff there about how we deal with the current situation that we are in, but how we then build from that, and build in a better way, and I think there is all sorts of opportunities there. There is a lot of kind of really good stuff out there in terms of courses and short courses and online courses. You know, you’ve got people like the Digital Catapult, you’ve got the Future Cities Catapult system. These places where you can make connections, and network, and learn. In Scotland you’ve got a thing called CodeClan, where they basically run 16-week data science causes for people who are coming from a completely different backgrounds.
We have actually recruited somebody from that course. There is – you’ve got innovation centres like The Data Lab. I think there is quite a lot of that stuff out there and I think there is a growing amount of help out there for people that want to maybe look at some of these tools and techniques, and learn more about it, and maybe move into that area. Certainly, when it comes to demand from the point of view of jobs in the market, I can only just see that growing really.
I occasionally have been into schools and just talk about geography and mapping and how important it is, but also how is this an opportunity. I mean when I was at school, geography was kind of like, yeah right. You’ve got your pencils and your tracing paper because all you do is you trace maps, don’t you? But I think clearly it’s moved on enormously and now we’ve got all of these obviously Google Maps and all the mapping platforms.
You’ve got the whole piece around satellite data, and the plethora of satellite platforms that are generating significant amounts of data. Somebody needs to analyse that and process that, and interpret it as well, and generate the kind of insights from that. I think there’s an all sort of really, really interesting opportunities out there for people that – and it is never too late. You know I am in my mid-50’s you know? I am an old guy and I am still trying to do something. I think that is my other thing: it is never too late.
[0:36:06.5] BOK: I think that is the inspiration there, as you said, this is this the thing that you are passionate about, and tying back to what you said before about not shying away. In fact, enjoying the tough challenges because that is where the excitement is, that is where the impact is, that is where the opportunity is, both business opportunity and as an individual. That’s really inspiring, and a huge thank you for sharing a real insight into your story, and we’ll put links out to all the things you mentioned there in the show notes at Happy Porch Radio as usual.
Very finally then, Mike, anybody who wants to find out more about the work that you are doing and about Topolytics, where should they go?
[0:36:44.1] MG: Well, you can find it at topolytics.com. You’ll find some information there but I am Michael Anthony Groves on LinkedIn. I am always happy to connect to people and I am always really happy to just talk about this stuff. If anybody wants to reach out, I am really happy to just have conversations, make connections, whatever it might be.
[0:37:01.1] BOK: Thank you so much. It’s been wonderful and inspiring to have you on the show. Thanks again, Mike.
[0:37:05.9] MG: No problem, great to talk to you both, thanks.
[0:37:08.0] EMILY: Thank you, Mike.
[0:37:09.3] MG: Thank you.
[0:37:11.6] ANNOUNCER: You can find notes and links from this episode plus a full transcript at happyporchradio.com. If you are enjoying the show, please take a moment to give us a positive review on your favourite podcast app. Thanks for listening to Happy Porch Radio.
