AI in Waste Management: Turning Trash into Data

Chad Watt: Welcome to the Infosys Knowledge Institute podcast, where business leaders share what they've learned on their technology journey. I'm Chad Watt, Infosys Knowledge Institute Researcher and Writer. Today I'm speaking with Rebecca McMorris, Senior Director for Strategy, Planning and Data Services with WM.

Chad Watt: WM is formerly known as Waste Management. It is North America's premier solid waste and environmental services provider. Today, we're talking about how WM uses data and AI to make the job easier and improve the bottom line. Welcome, Rebecca.

Rebecca McMorris: Hi, Chad. Nice to talk to you this afternoon.

Chad Watt: So Rebecca, our U.S. listeners will know a bit about WM from your trucks they may see on the road. Tell us a little bit more about the size and scope of WM.

Rebecca McMorris: Yeah, it's a great question. I think most people are familiar with the trucks that they see on the road that's picking up, it may be their waste from their home or recycling at their home or their place of business. But WM does operate many different businesses that help in sustainability and environmental services.

Rebecca McMorris: And a few statistics that I think bring to life the scale of WM. One is around our fleet of trucks. So, we operate over 12,000 natural gas powered trucks. And that is the largest heavy duty fleet of natural gas powered trucks in North America, and we're extremely proud of that. In addition, we are also North America's largest recycler as well as the largest operator of landfills in the U.S. So there's a lot of the largest of in our business, and it's exciting to be able to share the broad suite of businesses that we operate with the audience today.

Chad Watt: Rebecca, tell us about your background and role at WM.

Rebecca McMorris: So I've been in it for approximately 22 years now. When I think about it's crazy to do that math. Time flies, I guess, when you're having fun. But I've served in a variety of positions through the course of my career, whether that be application support, major project delivery. And for the last 10 to 12 years, I've been in the data and analytics space.

Rebecca McMorris: The first 20 years I actually was at an oil and gas company. You've probably heard about it. It's called ExxonMobil. And there was where I spent the majority of my professional career and learning about how to deploy technology at scale.

Rebecca McMorris: And then two and a half years ago, I had the opportunity to join WM. And it was a company that when I did my research, just fit with the values and the opportunities I was looking for to continue my career. And so today, I operate both our strategic planning function within WM Digital, as well as our data services function that oversees our data and analytics portfolio of projects.

Chad Watt: Tell me a little bit more. You've spent decades in data and how does WM think about data?

Rebecca McMorris: So one of the things that brought me to WM was the people that I interacted with across the company really got it. And that goes a thousand miles in terms of being able to connect what we're doing in the data and analytics space from an IT perspective to business outcomes. And so when I talk to business leaders across the company, they get the fact that good data will mean good business results, and will help them drive their business forward. And so I don't have to sell them on that, they get it. And we can then focus on the problem or the opportunity from a business standpoint that they're having that they want to capitalize on. And it just makes the conversation go so much more smoothly and getting to outcomes quicker.

Chad Watt: What was it that locked you in to know that they really get the value of data and the business value you can unlock from data? What was it that persuaded you?

Rebecca McMorris: Yeah, I think it's two things. One is they were putting their money where their mouth was. So, they were investing in projects that leveraged data at its core to bring change to how they operated from a business standpoint. And not only projects, but those projects included things like governance and data quality. So to me, that proved their understanding.

Rebecca McMorris: And on the flip side of that, they were also talking about, what are the roles, what are the decision makers that I need in my organization to ensure that that data is maintained and achieves a level of quality that's going to continue to support my business objectives? And so through those conversations, through those project investments, that to me, has proven that they understand the value.

Chad Watt: On this podcast and within the Knowledge Institute, we talk a lot about data and how business leaders think about data. So to get at that, I want to ask you, what is your favorite analogy for data?

Rebecca McMorris: So I would be remiss if I didn't say that with my 20 years in oil and gas, I think the easy answer to this is data is the new oil. And I think we've all heard that analogy. But I really like to think of data as water. And water is critical to life for us humans, and I think data is critical to the business. And especially in this age of AI, I think there's a way to maybe get by for a time if your data's not up to par, but I think ultimately, it will limit you as a business. And so through having access to clean quality data, to me is what is going to make a business thrive in this day and age.

Chad Watt: I see how you picked up on the water angle there. That was nice. Now that said, we're talking about the possibilities of data. What about the risk? What are the challenges? What are the special challenges that come into play when it comes to data in your line of work?

Rebecca McMorris: Yes, we have lots of forms of data that we have to deal with. And I think this is going to be commonplace for lots of companies, especially those that are in non-digital native histories. So, we have lots of systems that were born in the age of pre-data and analytics. And so we're having to continue to work with those legacy systems, do our best to extract that information out, and put it in a place that we can take advantage of it through these new digital and AI capabilities. In addition, we still have processes that are pretty manual that may be generating even analog data, so data on a clipboard out in the field that we have to translate in. And then we marry that up with very sophisticated new types of data, for example, satellite information.

Rebecca McMorris: So, it's the combination of all of these complex and both new and old data sets that we have to bring together to really make the data and information that our business needs to run accessible. But again, that's part of our challenge. That's what excites us and gets us up every day. So, it's a fun project.

Chad Watt: I understand that one of your data initiatives involves taking pictures of the waste containers. How is WM making use of trashy pictures?

Rebecca McMorris: Yeah, first, so much fun. Trashy in a true waste sense of the word. But yeah, we have a program called Smart Truck. And what we do with that is essentially if you think of one of our collection trucks as like a rolling data center. And we have both sensors as well as image cameras on the truck. And so when we go to a customer and we actually pick up the recyclables and mechanically put it in the truck, we are scanning and taking video of the contents of that container. And utilizing AI, we're able to essentially identify contamination and overages, which has the potential to limit our ability to process those recyclables and maximize the second reuse of contents.

Rebecca McMorris: And so, it has been a highly successful program for us. I think in the pilot utilizing this imagery and essentially taking the results of that and sharing it back with our customers. And helping provide education if they are including contaminants, for example, in their container, we've been able to reduce contamination by over 20%. And I think that that just shows where we're having true results utilizing these capabilities, even with our customers.

Chad Watt: We're talking about data and AI and we can't do that without talking about generative AI. So from a corporate perspective, we are coming out of this kind of sandbox phase with generative AI. Can you describe the move from kind of experimenting with generative AI to using it at scale?

Rebecca McMorris: Yeah, generative AI, I think is top of mind for anyone in digital right now. And even at the senior leadership level of the company, I think everybody is thinking about it. And for us, the advantage also comes with some risks. And for us as a company, we wanted to ensure we were mitigating those risks first and then quickly looking for all of the advantages as a quick follow. So, we've been working very diligently over the past several months to set up our AI governance framework. Which will allow us then to analyze and to evaluate all of the business opportunities we have for generative AI. And to select the ones that are going to be, one, not too much risk for us, but also those that are most advantageous to us as a company to continue to move us forward. So, we've tried to come at it with both a risk mitigation as well as an opportunity mindset.

Chad Watt: Can I ask you to kind of double click a little bit more on WM's approach and outlook to traditional AI versus generative AI? We've been talking about kind of data and AI in ways of making the job easier and also about improving the bottom line. Can you talk a little bit more about how you're applying technology to improve the bottom line at WM?

Rebecca McMorris: Yeah, it's a great question. We use technology all the time to help improve our business operations. And I think if you listen to our senior leadership, whether on an earnings call or in some of their public interviews that they do, they have highlighted use of technology as part of our strategic initiatives to continue to improve the position of the company. One example that is top of mind is our application of data and AI in route optimization that our drivers and our managers out in the field use every day to help ensure that we're taking the most effective routes along the roadways as we can, getting our drivers to their destination and back safely.

Rebecca McMorris: We also weave in other technologies that are, quite frankly, pretty simple, but also have a very meaningful impact. So if you think about a simple notification that we take into account when we build routes that says, "How high is a bridge overpass on the route that we're taking to ensure that our trucks will fit under?" That's critical. And it's not necessarily anything super sophisticated, but it is using data that's available to us to ensure that we are building in constraints that we may need to think about into our solutions as well. So to me, it's a very nice blend of sophistication as well as meaningful data to help achieve those outcomes for our business.

Chad Watt: Rebecca, how does your work with data, AI, and advanced technology address the sustainability ambitions that WM has?

Rebecca McMorris: We are absolutely leveraging data and AI with our sustainability objectives, specifically, and it's included in our sustainability report. And I just want to put a plug out there for all the audience, if you haven't taken a look, it's a great report that showcases all the work we're doing on sustainability. But specifically within the data and AI area, we are piloting and scaling our ability to measure more specifically, the surface level emissions from our landfills. And that is a key area of focus for us to ensure not only that we're doing right by the environment and the communities that we operate in by collecting and containing those emissions more efficiently and effectively. But we're also able to convert those methane emissions into more renewable natural gas, for us that is part of our business. And so, it's both a positive on an environmental and community front as well as on a business front, and those are the win-wins we're looking for from a sustainability standpoint.

Rebecca McMorris: I think our approach to, quite frankly, any technology investment, but we can apply it here to how we think about AI and generative AI as well, first and foremost, we look for business problems or business opportunities that we want to go after. And that to me, when we focus on that rather than on the technology itself that's going to solve that problem, we have the right conversations with our business partners and with our leadership in terms of, is this something that's important for us to spend time and money on?

Rebecca McMorris: But we are always looking for ways in which we can continue to evolve and mature and transform the way we solve problems through technology. So, we will continue to look at the latest developments on AI and generative AI to help us solve the problems that we want to solve in the most efficient and effective way. But certainly in terms of how we think about technology, whether it's AI or something else, is, what problem are we going to solve? And then everything else flows from that. And that has served us well, and I have no doubt will continue to serve as well.

Chad Watt: Finally, let's spin it forward. Rebecca, take a high case scenario. What new data AI technology enhancement is making a difference for WM and your customers?

Rebecca McMorris: So, I'm super excited and kind of building on the thread we were just on around generative AI, around taking the data that we've been collecting in our enterprise data warehouses or data platforms and data lakes. Call it what you will. It's had many names over the past 10 or so years, but it's all of the structured information we've invested heavily on. And the opportunity ahead of us by combining that with all of the unstructured information that companies like WM have been gathering as well. The marriage of those two data sets and applying AI and generative AI capabilities to them to extract new insights, potentially new automations from that really excites me. And I think while it's still early days, I'm very optimistic that the technology is going to be able to make a lot of new insights from that larger kind of combined corpus of information than we've been able to do in the past. And so, really looking forward to digging into that some more.

Chad Watt: Rebecca, is there any subject I neglected, anything you would like to add at this point?

Rebecca McMorris: It's been a great conversation today, Chad, and I appreciate the invitation here to discuss with you and the audience. I would just say these are my thoughts and don't reflect necessarily the views of WM, and not an endorsement of any particular vendor. But it's been fun chatting with you about AI and my history with it so far, so I appreciate it.

Chad Watt: Well, thank you for sharing your insights and your ideas. This podcast is presented by MIT Tech Review in partnership with Emphasis Topaz. Visit our content hub at technologyreview.com to learn more. And be sure to follow us wherever you get your podcasts. You can find more details in our show notes and transcripts at infosys.com/iki in our podcast section. Thanks to our producers, Christine Calhoun and Yulia De Bari. Dode Bigley is our audio technician, and I am Chad Watt with the Infosys Knowledge Institute signing off. Until next time, keep learning and keep sharing.