Artificial Intelligence and Business Strategy
In collaboration withBCG
When Ranjeet Banerjee talks about the work his organization, Cold Chain Technologies (CCT), does to transport vaccines and other biologics that must be temperature controlled, he stresses that the company doesn’t solely rely on technology. CCT approaches its work by first considering what problems it’s trying to solve, developing use cases, and then considering whether a technology solution might be the best way forward.
In this episode of the Me, Myself, and AI podcast, we learn how a combination of Ranjeet’s background in chemical engineering, his experience working in the health care space, and a holistic approach to leadership and problem-solving enable him to lead CCT to constantly innovate in the supply chain space. Ranjeet also discusses the benefits of a customer-first mindset and shares insights applicable to leaders in industries beyond health care.
Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast.
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Shervin Khodabandeh: AI is pretty hot these days, but how often do we think of AI keeping things cool? Find out today as we talk with Ranjeet Banerjee, CEO of Cold Chain Technologies.
Sam Ransbotham: Welcome to Me, Myself, and AI, a podcast on artificial intelligence in business. Each episode, we introduce you to someone innovating with AI. I’m Sam Ransbotham, professor of information systems at Boston College. I’m also the guest editor for the AI and Business Strategy Big Idea program at MIT Sloan Management Review.
Shervin Khodabandeh: And I’m Shervin Khodabandeh, senior partner with BCG, and I colead BCG’s AI practice in North America. Together, MIT SMR and BCG have been researching AI for five years, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities across the organization and really transform the way organizations operate.
Sam Ransbotham: Today we’re talking with Ranjeet Banerjee, currently the CEO of Cold Chain Technologies. Ranjeet, great to talk with you again. Welcome.
Ranjeet Banerjee: Thanks, Sam, and thanks, Shervin.
Shervin Khodabandeh: Hi. Good to see you.
Sam Ransbotham: Our podcast is Me, Myself, and AI, and we’re particularly interested in individual stories about people working with artificial intelligence. And I said “Welcome again” because I think we got to know Ranjeet from his work at Becton Dickinson, and Shervin’s known him long before that, I think. Ranjeet helped us with our research a couple years ago, and we did a webinar together. But Ranjeet, you’ve got a new role now. Can you tell us about your work with Cold Chain Technologies?
Ranjeet Banerjee: I joined Cold Chain Technologies in August of 2020, and it’s been a very exciting journey. What excited me about the company and what it does and the entire industry space it’s in is the potential to really transform and address a key need [when] it comes to the life sciences industry, and that is the need for … really, the simplest way I can say this is, how do you provide assurance when you are transporting drugs, biologics, [and] vaccines over long distances, over complicated routes? How are you providing assurance that the product that is getting transported is meeting all the right conditions and ensuring safety and efficacy? That’s the challenge statement that got me excited about Cold Chain Technologies, which is what this company does. So CCT, or Cold Chain Technologies, is the leader in thermal assurance packaging for life sciences. At the time when I was taking on the role, COVID was starting to become an important topic — a pandemic — and since then, we’ve also played a huge role in supporting the distribution of COVID vaccines.
Sam Ransbotham: That seems important to me, and I’m sure my own personal health has benefited from that, but what does artificial intelligence have to do with transporting cold stuff?
Ranjeet Banerjee: If you think [about] where we want to go … from providing visibility today, which is available, to providing assurance that the drug, the vaccine, or the biologic — when it moves from point A to point B, and point B being the last mile, being the recipient, the patient — how do we assure that the product has reached in the right conditions? And that’s where AI and other technologies come into play. So, think of it this way: Today we can monitor where the product is, where the drug is, what conditions it’s seeing, but we want to know more. What we want to know is, when will it reach the patient? And when it reaches the patient, what’s the probability that it’ll be safe and effective, or is there a chance that there’ll be an excursion [that is, a deviation from expectations]?
So imagine now there is a drug being transported. It’s stuck at an airport. A lot of drugs are air-freighted, so they’re stuck at the airport. Now you want to know: OK, there’s a delay; is that a meaningful delay? And if so, what actions do we need to take? So when you start translating this from simple visibility to providing assurance, that’s where AI comes in.
Shervin Khodabandeh: This probability is an interesting take on packaging and logistics. So if I understand correctly, one of the applications of how you’re using AI is to figure out the likelihood that that item that’s being transported is going to get to the recipient not just in time and in place, but also intact or in usable form. Is that right?
Ranjeet Banerjee: Correct.
Shervin Khodabandeh: And then let’s say the probability is low. Then what would you do?
Ranjeet Banerjee: There would be an intervention. Exactly. Let me explain where we are right now. We have launched our first path platform, which I’m calling Visibility. It tells you exactly where a vaccine is, what conditions it sees … or it could be also a drug or a biologic, a cell and gene therapy product. Where is the product, and what conditions is it seeing right now? So that’s what we have today. What we are working on — and that’s going to be coming in pretty soon — is, how do you now take the routes? We know exactly where it’s going to be shipping; we know the ambient conditions. We could take in other factors — like, there could be delays, there could be issues that could create a disruption. And then you take that data, combine that with the design of the packaging, and say, “Is there enough thermal capacity that can take care of these disruptions or not?”
And if the answer is, “Yes, there’s enough thermal capacity; yes, the product is going to reach maybe six hours late, but it’s going to be good,” that’s one implication. The other could be, “It’s going to arrive one day late, and it’s still going to be good.” That’s called another implication. The third could be, “It’s going to arrive one day late, and it’s not going to be good.” Right? Imagine now, once you have that information, you can then take intervention steps as simple as alerting the recipient or sending another shipment, but you can do a lot better and more rather than waiting and losing time and, more importantly, [address] patient safety implications.
Shervin Khodabandeh: This is quite fascinating because I have to imagine a lot of our audience is familiar with the inherent complexities of just the typical logistics problem, which is something has to go from point A to point B and go through a global supply chain with lots of disruptions, and that’s a multimillion-parameter problem, which is a typical logistics problem. Now, Ranjeet, you’re talking about overlaying a whole bunch of other conditions — about temperature and delays and packaging integrity and a lot of other things — that make this one or two or three orders of magnitude even more complex. I could imagine that’s going to be a daunting problem for any human to solve, which is where AI comes in, I would assume.
Ranjeet Banerjee: Exactly. And we are also realistic that this is going to be a multigenerational approach, and you’ve got to kind of crawl, walk, and run. But if you step back … technology always is an enabler to solve problems, right? It’s not an end in itself. But the goal here is what I like calling, “How do you deliver assurance when you are transporting drugs and pharmaceuticals?” How do you deliver assurance — assurance as defined by, “Will the drug be effective when it reaches its intended point of use, or not? And will it be on time, and will it be effective?” And it’s really a whole new value chain creation. And there was a phrase — and this obviously does not come from me; this phrase was used quite intensively in this COVID vaccine program. People said, “Look, you can have [a] vaccine, but the vaccine does not translate into vaccinations.” Folks much smarter than me figured that out and said that. But that is key. You could do a tremendous amount of work in developing the vaccine or the drug or the biologic, manufacturing it, but how do you make sure that you are assuring it in what we call the mid-mile and the last mile?
As we are creating the use cases, we try to always start with real problems and then back into technology, so as we are creating use cases, just imagine the drug arrives, and you say, “OK, there’s been an excursion.” Now, the next question is, is the excursion relevant or not? We could create algorithms there to say, “OK, here’s the manufacturer’s data of what is reliable, what is not reliable.” If there’s an excursion, is the excursion relevant to the point where you have to discard the drug?
You can automate a lot of these to improve efficiency and, more importantly, improve patient safety. You can also create compliance benefits, because everything can then be converted into a record that creates the chain of custody of the product. So those are some of the things that we are working on.
Sam Ransbotham: To what degree does this process transcend your organization? Are you working with your upstream manufacturers to coordinate better? How localized are these improvements to your specific process, and how much can you involve your upstream and downstream partners in that process?
Ranjeet Banerjee: So it’s also a really good question, Sam. At this point, it’s us more connecting with our own manufacturing plants in this network, but I do see our ability to pull the thread all the way to our suppliers. You can take these multiple layers, and … in the same context of providing assurance, and along with assurance, it’s a question of cost. The best thing you can do is provide a high level of assurance at the lowest possible cost. And that’s where, beyond just our manufacturing plants, our suppliers and their suppliers, all that comes in. And you can actually — using data, technology, and AI — you can build systems that are enabling that.
Shervin Khodabandeh: Is the premise here, though, that use of these kinds of technologies in the cold chain logistics … that there would be drugs that would be used that weren’t effective and nobody even knew about it?
Ranjeet Banerjee: Yes. This is actually a well-documented fact, but it’s not probably well understood, I would say. But it’s been documented [in] studies. If you look at the normal waste associated with temperature-controlled pharmaceutical shipments, it could be as high as 10% to 15%. For vaccines, which is a subset — vaccines [are] a subset of the entire family of pharmaceuticals — but vaccines, I’ve seen studies where you can have 20% waste on vaccines. Ten [percent], 15%, 20% is not uncommon — even higher sometimes, depending on where you are sending it. … While this was all known, I think what happened was, with COVID, there was a spotlight on how important it is to get this right. And that was another reason I was excited about … here’s an opportunity to really create some transformational change.
The other thing that I would say is, if you look at pharmaceutical research and innovation, a lot of pharmaceutical research and innovation today is focused on large molecules, as opposed to the small molecules in organics. They are both focused on large molecules. Typically, large molecules — cell and gene therapy products — these require careful condition monitoring, not just temperature. Even some of these are beyond temperature. But these are overall condition monitoring, and that has to be as much thought through as the discovery and the manufacture of these drugs and pharmaceuticals.
Sam Ransbotham: I love the options this creates, because I can even see scenarios that, let’s say, you’re not going to get to the original destination in time, but you can say, “Hey, it’s pretty close to this other place that could use it right now.” I can’t see, really, a human thinking through all that. So, what was the process for doing this before you started to implement these artificial intelligence technologies? How did you figure these implications out beforehand?
Ranjeet Banerjee: I personally am a big believer — and our team believes this too — [that] you don’t lead with technology; you lead with what are the challenges that are out there and then come back and say, “What technologies can be used to address those challenges?” So we started — and we did this over the last year or so — we spent a lot of time talking to the stakeholders, understanding. We also had internal experts. So we started with our own kind of view on what the industry issues are. We went to talk to customers. And we started creating these use cases. Each use case is a real-life problem that technology can potentially solve. We didn’t even ask what kind of technology yet. It’s just like, “OK, what’s the problem first?”
Then what we did was, we tried to rank them — bucket them together, make them more meaningful. And then, from several use cases, we came to three or four big use cases. And then we said, “OK, how do we now solve for them?” And that’s where the role of technology comes in. It could be AI. We are looking at things like blockchain, where you need to get data across different stakeholders. So there’ll be different types of technologies that address the problem. But that’s kind of how we went about trying to understand what are the big challenges out there.
Sam Ransbotham: Shervin, that’s coming up as a theme from lots of people we’ve talked to — this idea of leading with the problem.
Shervin Khodabandeh: Well, I was just going to say, there is a quote in our 2019 report from Ranjeet on exactly that, back when you were at Becton Dickinson. I’m paraphrasing, but it was something along the lines of, companies spend a lot of wasted time on looking at technology where they don’t really have a good appreciation of what the business value is and what the strategy is. And I do remember a very eloquent quote from Ranjeet around, you’ve got to get the strategy right of “What are we trying to get done?” You’ll find the technologies, but first focus on what it is that you’re trying to get done.
Sam Ransbotham: Actually, Shervin’s got a good segue there by bringing up Becton Dickinson. How did you end up in this position? Tell us a little bit about your background. For example, I know that … actually, I’m not even looking at our producer, Allison, and sound engineer, Dave, right now, because I know they play bingo with how Shervin and I have to mention chemical engineering every single episode. And right now, they’re both checking their bingo cards for this, but we’re all chemical engineers here. How did you come from that chemical engineering background through these steps to end up where you are today?
Ranjeet Banerjee: I really don’t use much of my chemical engineering these days, but I graduated from IIT Kanpur in India with [a degree in] chemical engineering, then I joined Unilever. I used chemical engineering there, and I also got into leadership positions. And then, to be honest with you, I think the chemical engineering teaches you a certain discipline, certain process thinking that is really good. I do believe, though … that there’s a certain disciplined process thinking that chemical engineers have — I’ve actually seen this in other chemical engineers as well — that kind of helps you think through big processes, break it down into each manageable chunk. So there’s probably some amount of background training [where] chemical engineering helps me.
After that, I joined Becton Dickinson, BD, in India. I moved with them from India to Singapore to the U.S. I was with BD for a long time. And then, more recently, in August of last year, I moved to Cold Chain Technologies and took over as the CEO.
Sam Ransbotham: Well, take us from chemical engineering, then. How did you get interested in artificial intelligence and machine learning as technologies?
Ranjeet Banerjee: Personally, different people have different points of view, but my point of view is this is a whole new revolution that is happening, where, using technologies that we did not have before, we can solve so many challenges that we could not before. And these challenges are … it’s in health care, it’s in financial, in fintech. It’s in so many areas. It’s in what we just discussed. In every part of the world, in every business, and in every organization, it’s almost like you have to step back and say, “Look, let’s make a list of these big, hairy problems we have never been able to tackle for the last 20 years and kind of step back and say, ‘What can we do? How can we tackle these now through the use of technology?’”
Shervin Khodabandeh: It’s really interesting because, Ranjeet, you’re also pointing out that you need two lenses, right? You need the first lens around, what can technology do for the garden-variety problems that any business has had? And then you also mentioned this notion of assurance as a radical new idea, a relatively new concept. So the second lens is, what are some problems or opportunities that we didn’t even think about?
Ranjeet Banerjee: Exactly.
Shervin Khodabandeh: And you need to really reimagine or really rethink some of your old beliefs around what’s important or what could be done, because, with the advent of the new technology, it allows you to actually conceive of new questions and new problems. And I can imagine — in fact, that’s maybe a question to you — this notion of assurance in supply chain: Do you see that making a leap into sort of more normal aspects of transport? That is, sort of … not necessarily temperature controlled, or not necessarily in health care? Do you see that as a way of inspiring other industries to rethink their supply chains?
Ranjeet Banerjee: I think so. I think the whole idea, if you go back 10, 15 years, people viewed supply chain as a cost center, right? It was about “How do you get product from point A to B?” And some of them were thinking of manufacturing; some of them just think of logistics.
If you now think of [how] you can create and unlock a whole new value from what you do, from the time you’re finishing the product to getting it all the way to the customer, you can create new value. And a lot of that value can be through … it could be for health care, it could be patient safety, it could be compliance. But for other industries, including health care, it could be hugely different customer satisfaction; the ability to make things simpler, make things more … So you are creating a whole new value that is beyond the traditional product innovation that people are thinking. When people think of innovation, they think, “OK, let’s go and create a new product or a new drug.” There’s a whole new innovation bucket here, which is around customer satisfaction, around compliance, patient safety, that’s associated with the value chain that you can go after.
Sam Ransbotham: How do you get people to think that way? They have to blend an awareness of the possibilities of the technology with these use cases that you mentioned before. How are you getting internal people savvy enough to recognize these possibilities?
Ranjeet Banerjee: It’s a great question, because typically, most companies, they will have some idea of technology, but technology is evolving so fast that you may not know what else is available. So when you create the use cases and you make sure they’re compelling, then the next thing we have done is we’ve talked to a lot of tech partners. And then we bring in people who are experts in different areas, and we have discussions that say, “OK,” and you start seeing some themes and trends emerge, and you start getting some idea: “OK, this is how we can connect this between the technology and the use cases.”
Shervin Khodabandeh: Ranjeet, you mentioned, in the ecosystem of tech possibilities and partners — and I have to imagine that also requires an ability to distinguish the pros and cons of a variety of technologies — what’s your view on talent and getting the right talent, and what is the right talent for these kinds of applications?
Ranjeet Banerjee: What we have done is, we bring in three or four types of expertise together. One is [the] domain experts who understand the industry space we operate in. They are the ones that are trying to understand the key customer problems, talk to the customers … so we bring in domain experts. The second is, then we bring in more from an IT perspective, because at the end of the day, when you do all this, you have to also integrate some of these technologies into your ERP systems, etc., because they have to be seamless, because information has to connect. And the third is, then we bring in the tech partners. We’ve also brought in talent internally sometimes through consultants or full-time people who kind of are integrators. They may not be domain experts completely, but they also understand technology, and they form a part of the team as well, and they sit in and listen. But the critical ingredient is leadership.
So, let me explain that. As we have these meetings, about three or four of my senior leaders, we sit in and listen in every session. It could be a use case session, where we are talking about the customer-facing use cases — the issue, the challenges from a customer perspective. There could be another session, where we are talking to a tech partner. And as we do this, what happens is, there’s a learning that happens as you go along. And it’s very important. I cannot underscore how important this learning is for leadership. … The leadership may not know — for instance, I’m not an AI expert, but I need to know, how will it work? What are the limitations? How will it connect to the use case? I need to understand that. At the same time, I may not be a complete domain expert, but I need to be able to understand the use case well, so the center of all this is, there should be a core group of leaders who are kind of constantly connecting the dots and taking help from the extended team of experts.
Shervin Khodabandeh: That’s very, very important; the integration of that team into a cohesive, single-purpose-focused team has to happen through real hands-on leadership involvement. And you can’t just delegate that, you’re saying, to just anybody. You’re saying senior leaders and mid-managers have to be intimately involved in the fate of these kinds of opportunities.
Ranjeet Banerjee: Exactly. I mean, if you think of this as a whole new avenue for innovation, value creation, value capture, you have to have senior leadership involved. This is also a learning process for senior leadership. And what it also helps is, senior leadership can make resources available. You start seeing the structural impact of these on the organization, what kind of talent you want to bring in. It’s not just another activity. You have to think of this as, how does this transform the way we operate, our business model, the way our customer satisfaction approach is, and everything?
Sam Ransbotham: This reminds me of Amit Shah at 1-800-Flowers. And there was a big theme there about democratizing and getting more and more people aware of the technologies so that they could apply them as well. Again, that’s another theme that seems to be coming out in many of the people we talked to.
So, Ranjeet, what are you excited about? What’s next? What’s the cool new thing that Cold Chain’s going to do or that you think is exciting in one way or the other? Technology-wise or process-wise, what’s fun and exciting?
Ranjeet Banerjee: I think this whole ability to provide solutions that deliver assurance. I like calling it “from plant to patient or recipient” — the plant being the manufacturer of a life science company, all the way to the recipient or the patient. But to me, it’s going to be pretty exciting and a whole new way to improve patient safety, satisfaction. And I think as we do this, we’ll come across new ideas as well of what we can do. As an example, I’ll give you some of the things we are thinking of. We can do design optimization. We can come up with products that make more sense, and we can also give recommendations on which product to use depending on what drug or pharmaceutical, which route, which time of the year. I mean, you can see this going in many directions, where you are using data and technology to create a whole new set of values.
Shervin Khodabandeh: Ranjeet, before joining the company and bringing some of these new technologies in, there was a way of working that the company had. I’m interested in what your views are or what, I guess, transformations or changes have happened in KPIs and metrics, and what’s important. I mean, you talked about, in quality assurance itself and customer satisfaction itself, new values and new measures that are being introduced. So have there been new KPIs or new metrics that have been introduced into the company to look at the efficacy of what’s happening?
Ranjeet Banerjee: I guess one of the things that we have been talking about over the last one year is this whole concept of, how do we provide comprehensive solutions that create value, as opposed to a product? So that’s the discussion we have been having. If you tie that in with “What are the big needs out there, what technologies exist to address the needs, and how do we then provide comprehensive solutions?” When you talk about comprehensive solutions, you get into product, but then you quickly go beyond products and services to data, to different types of customer satisfaction approaches. … You go from one dimension of innovation, which is product focused, to multiple dimensions of innovation that you could do. CCT as a company has got very talented people, very strong roots in its thermal design capabilities, testing, validation. I think [in] the last 12 months, our conversation has been more around, how do you translate all those core capabilities that this company has built over more than 50 years into providing these comprehensive solutions that create true value?
Sam Ransbotham: Yeah, that comprehensive word is really coming out strong, both here and, Shervin, I feel like we’re seeing a theme of that. So many people who are doing well with these technologies are finding ways that they’re working more holistically. Yes, they can use them to pick up on one part of the organization and improve one part of the organization, but lots of folks are starting to think about the big picture and how all these connect. You hear trite things about removing silos and stuff, but I’m starting to see some legs to that, perhaps.
Shervin Khodabandeh: That’s very true. Ranjeet, what’s been your biggest positive surprise as you’ve brought these changes in and you’ve brought in more advanced technologies to address these opportunities?
Ranjeet Banerjee: I think the team has embraced it. I really mean that. I think we have an extremely talented, passionate team at CCT, a lot of domain experts. I get a lot of energy from them, and they can help me connect the dots and make this bigger. We also had tremendous support from our customers and other partners. So that’s kind of the approach we are taking. And I think, to me, I really give a lot of credit to our team here, which is really stellar.
Sam Ransbotham: Ranjeet, great talking with you. Your work at Cold Chain really shows how pervasive artificial intelligence can be. The connection between cold chain and AI isn’t obvious at first, but it makes complete sense in retrospect. You’re not myopically moving material from one place to another, but you’re creating a cohesive, holistic process. Thank you for taking the time to talk with us. We’ve really enjoyed it.
Ranjeet Banerjee: Likewise, Sam. And thanks to both you and Shervin. It was a great discussion. I enjoyed it as well.
Sam Ransbotham: On our next episode, our guest is Gerri Martin-Flickinger, former executive vice president and chief technology officer at Starbucks. Please join us.
Allison Ryder: Thanks for listening to Me, Myself, and AI. We believe, like you, that the conversation about AI implementation doesn’t start and stop with this podcast. That’s why we’ve created a group on LinkedIn, specifically for leaders like you. It’s called AI for Leaders, and if you join us, you can chat with show creators and hosts, ask your own questions, share insights, and gain access to valuable resources about AI implementation from MIT SMR and BCG. You can access it by visiting mitsmr.com/AIforLeaders. We’ll put that link in the show notes, and we hope to see you there.