Opportunity, MIT SMR + BCG
EXCEPTIONAL “Full Pack Golden Knowledge Container”
This transportation and logistics company relies on AI to deliver COVID-19 vaccines safely and efficiently.
- 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.
ABOUT THE HOSTS
Ranjeet Banerjee, Cold Chain Technologies
Lessons learned, MIT SMR + BCG
Golden Knowledge (GK) Juice
- 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.
- CONTEXT: The Golden Knowledge Path ("GKPath") digital highway
- Opportunity, Discovering and exploiting the treasure of the digital age
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- g-f(2)260 The Big Picture of the Digital Age (5/4/2021), geniouxfacts, Alerts, Warnings and Relevant Lessons Learned Traveling at High Speed on GKPath.
Lessons learned, MIT SMR + BCG
Golden Knowledge (GK) Juice
- Ranjeet Banerjee: 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: 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.
- 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?”
- 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?’”
Some relevant characteristics of this "genioux fact"
- Category 2: The Big Picture of the Digital Age
- [genioux fact deduced or extracted from MIT SMR + BCG]
- This is a “genioux fact fast solution.”
- Tag Opportunities those travelling at high speed on GKPath
- Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
- Type of validity of the "genioux fact".
- Inherited from sources + Supported by the knowledge of one or more experts.
- Authors of the genioux fact
ABOUT THE AUTHORS
PhD with awarded honors in computer science in France
Fernando is the director of "genioux facts". He is the entrepreneur, researcher and professor who has a disruptive proposal in The Digital Age to improve the world and reduce poverty + ignorance + violence. A critical piece of the solution puzzle is "genioux facts". The Innovation Value of "genioux facts" is exceptional for individuals, companies and any kind of organization.
Key “genioux facts”
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