Why Digitalization is a Fundamental Business Imperative for the Life Sciences Supply Chain

Flavio Aliberti: Let's start over here. I come from Switzerland. I just read a report that was saying that in 2023, we had 1,000 essential drugs unobtainable, although they were covered in insurance. The problem of bottlenecking supply chain hits everybody everywhere. It's something that is really present.

The idea of looking why there are these manufacturing shutdown, why there is this disruption at the moment in where we are balancing, it's something that touches us not only professionally, but as well, personally.

In Genpact, we gave priority to this. Giving you a snapshot of what Genpact is. Genpact was born in 2005 as a spinoff of General Electrics. We focused on growth over the years. Life science is one of the key industries where we think we can provide a huge value in the role of business partners.

From that perspective, there is one thing that makes us different and puts us in that spotlight. We do not look only on the technology side, we look at the consultation of organization, technology, process, and data. We do believe that it's very important to understand the intersect and try to basically evaluate the maturity of all these different aspects in order to reach a solution.

This is even more valuable in a moment in which we're living a technology leap, where it looks like the technology with this glittering is able to produce that value that we are expecting, and then we get stuck. Let's look into details what that means.

Basically, when you look at the intersection, you're looking at the technical operating model of the organization. The technical operating model is where you're finding, defining, and understanding how you can connect your capabilities, how you can make informed decisions by creating innovation and collaboration.

Collaboration and innovation are two words that I'm going to repeat a few times in this presentation, because they're the core of what we're going to look and do more in the future. I will tell you a little bit more after.

What is so important is to look at technology, as well how it's impacting the organization. Sometimes it's said that the best technology from an IT standpoint is one that is not used because it doesn't generate tickets. That's a bit of the thing that we need to avoid.

We need to be sure that the technology is implemented in the organization in a way that produces value before it's adopted and accepted. This is a completely different approach, but why it is important to work and adjust the technical operating model.

We are living in a huge discontinuity at the moment. There are several aspects from a strategy standpoint that are stepping in our pipeline. In a way, the pandemic has explained and has shown us that these things are real. We can't keep looking at the future with the model that we had in the past because there are changes that are happening.

They are basically impacting the way that we manage all the different timelines, all the different horizons. New technologies are coming there. Think about the idea of mRNA before the COVID and after the COVID. How many organizations were investing in there?

How many organizations were looking at their supply chain in order to scale up and produce that technology, which had a completely different setup compared to API or biologics? Think about it, new approvals, the way that strategy goal changed, the rate on M&A. M&A is another thing that I follow a lot, is very high on our side.

You can be in a situation where you're running your exercise on one organization and then you get acquired or acquire a new organization, your strategic goal changes. How flexible are you in your supply chain in understanding the impact? 75 percent of the M&A deals fail in giving the expected value.

Why? Because when you get on the real things running, the supply chain is patched, the supply chain is not harmonized, and this generates additional problems. It's important to understand that the flexibility and the resilience of the technical operating model is something that we need to embed in our processes everywhere.

To do that, we need to have a much better understanding of who is doing what. This is something that sometimes we see struggling a lot because this is the core of the cross operation of the organization. In many situations, we see the middle horizon as the domain of the supply chain.

We see technology, we have very strong partner at technology that are providing a huge value on the middle horizon. Then when we move toward the short term where, let's say, it becomes a little bit more blurry, the overlap between supply chain and other functions, S&B procurement, S&B operation, we tend to stretch technology.

We don't see that there is a specific different focus that needs to be followed on that side. The same applies on the long term. On the long term, we think and keep to looking at adapting the supply chain in order to reach the strategic goal that we have seen before, but adapting is not the scope. The scope should be innovate, should be to look from a completely different perspective.

Now, in order to achieve this focalization of different horizons, we need to have a common layer that helps us to communicate, that helps the function to communicate. There is as well an additional thing, a lot has changed in the last years. If you look at the situation 20 years ago, more and more, the focus was internal to the organization.

The big boom of ERP that we had in the year 2000 was related to the fact that we want to have functions communicate to each other. Now, although we have reached that in a way, every organization has an ERP, we are in a situation where, actually, we are depending more and more from the external providers.

That means that even if we reach high level of accuracy in understanding what is inside, we are not able to communicate exactly our needs externally, we are not able to get information from the terms of value and volume from outside into our organization, and therefore our decision processes that we were targeting before gets hampered.

What we did in Genpact is to focus a lot. We started with technical operating model in creating a control tower approach, which is a little bit different from what you can find in other technology. What is the difference? The difference is that if you scroll any control tower offering, most likely you will end up using an analogy to something that is close to a post office.

Something that is able to move package around in and out, tracking, and increasing the speed of that. According to us, if we really want to work around the technical operating model, if we really want to work around creating value for the ecosystem, not only for the organization, the approach should be more like a paid traffic control tower.

Something that is able not only to control the safe landing and takeoff of each single document flow, you can go from a clinical trial to any single SKU that is moved around, but is able as well to communicate the value around.

It has a phraseology that is able to connect your traffic. It gives you basically that visibility that will increase you, not only internally, but as well externally, the capability of improving your accuracy. This is where we do see the approach.

We need to be able to have solutions from a control standpoint that are able to connect what is coming, the changes that are coming from the market, from the information that are internal to the organization, and grant a level of accuracy that leverages both networks.

If we use this approach, where basically we break the silos, and this is something that I've heard a lot about it, we talked about breaking the silos, talked about data. Most of these things are resonating, I think, with the other discussion we have seen, what kind of life cycle ecosystem we can conceive.

The idea is that we go in that direction, we are going to have more ecosystem reaction and less company-based reaction. There is no organization that is applying the forwarding approach that was in two centuries ago. Everybody now works together.

We need to create a new way of operating that gives us the opportunity to put a common factor, the information that we have for a better good, as TraceLink says, but as well to create new value and new different services.

The way that we see it, if you see, for instance, all these four different items, there is the opportunity to create a completely new set of services, where every single organization on any transaction, in a granular level, can add a little bit more and profit from that.

That profit is not only in terms of money, it's a profit in terms of service customer, making things more available, products more available, more accessible, more affordable. If you move ahead, all of this is possible only if we have a transactional network that gives the opportunity to connect all the single dots.

What we have done with our partnership is plugging our control tower on the MINT infrastructure with the idea of having a very fast controlled way. Exactly what happened with ERP basically 20 years ago just now happened at transactional level, at network level.

Basically, we are moving the concept from transactional system, which has created a huge boom in the way that we globally collaborate together, to transactional network, which is going to generate a completely new wave of value.

Any single flow of data and information that you have with any of the suppliers of your ecosystem can be an opportunity of creating value, creating value for yourself, creating value for the supplier, for your partner, creating value for the partners. We can do that in a controlled way. We can do it in a way that we can interoperate, and we have a very clear way of approaching this.

Now, the point that comes after -- you can go ahead -- is all good. We are life science and life science is always quite adverse to change. How can we basically scale this up? We questioned ourselves in the last month, and we decided to come up with a specific methodology that can address exactly this point. You need to start from what you have.

You have, as you're here, TraceLink. You have a network available. You know that it's valuable. It's an asset already there. For sure, you have on your table as well some hot topic, issues. You can decide the criteria, the last one you had just to test it, the one that is more burning for your specific partner, something that is hitting your KPI of your stakeholders.

You have issues that depend from outside, depend from some conditions and information that you're not getting. Give us a proof, and with this methodology, in 90 days, we are able to create basically a use case, we call it rapid start prototype, that helps you to pay back the value that you're putting in there. That is a little bit the better you're putting on the table.

With the demo of the technology, understanding what is the case, we can get one single specific case, and we can put it in place in a very short amount of time. We can do it for one simple reason, the asset is there.

TraceLink and MINT are live, have been live forever, so we know what we need to touch. We know how we can do it, and we can do it. Once we have that, we can assure scalability, and then we can move ahead. The first step is very important, and you need to be able to measure each single step you make.

Before concluding here, I want to give you another reading key of why it's important. We talked about data. We talked about AI. We talked about the importance of collaboration. I want to give you another perspective that I was thinking about it lately.

If we look at technology leaps that have happened in history -- and we were discussing before -- we have really seen them as something that are related to generating new content. You can start from Gutenberg printer, generating new books. In reality, what has changed is not that. What has changed is the collaboration, the ability to read, the ability of sharing information.

The boom that we have had even in science, has been strongly related to the fact that people could read what the others were doing. Collaboration was the real outcome. If you look at the Internet in 2000, we saw a huge bubble related to creating new content, new sites, and so on. The real boom has happened with social media, with the idea of generating new way of collaborating.
My question to you is, why do you think with AI it's going to be different? AI, at the moment, is all about generating new content, facilitating that. What we can really see and foresee is that in few years, probably months, considering the speed, the point will become generating new way of collaborating.

This new way of collaborating will require as well an infrastructure that helps agents to collaborate together. We strongly believe that the slide you have seen before, the approach that we are providing with the control tower on top of the MINT is the way of granting that infrastructure that can help you to harvest value as well from AI approach.

To conclude, just to make it a little bit more on the topic, again, what we are bringing with our work is our experience on supply chain. We have as well in our firm people that are coming directly from the life science domain. This is because, again, we are bringing a business cut to what we do.

Our approach is modular and adaptable because we know that not everyone has the same Georgia, and specific in life science, there is a huge difference in the way that the stack is organized. You are very advanced on some areas, and there are some other areas that information are still unstructured, still probably on paper.

That's why it's important to recognize that and have an approach that does adjust to that. We bring best practice, which is something that we need to leverage more and more. The creation of new standards is absolutely relevant to collaborate and comprehend the idea of the phraseology that we saw in managing the air sky.

Again, the objective is not only flexibility, but it's flexibility and resilience together. We've looked at COVID, we have seen the approach. We have seen it from organization being able to produce a result, but then being hit back because they were not able to scale back. We've seen organizations that have not even been able to catch the opportunity.

It's a demand, and again, it's not something only from a professional standpoint, it's something that touches our life. It's even personal because when there are 1,000 different drugs that are unavailable in a very manufacturing pharma, manufacturing market like Switzerland, there is something that we need to do about it.

Moderator: Well, I'm going to start then, but please, by all means, this is your opportunity to ask questions. You talked about the slowness of the life sciences vertical. I've always said that life sciences moves lockstep at a snail's pace. No one wants to be too far ahead, but no one wants to be too far behind.

They're all measuring each other against the same set of scorecards. What are your thoughts about getting started? You talked about a rapid onboarding process. We heard from Shabir earlier this morning. How do you actually put this into practice?

Flavio: That's a great question. For me, the clear point is, and again, it comes from where the life science is, why life science has this behavior. We have seen in the past, in the history of life science, rush indirection, and after years, we have realized we're the wrong ones. There is always a peer control and checks. The compliance basically creates as well those barriers.

We have seen, and again, in the latest experience, that the more we share information, the easier it is to understand the value that this stuff can create in a safe manner. We didn't lose in safety, for instance, to find the right vaccines. We kept the safety principle even if we relaxed some of the principles in validating the new drugs.

At the same time, we were much faster than what we ever experienced in the past. We can't afford to have three billions for new drugs for the long run. We need to find new ways together. The thing that I can say is you don't want to be the first, but probably don't want to be as well the last. Everybody's looking in that direction.

We are having several discussions, and the discussions are all around, what are we going to do? What's going to happen on the long term? How can we increase our ability to predict? This is another thing that was coming out. One of the major criteria that you need to consider is that you need to adjust and you need to be able to react quick. That goes even beyond being proactive.

I'll tell you one example. Think about the 7th October. The 7th October, we had plans, forecasts with very high accuracy happening all over the world, but the world changed in one night and no one was able to understand what was there. What was the real approach there? Having predictive ML algorithm that we're able to understand what was going on.

Nobody in the world knew that this stuff was happening, or having the ability to quickly react, putting people together and coming out with alternative plan that could grant a potential new forecast, a potential new result. We live in a world where machines are going to help us quite a lot to organize us around the bell curve, understanding what is historical data, what we can do with it.

We are going to beat more and more from events on the tail, from events that are going to happen, that are going to be seldom, because they're working all together. Any disruption will hit each one. There is a need of flexibility that is absolutely required and is where to start.

Where are you are more rigid? What are the information that you are not able to manage and you are only guessing? This is where I will start because any flexibility you're adding in there, any information you are able to process quickly in that front is going to help you when the crisis will come.

Moderator: Thank you. We've got a taker.

Audience Member: Quick one. I saw that you are leveraging main solution as a code of basically your solution. Do you receive data from suppliers or any partners? Can you give me two or three lesson learns while you were integrating with MINT for those companies that are planning to use MINT in the future?

Flavio: The biggest thing that comes out that when you start to integrate information, you realize that basically some of the information you're relying in the past were wrong. There is a huge plus that comes in creating a much healthier environment from that perspective. This is something that the work and basically the visibility that we're creating is giving absolutely that level of advantage.

When you're managing unstructured information, you're not only creating a delay, in some cases, you're basing your decision when you roll them up on a level of, let's say, approximation that is much higher than you can get if you're at a granular level doing it.

The other things that come up is that the speed of integration is much faster than what we were programming at the beginning. We're not coming with a bold statement like 90 days, even simple nine months ago. We realized that by simply implementing, we will be able to produce immediately value, and there was another important value that was coming out.

The third thing, which is in our methodology, is the self-sufficiency of the approach. Basically, it becomes very tangible to understand the value of the things that you're doing, and that helps a lot as well to then fuel the journey forward.

There are elements that are very strategic and qualitative from that perspective, but they're very tangible in a very short amount of time, and then everybody can get their own lesson. The seamless of integration from a technology and structure standpoint is there, and has been a place played by Shabir. There was no challenge from their front.

The challenge was explaining, adapting, and convincing as well from their perspective that the data that were there were not the right one and they were not used in the right way. When you go over denial, you start to see a complete difference between catching up and expanding forward. That's why we're making that investment as well.

Audience Member: Miguel from Adelen. Several questions that are connected to each other. I assume that your teams are not only developing these algorithms on the TraceLink technology. How do you see the future for you? Are you going to go work more and more on this TraceLink technology, or do you plan to anyway keep having a mix of ways of working? If yes, then why?

That's my first question. The second one is more the onboarding you make to the customers. At some point, you want also the customers to be autonomous on growing this by themselves. That's also the spirit of the TraceLink concept. How do you manage that as a partner when you are engaging and proposing new solutions to the customers? How do you grow that competency on the customer side?

Flavio: On the first one, we have Kinaxis as well in the room, and they can testify that that's our approach.

We tend to define ourselves as technology agnostic, which means we don't want to develop technology ourselves, we want to partner with the technology that we believe are key and are going to be leader in the future and not only in the present, so that we can help them to bring our business insight.

Again, we start from the beginning. We are business partner. We are not technology implementers. What we do, and we collaborate with TraceLink, with Kinaxis, which is another example.

We can collaborate at strategy level as well to anticipate with our accelerator features that are going to come in the future in the technology so that the technology vendor does the technology vendor and we do what we do the best, which is basically adjusting and transforming the organization from a business standpoint so they can have a higher adoption and create more value.

That goes to your second question. You were right. They were connected to each other. In order to create value, we need to empower the edge. The entire model with AI, we go back on the same topic, it's going to come more and more. The entire model of adding centralized approach that develop and deliver things that are going to be used by others is going to change.

We're going to have more empowering power within the edge, and the technology is going to support that. The no code capabilities that we have seen today, apart some checks that we saw that were still a little bit scripting, are the things that we want to empower.

We have a strong change management practice that looks at the specific needs, can create trainings, can help in ramping up the situation. The major difference that we bring in, just to clear up the point, is that we do not see the go-live as the end of the journey. Actually, that's the start of the journey for us.

Why? Because in the core, in the deep, in our DNA, there is the BPO and the managed share service approach. We are owning in CPG one of the largest 4PL in the world. Our idea, and that's why we take information, even if again the customer keeps centralized and does not share the service, it's understanding what is the best practice there.

That best practice brings value to the entire industry. The best way to be right at the point when you go live is to work the journey in an incremental way since the beginning with the community that is going to grow.

One thing that we have seen, for instance, happening that has hampered very valuable implementation is that you implement with a team and then the team goes back to do other things or leaves the organization and you end up with a technology that then doesn't work.

It's not because the journey was not done in a certain way, it's just that you were moving a trolley uphill, then you stopped midway, and then you lose all the inertia. It's important to build a change management plan within your journey so that when you start, there is this level of excitement that brings in because you see the value coming in.

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