Pioneers of Cognitive Automation Panel at the Cognitive Automation Summit

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Panel of Senior Executives
34m
Pioneers of Cognitive Automation Panel at the Cognitive Automation Summit

4 Top Innovators discuss the impact of cognitive automation on their global business at CAS 2020.

Alessandro de Luca of Merck Group, Biswaranjan Sen of Unilever, Saqib Mehmood of RB, and Neil Ackerman from Johnson & Johnson - four exceptional executives who are the true pioneers of Cognitive Automation share how cognitive automation transformed their businesses.

The Future of Decisions Will Require Cognitive Automation

Fred Laluyaux:

I want to bring four very special guests to this conversation. To be a pioneer, you not only have to understand early on the value of a specific innovation, but also have the passion, the leadership, and the relentless drive to convince others to follow you as you implement it. These gentlemen have all these qualities. They understood before most that they had to digitize entire decision making processes at scale, if they wanted to improve their whole speed, and reach a whole new level of agility and performance. I say a whole speed, because think about how foiling has changed sailing forever. Boats used to cut through water to win races. Size and [the] whole design really mattered. Now boats are foiling out of the water. The whole is just a small factor in a larger orchestrated system.

What does it take to get the entire boat flying up, out, and on top of the water. The entire system has to be balanced, responsive, and the designers have to be able to model what happens everywhere in the system, so nothing breaks while achieving maximum speed. It takes data and the ability to act on that data. That's agility. That's how you win today. It's a whole new race. Changes like these are not just one off. You can't cut a new sail and think you'll have a new boat. The concept of transformation has to be clear and distributed across all teams and with them working perpetually together. You can take the best of what you have, experienced design skills, and make them into something more powerful than you ever imagined. This kind of breakthrough takes real vision and leadership, and this is a wonderful segue into our next panel. So before we start gentlemen, may I ask you to briefly introduce yourselves? We'll start with you, Alessandro from Geneva. I believe.

Alessandro De Luca:

Absolutely. Thanks a lot for inviting me, Fred, [it] has been a pleasure. My name is Alessandro De Luca, and I work in Merck as CIO of [the] healthcare sector.

Fred Laluyaux:

Thank you. Welcome Alessandro. [Coming] up on the list I see Saqib here in Amsterdam. Saqib, welcome.

Saqib Mehmood:

Hi. Hi Fred. Hi everyone. Thank you for inviting me. I'm the SVP for business solutions and insights for Reckitt Benckiser. I look after the hygiene division business unit. Responsible really for data and digital transformation within the business unit.

Fred Laluyaux:

Great. So good to have you here my friend, thank you. Neil sitting in Israel. It's late for you. Thank you for joining us late. How are you?

Neil Ackerman:

Terrific. Thank you for having me Fred and thank you to my colleagues on the phone here and everyone listening. I really appreciate it. I head up advanced technologies for Johnson and Johnson. My name is Neil Ackerman and I [head] up [the] global supply chain. I'm a global expat living in Tel Aviv.

Fred Laluyaux:

Last but certainly not least in London, Bish, welcome as well.

Biswaranjan Sen:

Hi, I'm Bish Sen. I'm leading the supply chain for beauty and personal care, and the supply chain transformation for Unilever.

Fred Laluyaux:

All right, so let's get started. Let's dive in guys. So happy to have you, as I said, I wish I could have you in person around the table, but the circumstances are what they are. We are all in different locations today, we will fix that next time.

You're the pioneers of cognitive automation, as I said. Can you talk about the context that drove you in your respective organizations to implement such pioneering approaches in technology? Alessandro I'll start with you because you use the, or you cornered, I don't know if you use or cornered the expression, the self-driving supply chain in an article in the wall street journal in 2016. So I want to hear from you about your vision there and what drove Merck, and what drove you, to push these kinds of technologies and approaches.

Alessandro De Luca:

Yeah, absolutely. Thanks for asking. Indeed when we started was 2016. First of all, look ages ago because a lot of things have changed in any area in the technological space not only. Anyways when we started to work together, and when we started Merck to develop this vision, really we were thinking about [a] self-driving supply chain. A name that sounded sexy at that time. But in practicality [it] meant very simple things. It meant that, I mean, supply chain is a simple animal. Allow me the word, it's all about balancing demand with supply. So what we meant with a self driving supply chain was really trying to get the demand automatically predicted from the system, no need {for] human intervention. And that would have been a combination of forecasting based on the latest machine [learning], and predicted demand base around POS, and customer signal, real world evidence. So really gathering this demand [is] automatic, no human intervention, no need for touch or slight modification.

And then the vision was that, well, let's get synchronize it with supply and let's get supply in such a way that we'll develop a sort of control tower with real time synchronization. That would dictate the takt time of the production planning. And that eventually would produce products that would have a personalized delivery to every single HCP, or every single patient around the world. So that was really the vision. Now a lot of these things became a commodity. I mean, when I looked at my colleagues and peer control tower as a commodity, everybody has it. Leveraging machine learning, probably everybody has it. And that's why the journey continue. And that first phase of cell driving by itself, the name [connotes] was really an automated supply chain. Now we are in the process of augmenting our supply chain, and I guess we'll discuss later on together. And that's been a really fantastic journey.

But when people ask me, hey, this has been a magnificent technological journey. I always repeat it. No, this is not a technology journey. This is a journey of people in which [the] skillset had to be changed [and the] mindset had to be really completely shifted. This is a journey of processes in which we really had to optimize the processes and [run] in a different way. And this is a journey of data really to become a data driven company, and the data driven supply chain for our patients. So that [to] summarize, if you want the idea that we go to the concept and where we are today.

Fred Laluyaux:

Excellent. No, that's really good insight. So Neil, Neil same question. We go back a few years. What were the drivers for you and your colleagues to actually push cognitive automation inside such a large organization, as Johnson and Johnson. Talk to us about that, please.

Neil Ackerman:

I loved what Alessandro just said, and to add to that the biggest drivers, so we have at J & J is delivering on the high expectations of our customers. So this has been a mantra that we have. We know that our customers and patients want great, fast, accurate, information. And when we think about driving our implementation of cognitive automation, we always think about [what the] customers want end to end. And what would be accurate and smart actions that we could take. And when you reduce the friction and you bring a wonderful process, such as cognitive automation, that brings value to customers, then we all win. And that's how we think about pioneering cognitive automation Fred.

Fred Laluyaux:

Thank you, Neil. No, really, really good insight. I'll turn to Bish and really same question. I'm trying to get a bit of the context of what drove you again. We've been working with you Bish for a few years now, pioneering, and pushing the technology and the approach, the methodology of cognitive automation. But talk about the driver Bish, what's been driving you, and the team to deploy such breakthrough technology and approach to your supply chain.

Biswaranjan Sen:

Thanks Fred. So look, we didn't start off on our technology journey and pretty similar to what Neil just said. I think for us it was about recognizing the fact that as a company and as an industry, we are going through a massive disruption. It's an industry that's been built on mass distribution, mass production, and mass communication. All three drivers have been disrupted. As we start heading into the new future, the question is, how do you deal with it? Everybody talks about who covers, how do you deal with it? And one of the first things you realized is that starting from our processes to our tech stack, we needed to look at it more holistically. So we started off actually on a journey to look at what [the processes should be]? What should the tech stack be? And on that journey, we came into a zone where we said, we are rapidly reaching a limit where the human mind can no longer cope with the sheer volume of calculations, or the sheer volume of analytics. That needs to be done.

We said if you embark on this journey, starting from the human being in the loop, to the human being on the loop, you're taking the human out of the loop. What does that journey require? And that is how we have been able to replicate the human mind's way of thinking. Led us into the zone of cognitive automation. So [the] short answer to your question is it's been a journey where we've been trying to see how you elevate the quality of human endeavor to deal with things where there's even no pattern, and focus on those and leave the more predictable stuff to machines.

Fred Laluyaux:

Awesome. Fantastic to hear that. Thank you Bish. Saqib same question for you. What was the main driver for you and your team at RB to push cognitive automation? Again, first call you and I, it goes back almost like three years I believe when we were really, right after we announced the division for the self driving enterprise. So what was the driver? What were you trying to achieve?

Saqib Mehmood:

I think for us, it was really about the purpose of what we were trying to solve. We didn't start out from an AI or a tech problem, which I think we really would. We really started from a problem of consumer access. We started from a problem of how do we improve supply chain, to improve the service for our consumers, and the fight for access. And this was really the whole driver [behind] which we came up with eight or nine areas within our business, where we said that if you really transform this using data, as one of our area[s], as key enablers, this has a big [price].

And I think this is extremely important that we don't start from an AI and a tech starting point, because that really has a big traction within the organization. So for us, it was only about how do we transform our brands and how do we provide our consumers with the right access levels and the right service. And that is where we started.

And I think the other thing which we did initially, which was extremely important, was not to make this into a tech business case. We really tried to make this into big transformational areas within the business, which we thought would really stand out. Because if you talk about a million, two million, no one wants to get out of bed. It's only when you can get the top management to be brought into multimillion dollar transformational value creation capabilities, using data. And I think that was extremely important for us to make sure that we link back our brands and what we are trying to achieve [with] big transformational areas and value creation within the company, which was opportunity left on the table, if you didn't go after this. And the third one that should [be] a drill, because if you start with this huge mantra, I think the biggest challenge that you have in the organization is half the people don't even understand what you're talking about. Because AI and data are great digital buzzwords, but really, people aren't able to connect what that means.

And what we try to do is then to take it a bit micro. So from the macro vision, we chose [the] US for example, as one of our pilot sites. And we worked with your team to really bring this to life, to be able to show to the organization that this is really possible. And it was amazing. I mean, you were [in] close touch with the supply chain director, and how she responded and transformed into someone who became the biggest champion for us in our organization. I think that [it] is extremely important that you have to take people on the journey, but you have to bring it to reality.

Fred Laluyaux:

Thank you. Thank you, Saqib. Great perspective. Next question I'll open up, maybe I'll direct initially to you Bish, but please guys jump in and I know the audio can be a little bit tricky, but we'll try to make it work, because I'd love to hear everyone's perspective on that question. But Bish, I know you have a specific point of view on agility. So the theme of the conference today really is redefining agility with cognitive automation. Can you share your perspective on this? How have cognitive automation and to an extent Aera has enabled your company to become more agile? What's your perspective on this?

Biswaranjan Sen:

So, first of all, I have been an operating planner in my life at some point in time. And when I did planning at that point in time, the holy grail was accuracy. And as planners, we always tried to be more accurate. One of the things we realized [is] that given the volatility in the environment it's very difficult to be accurate. And therefore the question was, if one could change the clock speed of organization in terms of the speed with which we take decisions, and the speed with which we recognize a weak signal from the shelf. The lead time between recognizing that weak signal and taking a decision, and the lead time between taking that decision and executing it. That is how we wanted to define agility. And as you start getting into a zone where agility basically takes over, or agility trumps forecasting, as we say, agility trumps accuracy, it drives us into a zone where the human capacity becomes [a] bottleneck for being able to make decisions.

It might be very rule bound decisions, it's not as if it's the very discretion of your decision. But it's the human capacity [that] becomes a bottleneck, [taking] those decisions at speed. And therefore the unlock comes out of asking the question, saying, what is it that is rule bound and can be, where can you take the human out of the loop, and bring the machine in to take the decisions? And that's how we ventured down the track with you guys in terms of what decisions [we can] automate. And for me, one of the things I'm very passionate about and I keep chasing my teams is, I believe that the future is about converting dashboards into logs. So our dashboard [is] a representation of information that, based on which a human being makes a decision. A log is when the machine has taken a decision, the human being can go back and audit it. And that to me, is a big shift that helped me, seeing that play out.

Fred Laluyaux:

We just got two really good nuggets here, right? We've got agility, trumps accuracy. And then we've got transforming dashboards into logs. Love this. Who wants to jump in, Alessandro, do you transform [the] dashboard into logs?

Alessandro De Luca:

Wow, that's a great statement. I love it. And I was really taking notes because I mean, absolutely spot on. I would say to compliment that, is that agility just to use another metaphor, for us has been really, I mean, let's put it in a different way. The fact that we implement cognitive automation, the fact that we could rely on a single source of truth, by the way the intelligent single source of truth, enable[s] us to really work in [an] agile way. It was a springboard to use a nice word, to the agility. Because before, I mean, yes, we have this agility mindset or whatever, but a lot of wasted time resources, we're looking for information, looking for data, exactly to your point before [we were] looking about, hey that decision cannot be taken. I don't have enough data. Now with this cognitive automation, adding the data accessible anytime, anywhere, single source of truth is really the fundament. Then from that, you can really work agile. So for me, it's a fantastic empowerment for the GVT. That's why I love the concept. Agility with cognitive automation. That's what's made the difference.

Fred Laluyaux:

I see Neil is nodding up there on the screen. Neil, jump in.

Neil Ackerman:

We have these inputs, and the inputs will drive our outputs. And so very often the way we release, we're thinking about it and adding onto what my friends on this call said, the aggregation of these inputs leads to a desired output. And over time, we can develop a strong performance agility index, and we have been doing that. Where, as you become more effective, you can raise the bar, and you can determine based on this index, what are the most important inputs that actually drove the results you were looking for? And by doing this, we empower more of our employees, of course, more use of the Aera technology, to partner humans and machines together to get the right inputs, to greet the outputs, to then raise the bar. And I just loved what everyone else said. And I just wanted to add that, that's how we kind of measure it over here.

Fred Laluyaux:

So I'll move to Saqid. First of all, do you want to react to that point of agility, or I've got a question for you.

Saqib Mehmood:

I think what agility really gives you as an organization [is] also resilien[ce]. And I think that's an extremely important point because our employees, our shareholders, our customers, reward us for being able to deliver day in and day out with a specific expectation that they have. And I think once you have that agility within your organization, and it's not just supply chain, but supply chain, sales, market. And you can use data to react to those situations as consumer[s] and employees and the environment is changing. It allows you to meet expectations. And I think this is really an extremely important point. And I love the example, or the analogy of having logs, because that is what really drives a corporate brain within the organization.

Fred Laluyaux:

Yeah.

Saqib Mehmood:

I think today the biggest challenge that we have is that these logs are really in people's mind[s]. They read the dashboards, and they make certain decisions, but you don't know what those decisions are because they're not recorded anywhere.

And as people come and go, these decisions are lost and the corporate knowledge is lost. And I think the biggest power that we saw of how you could bring error into an organization was to build a corporate brain. Was to maintain all these logs, where it could be referred in, and as people come in and go out of the organization, they enhanced these logs. They enhance the decision making power of the organization. A new person who comes in really gets all the benefit[s] of the previous smart people who [make] good decisions that have been able to. So I think this is really where you start [seeing very] resilient long term implications of organization and decision making within the business.

Fred Laluyaux:

You're jumping in right there to my next question which I was going to direct to you. Which is the global pandemic, right, has undeniably demonstrated that supply chain resilience means agility. Can you discuss how cognitive automation has helped you specifically during the pandemic? I mean, you, so at RB, the demand for hand sanitizers and home cleaning products, just spiking overnight. So do you want to stay with you for a minute Saqib, we got a good audio with you right now. Talk a little bit about how cognitive automation allowed that resilience during that crisis, or not. What was the situation with you guys?

Saqib Mehmood:

Yeah, I think it's very interesting because what we've seen and the company I think is really unprecedented. And I think this is not just us. I think all companies have been through a similar kind of a situation where you could clearly see that a lot of things that supply chain, or marketeers, or brand managers used to do just doesn't apply for [the] future because the trends have changed. And hence it required us to react in, I would say, it was a two spoke way of how we started to react [to] the situation.

The first one, which I think because we had, and [the] US is one of our biggest markets, and I think with our brands, we were already relevant in the space of the challenges that were being brought in by COVID. The first thing for us was to make sure that we had reliable data available. And I think NRA helped us because it's not about just your ERP system. It's about data, which is lying in 15 different places. And I think what we had done in some of the previous engagements with Aera was really how do we bring a single source of truth within the organization? And we had separate different systems that should have already been connected together.

I think having that kind of information at your fingertips when you need it [in a] crisis, really starts to bring up a true new value, which is that you can make decisions on the fly. You can start to, because the real challenge for us [is] to make sure that not even one minute of our capacity goes unutilized because that could be used to feed into an unmet consumer need or a consumer who really needed our products. And hence we needed to make sure that every contract manufacturing, our own side manufacturing, we had a great visibility of what's coming in, what's going out, what's the demand. And how do you make sure that you start to really shape that space?

And I think this is where Aera has really helped us in terms of not just an ERP lens, but making a network of data, which our ecosystem holds within the supply chain to really help. And I think the other piece which really helped us also is we were not just focused on this. We had to make sure that we could make a rule-based operation for other parts of our business, which was not really impacted. We still followed the same kind of pattern so that the demand planners, and supply chain could really focus on where they needed to focus. So we tried to bring a lot of automation, a rule-based operation and other parts of our brands and business, [which could] take away the time from the demand planners to work on something which was far more strategic and compelling for the crisis at hand.

Fred Laluyaux:

Great. No, thank you so much. Yeah. So the cognitive data layer collecting the data from all the different transactional and planning tools in feeding the brain for all base automation was very helpful. Is that your perspective Bish or Alessandro? Maybe Bish should go first.

Biswaranjan Sen:

Yeah. So very similar to what Saqib said. I think the first part of it was I think the cognitive data layer did make a big difference in terms of how we managed to get the whole, holistic set of scenarios played out using the graph database tool that you and your team built for us.

I think the second thing that worked for us, was the fact that during the pandemic, one of the things we needed to do was to change, I refer to the clock speed, change the cycles, the business cycle. So instead of running a four week SNLP cycle that was focused [on] studying the south, we had to pivot to a one week SNLP cycle that focused four weeks off.

And that shift was enabled by the cognitive applications that we got in. And it was, it would have been humanly impossible to do that. To move to a weekly cycle with a four week horizon would have been absolutely impossible had we not had the cognitive. My dream is to move towards a three day cycle for at least the key skills. And that's the journey that I think the cognitive applications have today.

Fred Laluyaux:

Three days, that's a new one. I didn't know about that one. Alessandro quick thoughts on complimenting what Saqib and Bish said, maybe from your pharma perspective, I don't know, on how it helps.

Alessandro De Luca:

Absolutely. I mean, it dramatically helped. I could not think, another crisis of this magnitude without having real time information, that [is] what we go through, the cognitive automation, facility to access the data to processes. I mean, to Bish[’s] point would be impossible with human[s]. Things were changing in us, in pharma, like everybody in the industry, they were changing by the hour. Supplier shutting down, logistics being blocked, and so on and so forth. So the only way to present this information was really through this automation and cognitive and laying of data that we could use for the data layer. And this, I mean, I definitely have to congratulate my colleague in supply chain, Marcus Heuber. He did a fantastic job really to maintain this top-notch IBT, that again, to Bish point shorten[ed] the cycle because we've all been running in much shorter cycles. Impossible to do manually or with legacy processes of before.

Fred Laluyaux:

Awesome. Neil, [the] next question will be for you then. Around value. Right? So the question that everybody's probably wondering [is] why we talk about cognitive automation. We talk about a single data layer, we talk about a brain that's automating and augmenting decisions. I know you've done a lot of work on the value. How do you measure the value that's generated by cognitive automation at J & J? How did you measure it? How did you make it tangible and define success?

Neil Ackerman:

So the first step that we did for measuring the value was we of course, started with our customers and got their feedback and their results. And customers always told us the same three typical things. They didn't wake up in the morning and say, I want to pay a lot of money. So customers and consumers told us they wanted a fair price. They didn't wake up and say, we want [fewer] options. So they always wanted more selection. And they never woke up and said, please, we want it to take 10 days to get to us. And we would like to have no idea of visibility. They don't ask that. They want visibility. They want more.

And so, as some of you know, we focused a lot on available to promise, and capable to promise, to improve accuracy for delivery to different customers of ours. And, you know Fred, we measured customer service levels, but improved in stock rates. But I can tell you what was the biggest thing; we did not cancel surgeries for patients because we knew when the items were going to arrive and therefore it was a better plan. And when you can get to that 90 plus percent accuracy, your end patient is happy because their convenience was there. They were there, the right item was there. So the selection was there. And of course we think it was a fair price. And so, as a result, when you have these reliable processes, we believe that's how you win. And so that's how we measured our value. And ultimately when the patient walked out and it was a successful surgery, and that was over 90% of the time, we knew we had a winner. And that's how we did it.

Fred Laluyaux:

That's awesome. Yeah, no, that's fantastic. We're going to be running out of time soon. But I'll wrap it up with my last question for you. You have been working with us for the last few years now. The pioneer is allowing us to innovate, to build the platform. You've been very patient. Thank you. What advice do you have for others who are just starting [on] this journey right now? What would you say to them? What's [one piece of] advice? I know you guys will give plenty of advice, but just pick one. What would be the one advice? I will start with you Saqib. I'm sure it's going to be interesting.

Saqib Mehmood:

Yeah. For me, my personal belief is that this is a 90 10 journey. It's 10% technology, it's 90% change management. And I think you have to start, you have to be the driver of change. You have to inspire people at times it will be difficult, but it is going to be a change management because that's really where it all starts. Don't make this a tech project. I think you will [rarely] be able to win if you make this a tech project. It really needs to start with a big change. The change needs to have a vision. It needs to have a purpose. And when you can inspire this within your business, your brand, your consumers, and you can make a deep rooted into the centric region and purpose within your organization, and you can drive this change, then technology will automatically follow. But don't lose sight of it.

Fred Laluyaux:

Thank you. Alessandro, would you agree? What advice would you give? I know you're talking to a lot of people about cognitive automation.

Alessandro De Luca:

No, absolutely. I fully agree with what's being said. And I would say keep the customer in focus for us or the patient, like also Neil said. There's a change [in] management of people and it's not about technology. And then communicate, communicate, communicate. It's a fantastic journey to be done together across all the functions.

Fred Laluyaux:

Neil, you're nodding.

Neil Ackerman:

I love that, “communicate”. I would say two things. When people have asked me. One, please take a use case, focus on it. Don't boil the whole thing. Just focus on it and win on that use case. Doing nothing is not an option. And you really have to, really get that in your head. And that's really hard because a lot of people like to, just not change, but it's not an option.

And the last thing I tell people is, especially the supply chain folks, don't think of yourself as a cost center. Take yourself as a revenue generating machine. Something that could really change the trajectory, or pioneer healthcare. And that's how I try to position it in the company. And so far, so good. We'll see what tomorrow brings.

Fred Laluyaux:

Thank you, Neil. Bish , what advice do you give internally, externally?

Biswaranjan Sen:

I agree with all that has been said by Saqib, Neil, and Alessandro. I think you have to start with a problem that is consumer or customer centric in our line of business, and address it holistically. So I think a large chunk of it has to be about redesigning the processes, redesigning the skill sets that are required. I think technology is very important as an enabler. It's crucial, it's a magic ingredient, it's the secret sauce. But it's not the only thing. So if I were to walk in saying, just because I signed up for a cognitive automation project with Aera, life's going to be different three months later. Absolutely not. So It is the magic ingredient that can unlock great results, but it requires many other things to change around it.

Fred Laluyaux:

I appreciate that completely. I wish we had more time, gentlemen. I want to ask you about -  what level are you on the journey of cognitive automation, your respective roadmaps, but we'll have plenty of opportunities to talk. Hopefully we'll be able to do that in person soon. From the bottom of our heart, I want to thank you on behalf of the entire Aera team for your partnership over the last few years. As I said before, I don't think we would be where we are without your vision, your energy, and your leadership. So thank you so much. Have a great rest of the evening. Of course most of you are on the other side of the Atlantic. And thank you for taking the time to [speak] with us today.


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Panel of Senior Executives
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Alessandro De Luca, Biswaranjan Sen, Saqib Mehmood & Neil Ackerman

Published:
September 20, 2020
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