 As talking about the speakers, we have our first keynote speaker already on screen. Let me take the opportunity here to introduce him formally to all of you, most of you know him already. Mr. Deepak Aayir is here. He's the president of Mondaliz India's private limited. He's responsible for leading the business of Mondaliz International in this dynamic and emerging market. He's also part of the Asia Pacific Middle East and Africa leadership team of Mondaliz International. He has extensive experience in the FMCG space with close to 30 years of management experience spanning sales, marketing, franchise and general management. He will be speaking today on the topic of building a data and digital enterprise. So ladies and gentlemen, please put your virtual applause and let's welcome formally Mr. Deepak Aayir, president India Mondaliz International. A very warm welcome to you Mr. Aayir. Thank you so much. Thank you. Hello and good evening everybody. It's a pleasure to be talking to all of you and thank you Anurag and Priyanka for having me here today. Like Kaguya just said, I'll be sharing my thoughts today on building a data and digital enterprise. A good starting point would be to step back and ask the question, why? Why should you even think of building a data and a digital enterprise? If you take a closer look at what's happening around us, what's changing around us, we soon realize that there are tectonic shifts happening in consumer behavior. They are shopping online more and more. The retail landscape is changing. The decalmers and social commerce emerging thick and fast. And companies are using technology to revolutionize that manufacturing. All these still have serious implications on our business. Today, our businesses could have competitive advantages stemming from powerful brands or let's say expensive distribution networks or ability to manufacture complex products at scale or let's say housing the best talent and living in an enabling culture. I'm not saying any of this will vanish tomorrow, but data and digital could well emerge as a bigger competitive advantage, which could sort of reduce the shame on some of these. And hence it becomes imperative to build a business that is tech, data and digital enterprise. Now that brings us to the next question, how? Also be a more important one, since most of us including me, I'm sure, have struggled to get this going. But even if you got this going, we have struggled to ramp it up fast enough to keep pace with the rapid changes around us. The most experts and the best of reading material in this space will say, you need to build a digital culture. I'm sure you'll agree with me that this one digital culture will be as legulous as it gets. I'm sure there are various ways to do this to build in any organization. But I'll talk about something that's worth for us in one piece. The five things that are worth for us. One is looking for inspiration from outside. Two is it's a stop down process. So start from, start fixing a strong goal at the top. Think of putting in place a digital council. Start with destined learns. And finally, you'll need to reskill your teams, correct? So I think these are the five things. And let me spend a couple of minutes on each of them. So let's say look for looking for inspiration from outside. The best way to do this is to go on learning books. Think of learning from industries, companies, consultants who are more advanced in it, but yet not 10 or 20 years ahead of you. If you choose to connect with any company which is cutting edge or digital or too far ahead, you struggle like you struggle to get meaningful examples of patterns to actually inspire our first steps, our baby steps. We can never be inspired with cutting edge examples. In our case, visits to innovation centers of the systems are attending conferences organized by experts. And holding tech base with this throw startups actually helped us immensely. Whichever way, I mean, I'm sure you'll find your way to start a learning throw, but just started that would be my advice. The second one that I talked about is the process starts stop down and a strong tone on the top. It is hence imperative to get the leadership skill in the game, sign on to this value and lead it. In our case, my entire country leadership team started with two things. One, going on learning towards the inspiration together. And to each of us taking one clear objective on data or digital goals for you. That is not important how big or small the goal is, but you need to take one. And for God's sake, don't take one that says, you know, I'll automate data. But that's passing. We should have done that 10 years ago, but take something meaningful. It could be anything. It could be small. It could be large. The third thing you could do is think of putting in place a digital concept. We want to be from day one, but at a certain stage in the journey. Especially once the leaders have signed on to this journey. Now, ideally, it should be constituted with talent one level below the leadership team and top talent you have and surely folks who have an open mind, great learning agility and a willingness to collaborate seamlessly between functions, right? Now, each of these are very important. So it has to be a handpicked group of people, right? Over weeks and months, this council, give them the kind of visibility and attention that really stands out. That is when it starts becoming aspirational to get a seat on the table in this council, right? The first time around, you may not get the best team in play, but eventually you will. And in seating, the right thing is very important for the council to work. I shifting on to the fourth point I talked about. I talked about starting a test and learn small pilots, small projects, launching MVPs for minimal viable products, right? Some will work, some will fail, but keep it. I usually realize that to win, you need to still your teams with proper training programs, example, local, local. The example, OMC works online marketing certified professionals. These are great training programs. And you don't need to figure out which one right now, but when you get to the stage, you'll get to know. So that was the part on how. And now, let me also sort of pause for a minute to tell you that as you traverse this journey, there'll be quite a few pitfalls and a few conundrums. I'll talk about them, a few of them, but with the caveat, there is more confidence in this, right? So let me start with the first one that you already would have already debated in your minds or will be debating now or will. Sure, I start with the point in the CDO, achieve data or achieve digital also, but some companies have succeeded in this, many have failed. The fallacy here is that digital then becomes the bonus of the CDO and the CDO. The intrinsic assumption is that one is expecting the CDO to do the job of what the CDO and the leadership team can actually do better, which is inspiring the teams and their functions to adopt digital ways. Now, a Maverick CEO can surely do that, but others will fall back on the leadership team to do this and what worked for us, at least in one case, is a bunch of digital ambassadors, I call them digitally evangelists, the CEO and the leadership team, these are our digital ambassadors and they may happen. And another pitfall, let me talk about this, the stimulus question of costs and ROIs associated with digitizing a company. Now, here's my learning, don't go around looking for ROI too early in the game because they will not know how to do it. You don't even know what's going to come out of some of these experiments. Just get around to putting something out there at acceptable cost. Look at it as test and learn, you don't need to change the whole organization, ROIs will follow. Sometimes it will be a force multiplier that you have never imagined. The other one is this entire concept of failing fast. So I haven't come across a single value company who will start with an agenda or fail. But these words are very often misinterpreted, right? The right way to look at it is failure is okay. But what have you learned to put out something better? Failure is a part of the game. So we won't kill only for failure. But get us some success next time. And this is the right way to start looking at failures. And again, the other one that I would bring forward as a pitfall will be finding the best talent with the right skills and capabilities is going to be a challenge. Why? It's very simple because the best talent in data and digital space doesn't think you are the best company to work for. Rightfully so, because you're just starting the journey and in their minds, we are the target, right? So maybe you need to work with consultants to house these capabilities when you start the journey, maybe the great paternity and who might be happy freelancing a part of the time, data scientists get statisticians, etc. And there's one more pitfall that seems very important to keep in mind, which is about data governance. So as you start accumulating data, you need to be making the organization to organize it such that you manage diversity, you manage security. And this is where if you miss out enrolling the legal counsel in the leadership, learning towards right in the beginning, you struggle later. So that was a bit false that could come your way is not a schedule to start the journey, but I think be conscious and look for these. And then each of them will have a song that's unstable. Now, good way to end my speech today would be to get a picture of a let's say a partial picture of a data and a digitally enabled enterprise. I'll paint it for an FMCG company knowing its manifestations to be very different for the kinds of businesses. And hence this might not necessarily apply to different industries. So in the FMCG, let me give you some use cases for marketing, sales and manufacturing. Let me start with a couple of use cases in marketing. I see one personalizing escape, right? Now, most marketers want to send a personal message to their consumers and to millions of consumers. How do we do that? Today in the world of digital marketing, it's possible. A great example would be possibly this ad of Mondays, which you might have seen in last the world, not just a category ad campaign. This is what we rolled out last the world. It was that time after COVID wave one and small retailers were desperately needing some business. So our marketing teams and agency thought of a serving a personalized ad with consumers. So if you were, for example, on YouTube, and you were selling this ad, we would go through Google's technology, your pin code, and our tech partner would pick up your pin code and customize the ad for you. So you will land up seeing names of four local retailers nearby you, depending on which pin for yourself in point on the ad. And this is a great example of hyper personalizing ads at scale. Both are important. One is personalizing. And second is not for one dozen consumers for millions of consumers, right? This is where technology can take us, right? Personalizing ads at scale. The other one could be using first party data. So for example, General Mills in the US, I'm going to understand accumulated more than 15 million unique consumer identities and got to know the attributes what we call likes and dislikes. This helped them customize the ranks of these consumers, which helped them significantly improve the media. There's a great use case for inspiration. And this is a great case where you have a proven ROI when you associate it with a cost. And the cost here of accumulating first party data is pretty huge. Those are two of the use cases for marketing. Now moving on to a couple of use cases from sales. So let me start with saying big data to expand distribution. How does our salesman know which village to start distributing our products? We have such like villages in this country, right? But today with Google Maps, it's possible to know which village has a metal road, which has a post office, which has electricity. How many houses in that village? How big does this habitat look on the screen? Using these key attributes of villages, they can open the right villages. Otherwise, it can be very confusing. It's almost like finding a needle in the exact room and 600,000 villages, which one has the right physical impossible. That's a great case of this is a great use case. Many companies are using this at scale in using big data. Big data, big data is any data that is lying outside your organization. Now, now let's look at another one, which is again being used by many companies at scale. This is about using analytical engines and machine learning or suggesting the perfect order to the salesman. See one challenge if you've been in sales, most sales managers won't resolve is for their frontline salesman to sell the perfect order to every store every day. We just tell you on what quantities. If you had a magical solution that could solve this, this would be the biggest solution in sales. Today, using your past data, which you have accumulated your sales that store using big data and some advanced analytics, we can get machines to simulate the perfect order. And over time, with machine learning, the machines can themselves improve on these algorithms and suggest the perfect order for every store every day improved. Now, these are two great examples in sales. So these are things which can dramatically shift your sales capabilities and your ability to execute in the market. Yeah, and let me let me finish in a couple of use cases in manufacturing. So let me start with augmented reality. Last year, just before COVID, I'll give an example, even in the process of shifting a line from one of our factories in China to India. Then COVID struck. And our OEM representatives would be there on site, they went to Europe and they can travel to China, not India. We still managed to shift a big complex chocolate line from China to India, using advanced mobile platforms and augmented reality. Using high tech camps mounted on the aurons of the shop to our colleagues. The OEM sitting in Europe to guide them on dismantling the line, packing it and shipping it. Then in India, guide our operators to unpack and release some of the line. All this policy and believe you need no delay from the original shipping. Look at where technology is taking us. So this is one example in manufacturing. The other example is also the most stunning example. Think of IoT internet of things, right? And an industrial advocate is called IOT, right? This is an application of connected devices. So four years ago, we started putting sensors in all our machines in our city factory and started getting key readings of machines like pressure, temperature, vibrations, etc. Now these are baby steps towards what we thought will help us in building an integrated packaging factory towards building a smart factory. Now at that time, we didn't know there'll be such a mistake. But come COVID wave one and the stringent lockdowns along with that. Our ship supervisor could not travel to the factory. It was he was traveling from the industry. Whereas all the operators were able to come. So our supervisor took the call to run the factory from his laptop sitting at his own, right? And he successfully ran the entire ship flawlessly. Now if you recall a point I made earlier, don't fuss too much about otherwise. If it's a small space, here is a classic case where connecting devices for connecting machines to devices wasn't such a huge investment. And at that time, somebody had asked me what's the ROI? I don't know. But today, after running that shift, or running three ships for that one day, this is this has had a huge this has been a force multiplier and the ROI will be more than 1000 possible, right? So let me end here. Hoping the session was a bit useful in either initiating you or accelerating you towards building your next thing compared to advantage, which is what according to me is a tech data and a digital enabled enterprise. Thank you.