Laurel: That’s a big point about partnering with Infosys and generally how you bring data and predictive analytics to your capabilities because you have so much data coming from fifty different brands, countless vendors, all these customers. How can this be maximized to gain this knowledge?
Amit: Yes, that’s a great question. And as you say, many brands and countless business partners and customers. We generate terabytes of data every year, and that data usually resides within our four walls. I mean, just in our ERP and our commercial warehouse systems. And based on that data, I think most industries like ours have gotten really good at doing traditional analytics. Traditional analysis equals, how are our finances? How is a particular brand performing based on historical data? And so on and so forth. I mean, those are the traditional analytics that we’ve gotten really good at. What becomes important now that you have good traditional analysis is, what don’t you know yet? What are these gems in your existing data that you haven’t tapped into?
What some of these newer technologies and platforms have started to help us do, and will probably continue to help us do, is to be able to collect our data and start to point out what it is that we’re not looking at. I mean, what we know is always great, but these unknowns that we haven’t really picked up on are what will help us look at some of these technologies that are coming forward. This is one aspect of the world.
Now, the second aspect of the world is, as I said, data exists right inside our four walls. But like I said before, social media data, point-of-sale data, data that doesn’t exist within our four walls, I think has a different insight and a different power.
Now, think about the fact that you can combine the data that comes from these external sources and the data that you have inside, and then think about some of the data that you generate just because you have consumers that are calling you. consumption division. Take all that data combined and I think you can create analytics that we haven’t been able to produce before. And I think that’s a power of what we get from just combining all this data and combining all this data together, and we can maximize a lot of insights.
And then once that mix occurs, I think the predictions are different. In the sense that many times our existing forecasting solutions typically rely heavily on historical data to be able to make predictions about our supply and demand. They are making predictions like this. However, with external data mastery, I think it goes further. I think it also starts to give us insight into what consumers are thinking, what customers are thinking, how their tastes and choices are changing. I think that’s the next big thing for us from a predictability perspective. And I think new technologies and platforms will help us do it even better.
Laurel: So that’s a good point. We have that data and you have to make some really good decisions from it, but you also have to really evaluate that analytics, make predictions into the future, but also make sure that all of your systems are working properly end-to-end. So how can cloud applications, along with this need and the progress of your digital transformation journey, help you with a tactic like the M&A you mentioned earlier were part of your career? How has that specifically been one of those things that helps the company create efficiencies and really see technology as a partner?
Amit: Yes, absolutely. This is a great question. One of the key reasons for acquisitions is that we can really take advantage of the synergies that we can get. That’s almost one plus one equals three. That’s number one. Number two is, then, on top of the synergies, the innovation pipeline, let’s say, that the acquired company has and the experience that we have. When you combine those two together, I think we can create innovation at scale.