Ep 58: From Clean Data to AI-Driven Advantage with General Mills Chief Digital & Technology Officer Jaime Montemayor

Evan Reiser: Hi there and welcome to Enterprise AI Innovators, a show where top technology executives share how AI is transforming the enterprise. In each episode, guests uncover the real-world applications of AI for improving products and optimizing operations to redefine the customer experience. I'm Evan Reiser, the founder and CEO of Abnormal AI.

Saam Motamedi: And I'm Saam Motamedi, a general partner at Greylock Partners.

Evan: Today on the show, we're bringing you a conversation with Jaime Montemayor, Chief Digital and Technology Officer at General Mills. General Mills’ products can be found in households across the world. They operate at a global scale with over 30,000 employees and 20 billion dollars in annual revenue. 

There are three things that really stood out to me in my conversation with Jaime.

First, General Mills made an early bet on their cloud and data infrastructure. That foundation now supports thousands of machine learning models across the business. Public teams better understand consumer needs, predict demand, and improve manufacturing efficiency. 

Second, they launched an internal generative AI tool called MillsChat. It's now used for company-wide performance reviews and development planning, and they're moving towards agent-based systems that can help employees redesign entire workflows.

And finally, Jaime shared several AI use cases delivering measurable impact, cutting waste in the supply chain to generating personalized marketing content, and speeding up how new products reach store shelves. 

Jaime, first of all, thank you so much for making time to chat with us today. I have Saam and I were really looking forward to this episode. Maybe to start. Do you mind giving our audience a bit overview of your career, and they should learn a little bit about your role at General Mills.

Jaime Montemayor: I originally started my career at Oracle. I did a lot of work as a very technical leader, helping big organizations leverage the latest and greatest technology that Oracle was creating to transform their businesses. Then I moved into consulting, and I always talk about my time at Booz Allen Hamilton as the MBA that I never had. And so, at Booz Allen, I learned how to how to do this strategy and how to use technology to drive the business.

And it was one of those big engagements that got me into the food industry because I developed the AI strategy for a major CPG company. And, I was invited to implement the strategy. And so that's how I got going. So I have spent, you know, the majority of my professional career working with business leadership teams, helping them frame up the actions they need to take to drive the business.

And then turning around and leading tech teams to enable those specific opportunities that the business has. And so I've had the chance to be a CIO in the small-business unit region of an international operation and a global operation. And so those different experiences have given me the opportunity to come to a company like General Mills to help them, take it from being just the necessary capability to run the business to a capability that it can actually help drive the business forward.

Saam: Maybe just to start high-level, like, give us a snapshot of sort of the business and what falls under your work and scope is the chief digital technology officer.

Jaime: This organization is, you know, we take pride in making food that the world will love. And so the organization focuses on understanding consumer needs, making sure that we innovate with products that can solve those needs of our consumers. We also communicate these needs effectively through best in class marketing capabilities. And then, the kind that we have an amazing supply chain team that makes sure that we create those products, you know, with the highest possible quality, with the right sanitary conditions, and that we can take these products to our multiple channels that we use to distribute the products, globally.

And so that's in a nutshell, what General Mills is all about. We take pride in the in the food that we manufacture. Our consumers love what we do. And we also take pride in the partnership that we have with our, you know, retailers and distributors, globally.

Evan: I think about, you know, me as a, you probably like elementary school, you know, first seeing, you know, General Mills on a box of cereal, right. I probably wouldn't have thought. I wouldn't have realized, probably as a young kid, what a big role technology plays. 

You mind kind of sharing a little bit about, kind of like the digital journey that you've been on at General Mills and kind of like, you know, maybe we should go a little bit deeper, explain kind of, you know, how technology kind of impacts and transforms the business today?

Jaime: What may not be obvious to everybody is we also have highly sophisticated systems that can help the business operate in a more efficient and effective way. globally. For instance, we have quite advanced supply chain planning systems that are fully integrated with these systems. We are able to better understand demand, we're able to better serve the demand, and we're better able to plan for the manufacturing and execution of our manufacturing operations globally.

And so that's not may not be too obvious to to everybody in terms of how much, it takes, you know, for us to be able to run the business like that. Now, what may not be obvious is that we have a quite sophisticated data foundation to enable that. And so if you sit back and look at General Mills and, you know, we use data for, so many aspects of our business data to better understand consumer needs; data to better gauge the demand coming from our consumers; data to innovate, on our on our product, platforms; data to serve, you know, our, the demand that is as is shaping in the marketplace and data to improve the manufacturing of our products. So data is a big component of our tech foundation. And that's why, you know, at this stage of the game, you know, we're able to use AI on top of the data. Our data is very clean, very well governed. And at this stage of the game, we're now able to build on that data foundation, expanding AI capabilities, particularly across the whole supply chain of the company.

Evan: What are some of the top use cases you have with AI, like where have you seen early wins? I love to hear more about how you're applying these technologies at General Mills.

Jaime: So yeah, our a journey started about five, six years ago. You know, when you know, they said, you know, we realized that we had these very clean and well-governed, data foundation in the company. So we made a decision to move all of that to the cloud. And, you know, we had a 100% cloud run right now in the corporation as well.

Evan: Oh wow.

Jaime: And and so we started to move everything to the cloud. And that was a very good call, because when we made that call, you know, we created a foundation that we've been able to build on top of that. And so the first use case in terms of how we use that data foundation was to enable our commercial capabilities, you know, in particular strategic revenue management.

We knew that we had an opportunity to improve the way we made promotions, the way we did pricing, the way we executed on our price architecture. We knew we had distribution opportunities, distribution of our products in the retail landscape. And so, in order for us to go after those opportunities, we created either of teams that built AI, machine learning based solutions that, helped our business teams with, specific recommendations on, on these opportunities.

So once we learned how to build those systems at scale then we moved to our supply chain and then in supply chain, we started with, you know, simple things like business performance management. You know we built a business performance management solution. Then we expanded into logistics. You know, we had significant opportunities in logistics. So as of today, we have thousands of those machine learning models running day in and day out in the company.

And with those models, our teams have the benefit of being able to leverage predictive analytics to run their business on a day-to-day basis, without having to do their own specific kind of analysis themselves. You know.

Saam: What are some of the other sort of interesting ways you all are using AI at General Mills today? And like, are there any examples that our listeners might find surprising?

Jaime: Within, you know, literally weeks after ChatGPT became a thing, we were able to create our own generative AI foundation, which we call MillsChat. And so this is behind all of our work capability. And so with that, like any other company, you know, when you deploy a solution like that, you've got to take your steps towards expansion of that capability.

So we started first by learning how to use these for, you know, what I would call individual productivity. You know, that some different groups wanted to go after in the organization. So we did that. We piloted them with multiple groups. And then after that, we decided to deploy that to the, to the whole company.

And then after that deployment that we did for the 30,000 employees that we have in the company, you know, we have seen, week after week, expansion in terms of the adoption of the tool. You know, right now we measure every week how many people actually use this foundation and up to 30% of our, workforce is using these new technology consistently.

We have some functions like HR, for instance, the use rate, goes all the way to 65, 75% of the of the workforce uses that consistently. Some of the the most basic use cases that people are working on are things like, for instance, in the case of HR, you know, simple things like doing performance assessments or helping people develop specific, development plans, those kinds of things, you know, simple things that, you can use to, to be more effective, more productive, more efficient.

But, you know, as we gain learnings from these opportunities, we're now focused on the next frontier, which for us is reinventing business workflows through agent architectures. You know, as our people become more comfortable taking on recommendations from these advanced systems that we're building, you know, and they're becoming more comfortable, using AI capabilities to run their business on a daily basis.

They are now giving us permission to go and implement new agents that can help them be that more efficient, more effective, or can help them eliminate tasks, you know, from their daily lives. And so, as you can see here, we're progressing from, you know, first, you know, building, you know, solutions that are you know, focused on specific functional areas to now expanding in the use of the capability.

And now looking into reinventing workflows  leveraging both traditional and machine learning capabilities, as well as now generative AI solutions.

Evan: Are there other areas where you'd say like, hey, here's three kind of use cases that really get up and running in a couple of weeks that like, we got maybe more value than expected given the kind of, you know, ease of kind of getting something going. Yeah. We'll be your, your, your quick win list for a CIO feeling like they need to, you know, up their AI game a little bit after this episode.

Jaime: Yeah, exactly. So, well, first, you know, the one area where we have had a significant win is in waste management. So an organization like ours, you know, with so many manufacturing lines on a global basis, you know, you can imagine we are squarely focused on waste, control. So that's one area where we have quickly putting a solution in place. And getting significant savings, by building a new solution that not only addresses the specific opportunities that we have line by line but that helps the business orchestrate actions across the supply chain to minimize waste. So waste management has been one area of opportunity. Another area that we're going after right now is content generation in our marketing function.

So we're also partnering with a third-party supplier that is helping us accelerate, the use of general AI capabilities to generate content dynamically. We have had historically good ability to understand our consumers and understand their needs and to develop marketing communications to connect with them. But what we need now is to tailor this content to the specific needs of that specific consumer, and we need to be able to deliver these content in a dynamic way. Primarily using social media channels. And so to enable that, you know, we truly need to leverage generative AI capabilities. So that's one other area where we're gaining significant savings. 

And then the next one where we're still not getting the full benefit, but we are actively working on is accelerating product innovation. You know, if you look at the time it takes for us to innovate to create a new product, to improve one product, the number of people that get involved in the whole company, the number of, human touches required to go from an idea to a product on the shelf.

We believe there is a significant opportunity for us to simplify the whole process, be a lot more focused, and reduce the time-to-market. And so this is what another use case where we we feel very passionate about. And we're actively working on that.

Evan: Not super recently, but you know, several months ago I spoke with Anuj Dhanda the CEO of Albertsons, and he talked to, you know, in a very similar story about how they were using AI machine learning to optimize kind of supply chains, also kind of remove waste, right? Okay. Good for the enterprise, but also really good for consumers as well.

To show a bit more about, you know, how do you think about using AI and machine learning to optimize supply chain and like, you know, at any kind of, you know, anecdotes there or kind of you know love to hear how you think about that just because I think we're we're you know globally rolling the business of waste management?

Jaime: The first job is to ensure that you have those digital signals without those digital signals, it's hard for you to understand the potential and the opportunity. So, for instance, at the factory level, it's about improving the sensors that we have at the line level and at the factory level. So we are on a multi-year journey to trying and revamp our, tech foundation at the at the factory level to ensure that we have the wealth of sensor data required to improve led, to improve waste in that area in logistics, we are focused on automating workflows and digitizing our operations in every warehouse and in every truck.

Again, the more information that we have, the higher the opportunity for us to mine that information through machine learning models and to better help our business, run the business in a more effective way. So those are examples.

Evan: You guys are doing something over like 5000 daily shipments, right? From plants or warehouses, like, I mean, that's like a serious scale, right? It's not just like a couple of trucks. Right? Can you share more about that? Like, you know, have you seen kind of, big wins there, right? Imagine, like, the supply chain historically always been a computer science problem. It seems ripe for optimization.

Jaime: You can imagine, you know, how hard it is, on a daily basis to make the right set of decisions, you know, in terms of which projects should going in which truck to, in which route on a daily basis, you know, and so we have automated all of that, complexity. And through the machine learning models that we have built in the complex or an advanced orchestration that we have built on top of that, our operators can, you know, quickly make these decisions in the most informed fashion.

And, you know, what this, solutions have given us is immediate productivity, immediate efficiency in how we run the supply chain. And they have also enabled us to build a foundation that we can now, build upon… on top of that. And this is what I'm talking about in terms of the next generation of change that we're that we want to drive in the organization is by not just looking at the individual opportunity that we have in a specific job or a specific location or specific function.

But to cut across the organization and look at all the workflow. And this is where generative AI will help us. Now, simplify and streamline, that work, hopefully taking away work that is, is not required.

Saam: Evan and I like to think about like, you know, how quickly the world is going to change over the next 1 to 5 years. And so I want to ask you about that. I mean, the context of General Mills and in the context of sort of the food landscape as well, like what are what are use cases that maybe aren't life today, but when you dream out two, three, five years, you know, you see AI having an impact on both at General Mills and then also more broadly into the food economy and food landscape? 

Jaime: Yeah, I think it's something that is happening, very quickly, is that our consumers are increasingly using more tools, you know, to inform their daily actions and decisions, you know, and so AI is inevitably making its way into the consumer, via the technology that we use on a daily basis. And I think that will have an impact in terms of how people, you know, make decisions with regards to, you know, activity, food consumption and such.

And so I think we, as a company need to be very close to that. We need to better understand how we can take those digital signals to inform our understanding of the consumer needs, understanding of those demand moments where demand of our products will be required. We should use those digital signals to better inform our innovation strategy.

You know, what products we need to produce, and what form in what shape to serve those needs. And, ultimately, it should also inform how we serve those needs, you know, and so so that's the first impact. And, the second impact is are we as a company, you know, have to use these, new technologies.

To be able to do a better job of serving, the needs of our stakeholders and the needs of our employees. And I think historically view, you see, General Mills have been in business for 160 years. We've done a very good job of serving those, those needs, over time. And I think, it's our obligation to take this new technology that is now changing the world in many different ways and bring it to bear.

And how do you how do you how do you bring it to life in a company like ours? Well, by what I said, you know, changing the way you run the business, by changing the way we make decisions. One thing that is often overlooked in our industry is speed to market. Speed to market is extremely important.

So if we can if we can connect a consumer need with a specific solution in a shorter period of time, well, that gives us the ability to lead in the market. If we can communicate with a consumer at the right moment, you know, the right feature or function and solution for their needs, then we have a higher probability of succeeding… and as a business.

Evan: You guys are moving so quick and innovating right. And outpacing some of your peers that don't have any of those maybe like, maybe headwinds unfair, but maybe those kind of challenges. Can you talk a little about like, how is that possible?

Jaime: I would like to think of General Mills as or as an always on organization. You know, because we serve consumers, we all we are always seeking for understanding in terms of what those consumer needs are. I think in our leadership team, where we always start by by talking about where consumers are and what they need from us and how we're serving those needs.

If you do that, on top of, of those strong values, then then you have a chance to succeed. The other thing that we do and, and I think is, is such a super strength of our organization is we have strategic clarity. We call our strategy accelerate. And, in that strategy, we have clarity as to which consumers we're serving, which product platforms we're focusing on, which markets, you know, we are serving, which their partnerships are critical for us and which capabilities enabled that.

And one of those capabilities is digital and technology. And and that's why for me, my job, even though it looks like very complicated because there are so many different aspects that need to be managed on a daily basis. It's actually very, very straightforward because with that strategic clarity, then you can quickly step back and organize yourself and ensure that first you have those core systems to enable the run of the business.

You know, we need those core systems that we have in the organization need to be there to enable the business to run and compete on a daily basis. I can then focus the rest of my energy, hopefully more energy into the capabilities that will actually help the business win in the marketplace. And that's where data analytics, AI, this is where these new capabilities, come to play.

And so that's how we manage these complexity, you know, and again, I just want to close by saying that, none of this is possible if you don't have a strong foundation. In our case, the that foundation is is tech and data, it's talent and these sorts of ways of working, which include the cultural side of it.

Saam: How are you most leveraging AI and like, you know, changing the way you do your own work with AI and, and also if you have any tips for listeners and for having an AI, you know, always curious.

Jaime: Well, first, I'm a very curious individual, so I'm always in learning mode. Okay. And so I am the first one operating my operating systems. I am the first one trying the latest tool. And so I do that on, consistently. And so I keep myself up to date in that regard. I use gen AI every day now.

I no longer do the traditional search. I use multiple tools. I actually use multiple tools so that I can, keep myself up to date in terms of, you know the depth and breadth of these of these, of these models, in my company, I use me as chat on a daily basis. I no longer go to our champions website to look for data.

I use MillsChat to look for data. And, you know, as we speak, we're deploying a new tech foundation that will bring a lot more context to our end users. As they engage means chat. They will be able to answer questions that are more specific to their functional areas, because we are now enhancing, that foundation with the specific, data from General Mills.

And so I'm a big proponent of it. I'm a big user of it. And I believe that we as leaders, need to champion the use of, of of new technology. And the best way to champion that is to actually use it yourself and not learn from others, about, you know, the value or the impact of these technologies.

Evan: At the end of our episodes, we like to do what we call a lightning round, which I know it's not very innovative, but just like for like, you're kind of like one tweet takes two questions that are a little hard to answer in the one tweet format. The newest, you can kick us off.

Saam: Awesome. So maybe you start. How should companies measure the success of the CTO in this AI era?

Jaime: That's a phenomenal question. Every time I talk to my team, you know, I'll make sure I make sure they understand that everything we do in this company is about generating value for for our company. Okay. And so in my case, you know, we are on a journey to move to a product platform organization. So every product team that we have set up and every platform team that we have set up in the organization, we have taken the time to define the value proposition of that of the team.

In some cases, the value proposition is just just, about keeping the business running or enabling the business to operate day in and day out. So we said that, very clear. But in most of the cases, the value proposition is about driving efficiency, improving time to market, reducing cost. Growing the top line. And what I've done is that I partnered with my CFO to, for them to be the ones that keep the score.

So they keep the score for every investment that we make in our in our organization. So I firmly believe that technology investments in, in this day and age are great contributors to value creation in corporations. And you need to have a good way to measure that value. And you have to have a good, transparent way to be able to make better decisions based on that, value proposition.

Evan: Will be kind of your advice to, you know, technology leaders are trying to, like, maybe learn more and keep up with the AI trends, especially a robot like, you know, new novel, you know, innovations and inventions like every week. How how do you like it? How do you stay on top?

Jaime: My first recommendation is stay. Focus on the value opportunity, you know, so if you're clear on what you're trying to achieve, then you can get the thing done as a tech leader, you need to be the best user of technology. So get involved, touch the technology, use it, you know as much as you can, and then be humble.

In my case, you know, what we do is we have these tech summits on a, yearly basis. We take time, a lot of time to go and visit with, you know, tech innovators. First, we lean on our tech partners that we have in the company. We have a handful of tech partners that we respect, that we work very closely with.

So we spend a lot of time with them. Then we go and visit with VCs, and we're always in the search for the next big thing. And when I go there, I don't go by myself. I bring my business partners with me. Obviously I don't I don't bring them all at the same time. So I try to make these tech summits a lot, a lot more focused.

I do take some is for the marketing space or tech summits for supply chain or tech summits for commercial. And so by, you know, peace meeting the effort, you know, we're able to cover a lot. And by doing it together with the business, you get a lot more benefit. You know, because when you walk out of those conversations, it is is always crystal clear that we need to continue evolving our capabilities.

And we are usually very clear as to what would be the next step, you know, for us to continue evolving these capabilities so you don't have to come back and, you know, convince anybody that we need to change or evolve or transform. We always come back and and the problem is, okay, how do we get that done?

Saam: I mean, maybe switching gears to the more personal side, what's a book you've read recently that's had a big impact on you and why?

Jaime: Well, I just read a book named wired, from Eric Lamarre. He's a next partner from McKinsey. He's closely affiliated with MIT. And, I love that book. You know, because we have actually implemented a lot of that book. Ketogenic meals. Why do I like it? Because it talks about digital transformation. And in the in the big thing about digital transformation is that successful digital transformation is nuanced.

So it's not just about the tech. It's not just about the talent. It's not just about the ways of working or your operating model. It's all of those things. And what I like about that, book is that it gives you a very good, set of tools, you know, to think about digital transformation and how to enable a successful program to transform your business.

Evan: What's an upcoming technology that you're just personally most excited about?

Jaime: I think we're still in early stages in the evolution of cloud computing. Edge computing is one area of of focus for us. You know, as a large corporation that wants to digitize every aspect of our business. And edge computing is something that is very interesting to us because we we do want to, not only capture more data, we want to mine the data and we want to do it in a cost effective way.

So edge computing is is an area of focus for us. And, you know, I think that's, that's an area that, will continue providing benefits down the road for us.

Saam: What do you believe about, you know, AI and its future impact that you think will be true that, like most people listening would say a science fiction?

Jaime: Well, that I think you'll be talking to your computer, talking to your phone very quickly. And and you'll be able to get things done using your voice. It is being done in many different places already. I think this is coming really fast and hard at us, and it's going to be a challenge, you know, for us, because if you don't have a clean data foundation, if you don't know what type of decisions these new agents, are going to be recommending, it's going to be hard for for you to make good use of that technology.

Evan: What would be your advice to up and coming technology leaders? Right. What you know, what inspires you? What motivates you? What would you kind of pass on to the next generation?

Jaime: When I would say that, you know, you need to be very humble. Things are changing really, really fast. And don't assume that you know know it all or that you have to know it all. I think is really important, as a leader, to surround yourself with people that can help you fill in the gaps and or can help you activate on your ideas and strategies.

So I would say be humble, you know, be curious. Make sure you surround yourself with the right, talent and collaborate. Teamwork is paramount to driving transformation. I don't want to use the word partnership because partnership is an overused word in our industry. Teamwork. Work, collaboratively with your teammates, in whatever level you are.

Evan: Highway. Thank you so much for taking the time. I really just enjoy the conversation. I got my own notes, and I. I'm feeling just, like, a little more, inspired clubhouse conversation, so I appreciate you taking the time. Thank you so much for joining us.

Jaime: Thank you again. I really appreciate you guys inviting me to join this, amazing podcast.

Saam: Yeah. Echo. I think this was an amazing episode, and we're excited to get it out to our listeners. Thanks, Amy.

‍Jaime: Thank you.

Evan: That was Jaime Montemayor, Chief Digital and Technology Officer at General Mills.

Saam: Thanks for listening to enterprise AI innovators. I'm Saam Motamedi, a general partner at Greylock Partners.

‍Evan: And I'm Evan Reiser, the founder and CEO of abnormal AI. Please be sure to subscribe so you never miss an episode. Learn more about enterprise AI transformation at Enterprise Software dot blog.

Saam: This show is produced by Josh Meer. See you next time.