Innovating Leadership:
Co-Creating Our Future

Resources:

Our host Maureen Metcalf posts a newsletter every week on LinkedIn. You can subscribe here.

Maureen’s latest book is Innovative Leadership & Followership in the Age of AI. You’ll find details about it at https://bit.ly/LeaderInAI. Her other 10 books are available on Amazon here.

Books we’re reading for fun or personal development right now include:

• Everyday Ubuntu: Living Better Together, the African Way by Mungi Ngomane. Hardback (https://amzn.to/48Doh6j) and audiobook (https://amzn.to/48YCRF4)
• Nerve: Lessons on Leadership from Two Women Who Went First by Martha Piper & Indira Samarasekera. Paperback (https://amzn.to/3tOtzg4) and audiobook (https://amzn.to/41OYdT5).
• Jilly Truit murder mysteries by Beverley McLachlin:
  • Full Disclosure – https://amzn.to/46TxW6Q (paperback) https://amzn.to/46VDL3Q (audiobook)
  • Denial – https://amzn.to/46YCbhs (paperback) https://amzn.to/3GJc0AA (audiobook)
• Women and Leadership: Journey Toward Equity by Sherylle J. Tan & Lisa DeFrank-Cole

NOTE: As an Amazon partner, we may make a small commission from books you buy through these links.

Guest(s):

Guest(s) Bio:

Steve Armato is Vice President, Amazon Transportation Services and Technology. His team works with over 50,000 service partners – many of whom are small- and medium-sized businesses – enabling them to grow their businesses by transporting items on behalf of Amazon.

With over two decades of experience at Amazon, Steve has a passion for innovating on behalf of customers, particularly at the intersection of technology, science, and operations. Prior to his current role, he spent a decade in Amazon’s Fulfillment and Supply Chain Optimization group, building large-scale predictive systems and optimization algorithms to optimize Amazon’s inventory supply chain. Steve holds a B.S. in Computer Science from Duke University.

Transcript
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Unknown Speaker 0:00
Many people fear artificial intelligence will take away jobs, including leadership roles. The reality is, leaders who don’t incorporate AI are the ones at risk. One secret to Amazon’s success is that they’ve been using machine learning and AI for around 25 years now, and Steve armato, their VP of middle mile and tech, wants to share that AI with small businesses. He sees it as a leadership Win win, and explains why. In this episode, we’ve been diving deep into studying the interplay of AI and leaders at the innovative leadership institute, find out how we help leaders build the mindsets and resilience to successfully adopt new tech at innovative leadership.com

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this is innovating leadership. CO creating our future. I’m your host. Maureen Metcalf, founder and CEO of the innovative Leadership Institute, where we help leaders be future ready, helping us in this mission. Today is Steve armato, Vice President of middle mile product and tech at Amazon. He’ll share his leadership journey at Amazon and how they use robotics and AI to fulfill their delivery commitments. So Steve, thank you for joining us. Thanks. Maureen, great to be here. Tell us a little bit about your journey at Amazon. So I’ve been at Amazon 22 years. I actually started in 2001 as a software intern, and even during that internship, I was able to have immediate empowerment and drive business results. And just thought that was uncanny, and that’s even more true today than it was 22 years ago. So I’ve been in Amazon 22 years. Started as a software engineer. I worked on our fulfillment center systems and then our supply chain optimization technologies for about a decade, and then I’ve been working on our transportation technology and services for the last six years. What does it mean? Transportation, technology and services. I know you’ve got AI and robotics in your title. What does that look like? Well, first of all, for those who haven’t been to fulfillment center, it’s pretty amazing. We have tours open in the public and can see our robotics in action. The first time I saw it, it was pretty amazing. It’s actually a ballet of robots working hand in hand with our employees. So it’s pretty remarkable. With transportation services, we work on empowering our employees and small businesses who work with us to get products to customers. I’m going to jump to small businesses because this is interesting to me as a small business owner. How do small businesses help Amazon get their products to people like me who want you know whatever the latest business stuff is, Amazon works with small businesses in a variety of ways. We’ve got hundreds of 1000s of small businesses selling on Amazon, but specifically in our transportation network, we work with about 3500 delivery partners who then basically do the last mile delivery of packages to our customers. So our fulfillment centers pick pack and ship robotics and employees, and then hand off to our delivery partners for that last mile delivery. Cool. Amazon’s optimizing its fulfillment and delivery network by combining robotics and automation and using AI in its delivery and supply chain. So what’s the potential of AI to transform the operations networks to create a better experience for employees, for your leaders and for customers like me? Amazon’s been applying artificial intelligence, AI and ML machine learning for more than 25 years. Some areas that I think people will be familiar with are personalization. So when you’re on the product detail page at Amazon, you can browse for a product and then see customers who bought this also bought this, and that helps you find other products that you might love. And so that’s personalization. Forecasting is basically taking any one of the hundreds of millions of products that we sell or that sellers sell, and then forecasting the right amount of inventory to have to make sure that we’re always in stock and can get that to effectively. And I assume you also rationalize where the inventory is around the world, which warehouse or which distribution center. Yeah, we’ve got some amazing algorithms that actually determine how we place predictively our inventory into each region and each fulfillment center, and that helps to optimize speed and cost for customers. But taking a step back, AI has a pretty wide ranging application for customers, employees and leaders. We started with forecasting and personalization over 25 years ago, and now with generative AI, I think this is the next major wave of technology. So if you kind of take a step back and look at technology waves overall, you know, we had the PC and computing, then we have networking and the internet, and then we have mobile the phone in your pocket is a high speed computer and high speed internet all together. And so I think generative AI.

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Is actually that next wave as important as these others, in terms of like unlocking a whole new wave of technology scheduling and optimization, is compute heavy algorithm, heavy and complex. How many warehouses Do you have even around the US just curious what these algorithms are trying to calculate across the product spectrum. We have hundreds of fulfillment centers. Just to give you a sense of scale, during the pandemic, over the course of 18 months, we more than doubled our fulfillment center footprint. So one of the things that we’ve been able to use AI for is to start to predict inventory placement for products. And you know, when you have sales history for a product, it’s pretty straightforward to get it in the right region and get it close to customers, but we work with hundreds of 1000s of sellers who are constantly sending in new products where we have no sales history. And so one way AI can help, along with some creativity, is we looked at personalization data so customers who buy product A also brought product B, that data can help us to predict how to place a product that we’ve never seen before and we have no sales history and still get it into the local customer region, so that we have the right products in the right places to ship them to quickly. And so this was a nice win where we benefited speed, we benefited cost, because products were shipping shorter distances, and then that all benefits sustainability because we’re shipping shorter distances, it’s a way that AI and technology can bring a win, win, win to our operations. I love the idea that it is hitting all of the wins and where you’re seeing things that just haven’t happened. Doubling warehouses was presumably not on the business roadmap. It’s not I think Amazon’s great at having agility and bias for action, and so you know, when a new problem emerges, we’re willing to drop everything we’re doing and focus on that if it’s right for customers. At this point, effective leadership looks different than it did in 2020 so how are you evolving as a leader, and what sets you apart that enables you to do this. We’ve got a leadership audience who wants to understand, what are you doing differently than they might be doing today? It’s an evolution, and I’ve thought a lot about innovation and innovating at scale. So I think, first of all, sometimes people think of innovation as you know, you just have a light bulb moment, and have a couple of really smart people, and they’re producing all the ideas. I believe that if we give our employees the right training, the right skills and the right empowerment, we can actually drive bottoms up innovation. And I call this innovation at scale. If you have your entire employee base coming up with ideas and generating innovation, then you’re going to be more productive than if you just have a couple people who are really smart coming up with all those ideas for my employee base, I think of what are the right ways to empower them for AI in this case, so, you know, Amazon has long focused on upskilling. I am a great example of upskilling too. Over 22 years, you know, I went from a software intern to a Vice President of Technology, but we have upskilling at all levels, from career choice, where 750,000

Unknown Speaker 8:05
people have access to technical and non technical training, to Mechatronics robotics apprenticeships to also free training that’s available to the whole public. We have a program called AWS AI ready, and this is a pledge to upskill 2 million people with free training. We pledge $12 million to provide scholarships to underrepresented communities. And all that is basically a way to make sure that as AI becomes more and more a part of technology. How do we have people at all levels savvy in that technology? So again, I think about with my employee base, how do I have them embrace AI, so we’ll package up best practices and publish that to our entire engineering community every other week. I have a demo or a show and tell where people can bring their prototypes of generative AI models, and I’m kind of incubating a list of ideas in my team. There are about eight great ideas where we can apply generative AI to areas that I own, half of those have come actually bottoms up. Half were top down ideas, and half came bottoms up. You never know exactly what’s going to work until you prototype it, and then you see it, and then if it’s working, well, then you iterate, and then you can double down when it’s working. By having the skills of our employees, having that open forum, and then by iterating, we were able to come up with twice as many ideas than we would have behind closed doors in the top down. How do you gather those suggestions? It’s easy to come up with an idea as one sentence. I think it’s really around like, you know, how do you create a prototype or show that this idea has legs? The cool thing about AI and again, these training sessions that we have is that people can create their own prototypes and then bring it to a demo session, and then we can kind of see what works. It’s kind of taking it a couple steps further than just a couple sentences. And I think as a result, that really won. It makes sure that people have passion around that idea. People at Amazon, the way that we structure our.

Unknown Speaker 10:00
Teams, they’re structured around having sort of a core business function or focus, and so people on each team have passion around that problem statement. Usually, when they’re coming up with a prototype, it’s because they’ve seen something. They’ve heard it from customers, they’ve seen it when they were in a fulfillment center. They’ve seen it in their business metrics. So they’ll have an idea that’s usually quite relevant to the problems that they’re working on day to day. And then they’ll set aside time and come up with a prototype, and then bring that to our larger Show and Tell session. And then if it works, then, you know, we find a way overall to make sure it’s a priority for that team to develop further and incubate, and we evaluate these ideas just like any other, you know, what’s the financial impact. What’s the customer impact? And so this becomes another tool in the toolkit to drive business innovation that drives a sort of discontinuous step change in our business metrics. You talked about people coming forward with prototypes, and yet that takes time. How is time allocated so that people can both do their daily tasks and also create prototypes that solve either short term or long term problems. I don’t see those two things competing doing your job is doing the cool stuff that’s going to result in moving the needle on those business metrics. Every team is empowered to allocate time towards big, forward looking ideas, some maintenance. Every team owns their own roadmap, and part of that roadmap is working in, you know, a little bit of these prototyping. We also we have this phrase called moon shots. So every year I have an off site where we look at big ideas that could really move the needle in five years. And so people will document their idea and bring it to a moon shop. What we found is about 30% of those ideas get funded the following year. Each team has time in their roadmap to come up with these big ideas to prototype, to also fix bugs. You know, I think of it as a time budget. What can employees expect to see over time as AI and robotics implementations expand specifically, how are these going to help employees as well as customers and the community? Our employees actually really like this. We call it collaborative technology. The prior paradigm was an employee would walk shelf to shelf and pick up items and put it onto a cart. And the new paradigm collaborative technology, the robot brings the products to an employee who then picks it off of the shelf. They like this because it’s less walking. It’s also in their ergonomic power zone, so they’re actually safer. It’s an example of win win. It costs less because we don’t need to wait on the walking from point to point. And it’s safer because they’re able to grab the item in their ergonomic power zone. We’re going to continue to look for these Win, win outcomes where employees benefit from the use of AI and robotics. That seems like it would be really important, especially during covid. If you doubled your warehouse footprint hiring that many people, when people didn’t want to leave their houses, would have been tough. And I assume robotics and AI were deployed heavily to allow this to happen. Yeah, we made 1000s of changes to our knower during the pandemic to keep employees safe, things like plastic guards between stations, proper distancing. Of course, there were 1000s of different changes, and robotics, of course, helped, because we’re able to bring those products to employees. We’ve talked about how AI is changing the employee experience. What can customers expect to see over time? We’re using AI in a number of ways to improve the customer experience. We started 25 years ago with personalization algorithms. Customer who bought this also bought this. You know, every product has hundreds of your reviews right at the top. There’s now an AI generated summary of those reviews, and it describes customers usually liked this aspect of the product, and they didn’t always like that aspect to me. Saves me as a customer a bunch of time, because I can really quickly decide, is this product going to work out for me, or is there another one I’d rather have? And so that’s just a small step in applying AI to improve the customer experience. The next step on this. And you know, again, with innovation, I believe it makes sense to iterate on an idea and make it better and better. And if it works, then double down on it. The next phase of that idea is we have a fit advisor that helps with apparel. And basically having a customer decide, do they like how this fits for me, based on what other customers had reported about the fit of that product. And then we recently announced Rufus, which is a customer shopping assistant that’s an invite only beta, and it’s really cool. You can ask it questions. 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Unknown Speaker 15:53
where it’s it’s wet, and so you can ask it, which trail running shooters have a soul that grips well in the wet? You know, that’s a pretty sophisticated question for technology to actually infer and then map to a set of products that have a wet gripping outsole. And so that’s just one example of how Rufus can help customers really quickly and conveniently find the products that they want to buy. So I think you’ll continue to see AI deployed to basically streamline the customer experience, help make decisions easier, get you the information curated that you need to make the decision. We also apply this to small businesses. One of the things I really love about my job with science and technology is we can build enterprise level tools that then we put in the hands of small businesses, whether it’s a seller or a delivery partner. For sellers, we recently announced generative AI that helps to make a product listing page more complete. So for example, it’ll help to add the right attributes into the product title. And so, you know, for set of headphones, do they have Bluetooth? Do they have USB C for the charging port? Those are things that consumers care about that not every seller is going to think to add because they haven’t necessarily done all the research and all the different ways to optimize your market and drive buying awareness. That’s an example of providing an AI based enterprise level tool to small businesses to grow their business. We do this with our delivery partners too. We have sophisticated mapping and routing tools that do things like measuring wait times or the duration of each stop in a given community, and that helps to suggest routes that then reduce the amount of driving time and allow them to deliver more packages in the same amount of time by reducing that driving time. So again, we look for Win Win ways to bring science and technology to build those tools that empower small businesses. As you say that I’m thinking about the size of your fleet and the amount of vehicles on the road, while I try to optimize, you know, my one car with 10s of 1000s of trucks that creates a significant sustainability benefit. It does. We have plans to deploy 100,000

Unknown Speaker 18:04
rivian electric delivery vans by 2030 and we already have more than 10,000 of those electric delivery vans on the road today, and they’ve done more than 260 million deliveries across 1800 cities. So it’s pretty remarkable and a great win. In terms of sustainability, we also have a path to 100% renewable energy. We have more than 500 solar and wind projects, and we’re the largest corporate purchaser of renewable energy for the fourth year in a row worldwide. Wow. So I know you have a commitment to sustainability. There are a lot of people who say they have a commitment and don’t deliver the results they had initially been optimistic about. Are there other ways that you’re looking to build sustainability into your business model? A big area of focus is optimizing our algorithms. And what I love about that is an algorithm is like a puzzle. You can never perfectly solve it, you know, but you can continue to optimize it to make it better and better. And so we have teams working on each of the algorithms that we have specifically in our mapping and routing every year. If we make it just a little bit smarter, it can reduce the amount of driving that the drivers do and better suggest those routes to sequence suggested stops, you know, from one neighborhood to the next neighborhood, changing the driving route to make different turns, and again, get from point A to point B more efficiently. That’s a win, win, because customers get their product sooner. Drivers are driving less, and it reduces our cost. Algorithms and technology and science are how we can drive that benefit where there’s really no compromise. So let’s jump back into sustainability. One personal project that I worked on back in 2008 I was reminded of this last night when I got a package. So I’ll tell you about it. I worked on a project to consolidate the shipping of multiple orders into the same package. So imagine you go to the website and place an order at 3pm and then you place an.

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Other Order at 8pm we created the ability, back in 2008 to ship those orders in the same package to the same customer. And so that was a nice win in terms of, you know, we had to build algorithms to detect that situation and then determine whether we had already started the fulfillment process for the first order, and then basically pull back that order and consolidate it with the second order, and then ship it all together in one package. And so last night, I got one of these. I had two Subscribe and Save items, and I had some other items I had placed, and they all came in the same package. What I loved about this was we were applying algorithms to our operations to deliver fewer packages for the same number of products that were delivered. And so we had a win win on sustainability with less packaging shipped and customer experience, because it’s more convenient to open one package and get all your items together. And as an employee, the level of empowerment that I had building that 15 years ago, I still have that legacy today, where when I get a consolidated order, you know, I look back and it’s like I did that with my team. I love that, and it’s a nice sustainability one too. It sounds like as you describe it, much of what Amazon does, we think of it as I place an order and I get stuff as I listen to you, I think of you more as a technology company, that everything’s driven by the algorithms. Amazon is a technology driven company. So when I first joined Amazon, you know, one of the things that I thought was remarkable as a software engineer myself is that top down the leadership saw technology as a key enabler of our business, from the customer experience, the employee experience, to the delivery experience that we have and then our operations technology is applied everywhere. Steve, you have talked a lot about the use of technology and your role. You started Amazon as an intern software developer. You’re now a VP over a major segment of the business. Actually one of my first jobs in high school, I worked for an Internet service provider. My wage was $4.25

Unknown Speaker 21:57
an hour. I started out handling the billing for that company. As I was there, I was able to learn from other technologists I was working with, and I started doing technical support. And along with that, I learned I did it because I was curious, but I also got a raise, and so from a very early point, that taught me about the value of upskilling some aspect of it needs to be self driven, but what I love about Amazon is that we’re big on upskilling. 750,000

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employees have access to a program called career choice, which equips them with technical and non technical jobs, things from a commercial driver’s license to becoming a technician. We also have a robotics apprenticeship program, and not just for employees. We also have a program called AWS AI ready, offering artificial intelligence training for free, and we pledge to give that to over 2 million people by end of 2025

Unknown Speaker 22:52
we also have pledged $12 million of scholarships for underrepresented communities in this area too. So Amazon’s big on upskilling, and I’ve certainly been a benefactor. And in turn, my leadership style is, how can I give my teams the skills that they need to innovate at scale with AI? How do I help my employees be savvy in that area, for example, with this free training? And then in turn, how do I make sure that I listen for those ideas and they have a forum where they can bring those ideas up? And you know, one of the things that we’ve seen is about half of our ideas actually come bottoms up, so not just from experts, but from employees, just like me when I first started, one of the things you referenced earlier in the conversation was Amazon’s commitment to developing its employees. Yeah, you know, I think Amazon focuses on empowering our employees, and certainly I’ve learned a bunch on the job. I see being a leader as role modeling the behaviors that you want to see from your team. So at Amazon, we call those leadership principles. We have 14 of them. Some of my favorites are, invent and simplify, hire and develop the best. Think big. I think about, how do we innovate at scale that’s giving our employees the tools they need to be successful and creative and listening mechanisms such as bi weekly demos, see their prototypes and hear their ideas. It seems like the commitments between the training of internal employees, but also external also creates the talent pipeline, you hire good people. You’ve said, hire the best and yet, as AI becomes more prevalent, presumably because there aren’t enough best people with those skills. Training has to be a big aspect of doing that work. Absolutely. If you look at technology trends, AI is one of many. It started with the PC, and then networking and the Internet and then mobile like those were major changes in technology. Employees needed to be equipped and customers needed to be equipped to understand these new technologies and use them and incorporate them into their day to day. I think generative AI is the next big wave, and we’ve all got to learn and be curious about how.

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We can apply generative AI to our jobs. As you talk about generative AI, how are leaders going to benefit from the developments in AI, you’ve talked about better scheduling, optimizing routes, optimizing the fulfillment centers. If I were running a department, what would become different about my job? One of the great things about leadership is when you’re being a great facilitator of your teams and a great leader of your teams, each change, if you’re agile, and you think about like, what’s the best way to embrace this change? And not just for myself as a leader, but for my entire team, that’s the mix of upskilling. It’s the rewarding employees who come up with great ideas. It’s listening to those ideas, and actually, it’s creating a collaborative, welcoming, inclusive work environment too. You know, when I was in middle school, I was verbally bullied. That was really tough. I wasn’t able to bring my best to school every day. On the contrary, what I want to do at Amazon is create an inclusive environment where everyone is able to bring their best best ideas are not just from one person. It’s several people sitting around the room. One person throws something out, the other one refines it a little bit. Ultimately, you come out with a great idea that’s truly teamwork, and that outcome is one where the whole is greater than the sum of the parts. And so when we create an inclusive workplace where everyone can bring their own ideas, they feel safe to share those ideas and they respect one another, we’re going to get a better total outcome. And so I think AI may have effects on how we lead our teams, but I think the leadership principles are going to remain the same, and we need to just embrace each new change as it comes along. I love that we talk about AI as kind of the largest change management initiative we will see in our careers. I love your example of bullying, and I’m sorry it happened, and yet it sounds like it has informed your entire leadership journey and your leadership philosophy. Taking that very personal story, if you were able to talk to every leadership student in colleges and a lot of senior leaders, do you have one piece of guidance that has either helped you be successful, or is a characteristic of leaders you admire. It’s hard to boil it down to just one, but I’ll give you a couple from the last story. You know, optimism and grit, I think, is an important part of being a leader, having the optimism that you can see through a problem or opportunity and see it coming to fruition, and the grit, you know, there’s always going to be hardship, so the grit to see it through, so that you can get to the other side and deliver on that to fruition. Amazing things are rarely easy to deliver, and so having that optimism and grit helps you get there, providing the right inclusive environment, such that people can bring their ideas and upskilling, so that they have the savvy in a new technology so that they can apply those new skills to a given area that they’re trying to innovate on. Once you have an idea, how do you prototype it? Iterate rapidly, learn from customers about what they like and dislike, and then double down and lastly, I look for bringing Win Win outcomes with science and technology, I don’t accept that we have to make a trade off. You know, the most elegant solutions are ones where you get both. And those are the types of outcomes that I like to see the most. Win. Win. Steve, what makes you passionate personally about small businesses? I love empowering entrepreneurs and small businesses, partly because when I was young, I started a business relied entirely on word of mouth. It was a key chain business where we braided lanyards and sell them, but it relied entirely on word of mouth, and it was all basically in person. We would go door to door, things like that. What I love about working at Amazon is, you know, we’re providing a great platform where you can take an idea and offer it to the world. My dad sold vintage guitars and amplifiers, and he, too was kind of limited by just the local region. And so imagine being able to sell your product or your idea sort of on the global stage. And that’s what I love about Amazon. They can grow their business by selling in our stores. Thank you, Steve, it’s lovely to hear how you’re using science and technology to improve Amazon’s customer experience, employee experience, small business leadership, obviously, and also the commitment to sustainability. We appreciate you sharing all of that with us. Thanks, Martin, it’s been a lot of fun.

Unknown Speaker 29:42
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