Big Technology Podcast - How Amazon Automated My Job: A Conversation With Elaine Kwon

Episode Date: April 14, 2021

Elaine Kwon was a vendor manager in Amazon's retail organization when the company started to turn her tasks over to machine learning in a program called "Hands Off The Wheel." She joins Big Technology Podcast to discuss how and why Amazon rolled the program out, how she and her fellow vendor managers reacted, and what it portends for the rest of us.

Hello, Elaine. Hey there. How are you doing? I'm good. Great to see you again. It's been, I think, probably two years. So we have a lot to catch up on. We do.

We do. Thanks for having me on. Oh, yeah. It's great to have you. I'll just pause for the ad break. And then we'll get started. Hello and welcome to the big technology podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. We talk a lot about automation on this show,

and today we're going to speak with someone who's seen it firsthand. Elaine Kwan is co-founder and partner a Quantify. And before that, she was a vendor manager at Amazon, and so it's white-collar automation program called Hands Off the Wheel, Get Off the Ground, and Go Operational. She joins us today to talk about her experiences and the implications automation might have on work and our global economy. welcome to the show. Thank you for having me, Alex. Thank you for coming on. We spoke in Seattle back when things were in person as I was trying to research what hands off the wheel was all about for my book, always day one. And the conversation just stuck with me and I've thought about it over and over as time goes on. So I thought, well, we talk theoretically about this stuff often on the show. Let's talk about how it actually works from a practical. standpoint. So I'm really stoked to have this conversation. Sounds good. And I would say the

implications that that has had even since 2016, which is when a lot of this got started, has been tremendous, even to this day. You know, even conversations I'm having with founders of companies even this week. Oh, wow. Yeah. That's that's wow. Okay. Yeah. And I'm very curious. So about how that's gone. So let's go back to the beginning quickly. You join Amazon in 24. as a vendor manager. So a vendor manager is in Amazon's retail organization. What does a vendor manager do inside Amazon? And in particular, what was the job description in 2014 before all the automation came in?

Oh, boy. Let's go down memory lane. Yeah, I know. I don't remember the exact, J.D. But what I can recall is that the role was a transition between what a traditional buying role entailed as well as what Amazon's demands entailed. And so, you know, in theory, the vendor manager is supposed to be the buyer. And there was a little bit of buying involved, especially within the fashion realm, which

is where I was working. But the conflict of the role itself came into being in the fact that at the heart of it, we weren't actually doing much buying. Now, if you're familiar with retail, by buying, by buying, sorry, you're going about to explain buying and you are on the phone with brands like in your case Gucci and Versace and I'm going to spitball here potentially saying you know we need this many handbags in these fulfillment centers at this price is that and the fulfillment center is obviously the warehouse that all this stuff gets stored and then shipped out to people once we hit

buy so is that broadly to the description of the job yes and I would say it even goes further which is, you know, if you're talking to a Macy's buyer, a Nordstrom buyer, you're going down skew by skew, color way by color way, line by line as to exactly what should be in your source. And that's really where this position harkens from. And I think where, you know, doing so at Amazon is really different or was really different back then, is that we still had that spirit. A lot of my peers came from that exact background, and that's what they were used to. But in reality, you know, a lot of Amazon's buying spirit is very much about the everything store, which is buy one and see if it sticks. Buy one of everything. See if it sticks.

And when you apply that to a role that had originated from this idea of curation, of taste, of being able to predict what future trends can and should be, you're at an impasse. And so I think that the vendor-manager role, it was a great learning experience. I really, really loved it. But it was really different than I think what perhaps others from the outside looking in might think it is. Right, right? Because if you're at Macy's, you're and you're a buyer, right?

Or you're managing vendors, right? The type of brands that come in, the Versace cheese. And the Gucci's, you're like, okay, I think this bag is going to be in style. I have limited shelf space. I'm going to buy these. And that's your job. At Amazon, you're dealing with these. uh, uh, uh, fulfillment centers that can fit an entire NFL's worth of football games on the land

that's in there. The limit of the Sundays. Yeah. So you're just out there buying like crazy and, and, uh, are and then seeing what the internet demands when they are on that site. And that's the first party retail, right? So Amazon just stocks products in these warehouses and then people go ahead and hit buy on their computer and then they get shipped out.

Yes, I think the going idea, the going thought process back then was that if we, you know, we're Amazon and at the time, we don't really care about being profitable. We just want to be the best e-commerce site in the world. So the customer will know what they want. So how about we just have everything and they'll tell us what should sell. That was the going thought process behind it. Now, where things changed and where we are, today, I would say it really started in 2016, a couple years later, where Amazon realized that they had to start valuing profitability a lot more than they had before. And, you know, we can't hold it against them. Every company must, you know, no, let me rephrase that. No company can shrink our profitability forever, right? And I think Amazon had the privilege of doing that for as long as it did. But a lot of things started changing and coming down the pipe in 2016, where you start realizing, okay, you know, there's a lot of inventory sitting at these warehouses because we

decided to buy one of everything. A lot of it isn't going anywhere. What do we start doing about that? Yeah. And so this sort of stems with Jeff Bezos telling investors, if you're going to buy Amazon, you're in it for the long haul. We're not going to, you know, generate profits right away. We're investing. And that's why Amazon's multiple, right, when you look at profit and and its stock prices and still in the stratosphere. It's wild. So let's go back to the practical side of these things. So we're going to get to the automation.

But, you know, while you're doing the job, how are you placing the orders? Are you like in a software tool where you're like, you know, basically, are you in Excel, are you in an Amazon software tool where you're like locking the orders and making forecasts and are you on the phone with these brands and saying, okay, this is how we want to do it? It's like, what does this job look like to you? from a practical standpoint when you're doing buying. Yeah, so a little bit of everything you just said. You know, every company is different.

You know, I learned that back then, working with all these brands, and still very much is true today, even with the proliferation of so many more D to C brands all over the Internet. But every single brand's different. And so, you know, you spend some time working with your portfolio of brands, understanding what they're trying to, what their goals are, and then ultimately how Amazon can, fit into that. And it's a little bit of push and pull. Now, for a lot of brands, it'll often be

a push from my side, meaning, hey, I really want you to grow this much in order to do that. These are all the things that we have to do or want to do. And again, so what would those things be? I mean, price negotiation or sometimes price negotiations, sometimes preparing for peak seasons in advance and trying to be strategic about it. Sometimes it's a matter of, even just, you know, inventory logistics excellence, right, understanding that, hey, we're opening up a new fulfillment center in this region of the country. We want to make sure that your products are there. Let's make certain moves supply chain-wise. So it involved every aspect of what it means to thrive within the e-commerce space today. But I think where it got difficult

is that, again, as Amazon realized, we got, we have to keep more of the money that we're actually making here. You know, a lot of things started to change. Meaning even that role, like the vendor manager's role or what that team's directives were. They started, you know, one of their new goals where we have to become more profitable. Our category of products has to become more profitable. Our transactions, every single one is now being measured, you know, with a new profitability standpoint. And so that's also where, you know, when I'm sitting in a meeting with a brand, it's a lot easier to talk when all of us are on the same, you know, page. to grow top line revenue. Everybody generally wants that. It's a very different conversation

when I'm sitting there and saying, I need you to give me a better price. I need you to give me X dollars in funding or I need you to make a big change in your processes in order to accommodate what I'm trying to do here. So it starts changing a lot of discussion. And I think that's where, you know, that's where we are today, which is that there is very little trust in this environment, especially when, you know, I mean, you're talking about even multinational publicly traded brands that, you know, everyone knows about, even they struggle when it comes to negotiating with Amazon because, frankly, they, they don't like to compromise. Yeah. And as you're doing this, they're collecting the data, right? They're collecting the data

on what the company bought, what it was priced at, what it sold. that and what demand was for what products and all that stuff and then all of a sudden I think probably around the time that you started there are some folks on the machine learning side inside Amazon that say hey what if we you know actually turn this over to automation to make sure that we can do this you know as efficiently as possible with the best margins they start calling it Project Yoda from what I heard like some people are like instead of us doing this as humans, why don't we use the force? And the force was machine learning.

That's what happens when you put a bunch of computer nerds in charge of the stuff. It always comes back to Star Wars. And eventually it starts, so they start the machines, I imagine, start to get good enough where the forecasting and the prices that they want, the negotiation range, becomes good enough where they think they can start to turn some of it over to that machine learning stuff. So now let's go back, like to your, from your perspective on the ground. Can I make a quick comment about what you said, though? Yeah.

So that's the funny thing. Even when I was an employee there, I had very similar thoughts to what you just said. Really? But the reality is, and this isn't just applicable to Amazon, but many other companies, many other industries as well, is that, you know, a lot of automation and even to, I would say, to a degree machine learning in many of these pieces of technology is still incredibly it's not ready to operate on its own or in a mass scale. And that definitely goes for this situation that we're talking about when it comes to Amazon. Yeah. So let's hear the story about how this stuff starts to become operational and sort of the pros and cons of it. So I love to

hear like from your perspective at the beginning, when did you start to hear that some automation might come into that process that you had in terms of buying and ordering from these brands? For those interested, I remember first hearing the phrase hands off the wheel. You know, I think it was late 2015 or early 2016. And it was interesting because it was, it was discussed very loss of fair, very nonchalantly, as if, you know. Don't worry about these machines. Exactly. It's like, you know, like this is just.

something that's happening. It's going to change, but it's no big deal. But I feel like if if anyone is taking a critical look at the situation, you can see the writing on the wall, which is stuff's changing. The priorities that we had are changing. What does this mean for the work that we used to do in a particular way? So, you know, the very first thing that they automated were promotions, the creation, management, and execution of things like discounts, you know, pricing changes, um, coupons, that sort of thing. And, um, it felt pretty innocuous. You know, I think most people were like, okay, you know, like this is just a new tech change, no big deal. But at least for me, I kind of looked at it and I'm like, all right, this may not

seem like a big deal to some, but for me, I kind of saw that as, okay, they're, they're trying to make some of what people are doing every day, uh, no longer part of their job. So what's, what's next? Because this is not just the, this is just a tip of the iceberg, right? And so I remember seeing that. I remember having conversations with brands introducing them to the tool. And one caveat I think we should make is that when we talk about automation at Amazon, we're not talking about automating something for everyone, for everybody. We're talking about automation so that Amazon no longer has the responsibility of having to do a certain thing. Yeah. So the brands on the other end might still have to do the inputs, but Amazon would basically take the human activity out.

Exactly. They no longer have to staff the person, the people, the team, the overhead in order to accommodate what was happening manually before. And in fact, what ended up happening and is still the case to the day is that they pushed a lot of that work onto brands, manufacturers, and sellers with very little, actually no forewarning, very little training, very little communication. They just kind of woke up one day if they logged into their Amazon portal and they realized, oh, what's this new thing? You're telling me that all, and it was especially a bit of a rude awakening for, you know,

brands that, let's say you had already committed a significant sum of money to Amazon. And you, let's say you've already paid a certain amount of money to Amazon. Amazon for the year saying, hey, I want to work with you closely and fund our partnerships so that we can have a really big, beautiful campaign during Mother's Day or a huge promotion during holiday this year. Now, all of a sudden, you have to do that work yourself. You're not being given much help at all. And in many cases, you may have to pay for that promotion yourself. And so, you know, it was a bit of a rude awakening, I think, to say the least. right and so just like taking it back to a practical level so these brands would be working with you as a vendor manager and that was your job right was basically like we'll promote you on the site this day and we want x amount of inventory and then you know somebody who's on the other i'll just use a brand let's not i know it's not necessarily the one but i'm just going to use it as an example somebody who's on the other line at Gucci you know who's been speaking with you now all of a sudden you know the whole idea of when they're going to get promoted on the

site how much inventory Amazon needs and what fulfillment centers and at what price and you know even the negotiation in terms of price in some areas ends up turning from human to a portal that they would log into because the machine learning is doing this on the back end is that right yeah I would say so and certain things came more gradually than others but the long story the long story short is essentially that that's exactly right even to this day, you know, we have a great partnership with Amazon, you know, my company, that is, and we talk to them all the time, but, you know, they're very, they're very open and honest about their limitations as people now in a way that I think we felt a bit uncomfortable to do so back then. And so now they're just very transparent. They're like, I have no control over that. I have no influence over this. I have no way of helping you with this. And sometimes it baffles, you know, kind of, companies on the other side because they're like, wait a second, you're actually charge of this thing, of whatever this thing is that we're discussing. What do you mean you can't change it? What do you mean you can't make an exception for a mistake that's actually wrong? And that's, that's the conversation I'm having a lot very often, unfortunately. Yeah, because overall, it seems to me that they said, okay, our algorithms are going to do the best possible job for the least possible overhead, figuring out how to maximize profits, as you mentioned, and get the right stuff into the fulfillment centers

at the right time at the right price? Yeah. Yeah. Oh, well, sorry, go ahead. Oh, no. You hit up a day. I love that you brought up the ordering side because that is, that's probably the biggest bane of everyone's existence when it comes to some of the automations.

That's happen. Right. So you would send like a purchase order back in the day for a certain amount of inventory. And now what does it just show up in people's inboxes? So they always showed up in people's inboxes, but there was a person who would send it before. But there was usually many people who touched it before. You know, usually it would involve me, you know, as someone from the vendor manager team, it would involve the in-stock management team whose entire job was to create, manage, watch,

and, you know, organize all the POs that are happening at any second. And so there used to actually be a set of people. that you could talk to. If you said, hey, this new thing is happening, a new trend that we're watching in the market. We want to make sure that we buy enough of X, Y, and Z product for this upcoming season. You could actually do that, but not anymore. Not once hands off the wheel really got implemented and not once it hit inventory and ordering algorithms. So everything suddenly became, no, we can't touch it anymore. Our algorithm is either going to order it or it's not, we can only hope to try to influence it and hope that what we, kind of like

the poking and prodding, will influence the animal to behave in a certain way, but we actually have no way of guaranteeing whether certain changes will happen. Okay, after the break, I want to speak with you about really the human side of this, how you and your colleagues reacted and, you know, what Amazon did to all the people who's work at automated. So folks, hang on for just a moment. We'll go to break and we'll be back right after this. Hey, everyone. Let me tell you about The Hustle Daily Show, a podcast filled with business, tech news,

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And we're back here for the second half of the big technology podcast with Alain Kwan, former vendor manager at Amazon who watched the automation program hands off the wheel, which is I talked about Project Yoda. It eventually turns into hands off the wheel where the vendor managers literally took their hands off the wheel and let the machine learning do the work. And she is now co-founder and partner at Kwan. Montified, which is a company up in Seattle, which I'm sure we're going to hear a little bit more about in the second half here. So let's go back to your reaction when you start to see some of the stuff go down.

You know, I know that Amazon employees are all pretty close to each other. What happened like at a happy hour or dinner or, you know, just kind of hanging out in the office when you and your colleagues start to see some of the stuff that you were doing end up being turned over to machines where you all like. Was there like a moment of realization where it was like, oh, the machine learning is in charge anymore? And it's kind of, oh, it's our hands off of the wheel. There was mixed reactions. I think some folks were righteously, you know, frustrated, annoyed, angry that carefully laid out, thoughtfully laid out plans were suddenly out of their hands.

Some of them, I think, including myself, started realizing. okay, this is the end of the line, essentially. You know, it's not that this role is going to disappear forever. And it hasn't. There are still vendor management teams in existence, but this role is going to change a lot. You know, instead of having full autonomy over how these brands will be projected on our site in terms of, you know, what we're going to sell, how we're going to sell it, what types of everything down to, you know, just how they're going to be merchandised on

on a detail page, all of that is going away. So what does that mean for me? And I know that for myself, one of the reasons why I took the job was because of that autonomy, was because of the freedom and the ability to really build these partnerships and say, how are we going to help each other achieve amazing growth together? When you start taking away bit by bit, all the tools that the team has in order to achieve any of those goals. Now you, it starts feeling more and more, what's the best way to describe it. They're still being asked to hit astronomical goals, but you have very, very little ability to

change anything to achieve them, if that makes sense. And that, that just felt like, you know, for me, you know, that's not something that I think spending my time on would be worth. So that's when I started realizing, all right, we need to, we need to find a new one. to help brands grow, frankly. And that's actually where I started thinking about the future of e-commerce. What does this mean? Because this is not just Amazon. You know, every single e-commerce marketplace is trying to do both things.

They're trying to grow and trying to scale how they can show the diversity of all their products online. That's not a small task. So this is not just an Amazon problem we're talking about. Amazon may have carried it out in a certain way. But, you know, Zolando, T-Mall, I'll leave a lot. Lava Mercado Libre, you're talking about the fact that all these companies are fighting to figure out how do we show this product off in the best way possible to convince you, customer,

to buy it from us while still scaling how we do all this work on the back end to cost us as little as possible. Right. And Zalondo, the German e-commerce company that you mentioned actually hired Ralph Hebrick, who headed up this whole program inside Amazon. So now he's off. And I'm sure his minions are off doing the same thing in other companies. Oh, yeah.

Oh, yeah. We're seeing it happen. It's very much happening. Yeah. Yeah. And Elaine, one of the remarkable things that I find when I spoke with you about this and some of your colleagues or former colleagues is that everybody who's experienced this says, oh, it actually made a lot of sense. And there's not a lot of ill will toward Amazon, even though, like, you know, people are, when people speak about automation and how, you know, work has been automated, you know, they. they are fearful of what happens to the worker and you were the worker but yet you maintain like a

pretty sunny attitude about that can you explain a little bit more about your your feelings you know i'm i i think i'm a i'm a fairly practical person so you know even back then when i saw what was happening i didn't get mad about it i wasn't angry about it myself it was just more like all right this makes sense i understand i understand why this is happening now is this going to hurt some people, some businesses, absolutely. But for myself, I kind of looked at it as an opportunity because, you know, these are what e-commerce marketplaces and companies, retailers are doing in order to survive themselves. That doesn't mean that the brands and manufacturers and sellers are all alone by themselves without any aid. That's where my thoughts went, which is, okay,

this is going to be a growing chasm in this industry. How do we bridge that gap? What do we need to do in order to solve this? Because this problem is maybe small today, but it is going to grow. And sure enough, you know, five, six years later, here we are. And like I said, even this week, I've had three conversations, you know, with different CEOs about issues related to stymie or I would say stemming from this exact thing. Wow. Okay. Yeah.

And, okay, now that as we're talking about it, I just grow kind of curious. So if I'm a vendor manager inside Amazon, how does this stuff show up in my, does it just, is it like an automate button in my tool that I use to buy? What did it look like from your own? How does the buying happen? Well, like, yeah, when you're turning stuff over to the machines. Yeah. Like, was it an automate button or was it just like, okay, that task that you were doing, you're not doing anymore? Yeah, there were, there were steps that we no longer did anymore, you know, before we would actually.

go, like I said, we would go through line by line and actually talk about products, what they were, what they were going to offer to the customer and decide, do we want to buy it, yes or no. Now, and again, not super familiar with how the tools may have changed, but my understanding, my understanding and what we saw happen back then was that, you know, the vendor, the brand now creates their new product listings, whatever they want to sell on Amazon. They create them on their own. They do all that. work by themselves, they submit it if once it's processed and created by Amazon, which is a process that, you know, the vendor manager doesn't touch anymore, then the algorithm will decide

based on the product information submitted, whether or not they want to buy. Unbelievable. Yeah. And one of the things I heard, I wonder if you experienced this was that the company like set hands off the wheel goals where like a certain person, oh, you're smiling. So, so, well, go ahead. I mean, you're bringing back. I'm sorry. I'm sorry. Some of this is fun. I'm sure some of this is less. Some of these things I haven't thought about in quite a while. But yeah, you're absolutely right. They set goals. You know, which again, makes sense. Like the percentage of stuff that should have been automated. Yes. Which again, makes sense. If you're if you're leading a team and you're trying to hit big changes and provide benchmarks for where the team should be. But in this case, the benchmarks are how much less of your job we want you to do. Yeah. Yeah. How much more we want you to teach or tell these vendors and brands do your job instead?

Yeah. I remember speaking one of your former colleagues who told me basically as soon as they had this meeting. There was one year where apparently leadership handed down these major hands off the wheel goals. And then this person sitting in this meeting was basically like, all right, it's time for us to find new jobs as a joke. But it turned out to be kind of serious. Yeah. Yeah. And the interesting thing that I found was a lot of, you know, and, you know, you can fact check me on this. But like, from my understanding, Amazon didn't like go out and, you know, do mass firings of vendor managers. A lot of people ended up moving into different roles inside the company, product manager and program manager.

So what happened there? Correct, correct. I would say, you know, everyone's part. It's very much sort of choose your own adventure. You know, they weren't out to, at least from my experience, they weren't out to fire. anybody. It was, I mean, the people that worked in these roles, I'd say for the most part, very talented, very smart, very driven, great. And specifically at Amazon, there's this idea that if you're hired into Amazon, you know, you're capable enough to serve in other roles,

other teams, other functions, even if you may not have a ton of experience in that particular, with that particular skill set yet. And so there was a cool, there was a cool opportunity for many that was, you know what, I'm going to go, you know, interview some other teams internally and see if there's a different role that might, you know, appeal to me. So that's what I would say many did. A small handful stayed behind within the team itself. You know, folks like me, I ended up getting poached by a startup at the time and kind of took that route, all the while still thinking and obsessed with this problem, which is why we're here today and what I'm, you know, what I've been working in ever since.

But I would say those, it wasn't, it wasn't a wide public announcement, but I think everyone again kind of realized, okay, this may be the end of an era. And so take it, you know, keep your eyes open and start thinking about what your next path really looks like. Yeah. And this is sort of something that's pretty amazing to me about what happened in Amazon. And I think other companies should really take note when they, they start to do this because there is there has been this feeling of like okay well automation's

going to come in and then people are gone but in reality it's not really the case and what amazon did was ended up putting them i mean project manager and program manager jobs are what i think of as essentially professional inventors inside the company people who are there to to shepherd along new products uh and uh and build the next new thing for amazon and it's interesting okay they were working on this one thing machine learning comes in now all of a sudden and, you know, help the company grow in another way. And that's, I think, one of the, you know, magical parts of the Amazon work culture that gets overlooked.

And there's a lot of criticism of Amazon. A lot of it, you know, definitely well deserved. But there's definitely some business brilliance there. And this is a big part of it. And I think, like, one of my favorite stories that I came across when I was writing always day one was Dilip Kumar, who was running pricing and promotions inside Amazon, right? Probably something close to what you were doing. And he goes to spend, after, you know, in maybe 2015, he goes to spend a year, year and a half, shadowing Jeff Bezos as his technical advisor.

He comes out, the thing's on its way to being automated. He's not going back there. So he ends up getting together with a bunch of people from the retail organization and building Amazon Go, which is the checkout free retail store. That's going to be a major part of Amazon's, you know, brick and mortar in real life shopping. Yeah, the first one is actually one block from me right now. So you're right in South Lake Union. Yeah. In Seattle. Yeah. And it is like people ask like, oh, how does Amazon reinvent itself so often? And this is I mean, this is the key example in my mind when it comes to the way that the company works.

I agree. I think that there's a lot of a lot of really interesting and very applicable principles that, you know, even I've taken into my own business practices. But there's also a lot of warnings too. I mean, I would be the first person to tell you that guess what? There's still a vendor management team. in existence. The problem, and this is again, my two cents, take it or leave it, but the problem in my opinion is that there are so few of them that are now, you know, still expected to manage huge goals, huge portfolios and brands. But because they've been given these hands-off-the-wheel automated tools,

I think the expectation was, well, you should have no problem, you know, managing a hundred times what people used to before because you won't be doing all of these things that people used to have to. But the problem is, is that automation or any tool that is automating a piece of work is only as good as the complexity of the rules designed within it. And the fact of the matter is Amazon has so many products, the diversity, the range of products really cannot even be fathomed. And so every rule we've seen that goes into part of, you know, whatever tools being automated, it makes mistakes. It makes a lot of mistakes. I mean, even right now, we're finding that thousands and thousands

of products are being mistakenly flagged as pesticides because someone implemented a rule to look for anything that could be a pesticide and suppress it, keep it off the site. And now you have pearl accessories, headbands, hand creams that are being, or even T-shirts with Silver Durr to help sweatproof, you know, sort of experiences, they're all being flagged as pesticides. And so, you know, I give this example to illustrate this idea that, you know, there is a lot that can be automated, but when you're dealing with the level of scale that Amazon's currently operating at, even the smallest rule can have devastating effects, if not managed incredibly well. Yeah, that's what for my, from my conversations with the company, it's the people, the vendor

managers really became auditors. So they went from making the orders to like auditing the system and making sure that it's ordering appropriately. And I remember speaking with Ralph Huberk, who I mentioned before, they had a machine learning who's since left. And he talked about how like, you know, they couldn't get the order of white socks right. And they were trying to figure out what was going on. And there was like, okay, the vendor manager went in and audited the system and found that they had 56 different ways of writing white socks. And so the whole, you know, machinery just ended up blowing up. because of that. So it does totally change the job. And the scale is also really interesting. I think he mentioned that people were going from, vendor managers were going from, you know, managing like

a thousand products to a hundred thousand. And then was then followed up and was like, well, that's not the exact number. I was just using that to illustrate the scale. But really is a hundred times what they were doing for. And there's no way to keep that the precision that you would have had otherwise. I would agree. So what is this portent for the rest of the economy? I mean, the one interesting thing I find about the tech giants when it comes to machine learning is that they've had in-house research organizations for much longer than anybody else. And a lot of them have the granddaddies of the field. You know, Facebook has Jan Lacoon, who basically is the guy who helped deep learning, you know, take off in a way people used to laugh at him. They said

that technique will never work. Then it worked and Facebook hired him right away. Google has, I think his name is Jeff Hinton, who's another one of the originators. And then Ralph, of course, you know, came to Amazon. So these companies all had a head start. And I wonder, is this something that ends up coming to the rest of the economy? Can people who aren't working for the tech giants anticipate this, you know, in their workplace at some point? Yeah, that's a great question. And I think it's one that I have very frequently because as you can imagine, you know, our company is all about a set. We are here to help all the brands, manufacturers, and sellers of the world thrive within these spaces. It can be done, but it is incredibly, it's incredibly difficult for

a single brand or manufacturer to do alone exactly because of what you just described, which is, you know, very few companies have the software, the data, the expertise, as well as the know-how to navigate what is actually a maze for each of their accounts. Imagine a brand that sells on Amazon, Walmart, Solando, Timo, and Rakuten, which is just a fraction of the incredible e-commerce marketplace that they could be selling. Let's just say, just five. Each of those five is its own maze in that each of these companies were built independently from one another, all of their algorithms on the back end are very unique and specific to that marketplace

and that particular pieces of software. And so from the consumer standpoint, it feels like it's pretty similar. You can go from Zolando to Amazon and you're like, all right, I search for something, I add to cart, I'm done. But that's where the similarities pretty much stop. And so for, you know, we talk to and work with, you know, again, multinational, traded companies. I would say it's kind of interesting because they tend to be the first to realize we don't have what it takes to do this. So they're usually the first to reach out

and work with companies like ours. I would say medium-sized businesses, depending on the leadership, will reach out immediately or they'll usually try it on their own. And when things start getting difficult, stagnating or failing for whatever reason, that's when they realize we need help. And then last but not least, we're seeing a proliferation of awesome small businesses, startups, VC back businesses that realize that they know enough to realize they don't know enough to do this internally. And so that's usually when they reach out. But it does take, frankly, the best defense is a killer offense, right? And I feel like, you know, it's a combination of data analysis and expertise that comes from having an actual team of people that have done

this, not just ones, not just twice, but hundreds of times over many, many years. combined with software. And that's what it takes today. So you've built a company to help other retailers navigate this stuff. Exactly. Which is important. I mean, I imagine it's a very big opportunity. Now, when it comes to just the idea that automation can make its way into the workforce or into workplaces beyond these tech giants, do you anticipate that that's going to happen?

Are you anticipating using it in your own workflows? where do you think automation as a whole goes, you know, from where it is today? Because right now it seems to be in some small number of companies, but a lot of people are predicting it's going to go much broader. I think the question that we actually ask ourselves is, what isn't going to get automated or what's going to get automated last? That's actually the conversations we have internally. Yeah.

Because, you know, when you start, especially when you're in the position we're in, which is we work with incredible companies, but many of them, enough to be able to see a lot of the trends that are happening. And when you start seeing that, you realize, okay, there is, everyone's different, but also a lot of what's happening is not unique. And I think that's really where the question is, is like, what's the last thing that's going to be automated? What's the, in my opinion, it'll likely be the most difficult thing, which is critical thinking, adapting to new pieces of information and data. I would say COVID has very much thrown all of the, forecasting that was run by machine learning into the drain.

And that's been one of the really fun, difficult, but very interesting challenges that we've been helping brands with, which is, how do you figure out what's going to happen when no one knows what's going to happen? And that's been, I would say, it just kind of goes to show you again that I feel like it's a long while yet before we see the level of automation that I think is depicted in movies and television at times, but it's coming. It's coming and it's happening step by step. How should people think about, I mean, you've obviously adjusted pretty well to having gone through this experience. How do you think people should look out for, you know, the potential

that stuff that they do might be automated and what type of skills do you think they should be investing in to make sure that they're able to thrive, you know, in a situation like this? Yeah, I was actually speaking to a graduating class at a university recently. that asked me exactly that, which is, man. Let's do the commencement address. Yeah. Exactly, right? But, like, you know, young people are wondering exactly that.

They see all the changes that are happening. And they're wondering, shoot, you know, do I have what it takes to truly make it today? What do I need to know that perhaps I wasn't taught in school? And frankly, there are two things. One is critical thinking, which I briefly mentioned before. But that is actually the number one trait that I know. For example, we hire and we work in the business of automating a lot of things for others. But that is one factor that, frankly, most machines still have not yet even come close to touching.

Being able to say, actually look at a situation with all of the nuances and complexities at hand and be able to communicate real time what's happening and what should happen, And that's another level that, again, you know, I think is going to be in demand for quite a while yet. The second of which is also may sound counterintuitive, but it's actually the ability to build trust. And the reason why I say that is because as long as companies are still being run by people, the number one detracting factor that I see coming between two companies or, you know, different partnerships is really whether or not the companies understand one another and are able to trust one another. And so I'd say if you have the ability to

connect and truly build trust in a way that goes deeper than just superficial connection, you can find amazing opportunity to survive beyond the age of automation. Yeah, I love how you said as long as companies are still being run by people. Who knows? Maybe, you know, one day. That'll be different. That'll be interesting. Maybe you and I will just give it over the robots. I'll sit on the side and take notes for the machine. Right. I think there's some book that talks about like, you know, automation, communism paradise or whatever it is where like, just let the machines do the work and we get to hang back and drink martinis, which, okay, I'll be into that. Oh, man.

Long term, are you, are you bullish on the future of work and on, you know, people's ability to continue to find, you know, meaningful employment despite the machines? or are you betting on the machines basically kicking our butts? That is a great question. I certainly hope they don't kick our butts, but I do think that I think the future of work is going to require that everyone, every job, every function that we all have is going to incorporate a certain level of technology that we never have had before.

And I think that even the way that we are currently have adapted to working today is just one step in that direction. But even what's, let's say, what we would call traditionally non-technological jobs, like, you know, being a UPS delivery driver, even that today incorporates a level of using technology, you know, scanners, taking digital photos and automated thumbprints. I mean, they are using technology in a way that they didn't before. And I think that we're only going to see that increase to the point where, you know, again, the things that humans are left doing or the things that only. humans can do. Right. Is Amazon going to do this drone delivery thing or was that bull? I don't know. I don't let you know if I find out, but I'm not sure. I haven't made a lot of progress since Jeff Bezos made that flashy announcement. He's going to leave the company before it

happens. So yeah. All right. Great. How can people get in touch with you or learn more about what you're doing at Quantified? Yeah. Feel free to, you know, I would say look me up on LinkedIn. My name is Elaine Kwan. I'm the managing partner at Quantified. And you can reach us on our website as well, Quantified.com. That's with K-W-O-N-T-I-F-I-E-D. Awesome. Elaine, so great to catch up. It's been too long, and I'm really glad we had an opportunity to chat again.

I agree. This is a lot of fun. Thanks, Alex. Super fun. Thank you. All right, everybody, Elaine Kwan, joining us on the Big Technology podcast. It was really great to have her on. And it's great to have you listening.

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