Bridging Gaps: Lean Manufacturing Meets Tech

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Back in 2015, Ashok foresaw the increasing importance of software engineers in driving product differentiation, and he was absolutely spot on. In this episode, we'll uncover many different aspects of this shift: your design approach mindset and moving from the project versus product approach. Think about that for a minute, and the power of qualitative data to the importance of making small bets and fostering an innovative culture. And we'll discuss what happens when a production line comes to a halt. It's more than just a pause in work. It's a moment that really tests an organization's culture. We'll talk about the leadership qualities essential for nurturing an environment of innovation and transforming people from mercenaries to missionaries. Do you have mercenaries or missionaries in your team? Plus, we'll learn why Ashok left a rock-star corporate career to start his own business and why he moved to Detroit and stayed. Join me as we unravel all of this and meet the man who's not just witnessing, but actively shaping the future of product design and technology. Ashok, welcome to the show.

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I was born in India. I grew up in the Middle East, my family were actually refugees in Desert Storm, and then, when we lived in Kuwait, and then I came to Canada as an international student, and that's where I would say maybe the career started, although my dad was a software engineer and my brothers and I were coding before we were 10, so you could argue one way or another.

And I went to school in a city called Hamilton, which is very similar to Detroit, very industrial, and worked as a forklift driver. And it's almost like every single job since then has been on a factory shop floor or has the lean manufacturing mindset in some way or another. I spent some time at a General Motors plant that was a partnership between General Motors and Suzuki called Cami Automotive. And rumor has it was one of the most efficient General Motors assembly plants, and one might surmise that it's because of a lot of the Japanese production influence that it has. We all had white shirts and blue pants; I had my name embroidered. My claim to fame there was that I shut the line down for like eight minutes when we were even running Sundays, and I learned a lot about how the Japanese culture kicks in. Like I had lost the company maybe five or six times what I got paid that entire year during that night, I was expecting to come in and put my stuff in a box and leave. And they did a very kind, non-judgmental, a sort of no-blame retrospective in a five whys exercise to figure out how this happened. And initially it was pointed at me of like, 'Hey, what did you do? How did that happen? Why is that?' He turned to my boss. They made some continuous improvement suggestions and he thanked me for my transparency. And we went back to work that day. And I then worked at an IoT company called Shoplogix that's based out of Toronto and also very rooted in Japanese or in manufacturing and helping manufacturers understanding what's going on in their plants. And so, I had to really study the Toyota Production System, Theory of Constraints. And I was always sort of the software person amongst the manufacturing folks. And I had to bridge back and forth to be really good at building the right products and helping them adopt those products the right way and getting into their mindset. So, I became a student of manufacturing there.

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And that really comes down to the mindset of the board and the executive team and how that flows down to what your staff look like in terms of manufacturing versus engineers. I was astonished to hear that Tesla has version numbers for their seats and versioning is something that you see way more in the software industry and less so in hardware, but the use of that term anyway, the other thing that I'd seen is that in terms of the team that they put together for the range extension. They combine not just the folks who are going to be working on the button that's on the screen that the user or the driver gets to decide what kind of if you want to go with the extended range mode or not. I've heard that they have folks working, not just on the screen, but the folks who work in the cloud to integrate that stuff into your apps, all the way down to folks who are materials engineers that work on the battery chemistry, and they all get to be put on one team to solve a customer problem, right? And I think anytime you use the word product, you want to be very clear as to who's it for and what's it for. So, who's the customer? And you have to be able to define them in some way. The smaller, the better initially. And then what problem is it solving? And this is as opposed to maybe the term project. It eliminates the silos. Like if you think about a traditional OEM, how many different countries, maybe even the folks that work on battery chemistry all the way through the folks who work on the touchscreen apps sit and how unlikely it is that they would have ever talked to each other. So, when you get all the cross-functional components together, or the constituents together, they're able to make decisions relatively more autonomously and be given the authority to go solve that problem. You're going way faster. And you're able to combine hardware and software very quickly to make these decisions. You're also able to place smaller bets to make sure this all connects together because what's not changing for Tesla or for one of the more traditional OEMs is there's a lot of integration that needs to happen between all these pieces in order for this problem to be solved for the customer. It's a huge assumption, though, as to whether those integrations are going to work or not, those handshakes between those components. But when you jam all those folks onto one team, they'll solve that really quickly. Versus like, there's going to be a bunch of contracts even that talk about what the integration points are going to look like. But when you realize that, "Oh, Hey, we had made an assumption here that doesn't actually hold true. We need to go change the design." Then, you don't want to have lawyers get involved and change the contract because your delivery team realized that there was an assumption. You want that collaboration to happen much faster and sort of give them a little bit more breathing room. That's maybe an example that's more tangible in this space in terms of how I would say digital transformation is not just the use of technology, but it's thinking in a different way and being enabled by technology and then using it to solve problems either for your customer or your internal operations and sometimes even just taking risk out of the decisions that you make.

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It's maybe not as great for effectiveness when there's a big paradigm shift happening, whether it's technology or BEV. And I think that those silos end up being kind of one of the bigger challenges, right? So, similar to that analogy of the range extender feature on that electric vehicle, I think that comes into play with many features across the board. Sometimes, it's even; you may have a leasing and financing team, and then you also have an e-commerce team as you're trying to sell vehicles, and for regulatory reasons, those folks have to work at technically different organizations. But the customer doesn't care about all that, right? When you're going to go buy a car, financing is just sort of part of the deal. Actually, financing has perpetuated its way into just other consumer goods too, with companies like Affirm. If you're buying like a big, you know, like a Peloton for your house, you can buy that on a leasing and financing plan. And it all kind of looks at the Peloton experience. And it's really hard to tell as a consumer that there are different departments coming together. It looks like one brand. And I think the more you can tell that different departments need to play as a consumer, and that's why there's a compromise in your experience, the less it feels like you're working with a truly digital or technology-enabled business.

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So, going back to your question around ideas, I think it falls very much into the first one, right? If you think about design thinking school, they talk about the importance of both divergent thinking and convergent thinking. And what that means in more layperson terms is when you're thinking divergently, you want all the ideas. It's quantity over quality. And initially, you're trying to get. As many ideas as possible, like put the bad ideas on there. Like, I just want to get the most number of sticky notes on this table. And then, so as humans, we almost need to force ourselves to sensor to, mute our sensors so that we can just come up with more ideas. And then it's almost doing a switch. Once you've been in the divergent mode to then into convergent mode where you say, "Okay, now we've got the quantity. Now let's pick from the quantity and prioritize which ones are the highest quality." So you're more likely to get ideas outside of the box if you separate that thinking versus, especially in this industry with there tend to be a high concentration of engineers, we focus a lot on precision and not being wrong and we're able to think about four steps down the line that's almost bad here. We just want to think in this immediate step and, like, let's get all the bad ideas, the good ideas, all of them before we start filtering; you could do this like three times cause there's three fundamentals that you got to like think diversionally and conversionally. The first one is your target audience or your customer. Like you can go serve everyone in the world, but there's probably some folks out there that are going to be more happy to know about what you have, whose problem is not just a headache. Their problem is a migraine for them. So initially like everyone wants to get to global domination and serve everything to everyone. And I think you've got to start by really identifying whose target audience we want to go after. And then again, do the divergent convergent where you say, "Hey, what are the various problems that we can solve for this customer?" And then converge that back down to, "Okay, out of all these problems, these are the headaches, but these are the migraines."

So, let's focus on the migraines, and let's just take the headache ones off the table. And then you do that a third time where you say, "Okay, we've got this short list of problems for this customer. What's the best solution? What's the most value we can bring them in the fastest amount of time." And the thing is, you have to paint with a crayon here where you're going to be wrong about the customer, maybe, but you can go test, you can go ask them questions. You can even go ask your own sales team, "Hey, who's likely in this category? Who's easier for us to get in front of?" There are many characteristics to prioritize a customer based on. The same thing with the problem; we can look at industry studies, but we can also go talk to five people, and we can go talk to five very point, like the five right people. If we did step one correctly and define those customers well, and I've done this so many times where by the time you talk to the sixth or seventh person, you're almost able to predict what they say if you ask them the questions the right way. I really don't like multiple-choice surveys. There's a science to doing contextual interviews or depth interviews to really understand your customer. And then it's getting kind of the broader team that's going to be helping with operationalizing the solution and understanding, "Hey, what can we get to market really quick?" And I think at this early stage, when we place really big bets, we want to be efficient. We want to look at the thing that we can use for all the vehicle lines, and we're going to get the volume discounts and the stuff that we're used to, right? And when you're making a $300 million, $500 million bet on a vehicle. Absolutely, it makes sense. I'm severely underqualified to advise the folks on new model line changes. On the other hand, if you're able to really get at the root of this and look at how you can spend $30,000 instead of $300 million to go learn more about what's the problem that's worth solving for a customer that's worth that we can get in front of that's big enough of a market size. That's a very viable solution. The cost of being wrong is really low, and the $30,000 to get viable piece of information you can do in like four weeks, right? To get to a definition.

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So, when I'm doing this test drive, there's someone in there with a checklist and asking me a bunch of questions. And that gets, for efficiency again, it gets synthesized and you lose so much of the emotion. Some of those things I bet you I was answering only because she asked. And other things, I was probably delighted, and there was, the emotion level was much higher or some things I was grimacing when I was complaining about in terms of the problem associated. But by the time that survey, multiplied by all the hundreds of people that you take it with, ends up with someone who can make a decision. It's been synthesized very quantitatively, which is very precise and it's important when you do things at that scale. But the qualitative analysis gets lost when you do go into multiple choice. And so, I think when you're thinking about placing smaller bets, the fail-fast mentality, if you will, that's a popular term, and you're losing only 30k on it. I would much, and it's an early stage of something that we know very little bit about rather than having a multiple choice, it's very efficient in going and talking to hundreds of people. I'd rather have a half an hour conversation, even recorded if I can, with just five or six people and then share that with the folks that are helping prioritize which problems are worth solving, share even with the folks who are building the solutions. There's nothing that can convert someone from mercenaries to missionaries, where my job isn't just coming in and getting a paycheck. It's something that I feel purpose around. There's nothing that's going to make that change in your team than helping them understand how bad something is today and how the work they're doing today is going to lead to that being much better for that person. And by multiplication, all the other folks out there that this could go help. And that's more likely to get folks out of bed in the morning. You're probably going to have way fewer HR issues on your list because folks are just wired and ready to go in terms of solving that problem for that customer and making a difference in the world.

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And they're having to choose today between, do I go work for a startup? Or do I get to work with this company whose values I'm aligned with? And it was the greatest thing for those initial folks to hear when they said, "Hey, I can go do the startup-like work and continue to work at Ford, a company that I find a lot of resonance with." And so we convinced everyone to go out to Ann Arbor, and we took over one of the old Google offices actually, and brought together design product folks, engineering folks, data folks, all in one team, which is a huge change culturally because usually you get designs handed down to a project manager, handed down to a technology team, and then put into deployment, and you could start to see how it's two to three years as opposed to 12 weeks when you have to do that versus having everyone sit in within a chair swivel of each other. We also make sure that someone from the line of business came and spent at least a couple of days with us. And so, we were able to get the best of sort of product development and the business context, all sitting in the same room, ideating, validating, prioritizing, developing, deploying, and we were able to prove out that this can happen in-house. And then, so, that has then spurred into some of that talent would decide, "Hey, I really enjoyed this thing that I'm working on. I'm going to leave Ford Labs and go and finish this with the department that brought this idea. And then folks in the department's going to say, "Hey, like, I feel like I'm really wired for this new line of work." so it's a place that you can go practice your discipline and hone these skills. With a little bit of extra air cover or authority and autonomy. And this was, I mean, many, many years ago Ford's hiring, retention, and software operations look a lot different than they were in 2015, 2016, when we started this. And I do believe that we provided the executives a lot of confidence about the possibilities of what can happen within Ford through Ford Labs. And then folks who work there have ended up kind of going, working at spin-out companies from Ford and other startup-like things, as well as really big initiatives and leading things that big LLCs like Ford Pro. So, that's kind of the way that I'm more familiar with. I've seen a lot more efficacy around proving it out in a small area, but going real deep with it. And then spreading that context and confidence to the broader enterprise versus trying to do a little bit of it, but spreading it across.

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