The Fourth Manufacturing Revolution | Geoff Tuff | Exponential Manufacturing

[Music] I am here to talk about the fourth Industrial Revolution who's heard of such a thing all right you've all heard about it and I'm actually not going to talk about the fourth Industrial Revolution for two reasons one I think it's a misnomer and I'm going to come back and talk about that in a moment but but secondly I think actually it's less interesting to talk about what's going on with the Revolution than it is what to do about it how do we act to it and how to make sense of everything that's coming at us in this time that is actually different from anything else that we have seen before so my hope over the next roughly twenty five thirty minutes or so is to hit on just two very simple practical pieces of advice that all of you can keep in your minds over the course of the next three days you're going to be bombarded with information and bombarded with all sorts of interesting and scary and hopefully energetic information about the way the world is changing but I'm trying to set in place just two fundamentals that as you carry as you go through those experiences and you think about how to bring this back into your businesses and actually make money from it both in the short term in the long term you can so here's the misnomer bit I'm sure all of you have seen some version of this slide before and depending on how you describe or set time frames around previous industrial revolutions we have gone through roughly three other times of pretty significant change when the world around us especially for manufacturers has changed and we're going through that now you can call the current time the connected revolution you can call it the smart automation revolution you can call it a lot of different things but what's fundamentally different now and what makes this not just another revolution and not not simply a continuous part of what you see on this slide is the pace of change in the past every single time we've gone through one of these revolutions information has come out at us at a reasonable pace we can look at see what's happening in the world we can react we can shift our operations accordingly and we can get on with things and that's not to make that's not to make sound like it's easy it has always been hard to react to change but we have been able to handle it because things have progressed in a reasonably linear fashion you're going to be hearing lots more about Exponential's and the impact of exponential trends over the course of the next three days but that's happening now and I can tell you that you won't be able to keep up every single one of us myself included are not wired to keep up and to think about the nature of change in the pace of change and to be able to ranked and react and shift our operations accordingly we can't act and react like we have in the past it's just moving too fast and so my hope over the course of these days as you look for those practical pieces of advice is that you not try to absorb every single bit of information about technologies coming at you but that you see it all through a lens of practical application because the reality is most of you are not going to last that long either in your jobs or at your company because your companies won't exist again many of you have probably seen some version of this slide before if you can't read it from the back there this is the average life the lifespan of a company listed in the S&P 500 so it goes back to 1960 I believe and it's over a seven-year rolling average so it's it's not just simply what happened in that individual year there are certainly some cycles to this but I'm guessing all of you can see the downward trend and where as it used to be a great gig 60 years ago or 70 years ago 60 to be in the S&P 500 cuz you knew you'd be around for 50 or 60 years it's not that great a gig anymore if you look at where we're falling today we're what roughly 20 years is the average lifespan and that's going down I actually don't know how to describe the uptick here at the end we'll see if that ends up taking place but that's the that's the reality of the world we're living in and I hope that every single one of you working as most of you do in large established really successful corporations understand that what's happened in the past isn't going to be what happens in the future and the reason that this is on a steady decline and why it's on such a precipitous decline over the next few years is because of the nature of exponential change and the fact that we are not wired as humans to keep up with it and to do something about it so I want to start with a graphic which for those of you that know me and I apologize for the locked-off l there are probably bored of hearing me talk about but this is a bit of research that we did about five years ago Harvard Business Review was nice enough to give us the cover of their magazine about the observation that we had at the time I am NOT going to bore you with the details of how we did it and what we did and how we did it and what the what the totality of the results were but the key punchline that came out of that research was that if you want to out-earn your peers in the capital markets if you're a big established public company and you're looking for ways to demonstrate to investors that you're great at innovation you can't just do one or two moonshots you have to be able to work across a whole a whole spectrum of levels of ambition behind innovation and what we discovered through the research is that on average across industries across companies etc if you're spending about 70% of your time innovating in your core business so taking your existing set of products and optimizing them for your existing customers sometimes edging a little bit into new customer segments or trying new things but 70% of your activity in the core 20% in the adjacent space so stretching your asset base trying to serve customers in different ways or trying new technologies to serve existing customers and 10% in that transformational space where you're genuinely trying to discover customer and market needs before they can ever tell you them themselves if that's if you can get that balance right and as I said on average was 70 2010 interestingly the return from that innovation system was virtually the inverse where 70% of what you earn from your innovation system over a three to five year period came from the few big bets in the transformational space 20% in the adjacent space from the adjacent space and 10% from the core so this is what our research told us five years ago and there's all sorts of challenges I have with the research this is now been called the golden ratio of innovation but actually the point of the article was to say have a strategic conversation to decide what the right ratio is for you just follow the 70-20-10 blindly but I discovered too and I think now increasingly a third what I'll call universal rule as I've been out talking to executive teams and exploring companies on on this topic the first is that no one has any clue where they're spend is today like no joke even even the best financially managed companies in the world you go to the executive team you say where do you think you're focusing your attention today just give me an estimate let's not pull out the books and look at the numbers it's give me an estimate and the guesses are all over the board it's just not something that a lot of companies track and related to that the second universal rule I've discovered is every one way overestimates the degree to which they're operating outside their core trying to innovate outside their core business and we actually sometimes people asked us to come in and root around and try to figure out what the balance of the portfolio is today and I can tell you the times we've done that it's been like 95 or 96 or 97 percent of the activity and the spend in the system is focused on the core but the only a few little attempts to stretch into the adjacent space and very very rarely get into the transformational space so interesting bit of research from five years ago and it hasn't changed that much the practical application of this if you just if we want to think about how to frame the opportunities in front of you in this so-called fourth Industrial Revolution is this simplified version of this chart and so the way to look at this is you just draw a line from the top left to the bottom right here and it cuts in it splits the world in half between two types of opportunities you can be pursuing below the line you've got the known or the knowable opportunities the stuff that you can go into a market and say to a customer a prospective customer do you like this how much will you buy and what will you pay and you're going to get pretty good data back they may not always tell you the truth we have pretty good data because it's a world that they can imagine it's a it's a market that exists today and for this you can use all sorts of traditional management techniques like quantitative surveys and getting information from your sales force and whatever you want to use to get signals as to what's going to be relevant in the market because it's in the here and now the stuff above the line though by definition is unknown and in some cases unknowable so the top right of this of this matrix is defined by the notion that customers can't even predict themselves what they're going to be looking for because they can't imagine the way that the world is going to change where they can't imagine the way that their operations are going to change and what we've discovered over time and it's not exactly a blinding insight but it but it happens in every single company we talk to is you cannot ask your existing business units and businesses that have been structured to do the below-the-line stuff for years and years and usually get pretty good at it to go try to work above the line you just can't it takes different people to take different metrics it takes different funding mechanisms and that's all fine and good when in the world of five years ago like 85 or 90% of what you need to do is below the line that's fine if 85 percent of what you're focused on is in the here-and-now you don't need new and different structures you don't need ways of interpreting the signals from the world to try to identify where opportunities are but that has changed and so the third universal rule that I think I'm now starting to understand is my research is old and bad 70-20-10 no longer applies and I have no idea what the right numbers are now but I'm pretty sure it's something more like 50 30 20 or I have a hard time imagining that the people shouldn't be spending half their innovation efforts and optimizing their core but maybe it's maybe it's 50/25/25 maybe it's even more aggressively out and to the right but that then defines a world where you are needing to set up completely different structures to as I said before interpret the signals of the world and identify what we should be focusing on next so that's the dilemma how do you as big successful companies and I've seen the guest list here I'd say virtually every single one of you is big and successful and great at what you do how do you do things differently to operate above the line and that obviously is one of the purposes of this conference so this is a picture of thee as the researchers put it the big data landscape of 2017 and you can see all sorts of blurred out colors and images up here these are all the logos of the companies that are populating the various different spaces whether it's machine learning or advertising or stat tools or financial and economic data and there's there's many more out there than these ones these are all the technologies I'm not going to be talking about today in part because I actually don't think they're as relevant as the points I now want to go to in the fundamentals and in part because honestly I'm not qualified to talk about it I'm a strategist not a technologist so I get myself in deep trouble if I tried to venture into that territory but I want to start with a fundamental that's directly related to this chart so as you may have seen in the subtitle on the first page of this the subtitle of this was to happen I actually came from exactly what it was but it was something like how to understand opportunity how to take action and and see through the fog of opportunity and what I meant by that is not just the literal fogging out of these brand names but there are thousands if not tens of thousands of technology applications and startups and all sorts of people in the market out there ready to help you go and do something digital and for a little while the natural reaction has been the following sequence of events when you try to think about how to innovate with digital technology you look out into that landscape and you say what what's out there what technologies exist today what applications of technologies exist today that we could take advantage of and how might we use them we know about sensors we put sensors onto our machines that might be an interesting move and then the next step is to say okay cool so if we've got sensors on our machines how can we use advanced analytics or artificial intelligence and machine learning how can we get more insights about the way things are working and then ultimately when that all plays out how do things change in the market behaviors change whether their customer behaviors or people in our operations and that's been that's a pretty logical approach you take a look at the technologies of your disposal and go figure out how to apply them there's too many you can't do that I don't care what intelligence systems you have to keep track of all the digital technologies or all the startups in the world you can't take that approach you can't just go say jeez there's this interesting startup what would it look like if we played it through our business system so I'd like to encourage you all as the first fundamental here not to pay attention to technology as the first step but instead start with humans and start with human behavior and I'm going to say something now which sounds tremendously kind of consultancy geeky and I'm sorry but I just don't know any other way to say it if you look at your operations today everything from and let's let's break it down into two worlds of trying to drive top-line growth we're trying to drive efficiency in your operations neither of those outcomes today and I would argue for the foreseeable future neither of those outcomes as possible without someone somewhere changing their behavior like literally their physical behavior sometimes the thought process but usually a physical behavior you cannot drive growth in your end markets unless someone decides to buy you instead of a competitor or if they decide to use your product differently than they've used it in the past that's the only way you unleash incremental growth and likewise in your operations you can't get more efficient unless someone does something differently they stop doing one activity they start doing another that actually brings this whole world of unknowable application of opportunity into the knowable space you can identify the behaviors in your system which i think of as the kind of the key economic gears of your business the way that value is created whether it's top-line growth or efficiency you can identify the behaviors in the market that will give you economic advantage and create new economic value and so the trick now is to identify what behavioral shifts will have the greatest economic value for us which ones we should focus on employee have so much value in better than them and from there pull it back and to say okay so how do we use data and insights to track those behavioral shifts and see if they're actually when we when we impact the behavior see if they're having the effect that we imagine they are and see if there's way that we can course correct along the way so that we optimize those behaviors and then the question should become okay based on that what technologies do we want to use so it obviously doesn't mean you can't be completely ignorant of the range of technologies or applications that exist out there but it shouldn't be the place you start it should be the place that you end up and if you follow that logic and if you set up your systems where you can identify the behaviors and then use technology to impact them in the way you want I can promise you you're going to get greater return from your digital innovation than if you do it in Reverse so there there are three basic ways that that we can break down human behavior and we're where the opportunity to create value from human behavior exists and I will say I'm venturing the territory I know at least two of these companies are here in the room maybe all three and I'm always nervous about trying to tell other people's stories so stand up and yell at me if I'm if I'm getting it wrong but think about breaking down the opportunity to impact human behavior into three different buckets starting from the left you can drive different outcomes in your own operations you can change the way that people act while they while they work within your operations you can change outcomes for your immediate downstream customers almost all of you in this room are quote unquote b2b which by the way I think is increasingly an irrelevant term but b2b where you're actually selling to not to end markets necessarily but usually to another customer in the value chain but you can change outcomes for those downstream customers and then you can you can change outcomes in the end market okay so I've got three simple examples here of companies and this is all public domain information by the way it's nothing that we have done necessarily but three simple examples of companies which some of its going to seem totally obvious but seeing through the lens of behavioral change I think it's an interesting way to look at what they've done and to diagnose how they had the impact we had so the first one here is Nissan and their use of what they call them cobots collaborative robots you can call whatever you want our PA cobots whatever the term may be the place they started was a recognition that for a variety of different reasons some of which I don't even know they were facing an ageing workforce it was just it was a long term trend and it was going to continue and so the question they had was not how can I get folks in my operations to do things differently but how do I stop them from doing things how do I stop them from doing the repetitive tasks that might actually contribute might actually be harder to do as aging goes on or might it might actually cause detriment to my workers how do I stop them from doing the complicated physical maneuvers that actually will become more difficult to do as that as those workers age and those were the types of questions that they were asking as they thought about the application of our PA for their plant settings and what they came up with were these solutions where these the so called cobots where they could do some of the highly repetitive picking and/or turning of screws whatever that whatever the case may be and what they're able to do with that does not only drive efficiency through their process but prevent worker absence and therefore save money in two different ways and by the way react to the reality of their aging workforce all of which was accomplished by a simple move which they could evade they could have presumably said okay how do I deploy our PA in my operations and they may have come to the same place but I bet you they would have tried all sorts of other applications before they got it the one that actually created the economic value that the cobots did for them so the second story is from Caterpillar and I want to encourage you to think about slicing this page roughly down the middle and this is this is this is for rough purposes for sure but the stuff on the left hand side is generally about creating efficiencies and reducing cost the stuff on the right hand side is mainly about generating top-line growth and the challenge that I've seen a lot of my manufacturing clients is it's pretty easy to think about the application of technology to drive efficiency and to shift your operations it's much more difficult to think about how to apply it for growth but I think both these examples of Caterpillar and United Technologies are interesting examples of where they have been able to drive real top-line growth from it so the story from Caterpillar is actually a very timely one because it has to do with their relationship with a company called Yard Club which many of you may have seen I think two years ago I know we've got some Caterpillar folks in the audience but to does just say years two weeks ago caterpillar just completed an acquisition it completed the acquisition of Yard Club and again it started with a reasonably non-intuitive move caterpillar wanted people to stop buying their machines that doesn't make a lot of sense but actually the other half of the sentences that they wanted customers to stop buying their machines and start renting them instead because the way that caterpillar not not overall but the way the caterpillar drives economic value in margin from their business is not just in selling big pieces of yellow capital equipment it's in selling all the work tools and attachments to that afterwards it's in selling the parts to those machines and the insight they had is yeah we may lose a few machine sales if people start renting instead of buying but if we can drive usage of our machines by creating an efficient market for those machines and we can drive the throughput of our work tools and our parts that actually is going to have better economic value for us than the potential loss of sales of the big pieces of capital equipment and so they took a small position in an interesting tiny little startup out in California and what the startup had was an app it was just a market making app there's there's thousands of these things in evidence around the world today that connected people who had construction machines with potential renters that's all it did and that was the key to them then getting into the rental market and driving this business model that again they may have they may have been able to approach this and say geez we should we should set up a rental app or but but that could also have been one of 50 other things we should do this app or that app the key insight there was they knew that driving rental would be the key to driving the economics in their business and that's why two weeks ago they completed the acquisition of Yard Club so United Technologies I realize like usual I'm taking a little bit longer than intended some to speed up a bit but United Technologies over on the right hand side here aerospace systems another interesting example of a company driving growth from the application of technology and the basic story here is United Technologies understood that they could drive both brand adherence if you will and better use of their systems in their airline customers if they could get the users of those airplanes to do things differently and importantly to work more efficiently to increase on-time performance do all the types of things that generally we don't believe Airlines do very well and make us hate airlines they wanted to flip that around and look for ways that they could get information into the hands of the people operating the planes the pilots the crew to do things differently to improve performance and so what they established was their ops insight platform which sits on a hundred iPad pilots can tap into it and understand real-time performance information as well as all sorts of other information whether what-have-you that would allow them to make decisions in the moment pre-flight during flight and post flight to improve the experience of their customers of the passengers flying on the plane and so this ultimately is something that was enabled by United Technologies be able to get the right information through the system onto the iPad at the right time but ultimately it was driven by a desired behavior in the end market United Technologies could say could think to themselves you know what we serve Airlines let's try to think about how we optimize the performance of our aerospace systems for those airlines and not think the next one or two steps down the value chain cuz that's how most manufacturing and b2b companies think but that's not what they did and again this created this created an interesting new business model and a whole lot of satisfaction amongst our customers anyway that's that's perhaps a bit long in the tooth version of fundamental number one but I do think it's actually the medius thing is you think about all these Exponential's you're going to be assailed with over the next few days think about how you're going to change human behavior with those technologies don't think about the technologies themselves and I mean learn and all that obviously I'm not saying don't pay attention to it but think about the application to drive behavior so the second fundamental is actually going to be totally obvious and straightforward to all of you and and I'm not sure how many people saw the economists I think was last week declaring that data may be the the new big oil so their their premise for those of you that didn't see it was that in previous industrial revolutions and X number of decades ago the the captains of industry those who were the business leaders were those who were able to control access to and production of oil and that because that was so embedded in the economics the economics of our of the business world generally then so the economists ask is big data than you oil are we now getting into an into an age when accessing and controlling and providing data is going to be one of the key the key engines for the economy and I would argue yet probably and the interesting question they asked also in some of their coverage was where were the wildcatters come from where were the people who were surrounding you to try to help with this or to take advantage of the data before you as big corporates recognized it yourself where are they going to be coming from over time so the basic premise behind fundamental to just just has to do with where you all as manufacturers sit in the VAT in the value chain whatever value chain you operate in you're in the middle and I know it's a simple overstatement but there is no better position to be in in an economy that's being driven by data than to be in the mix in the middle of the value chain you in theory have access to an ability to influence your suppliers you and when it comes to data you have the same in your downstream customers and your customers customers and if you can figure out ways to use that data to do these types all I've done on this circle here start to identify some of the ways that data is used to drive economic value whether it's internal process optimization licensing the data or selling it to others using crowdsourcing to augment your data and turn it into something more valuable or using it to identify add-on services or new products you can bringing to be bringing to market you sit in the middle of all of this and so you can short-circuit a bunch of the other like mind-blowing questions of how to apply Exponential's and how to shift your business model to operate more effectively and how to drive new value from innovation simply by saying how can we access and monetize data I'm sure that's not lost on anyone but I would say start there once you've figured out the behaviors you're trying to drive in the market start with the question of data how are you going to make money from the data that you should have a right to own and use as the quote unquote new oil so one of the challenges that we hear from our clients all the time is ok you tell us you can't do the quote unquote below the line stuff going back to my first I can't do the below the line stuff sorry you can't do above line stuff with your below the line resources what do you do how do you set up a structure to go and take advantage of these opportunities and the best answer with perhaps a goofy name that that I have and that we have so far is to set up a digital foundry call it whatever you want but the basic notion is to co-locate certain specialists whose job should be to constantly be thinking about human behavior and how to impact human behavior and how to get insights into the behavior that's going to create the most economic value constantly thinking about how to access data and turn it into something valuable and constantly trying digital prototypes to get all this stuff into the market and those are just a few of the specialist resources you need it doesn't need to be a huge team but it does need to be a team that's at the service not only for any of your corporations overall because it should be exploring the place that business units are not directly aimed at but it should also be the resource for those businesses to come and say I'm scared I don't know what I'm going to do to take advantage of these technologies I can't sort it out can you help me and when they're deployed effectively digital foundries can get the job done way better than anyone in your existing operations so I am almost out of time which is disappointing because there's another great story out there about Michelin many of you probably know it the punchline behind this is Michelin is a big rubber round thing manufacturer always has been but they've built an amazing system around their access to data based on that rubber that started with a very simple insight a behavioral insight and the behavioral insight was no one no one actively monitors their tire pressure and on account of that they don't take advantage of all the fuel savings that can come from keeping your tires inflated we happen to own the tire I wonder if we can help them with that and so in the first iteration of what they ended up developing something called EFI tires they were able to set up a data flow by putting sensors in the tires a data flow about the level of of tire inflation that would allow truck fleet managers and truck operators to understand when their tires were becoming deflated and when it was time to inflate them to and the punchline and the important thing was to increase fuel efficiency they got into that business and suddenly this thing took off where they started to be known not just as the interesting smart tire manufacturers but the partner to help me manage the fuel consumption in my trucks lead and so they started layering on other services to - as it says here to get into quote-unquote eco driving so they would offer tips on how to drive more more eco-friendly how to make sure that you're doing everything when you drive to make sure you're minimizing fuel consumption and that then became known as EFI fuel and that then bought them the opportunity to get into something that they now call efi trailers now michelin the provider of a single component an epi trailers by the way is about optimizing the use of trailers that are attached to the trucks that have the tires on them but now michelin the company that makes rubber round things owns the truck and the truck usage information and so they now have an entire business called Michelin solutions that is centered on EFI fuel that drives all this economic value both for themselves and for their downstream customers and it's it and it started with a single simple behavioral inside so that's what I got I thought I'd end on this not because it's just a completely overused and and but still true quote but I was personally amused to find out that actually apparently Darwin didn't say this I can't tell you who did chef elite Steve Shepley one of my colleagues knows but I'd love if anyone does know that catch me at a break and let me know what you think I hope this was helpful I hope if nothing else as you go through the next few days you reflect back on how to peel away all the complexity and all the fog of opportunity to identify just a few things that you can then take back to your businesses and take action on when you leave Boston in a few days thank you all very much and I look forward to chatting over breaks and in various different meals [Applause] you [Music]

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Keywords: Singularity, Singularity University, Education, Science, Business, Biotechnology, artificial intelligence, research, startup, lecture, turotials, learning, leadership, silicon valley, conference, boston, manufacturing, future, executive, entrepreneur, investor, Geoff Tuff

Id: FBn-7s-Z0No

Length: 32min 44sec (1964 seconds)

Published: Thu Jun 29 2017