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How Web Design will reinvent manufacturing
 

How Web Design will reinvent manufacturing

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Picture a world where Amazon.com is a factory. Products are made as needed, based on direct input from users to designers and developers. Consumption directly drives production, and data informs ...

Picture a world where Amazon.com is a factory. Products are made as needed, based on direct input from users to designers and developers. Consumption directly drives production, and data informs design. If we weren't talking about physical products, this would sound a lot like Web/app interaction design, but the worlds of making atoms and bits are quickly colliding, and the implications are profound. By mapping what we have learned creating analytics-driven digital design to the physical world, we can change how everything is made, for the better.

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  • Thank you Danny for inviting me this afternoon. Today I’m going to tell you why the design of everyday consumer products in the future will look a lot like Web design does today, and how Web designers and the analysis tools they have developed will play a big role in it.
  • I’m going to start by telling you a bit about who I am and how I personally went from thinking about Web design to manufacturing. Then I’m going to give you some history on the amount of work it takes to make a thing, because I think it’s important to regularly think about the context in which we work. Then I’ll describe a vision that proposes a world 8 years from now that resembles today from consumers’ perspective, but behaves very differently from virtually every other angle. And then I’ll look back to recent history to talk about related ideas that look similar, but are based on different assumptions. I’ll tell you where this project most needs help. And why it’ll be awesome, and why your skills will play a critical role, if it all works out.
  • Let me begin by telling you a bit about my background. I ’m a user experience designer. I was one of the first professional Web designers. I ’ ve now been designing Web sites for nearly 20 years. This is the navigation for a hot sauce shopping site I designed in 1994.
  • I’m proud of the fact that 16 years later they were still using the same visual identity. These were some of the oldest pixels on the Web.
  • Here’s one of my UI designs for the advanced search for HotBot, an early search engine, from 1997. If you’re wondering why Google’s front page is no minimal, I think it was because we were doing this.
  • Since then I’ve consulted on the user experience design of dozens, maybe hundreds of web sites. Here’s one for credit.com, who were fantastic clients a couple of years ago.
  • I sat out the first dotcom crash writing a book based on the work I had been doing during the first boom. It ’s a cookbook of user research methods. It came out in 2003. The second edition just came out in September. 80% of the content is new. Buy a copy for everyone on your team!
  • And 2001 I co-founded a design and consulting company called Adaptive Path.
  • I left the Web behind in 2004 and founded a company with Tod E. Kurt called ThingM in 2006.
  • ThingM is an R&D lab and a micro-manufacturer. We design and manufacture smart LEDs for architects, industrial designers and hackers. Our products appear on everything from flying robots to Lady Gaga’s stage show. Here are some projects that have used them.
  • We also do projects to explore the potential uses of embedded computing as a design material. This is an RFID wine rack that’s faceted classification browser to a cloud-based service. This is a capacitive sensing kitchen cabinet knob that glows when you touch it. This was an exploration in making a digital product that would still be useful 20 years after it was made.
  • However, ThingM is not my day job. My primary day job is as an innovation and user experience design consultant focusing on the design of digital consumer products. Here are some I’ve worked on for Yamaha, Whirlpool and Qualcomm.
  • The last couple of years my clients have been large consumer electronics companies. I can’t give you any details.
  • In 2010 I wrote a book on the UX design of ubiquitous computing devices—appliances, tools and environments that process information and which are connected to the cloud, but which are not experienced as general purpose computing devices.
  • Here’s an example from my friends and clients at Sifteo. When you get a box of Sifteo cubes, you get a box of tiny computers, but you think of them as digital game pieces, not tiny general-purpose computing devices.
  • All this work designing physical digital products made me think about the digital practice pioneered on the Web, and the relationship of those screen-based practices to the physical world.
  • This got me reading about the development of manufacturing technology. And as I came up with a model for understanding several trends in manufacturing. I’m not a historian this is not proper history, but and I think it has some face validity. Let’s start with a history of mass production. If you look at how many things you could produce from one unit of work, you see an interesting curve. For most of the last ten thousand or however many years, when you put one person’s effort into a project, you got roughly one thing out of it over a given period of time. You see some gains in efficiency through tools like the potter’s wheel, the plow, the horse, the lever, fire, but those efficiencies were, roughly speaking linear. Until the very recent past, no one had the capability to make 10,000 cooking pots in a day, but if the potter chose, each could be different. Then this thing happens in 1800. Parliament’s patent granting James Watt a monopoly on his improvement to Newcomen’s steam engine expires. Boom. The Industrial Revolution. We know this story. The skies over Manchester darken, the railroad comes to Brighton. 10,000 cooking pots a day is easy, and each pot is pretty cheap and much fancier than could be made by hand. That’s followed by steady increases in efficiency until we get to today’s industrial society. OK, that’s a familiar narrative. Now, let’s look at a related curve, the amount of work required to make the FIRST thing. Making the first thing of any set is hard. You become efficient later on, but the first time is not efficient. For most of history, that’s about one unit of work as I’m defining it. However, the funny thing about the Industrial Revolution is that as it made it much easier to make many things, it made it much harder to make that first thing. Mass produced objects are really complex, they require you to make the tools that make the tools that make the end product. Moreover, once you set up the system, there’s almost no variation in the end product. All 10,000 cooking pots have to be identical. This is our familiar experience of manufactured products: pick nearly everything you own or see and it’s almost impossibly complex for you to make one and there are thousands or millions like it out in the world. And then this other thing happens. In October 2009 Stratasys’ core patent on computer controlled additive manufacturing expires. Boom. The cost of making the first thing starts to plummet while the cost of making lots of things stays the same.
  • Until now you could have one or the other. Design flexibility or scale and cost, but not both. Digital manufacturing lets you have high flexibility and mass scale because it scales linearly. The upfront cost of making one or a thousand is the same. The machine you use to prototype with can be the machine you produce with. Thus, potentially the cost of making design changes is small. This is from MakieLab, a London toy startup that lets you configure your own doll and then they 3D print them. Their manufacturing costs are linearly tied to how many individual dolls people make. There isn’t a giant hump at the beginning of production for each doll. This implies a shift in the power dynamics of product creation as power and responsibility shifts from those who create supply—entities that are large enough that they can afford to produce large numbers of products—to those who create demand, designers and those who enable product discovery.
  • Which leads me to this.
  • Imagine Amazon 8 years from now. It looks like this. Yes, it looks exactly like the Amazon today. It has all of the familiar ways to discover new products, to compare them, to see what people think of them, to see what goes with what. It has wish lists, Gold Boxes, the whole thing. But there’s a crucial difference. Instead of Amazon being the front end to a fulfillment system, as it is today, the Amazon of 2020 is the front end to a set of factories.
  • The back end doesn’t look like UPS, but Ford Motor Company. When you click on on buy you start a manufacturing process at the factory nearest you, instead of a delivery process from a warehouse far away. River Rouge photo by Lotus Carroll, creative commons http://www.flickr.com/photos/thelotuscarroll/6695794423/q
  • What created this change? The obvious answer is, of course, open source 3D printing technologies, such as this Form1 printer that just got funded through Kickstarter. Yes, but not only. Rapid, distributed manufacturing is a necessary, but not sufficient condition. These printers have been around for a long time and if that’s all that was necessary, we would have had this revolution earlier. We didn’t need open source laser printers to create desktop publishing.
  • No, the major change is going to be analytics, as pioneered by the Web. When you order from the Amazon of 2020 a counter is incremented that registers that you, a human being with a set of well-known behaviors and a demographic background, decided to buy this specific version of this specific idea. Moreover, since the world of 2020 is a world of ubiquitous computing, every product has a small bit of digital hardware in it that tracks how the product is used and, with your implicit permission, sends that information back to a central server, which aggregates and anonymizes the results.
  • This allows designers to create multiple versions of an idea, and see how each version performs in the marketplace and in actual use. That should seem familiar, because it’s how much of Web design currently happens. Rather than depending solely on experience and intuition, as product design does right now, this process will give designers information about which product variation is preferred, who prefers it and how people use it when they get it. Those of you who have ever designed like this know how enormously powerful quantitative feedback on the user experience of a product can be. Designers can now make and test hypotheses about people’s behavior, preferences and interests by creating designs, then observing actual behavior with those designs.
  • Understanding why people buy things and how they use them was always a goal of traditional product design, but one that was very hard to reach. Traditional product development is where we get techniques such as test marketing, focus groups, and conjoint analysis. These are all in essence user-centered techniques designed to short circuit the long and complex Industrial Revolution manufacturing process, but it’s incredibly hard to really put a dent in it. In practice, the annual mass release of a completely finished product IS the primary form of user research in most manufacturing, but it’s such a multivariate problem that it’s almost impossible for designers to see the signal through the noise to understand what makes a product successful, and what doesn’t. This noisy feedback mechanism when it’s coupled with the high cost of failure we get the ultraconservative product design of today, which moves so slowly and is so prone to disruption from small players. However, when you have rapid, cheap, distributed low-volume manufacturing capability AND real-time analytics you have a new way of designing products. You can take those Industrial Age design processes that took years to test hypotheses, and you can speed them up by orders of magnitude. Image: http://commons.wikimedia.org/wiki/File:Tailfins-evolution-1957-1959.jpg
  • Tight loop iteration between an idea and inexpensive market validation of that idea is the core of Eric Ries’ and Steve Blank’s Lean Startup approach. The core goal of the Lean Startup approach is to rapidly identify WHO your customers are, and what they find valuable, useful or interesting, so that if your assumptions are wrong—which they usually are—you can find that out quickly and change course, and when they’re right, you can follow them and expand on them. The Lean Startup approach has produced an enormous amount of product innovation in both Web services and apps. My vision--MY hypothesis--is that it’s possible to do this with ANYTHING by applying the ideas, practices and technologies we developed for the Net to everything else.
  • So how do you test your product hypothesis? On the Web manufacturing and distribution are pretty easy: in the most basic smoke test, you put up some marketing copy, buy some keywords and see how many people sign up for your nonexistant beta. How do you validate your idea without investing a lot in manufacturing? Well, that component is also coming online very quickly. People talk about crowdfunding as a kind of investment vehicle, but I think it’s just as much a kind of commerce. Even though they sometimes deny it, Kickstarter is a catalog for products that don't exist yet, but will if enough people want them, which is exactly the kind of signal you want when you’re doing a Lean Startup. It gives developers feedback about the popularity of their idea and makes them think about how to position it for a market before they’ve made a single final product
  • Kickstarter is not the only kind of low-volume social commerce service. Etsy is all about selling small numbers of things, and it even allows very small run electronic products (as long as they’re made of felt).
  • Even fab.com, which sells limited-edition high design products like rugs and backpacks, sells small run electronics.
  • Sites like The Fancy are also coming online that combine the idea of a magazine, a blog, Tumblr and a catalog.
  • And then of course there’s this. For those who don’t recognize it, it’s Facebook’s new button. Straight up signal with no implied promise of fulfillment. We’ll see if Facebook actually manages to become a genuine commerce site, but it’s a very interesting play, since it makes your social network a discovery platform, and everything that’s a discovery platform is also a hypothesis testing and analytics platform.
  • There’s a store in my neighborhood in San Francisco that’s opening in about a month. It’s called Dijital Fix. They are a boutique specializing in limited-run electronics. At the same time that Dijital Fix is opening new stores, Best Buy—which is a giant chain of brick mortar consumer electronics stores—is struggling. These channels are immature, but they’re becoming increasingly popular. In effect, they’re doing an end run around the traditional consumer electronic sales channels and giving developers access to their customers so they can test their product hypotheses directly. This is bringing product development closer to what we’ve become accustomed to when deploying software on the Web.
  • So 2020 will look and work exactly like our world today, when seen from the outside. It will be driven by the same motivations. You’ll still have the thrill of finding something awesome when you’re bored surfing the Internet and then making it yours by buying it. However, behind the scenes nearly everything will have changed. The power shift will mean that design and production cycles will be tight, and led by designers working with analytics as one core tool and rapid manufacturing as the other. Like the flurry of apps we have today, discovery and positioning—how you get people to find your idea, not just what the idea is—will become important. It’ll be a new, complex, dynamic and ultimately profoundly different environment that shift how we think about products in the same way that the Web has changed how we think about information.
  • I know what you’re thinking: “Mike just saw a MakerBot and got all excited. We’ve heard this all before, it’s called mass customization, we heard about it 15 years ago and it never worked out.” Why talk about this again? Because I think that the presentation of mass customization as “configurators for everything” (such as this 1998 project from Levi’s) missed the point. That totally gets the user motivation wrong: most people don’t want to be designers of everything, they want to design a couple of things, but be consumers of the rest. Some people want to make their own clothes, but those people typically don’t build their own cars, and vice versa. MakieLab’s doll configurator is fun, but you’re not going to do that for everything. Most people have better things to do than figure out what colors and patterns look good together, what makes them look sexy or powerful, how much firmware will fit into the onboard memory. They’re busy. They want someone who is a professional to do that research, to think really hard about what they need, to be really fluent in the tools that make it good, then to create a solution.
  • I’m also not talking about desktop manufacturing. As much as all us geeks want a Star Trek replicator, it’s not that useful in practice. We just don’t need that much new stuff all the time. Paper printers are useful because they represent high density information that fits into a rich existing culture of information use, and even they’re not used nearly as much as ecommerce sites. Outside of work, people probably shop a lot more than they print.
  • I think more importantly, both mass customization and desktop fabrication imagine a new world that’s different than ours. I have nothing against envisioning new worlds and working toward their creation—that’s one of the things I do for my clients—but my experience has taught me that creating new worlds, changing the behavior of millions of people, is really hard and takes a really long time. If we look to a world 8 years into the future, odds are that it’s not going to have changed that much, the odds are that most of us are not going to have a whole bunch more time on our hands to become mechanical engineers, electrical engineers, software engineers, and material scientists, as much as we’d like to. I fully support the maker movement, but I think that opening manufacturing technologies doesn’t just democratize access, it also demonstrates how complex the craft of designing a product really is. Makerbot photo by Scott Beale
  • There are probably many steps to getting momentum for this vision, but as I compare Web software to what we have in the manufacturing world, one piece stands out: distributed collaborative design tools. To make better hypotheses we need to be able to take advantage of all of those specialized skills—all the different kinds of engineering—wherever they are, and to work together to create a shared understanding of what that hypothesis, that product, is. For purely digital products we have Github, Basecamp, WebEx, Balsamiq and similar products, but the physical world is way behind. Commercial CAD systems are huge and incredibly difficult to learn. Product Lifecycle Management systems assume that you’re always building a commercial airplane, and are also insanely complex.
  • We are getting new tools, Autodesk’s 123D is starting , Ponoko has publishing tools, you can kind of fork projects on Thingiverse. But these tools are really immature. Sunglass just pivoted a couple of weeks ago from being an online CAD system to being a “ Github for 3D. ” When these products mature, this is going to open creative possibilities immensely. Think about how people use these products right now: they share and expand basic building blocks, they collaborate remotely, they track what worked and what didn ’ t. Moreover, these tools have moved through several generations, from primitive, to over-complex, to differentiated for different tasks and different ways of collaborating. Nothing like that exists for the physical world, as far as I know. And I realize it’s going to take time. Github got to where it is through an evolution of tools and practices that began with makefiles. The physical world isn’t even at the makefile stage.
  • So, let me pull all this together. To me, the whole ecosystem looks like this. Here come the buzz words, so excuse me in advance. Digital fabrication, we know what that is. It will allow us to make all kinds of things in small batches. Ubiquitous Computing and the Internet of Things is leading to everyday objects that send a stream of telemetry when we bring them home. They have an information shadow in the cloud that can be data mined. Big Data Analytics crunches all of that data to create information about people’s behavior. Social commerce creates sales channels that sell small numbers of products by finding niche markets and letting them market to each other And finally, cloud-based design tools will allow designers and engineers to collaborate on the distributed development of physical products. This is my ecosystem vision: a world where design directly drives product creation, and where data informs design. This is a world where products are made in small numbers only when they are requested. They are made locally, with local materials and workers, while at the same time being able to use design and engineering talent from anywhere on earth. In other words, they use the best qualities of both atoms and bits: atoms are available everywhere, bits travel fast. Designers in this vision add hypotheses testing against the actual market to their toolbox of design methods. In the full pipe dream, this means we use fewer natural resources, take full advantage of talented people wherever they are, create only products in large quantities that people need and want, meet the needs of tiny niche audiences, while still taking advantage of the infinite variety implicit in digital manufacturing technologies. Whew!
  • And who knows the most about this? It’s you. Many of you are designers who have been working with purely digital tools their whole careers. You may not know how to do 3D CAD, but you know what it means to collaborate on a design. You may have never done any mechanical engineering, but you have worked with engineers. You may have never made a product, but you have collaborated on a complex project with many technical challenges and, pardon the pun, many moving parts. You have worked in a tight loop with end consumers to understand how they experience the product you designed. Some of you have even been in Lean Startups or on agile teams, practicing data driven design using the information about people’s behaviors to guide your design innovations. These are all skills that are critical to successful product design. Your way of seeing the world will become increasingly dominant and if you are not guiding your organization’s strategy today, you will be very soon. As computers shatter and embed themselves in our environment, your perspective will guide the design of everything digital, which is quickly becoming everything. Designers are already changing the corporate culture of many manufacturing companies that were traditionally run by technologists or marketers. You will change the way that we perceive how all things are made, for the better.
  • Now, an epilogue. After that grandiose vision, I felt I should show some of my personal experience with these ideas.
  • I intend to make this vision my next focus as a designer and entrepreneur. At ThingM we just did the first iteration on Kickstarter of a product we hope will become different and more interesting as we iterate on it. It’s the world’s best indicator light. It’s a highly configurable USB LED and it gives you peripheral awareness of things that are happening on the Net and your local machine. You can pre-order one from us today. However, I don’t expect that we will be able to do all of this by ourselves. I need your help: tell me what I don’t know, where I’m wrong. Tell me who I should talk to and where the opportunities are. I think this will change the world. I want to change the world. Interested? Talk to me.
  • Thank you.

How Web Design will reinvent manufacturing How Web Design will reinvent manufacturing Presentation Transcript

  • HOW WEB DESIGN WILLREINVENTMANUFACTURING Mike Kuniavsky November 2, 2012 UX Brighton
  • ABOUT MEPROLOGUE: UNITS OF WORKTHE NEW PRODUCT ECOSYSTEMWHAT THIS IS NOT, AND WHYWHAT WE NEED TO DOWHY YOU WILL RULE THEWORLD
  • PROLOGUE: UNITS OF WORK
  • # of things from 1 unit of work etc10K1000100 10 1 # units of work to make the first thing 1800 Watt’s patent expires Anitquity patent expires 2009 y Toda Stratasys
  • VARIETY AND SCALE > Variety OR SCALE
  • THE NEW PRODUCTDEVELOPMENT ECOSYSTEM
  • AMAZON 2020
  • +
  • ANALYTICS
  • HYPOTHESIS GENERATION
  • 195719581959
  • STEVE Blank’s Customer discovery
  • LOW VOLUME SOCIAL COMMERCE
  • LOW VOLUME SOCIAL COMMERCE
  • LOW VOLUME SOCIAL COMMERCE
  • LOW VOLUME SOCIAL COMMERCE
  • LOW VOLUME SOCIAL COMMERCE
  • LoW volume social commerce
  • 2020
  • What this is not
  • MASS CUSTOMIZATION ISSO 1996!
  • COPY SHOPS FOR 3D ANDDESKTOP MANUFACTURING?
  • 2020?
  • What we need to do
  • COLLABORATIVE DESIGN TOOLS
  • COLLABORATIVE DESIGN TOOLS
  • DIGITAL FABRICATION+UBICOMP/IOT+BIG DATA ANALYTICS+SOCIAL COMMERCE+CLOUD-BASED DESIGN TOOLS=THE NEW PRODUCTDEVELOPMENT ECOSYSTEM
  • EPILOGUE:PUTTING MY MONEY WHEREMY MOUTH IS
  • CONCLUSION Pre-order at shop.thingm.com
  • Mike Kuniavskymikek@thingm.com
  • idea. Moreover, since the world of 2020 is a world of ubiquitous computing, every product has a small bit of digital hardware in it that tracks how the product is used and, with your implicit permission, sends that informationback to a central server, which aggregates and anonymizes the results.This allows designers to create multiple versions of an idea, and see how each version performs in the marketplace and in actual use.That should seem familiar, because it’s how much of Web design currently happens.Rather than depending solely on experience and intuition, as product design does right now, this process will give designers information about which product variation is preferred, who prefers it and how people use it when theyget it.Those of you who have ever designed like this know how enormously powerful quantitative feedback on the user experience of a product can be. Designers can now make and test hypotheses about people’s behavior,preferences and interests by creating designs, then observing actual behavior with those designs.Understanding why people buy things and how they use them was always a goal of traditional product design, but one that was very hard to reach. Traditional product development is where we get techniques such as testmarketing, focus groups, and conjoint analysis. These are all in essence user- centered techniques designed to short circuit the long and complex Industrial Revolution manufacturing process, but it’s incredibly hard to really puta dent in it. In practice, the annual mass release of a completely finished product IS the primary form of user research in most manufacturing, but it’s such a multivariate problem that it’s almost impossible for designers to seethe signal through the noise to understand what makes a product successful, and what doesn’t. This noisy feedback mechanism when it’s coupled with the high cost of failure we get the ultraconservative product design of today,which moves so slowly and is so prone to disruption from small players.However, when you have rapid, cheap, distributed low-volume manufacturing capability AND real- time analytics you have a new way of designing products. You can take those Industrial Age design processes that took yearsto test hypotheses, and you can speed them up by orders of magnitude.Image: http://commons.wikimedia.org/wiki/File:Tailfins-evolution-1957-1959.jpgTight loop iteration between an idea and inexpensive market validation of that idea is the core of Eric Ries’ and Steve Blank’s Lean Startup approach. The core goal of the Lean Startup approach is to rapidly identify WHO yourcustomers are, and what they find valuable, useful or interesting, so that if your assumptions are wrong—which they usually are—you can find that out quickly and change course, and when they’re right, you can follow themand expand on them.The Lean Startup approach has produced an enormous amount of product innovation in both Web services and apps.My vision--MY hypothesis--is that it’s possible to do this with ANYTHING by applying the ideas, practices and technologies we developed for the Net to everything else.So how do you test your product hypothesis? On the Web manufacturing and distribution are pretty easy: in the most basic smoke test, you put up some marketing copy, buy some keywords and see how many people sign up foryour nonexistant beta. How do you validate your idea without investing a lot in manufacturing? Well, that component is also coming online very quickly.People talk about crowdfunding as a kind of investment vehicle, but I think it’s just as much a kind of commerce.Even though they sometimes deny it, Kickstarter is a catalog for products that dont exist yet, but will if enough people want them, which is exactly the kind of signal you want when you’re doing a Lean Startup. It givesdevelopers feedback about the popularity of their idea and makes them think about how to position it for a market before they’ve made a single final productKickstarter is not the only kind of low-volume social commerce service.Etsy is all about selling small numbers of things, and it even allows very small run electronic products (as long as they’re made of felt).Even fab.com, which sells limited-edition high design products like rugs and backpacks, sells small run electronics.Sites like The Fancy are also coming online that combine the idea of a magazine, a blog, Tumblr and a catalog.And then of course there’s this. For those who don’t recognize it, it’s Facebook’s new button. Straight up signal with no implied promise of fulfillment. We’ll see if Facebook actually manages to become a genuine commercesite, but it’s a very interesting play, since it makes your social network a discovery platform, and everything that’s a discovery platform is also a hypothesis testing and analytics platform.There’s a store in my neighborhood in San Francisco that’s opening in about a month. It’s called Dijital Fix. They are a boutique specializing in limited-run electronics. At the same time that Dijital Fix is opening new stores,Best Buy —which is a giant chain of brick mortar consumer electronics stores—is struggling.These channels are immature, but they’re becoming increasingly popular. In effect, they’re doing an end run around the traditional consumer electronic sales channels and giving developers access to their customers so they cantest their product hypotheses directly.This is bringing product development closer to what we’ve become accustomed to when deploying software on the Web.So 2020 will look and work exactly like our world today, when seen from the outside. It will be driven by the same motivations. You’ll still have the thrill of finding something awesome when you’re bored surfing the Internetand then making it yours by buying it.However, behind the scenes nearly everything will have changed. The power shift will mean that design and production cycles will be tight, and led by designers working with analytics as one core tool and rapid manufacturingas the other. Like the flurry of apps we have today, discovery and positioning—how you get people to find your idea, not just what the idea is—will become important. It’ll be a new, complex, dynamic and ultimately profoundlydifferent environment that shift how we think about products in the same way that the Web has changed how we think about information.I know what you’re thinking: “Mike just saw a MakerBot and got all excited. We’ve heard this all before, it’s called mass customization, we heard about it 15 years ago and it never worked out.” Why talk about this again?Because I think that the presentation of mass customization as “configurators for everything” (such as this 1998 project from Levi’s) missed the point. That totally gets the user motivation wrong: most people don’t want to bedesigners of everything, they want to design a couple of things, but be consumers of the rest. Some people want to make their own clothes, but those people typically don’t build their own cars, and vice versa. MakieLab’s dollconfigurator is fun, but you’re not going to do that for everything. Most people have better things to do than figure out what colors and patterns look good together, what makes them look sexy or powerful, how much firmwarewill fit into the onboard memory. They’re busy. They want someone who is a professional to do that research, to think really hard about what they need, to be really fluent in the tools that make it good, then to create a solution.I’m also not talking about desktop manufacturing. As much as all us geeks want a Star Trek replicator, it’s not that useful in practice. We just don’t need that much new stuff all the time. Paper printers are useful because theyrepresent high density information that fits into a rich existing culture of information use, and even they’re not used nearly as much as ecommerce sites. Outside of work, people probably shop a lot more than they print.I think more importantly, both mass customization and desktop fabrication imagine a new world that’s different than ours. I have nothing against envisioning new worlds and working toward their creation—that’s one of thethings I do for my clients—but my experience has taught me that creating new worlds, changing the behavior of millions of people, is really hard and takes a really long time.If we look to a world 8 years into the future, odds are that it’s not going to have changed that much, the odds are that most of us are not going to have a whole bunch more time on our hands to become mechanical engineers,electrical engineers, software engineers, and material scientists, as much as we’d like to. I fully support the maker movement, but I think that opening manufacturing technologies doesn’t just democratize access, it alsodemonstrates how complex the craft of designing a product really is.Makerbot photo by Scott BealeThere are probably many steps to getting momentum for this vision, but as I compare Web software to what we have in the manufacturing world, one piece stands out: distributed collaborative design tools. To make betterhypotheses we need to be able to take advantage of all of those specialized skills—all the different kinds of engineering—wherever they are, and to work together to create a shared understanding of what that hypothesis, thatproduct, is.For purely digital products we have Github, Basecamp, WebEx, Balsamiq and similar products, but the physical world is way behind. Commercial CAD systems are huge and incredibly difficult to learn. Product LifecycleManagement systems assume that you’re always building a commercial airplane, and are also insanely complex.We are getting new tools, Autodesk’s 123D is starting , Ponoko has publishing tools, you can kind of fork projects on Thingiverse. But these tools are really immature.Sunglass just pivoted a couple of weeks ago from being an online CAD system to being a “Github for 3D.” When these products mature, this is going to open creative possibilities immensely. Think about how people use these