Disclaimer: this thought is “foxy”, in the sense that I don’t assert it’s definitively true, but I still think it could be a useful lens for viewing the world.
Startups Don’t Create New Technology
Contra gurus like Paul Graham and Peter Thiel, successful tech startup companies do not actually create new technology. Good tech startups do one of two things: 1) invent a new technology-dependent business model, or 2) repackage and polish existing technology in such a way as to bring it above the threshold for widespread use.
Consider a couple of recent successful tech startups: Facebook, Twitter, Uber, AirBNB, and Dropbox. None of these can be said to have innovated deeply new technology. Instead, they realized that they could create a new business model based entirely on available technology.
Uber is a particularly illustrative example. The company depends enormously on several powerful new recent technologies: smart phones, GPS, and mapping software. However, Uber itself did not innovate any of those. If one of those technologies hadn’t been available, Uber probably would not have been successful. Uber certainly could not have created any of those technologies as part of its business plan.
I’m not suggesting here, of course, that tech companies in general do not create new technology. The point is that startups don’t create technology. Instead, deeply new technology is primarily developed by large, established companies. The basic pattern for technology creation is:
Invent a new business model that depends on currently available technology (startup phase)
Grow the business fast based on profits from new business model (growth phase)
Using newly-available resources of finance and talent resulting from initial success, develop deeply new technology (mature phase)
The history of Amazon illustrates this pattern very well. Amazon started by creating a new business model using currently available web technology. It depended on a huge array of technology that was developed by others—web browsers, web servers, databases, the internet, personal computers—but it did not develop any of that technology itself and would not have been successful if it had had tried to do so (imagine trying to innovate the web browser so you could sell books online).
While Amazon did not create new technology in its startup phase, it certainly has created deeply new technology now that it is in its mature phase. The clearest example of deeply new technology created by Amazon is cloud computing (some people might also point to eBooks). Cloud computing could never have been innovated by a startup company—the resources required in terms of finance, talent, and corporate resilience are far too great. While cloud computing could never have been innovated by a startup, it is now becoming a foundational technology for the new generation of startups.
So the lifecycle of entrepreneurial technology development suggests a kind of virtuous circle. A company becomes profitable by building a new technology-dependent business model or repackaging technology developed by others. Then it grows, and when it reaches a certain point, it becomes able to create new technology that feeds the next generation of startups.
To add a bit of empirical analysis to this comment, I analyzed the YCombinator Winter 2015 batch. I categorized the startups into one of three buckets: Tech-Dependent Business Model (TDBM), RePackaging and Polishing existing tech (RPP), and Novel Tech (NT). The list can be found here.
CampusJob—TDBM
Seed—TDBM
NextTravel—TDBM
TheMidGame—TDBM
eBrandValue—TDBM
Standard Cyborg—RPP, maybe NT
Rescue Forensics—TDBM (social entrepreneurship)
Lumi—TDBM/RPP
Undeground Cellar—TDBM
Transcriptic—NT?? but not easily evaluated
Atomwise—maybe NT but probably RPP/TDBM of machine learning (I doubt they created new ML algos)
Spark Gift—TDBM
Gradberry—TDBM
Industrial Microbes—NT?? but probably TDBM/RPP of existing chemical engineering tech
TechList—TDBM
Meadow—TDBM
ReSchedule—TDBM
Diassess—RPP, synthesis of biotech and infotech
RazorPay—TDBM
DirectMatch—TDBM
BuildScience—TDBM/RPP
ShiftLabs—RPP, making medical devices cheaper.
Valor Water Analytics—TDBM
Instavest—TDBM
Open Listings—TDBM
CloudMedx—TDBM/RPP
BankJoy—TDBM
TransitMix—TDBM
ZenFlow—NT, in biotech space.
Final—TDBM
Lully—maybe NT but probably RPP
Spire—TDBM/RPP
AnalyticsMD—TDBM
Smarking—TDBM
20N—NT
GrubMarket—TDBM
CribSpot—TDBM
KickPay—TDBM
Notable Labs—uncategorizable but brilliant, some kind of legal/biotech/infotech combination play
Pretty Instant—TDBM
VetPronto—TDBM
Akido—TDBM
DroneBase—TDBM
MashGin—maybe NT in computer vision space but probably RPP/TDBM
LabDoor—RPP/TDBM
Bonfire—TDBM
EquipmentShare—TDBM
The following pattern emerged from this exercise: YC is not funding startups that are developing new computer science technology, with the possible exception of MashGin and AtomWise. The YC startups that are attempting to develop new technology are in the biotech/medtech space—Transcriptic, Standard Cyborg, Industrial Microbes, Zenflow, Lully, and 20N.
Edit I noticed after writing that the list is from Demo Day 2, representing the second half of the Winter 2015 batch. However, it doesn’t appear to me that analyzing only half the batch causes a serious bias in the conclusion. The Demo Day 1 batch is available here.
Contra gurus like Paul Graham and Peter Thiel, successful tech startup companies do not actually create new technology. Good tech startups do one of two things: 1) invent a new technology-dependent business model, or 2) repackage and polish existing technology in such a way as to bring it above the threshold for widespread use.
I think this is coming from both the way you’re defining technology (which looks like it’s excluding various forms of cultural or social technology) and the set of startups you’re considering. I think both Graham or Thiel would agree with you that entrepreneurs create businesses, which seems like the short version of your claim. Yes, both of them think that new technology is a fruitful place to look for new businesses, but it isn’t the only one.
Consider biotech startups, specifically Genentech. The company wasn’t founded until a few years after the underlying tech had been invented in a university lab, and while now it has extensive research labs that do basic as well as applied research, most of the startups I’m familiar with (and early Genentech) are very much in the ‘applied research’ category.
One of the most sensible books I’ve read about how technology works, from an economic perspective, is The Nature of Technology, by Brian Arthur. It talks about how different technologies interact with each other, and with the economy, and how what he calls standard engineering, which mostly involves assembling off-the-shelf parts, contributes to the advancement of technology as a whole.
A lot of the concepts he talks about can be experienced by using an open source operating system with package management, such as Ubuntu. At least, as I was reading the book, a lot of open source software examples came to mind.
Brian Arthur was involved in the founding of the Santa Fe institute that studies complexity.
First, absolutely everyone depends on technologies invented by others and it’s turtles all the way down—a start-up depends on personal computers which depend microprocessors which depend on transistors… etc.
Second, Google and Apple would probably be the canonical examples of startups which actually created new technology. Not coincidentally they belong to the biggest and richest companies in the world. I think Facebook also created new technology, albeit intangible, and also joined that club.
Third, look beyond bits. Biotech startups, for example, attempt to create technology much more often that the code-driven ventures.
I see Google and Apple as marginal examples—they don’t exactly fit into my schema, but they don’t exactly break my schema either. Apple’s success depended on two key insights contributed by the two founders. Jobs saw that a market for personal computers could exist, and Wozniak saw a way to repackage existing computer technology cheaply and usably enough for the customers in that market. Google did build a better search engine, but they also saw a new way to make money with search, and it’s not clear which insight was more important.
You are now arguing that a start-up must have business sense to succeed—which is entirely true, but not related to your original claim that start-ups don’t create new technology.
If Google’s business model were more important than its technology, that wouldn’t cause its technology to cease to exist. Your original claim was that startups don’t create technology, which is a very, very different claim than people who want to become rich should pursue business models, rather than technology.
But, actually, I don’t think that Google’s business model was more important to its earning power than its technology. Many people have copied its business model, but they don’t have the scale of being the most popular website, so they don’t make as much money. Part of that is that other companies have copied its basic search technology, but the first-mover advantage has turned Google’s early technology into an enduring brand advantage.
Also, my guess is that Google had better technology 10 years ago for running scalable infrastructure than Microsoft has today. While that may have contributed to their bottom line, I’m not sure it contributed much to their popularity.
I agree with your first premise (that startups don’t create new technology), but not the second premise (that large, established companies do).
Read ‘The Sources of Innovation’ by Eric von Hippel. It reaffirms what your first point, and shows that real technological progress usually comes from users of technology rather than producers (or, to put it in a better way, from cooperation between users and producers). More precisely, innovation happens when there is a feedback loop where users use technology in creative ways (according to needs not foreseen by the original producers) and producers incorporate those ideas back into their products. The contribution of the producer is to identify creative uses of their products and formulate business models around them. Amazon’s cloud computing initiative is definitely consistent with this point of view.
Another major source of innovation is academic institutions, where risk-taking is encouraged when it comes to new ideas. Of course, it’s also true that established companies also fund research.
I have the exact opposite feeling about Uber. I think that their main business model is: a taxi dispatch service that actually comes when you call it. There is no technology in that at all. The problem is that it is very difficult to enter a business where everyone else is frauds. You can’t just advertise that you aren’t a fraud, because who would believe you? Uber differentiated itself by being techy, to get people to try it. Maybe the technology was necessary to allow people to monitor cabs and allow people to trust it, but if the industry hadn’t dug itself into a hole, a similar business could have been built 50 years ago.
TDBM, I would argue is the most important step. A single discovery could have hundreds of different ways to coordinate with existing technologies. As for RPP, often the people who are best at creating and the ones who are best at distributing are very different. It’s a shame the distributor gets the lion’s share, but such is life. There are also levels below technology creation. Before the technology can be applied, it’s principles must be experimentally tested. Before an experimental test can be conducted, a theory must be developed to explain what you are testing for although some technologies skip this step. The experimenter and the theorist often receive even less than the applier who receives less than the distributor.
I don’t think that it’s fair to say that software isn’t technology. Facebook didn’t create new hardware but the idea of the timeline was new.
But even if we look at hardware I don’t think it’s true. Bre’s MakerBot industries did manage to sell MakerBots while it was a startup.
Arduino is created by a startup.
Pebble is a YCombinator startup. Technology like Arduino allowed Pebble to do their prototyping easier than was possible before. There are also a bunch of other Kickstarter projects that produce technology.
I do consider the Hackerspace ecosystem capable of creating new hardware.
A lot of new technology get’s developed by repurposing existing technology. Arduino couldn’t have been developed without the ability to buy cheap chips but Arduino is still new technology.
Disclaimer: this thought is “foxy”, in the sense that I don’t assert it’s definitively true, but I still think it could be a useful lens for viewing the world.
Startups Don’t Create New Technology
Contra gurus like Paul Graham and Peter Thiel, successful tech startup companies do not actually create new technology. Good tech startups do one of two things: 1) invent a new technology-dependent business model, or 2) repackage and polish existing technology in such a way as to bring it above the threshold for widespread use.
Consider a couple of recent successful tech startups: Facebook, Twitter, Uber, AirBNB, and Dropbox. None of these can be said to have innovated deeply new technology. Instead, they realized that they could create a new business model based entirely on available technology.
Uber is a particularly illustrative example. The company depends enormously on several powerful new recent technologies: smart phones, GPS, and mapping software. However, Uber itself did not innovate any of those. If one of those technologies hadn’t been available, Uber probably would not have been successful. Uber certainly could not have created any of those technologies as part of its business plan.
I’m not suggesting here, of course, that tech companies in general do not create new technology. The point is that startups don’t create technology. Instead, deeply new technology is primarily developed by large, established companies. The basic pattern for technology creation is:
Invent a new business model that depends on currently available technology (startup phase)
Grow the business fast based on profits from new business model (growth phase)
Using newly-available resources of finance and talent resulting from initial success, develop deeply new technology (mature phase)
The history of Amazon illustrates this pattern very well. Amazon started by creating a new business model using currently available web technology. It depended on a huge array of technology that was developed by others—web browsers, web servers, databases, the internet, personal computers—but it did not develop any of that technology itself and would not have been successful if it had had tried to do so (imagine trying to innovate the web browser so you could sell books online).
While Amazon did not create new technology in its startup phase, it certainly has created deeply new technology now that it is in its mature phase. The clearest example of deeply new technology created by Amazon is cloud computing (some people might also point to eBooks). Cloud computing could never have been innovated by a startup company—the resources required in terms of finance, talent, and corporate resilience are far too great. While cloud computing could never have been innovated by a startup, it is now becoming a foundational technology for the new generation of startups.
So the lifecycle of entrepreneurial technology development suggests a kind of virtuous circle. A company becomes profitable by building a new technology-dependent business model or repackaging technology developed by others. Then it grows, and when it reaches a certain point, it becomes able to create new technology that feeds the next generation of startups.
To add a bit of empirical analysis to this comment, I analyzed the YCombinator Winter 2015 batch. I categorized the startups into one of three buckets: Tech-Dependent Business Model (TDBM), RePackaging and Polishing existing tech (RPP), and Novel Tech (NT). The list can be found here.
CampusJob—TDBM
Seed—TDBM
NextTravel—TDBM
TheMidGame—TDBM
eBrandValue—TDBM
Standard Cyborg—RPP, maybe NT
Rescue Forensics—TDBM (social entrepreneurship)
Lumi—TDBM/RPP
Undeground Cellar—TDBM
Transcriptic—NT?? but not easily evaluated
Atomwise—maybe NT but probably RPP/TDBM of machine learning (I doubt they created new ML algos)
Spark Gift—TDBM
Gradberry—TDBM
Industrial Microbes—NT?? but probably TDBM/RPP of existing chemical engineering tech
TechList—TDBM
Meadow—TDBM
ReSchedule—TDBM
Diassess—RPP, synthesis of biotech and infotech
RazorPay—TDBM
DirectMatch—TDBM
BuildScience—TDBM/RPP
ShiftLabs—RPP, making medical devices cheaper.
Valor Water Analytics—TDBM
Instavest—TDBM
Open Listings—TDBM
CloudMedx—TDBM/RPP
BankJoy—TDBM
TransitMix—TDBM
ZenFlow—NT, in biotech space.
Final—TDBM
Lully—maybe NT but probably RPP
Spire—TDBM/RPP
AnalyticsMD—TDBM
Smarking—TDBM
20N—NT
GrubMarket—TDBM
CribSpot—TDBM
KickPay—TDBM
Notable Labs—uncategorizable but brilliant, some kind of legal/biotech/infotech combination play
Pretty Instant—TDBM
VetPronto—TDBM
Akido—TDBM
DroneBase—TDBM
MashGin—maybe NT in computer vision space but probably RPP/TDBM
LabDoor—RPP/TDBM
Bonfire—TDBM
EquipmentShare—TDBM
The following pattern emerged from this exercise: YC is not funding startups that are developing new computer science technology, with the possible exception of MashGin and AtomWise. The YC startups that are attempting to develop new technology are in the biotech/medtech space—Transcriptic, Standard Cyborg, Industrial Microbes, Zenflow, Lully, and 20N.
Edit I noticed after writing that the list is from Demo Day 2, representing the second half of the Winter 2015 batch. However, it doesn’t appear to me that analyzing only half the batch causes a serious bias in the conclusion. The Demo Day 1 batch is available here.
“New technology” is ill-defined. Is a more practical version of something which already exists considered new technology or old technology?
I think this is coming from both the way you’re defining technology (which looks like it’s excluding various forms of cultural or social technology) and the set of startups you’re considering. I think both Graham or Thiel would agree with you that entrepreneurs create businesses, which seems like the short version of your claim. Yes, both of them think that new technology is a fruitful place to look for new businesses, but it isn’t the only one.
Consider biotech startups, specifically Genentech. The company wasn’t founded until a few years after the underlying tech had been invented in a university lab, and while now it has extensive research labs that do basic as well as applied research, most of the startups I’m familiar with (and early Genentech) are very much in the ‘applied research’ category.
One of the most sensible books I’ve read about how technology works, from an economic perspective, is The Nature of Technology, by Brian Arthur. It talks about how different technologies interact with each other, and with the economy, and how what he calls standard engineering, which mostly involves assembling off-the-shelf parts, contributes to the advancement of technology as a whole.
A lot of the concepts he talks about can be experienced by using an open source operating system with package management, such as Ubuntu. At least, as I was reading the book, a lot of open source software examples came to mind.
Brian Arthur was involved in the founding of the Santa Fe institute that studies complexity.
I am not sure I’m willing to agree with that.
First, absolutely everyone depends on technologies invented by others and it’s turtles all the way down—a start-up depends on personal computers which depend microprocessors which depend on transistors… etc.
Second, Google and Apple would probably be the canonical examples of startups which actually created new technology. Not coincidentally they belong to the biggest and richest companies in the world. I think Facebook also created new technology, albeit intangible, and also joined that club.
Third, look beyond bits. Biotech startups, for example, attempt to create technology much more often that the code-driven ventures.
I see Google and Apple as marginal examples—they don’t exactly fit into my schema, but they don’t exactly break my schema either. Apple’s success depended on two key insights contributed by the two founders. Jobs saw that a market for personal computers could exist, and Wozniak saw a way to repackage existing computer technology cheaply and usably enough for the customers in that market. Google did build a better search engine, but they also saw a new way to make money with search, and it’s not clear which insight was more important.
You are now arguing that a start-up must have business sense to succeed—which is entirely true, but not related to your original claim that start-ups don’t create new technology.
If Google’s business model were more important than its technology, that wouldn’t cause its technology to cease to exist. Your original claim was that startups don’t create technology, which is a very, very different claim than people who want to become rich should pursue business models, rather than technology.
But, actually, I don’t think that Google’s business model was more important to its earning power than its technology. Many people have copied its business model, but they don’t have the scale of being the most popular website, so they don’t make as much money. Part of that is that other companies have copied its basic search technology, but the first-mover advantage has turned Google’s early technology into an enduring brand advantage.
Also, my guess is that Google had better technology 10 years ago for running scalable infrastructure than Microsoft has today. While that may have contributed to their bottom line, I’m not sure it contributed much to their popularity.
I agree with your first premise (that startups don’t create new technology), but not the second premise (that large, established companies do).
Read ‘The Sources of Innovation’ by Eric von Hippel. It reaffirms what your first point, and shows that real technological progress usually comes from users of technology rather than producers (or, to put it in a better way, from cooperation between users and producers). More precisely, innovation happens when there is a feedback loop where users use technology in creative ways (according to needs not foreseen by the original producers) and producers incorporate those ideas back into their products. The contribution of the producer is to identify creative uses of their products and formulate business models around them. Amazon’s cloud computing initiative is definitely consistent with this point of view.
Another major source of innovation is academic institutions, where risk-taking is encouraged when it comes to new ideas. Of course, it’s also true that established companies also fund research.
I have the exact opposite feeling about Uber. I think that their main business model is: a taxi dispatch service that actually comes when you call it. There is no technology in that at all. The problem is that it is very difficult to enter a business where everyone else is frauds. You can’t just advertise that you aren’t a fraud, because who would believe you? Uber differentiated itself by being techy, to get people to try it. Maybe the technology was necessary to allow people to monitor cabs and allow people to trust it, but if the industry hadn’t dug itself into a hole, a similar business could have been built 50 years ago.
TDBM, I would argue is the most important step. A single discovery could have hundreds of different ways to coordinate with existing technologies. As for RPP, often the people who are best at creating and the ones who are best at distributing are very different. It’s a shame the distributor gets the lion’s share, but such is life. There are also levels below technology creation. Before the technology can be applied, it’s principles must be experimentally tested. Before an experimental test can be conducted, a theory must be developed to explain what you are testing for although some technologies skip this step. The experimenter and the theorist often receive even less than the applier who receives less than the distributor.
I don’t think that it’s fair to say that software isn’t technology. Facebook didn’t create new hardware but the idea of the timeline was new.
But even if we look at hardware I don’t think it’s true. Bre’s MakerBot industries did manage to sell MakerBots while it was a startup.
Arduino is created by a startup.
Pebble is a YCombinator startup. Technology like Arduino allowed Pebble to do their prototyping easier than was possible before. There are also a bunch of other Kickstarter projects that produce technology.
I do consider the Hackerspace ecosystem capable of creating new hardware.
A lot of new technology get’s developed by repurposing existing technology. Arduino couldn’t have been developed without the ability to buy cheap chips but Arduino is still new technology.