Reid Hoffman discusses the company of the future

well thank you video and I'd like to invite up on stage our first guest of the morning and Reid Hoffman the co-founder of LinkedIn I think one of the most influential thinkers in Silicon Valley and in the world of tech Vijay set us a very high standard I guess we have to be the best opening keynote conversation you've ever heard if we're going to get the get off on the right foot to achieve his challenge for the day but we have just the man for the job and I would I want to start read by asking you about this new concept that you've been talking about over the last year or so blitz-scaling what is that so if you actually ask most of the intelligent experts within Silicon Valley what the secret of Silicon Valley is they will give you the same story they were giving you about 20 years ago which is a land of startups you have technology venture capital technology universities technology companies you put them in a pot used to and you have a culture which has a general lack of a fear of failure and you have lots of shots on goal and some of those become the unicorns and dragons and other kinds of companies that are transforming industries and yet that story is necessary but actually now insufficient because actually in fact we were going to take that story and look at at least 20 places in the world you would actually see unicorns and dragons essentially distributed roughly indexed by technological population and the actual real thing is that Silicon Valley has developed we developed a living playbook of essentially how to scale globally very quickly and I'm calling a blitzscaling because actually in fact it has parallels to the kinds of techniques that were invented actually in blitzkrieg even on the military metaphor is a little uncomfortable obviously which is how do you essentially pare down and move very fast in order to capture a large market opportunities and uber of course is a canonical current example and the key thing about this is that actually blitzscaling is not necessarily done through operational efficiency it's done through this through being able to move very fast to capture a large opportunity and so the very attributes that matter to it like for example you have to have a big prize it has to be something where when you get there actually you can entrench in a pretty good way because otherwise it isn't worth the massive amount of capital and everything else that goes into it frequently in Silicon Valley we tend to align that with companies that we call which we say have Network effects and then there's a set of techniques about how you grow the organization how you go product market fit how you actually go from single-threaded to multi-threaded how you bring in new talent at fast rates and effectively how you build the culture of the company and I taught a class at Stanford on this interviewing a bunch of the people who have done is like you know such as Eric Schmidt and Reed Hastings last fall and the links are online if people are interested I just just fell out in the case of uber what what is it that the traditional Silicon Valley narrative doesn't tell us about what uber is done thus allowing burr to scale so fast well so for example the traditional Silicon Valley narrative tends to be the you invent a piece of technology and that technology has such market demand you just kind of hold on to it as it goes and obviously there is a lot of market demand for uber probably most of the people if not all the people have actually used it you know an easy ability to call a car and revolutionize transports really important but actually what's going on behind it was essentially a road map for you know a playbook for how do we launch a lot of cities quickly what is the way that we establish a local team how is it we start validating drivers into it we need to scale the the number of different efforts were doing technologically everything from self-driving cars to route mapping and everything else and so for example as a example of some of the things that Ebor has done in terms of blitzscaling one thing they do is when they hire an engineer not always but frequently when they hire an engineer that they like they will say ok in your previous company who you were working with who are the three best engineers and they will send them off for letters without an interview all right that is a blitzscaling technique because it's it's more important to go fast get big this of course there will be some cultural thing some people will turn out and everything else but that will essentially allow you to grow your engineering team at a very fast rate in order to be capturing the the set of things that you need to be doing in this playbook I mean is this this something that's written down that's there from day one that you know you've got a a y combinator or whatever and they're gonna give you this as part of the training or is this something that yeah with the case of uber I mean at what point in the process did they know they were going to be doing this blitzkrieg well so but scaling this I'm sorry the many cities yeah your industry yes and so essentially what you do is you begin the the reason you may make a decision to go to go blitzscaling is you both have to be able to get access to the capital to do it because it is actually in fact inexpensive things in a few cases you can have a revenue engine that's powering it but frequently you actually need a deep pool of capital because you're frequently scaling far beyond far beyond expansive your current actual revenue the second thing you have to do is you have to say okay there's a it's it's inefficient so you have to actually have a reason to do it the reason could be first to market the reason could be critical mass scale the reason could be competitive defensive ness all of these are good reasons in order to do it and so you know uber launched they usually you want to have very good data that you have good product market fit frequently you know many of the big flame out you'll see is you actually haven't really figured out your business model you'll really figure it out product market fit you decided to blitz scale and that can be if you can raise the capital for it that can be the particularly big craters but so they say look we have competitive issues there is essentially transport you know people transport like startups going around all over the world this is recognized as really good category it is city by city so we have to get to every cities very quickly and so some of the stuff that Travis and the team did very well is they said okay it's time to raise a whole bunch of capital and go very fast and then part of the thing that makes this work within Silicon Valley is a part of essential part of what powered Silicon Valley's the network and it's not just the network of talent which is certainly important you can bring people in who had experience of high scale companies before or fast scaling companies four had experience with irrelevant technologies but there's also a learning network that is composed within Silicon Valley because whether it's venture capitalists angel investors experts who can say ok here is here's things you can you can ignore because part of what's happening when you're blitz scaling is you're actually ignoring problems because you're the know actually speed the scale is the thing that matters and so if we're actually having difficulties with exactly for example the tool development of how we are going to be deploying our software maybe lagging behind that will cause frictions organizational frictions development friction that's ok also what are the key things that you need to do now such that you don't hit a hit a wall that you didn't have to work around but you can actually continue growing through that and so you bring in various folks who have solved it's almost never the same problem but similar problems in terms of advice around the company because when you move from and part of what we did in our Stanford class as we said organizational scale is the thing that powers revenue scale and customer scale and so how do you essentially effectively move to the organization scales and be doing a good you know kind of producing good product and service and operating reasonably effectively while doing that you don't say when I move from 10 people to 50 people I get rid of the 10 people and I hire 50 new people I'm hiring 40 new people how do I bring them in effectively and how do I take the original 10 and how do I help them learn that way and then 50 to a hundred and a hundred to a thousand that's the kind of pattern that's happening within blitzscaling I guess but scaling is not a Six Sigma activity and that's nothing so I mean I suppose one of the attractions of the traditional Silicon Valley narrative about the technology being the magic bullets in a sense I'm just going of its own accord is it does allow for this small scale bootstrapping startup idea to really take off whereas I suppose what you're describing seems like much more of a large-scale plan as you say very capital-intensive which in a way ought to make it something that traditional large companies and we many of those represented here they ought to be able to to do better than the startups in some way so what I'm interested how you think about if you're if you're talking to a big company that sort of thinking about innovation and how is it how does it stop so they can barely eating its lunch or whatever it is there are there lessons in blitzscaling for them I think there are I think what you want to do is you want to look at their strengths and weaknesses you have as an existing large company including when you're an existing large company within Silicon Valley and you want to try to set the battlefield as much towards your strengths and away from your weaknesses so if it's simply kind of going to a radical green new field which has a different business model or a very very different technological base you can get there that's that's very difficult and it's difficult to compete with because usually it's not just competing with one startup usually there's a hundred startups going at that speed you know at that area and so you may have triple the chance of one of the hundred startups but that doesn't give you a very good batting average relative to which of you will win that the kinds of things I think you think about when you're in areas where you may be competing with blitzscaling companies is to say okay what are the ways that I can take my current advantages and doesn't mean leet rents and only what I'm doing but use them so one of them is for example blitzscaling companies almost always have very short time windows they have to have quick progress month by month quarter by quarter longer development projects are the kind of things that can actually in fact if you say look I'm doing a five-year plan and it's still going to compound through that and and do that effectively that gives you a time window that most startups actually don't operate in and so if you can look move into some regulatory battles twelve years yeah you have to a lobbying power so that that wasn't the one I would recommend obviously I have seen people try to deploy that one and it usually only delays the inevitable right I was there an example of a company that has well let me use let me let me talk about a Silicon Valley example which is one of the things that's happening right now is Facebook I was I put him in order Google Facebook and Microsoft are all working pretty intensely on artificial intelligence technologies and and while there are startups they're doing artificial intelligence technology is the likelihood is these neut should the techniques are not hugely new there's some important new additions but the application of these techniques with large server farms and large datasets is creating amazing results in terms of self-driving cars medical diagnosis a set of different things this is actually an area where large companies touches you know Google and Facebook can actually deploy much more strongly than startups right so like even Facebook would have difficulty going after uber Airbnb because it's a greenfield they're going after but actually in fact building a new AI technology which will take multiple years in order to refine on the data sets get the applications right is a perfect kind of innovation from a large company versus a start-up in terms of being able to capture broad new swaths and and and be the company of the future and so when you're looking at other companies that's the kind of thing to look at is okay what what part of that my assets my position allows me to develop a longer timeframe thing that I'll actually impact be the kind of company the future I want now there's one caveat to this that I think is very important which is I do think software is transforming the world my friend Marc Andreessen frequently defers this a software eating the world and so I'm more or less think that any organization that is a hundred people or more should actually say what is my software strategy and if you don't actually have a software strategy you should think hard and long about whether or not you need one because the innovation clock and what's possible through software becomes more and more of a competitive advantage whether it's a data advantage whether it's a distribution advantage whether it's for example the thing that's interesting about Tesla is not that it's an electric car but it's a software car right those kinds of things are the things that you need to think about and that's usually a new competency which will be difficult as opposed to your existing assets so you mentioned AI a couple of questions that come up a lot of them one is you know how fast is this going to be adopted in a way that radically changes people's workforces so they can either get rid of lots of jobs or greatly increase the productivity of other kinds of workers so I think that let's see usually the future is sooner and stranger than you think so the fact that AI will start being deployed sooner than most people reflexively think medevacking essentially already is is I think something to really pay attention to but it doesn't mean that you know then what happens is people go oh we're gonna have robots you know taking all the jobs five years from now which is not gonna happen that goes well because actually in fact getting robots like so for example the kind of thing you're already seeing through AI is you can actually have an app on your mobile phone that can diagnose whether or not the skin lesion is cancerous or not better than your average doctor that that's essentially present today in terms of functionality so you say all right well does that mean that doctors are all going to go away not necessarily because essentially when you look at he said now we have a a cross-check of a very good way of saying is this particular skin thing something we should be worried about or not that allows doctors to focus on a lot of other things or have higher touch with the patients and so forth so it doesn't doesn't mean that we're gonna have all robot doctors because you have this specific thing that's that's actually an example of it and if you actually look at most of these technological developments they tend to be oriented towards how do you amplify productivity from individuals now sometimes that will lead to great job location because for example if you go to self-driving cars and essentially say okay now every car is self-driving or the vast majority then essentially you say okay we have a transportation workforce that needs to Tran needs to transfer us kind of skills and industries it's very painful it's difficult Industrial Revolution was painful and difficult and we need to as a society and as companies help facilitate that because we would actually in fact rather have you know and kind of everyone engaged in participating in the future however that is not that's probably the worst one I didn't see coming in terms of the biggest like you know digital leap but I actually think that there's ways that when you for example look at tellers when they're brought into the banking system you had ATMs that didn't actually reduce the number of tellers the tellers just started doing different jobs so it kind of it's an uneven thing that doesn't lead to all the robots are doing although some of the some leading technology people like Elon Musk and Bill Gates have talked about AI as potentially for posing existential threat to humanity did you share that fear so let's see that the short answer is I truly generalized artificial intelligence will be a new species and as part of a new species what our relationship with it will be complicated however I actually think I worry about people who are worried about that one being the primary concern because actually I think it's a set of other things including the labor translocation that are the more real present issues for how we should be thinking about both the opportunities and the challenges for artificial intelligence and so I myself tena say don't worry too much about you know yes we've seen this movie The Terminator yes we've seen this movie The Matrix these are movies and part of the thing is that an AI wouldn't necessarily go my reason that is to dominate humanity they may actually have very other kinds of things other things to do better things to do and so the real question is actually in fact how we evolved and how we deploy artificial intelligence and so I'm more worried about what humans will do with it than what prospective future intelligences and one other actually point that's actually useful here is part of how I actually calibrate amongst technologists what their views on AI is as I asked them for generalized AI when between ten and a hundred plus years from now do you think that a generalized AI will be created if they say ten or twenty or third they have some worries about this transformation and they say 30 or more then generally speaking what they're partially saying is there's enough big jumps that are happening here that's uncle it'll happen but it's unclear when it will happen and then as you get closer then you'll actually have a better sense of what the opportunities and challenges are now one other area the way you've been a notable commentator in public has been on the rise of the blockchain and which is a software underlying Bitcoin and I guess your notable I'm not being a extreme libertarian that wants to bring them to stay and create a parallel money and so forth I mean what's the most exciting thing to you about the blockchain so what makes the Internet is the Internet's an open platform that unlocked a lot of creativity and many different software development efforts that could create everything from all the world's information in your fingertips to discovering entertainment to you know medicine to transfer to to being able to be much more efficient as a individual in your career such as LinkedIn or companies hiring talent all all of this stuff became available because the internet where the internet was an open set of technologies however one of the open set of technologies that doesn't exist is financial applications and that's because you know there's everything from regulatory and risk management and a kind of a jointly held na Polly from banks the thing that is interesting about Bitcoin and blockchain is it creates the first open platform for value systems so things that touch money and exchange and contracts essentially you can you use blockchain as a platform in order to to build new kind of software applications on top of it and that's the first of that sort I wrote an article last year and Wired UK on this because part of what I wanted to make sure that people saw was it isn't just the ha it's a currency that you can track which is by the way not entirely true and we can go into the details of that if we have time I think we're shorten whatnot but it's actually in fact the possibility that knew that large numbers of new creative entrepreneurial innovators can try to create new things that enable our financial system and our value system to operate in new potentially great ways is the thing that is potentially massively valued transforming and just briefly I mean if it's not going to be replayed quite and placing the dollar where do you see the big disruption happening first as a result of this innovation well so big Bitcoin and blockchain are tied together there's a fashion amongst banks now to say we love the blockchain we don't like Bitcoin Bitcoin gives you the economic incentive for the distributed ledger cryptographic ledger that blockchain is and that platform by the way if you think about it it's like a an open spreadsheet that people can write to and that spreadsheet is like the platform for you can think about like models and other kinds of things you're doing you know I think it'll be anything from banking in the unbanked world to money transfers to smart contracts and part of the thing that's interesting is like when you saw the internet starting ago you wouldn't have necessarily predicted Facebook and Netflix right at the you know 1993-1994 when it started getting commercialized I think that the the same thing is where I think we're gonna be surprised but what the interesting applications are okay let's take a couple of quick questions from the audience anyone want to kick us off gentlemen right at the front here the microphone will come to you and ride the weekend why don't you call out alone yeah yeah just say who you are right so the question the question is what would LinkedIn vast amount of data what what big Jen's using from that data what we do actually do occasional release in this we don't mind data all the data is data that numbers give us and for reasons that are helpful to them but you know we can see for example like which kind of job categories are growing we can see which industries are growing in which regions we can see which skills are trending up and trending down we have an index of every kind of English language description of the skill all of those kinds of things are parts of the data that then we then use to conceptualize applications to help both individuals and corporations essentially adapt into the future and there's a bunch of different initiatives we're very short on time here so if you're curious with this look at LinkedIn cities which is trying to help cities figure out how to essentially progress their workforces and make sure that they're helping their companies be companies of the future and then there's various trends on like which which which jobs and which skills are in strong growth modes because we try to give those to students and to other folks there's a lady in the middle here we got a microphone yeah I've got a cultural question as well sorry I'm in bad ways I'm hiring on there should I go ahead or chilli sauce the question it would also take the lady in the middle and that will be sure Henry Milani with the Cutie read thank you for your comments on blitz-scaling it really harkens back to web 1.0 and that's what I'm thinking in my mind right I'm not a millennial so I've seen the the the web points 1.0 go to web 2.0 time it's fairly short circuit the question speed to scale I think there are lessons to be learned from web 1.0 what is it that we need to be aware of as we looking at litt scaling today well and then we'll just take the question from the lady as well and then we can do both okay great okay great thanks and I think there's a lot of ways there's Oh Carolyn's antenna from farm and there's a lot of conversation around what Silicon Valley can learn or what big companies can learn from Silicon Valley right but I do think there is sort of the flip question as well of what Silicon Valley can learn from large and established companies especially with blitzscaling and sort of retaining your brand values as well as culture and I'd love to just hear your thoughts on that okay so thank you first question a lot of the web pointone web one o stuff was essentially the first real that was the first area where there was a lot of systemic blitzscaling and so we learned a lot of negative lessons we learned the negative lessons of have a pretty good sense of what your business model was before you blitzscale we had the lesson of make sure that actually in fact because you actually have these operational inefficiencies as you're blitzscaling make sure that the the market you're heading towards is a very valuable market because it gives you enough to actually in sense correct your business and so the businesses that actually impact worked in web 100 and persisted were the ones that really did that well and many others were essentially creators that's that's essentially the web 100 now the what Silicon Valley can learn from other businesses it's actually a tricky question there's obviously a ton of things as we're bad at brands were bad at marketing there's questions of we're all fairly young businesses so how you sustain is actually in fact one of the things that's that's important on the other hand there's this contrast people tend to want to have all strengths and no weaknesses and actually almost every strength that's worth having has corresponding weaknesses and so Silicon Valley tends to be very good at this kind of disruptive innovation because it's willing to throw everything out and start from the beginning and so it's very difficult to say we're going to do that mindset and we're going to be learning from existing businesses so in fact many of the strengths that allow Silicon Valley to operate in particular ways is one of the things that actually in fact then makes that actually a challenging thing for most Silicon Valley companies and it's it's because of strengths they have now frequently when I'm asked about how do you create a Silicon Valley elsewhere and what kinds of things you do you say well for example if I'm trying to do that in New York I would orient that more around the financial system or things that where you have these kinds of assets that people can learn from and and create a unique ecosystem there if it's a pure independent software system it should be within the US more done in Silicon Valley so one last question for me and that is you know what is the area of innovation that you were moat spending most time wrestling with at the moment well there's two obviously think a lot about artificial intelligence but I already talked about that so the other one I'm thinking a lot about is the intersection of biology and digital right essentially genetics is is moving the sequencing of genetics is decreasing cost faster than Moore's law and it's moving to a readwrite where you can both read that's the sequencing and also right through CRISPR and so forth and the the opportunity and and challenges of this I think are more significant than AI great well I think you've given the audience lots of food for thought to kick off the day and so Reed thank you so much for coming we could I think talk for hours but unfortunately with the agenda has to go on so thank you very much thank you

Channel: WithTheEconomist

Views: 9,819

Rating: 4.9411764 out of 5

Keywords: The Economist, The Economist Group, The Economist Events, Reid Hoffman, LinkedIn, Innovation, Company of the future, Business disruption, Blitz scaling, Technological innovation, Innovating at scale

Id: 0RpZso3KQeE

Length: 27min 32sec (1652 seconds)

Published: Tue Mar 29 2016