I really enjoyed this piece. It lays out a line of reasoning I would certainly like to be true, but is it?
My start-up vocabulary is failing me here so I'm going to have to use an analogy.
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In boxing, the most profitable fighter is not necessarily the best fighter.
A promoter will use an expert eye for the sound fundamentals of a great fighter at least as much to avoid bad match-ups for his prospects as he will to find those prospects in the first place.
Great fighters are not necessarily marketable fighters and their value falls through the through floor once they take an L.
What the promoter really wants is the right face, a guy with a great story and charisma, someone the people will pay to watch beat up cab drivers - he needs him to be good, but only good enough.
The promoter has all the resources to arrange the rest.
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So, is the issue that the VCs are overlooking / ignorant to these technical factors of great companies or is it simply that great companies are too much effort when they can get rich(er) on status quo games of cash and connections?
The sad truth is that they are in it for the money, right?
If the market is rewarding me-too mobile apps, then by Christ that's what they'll fund, because that's where the money is. Why fund a cancer drug or space company or whatever when there is no clear case that that is going to make a good ROI (or succeed at all).
The perception is that VCs are the money-men behind startups that change the world and make everything better and create value and value. The reality instead is that they have to make money and pay for themselves too, and the surest way to do that is to bet on "safe" products and things the market provably wants.
It is a great shame that the narrative is that VC-backed startups are the best actors for positive progress--I don't think we could be further from the truth.
It's understandable that being up-to-date with the latest academic results doesn't guarantee success. There are many, many other factors that determine the eventual success of a startup, and therefore it's investment appeal.
But I didn't see the article as a complaint that "investors are wrong", but rather "before you spend months inventing and building a new UX flow, take a few days to read about the latest research".
If a developer needs a balanced binary tree, they will first look for an existing implementation in the language they are using. If one doesn't exist, a good developer will check Knuth/CLRS/Wikipedia for the suitable algorithms and build it based on these recommendations, instead of jumping in and hacking something together on the spot.
I think the article argues that UX and product design could use a similar approach. If you are deliberately testing a new approach, sure, go build whatever comes to mind. But if you just need an "incentive mechanism" in your app, then it makes sense to read up about the existing research on what kinds and how large incentives work, instead of making a guess on the spot. And even if you are innovating on some aspect, it's useful to use the existing best practices as the starting point and improve & measure from there.
Further more, what is the exact connection between academic talent and great companies? Is there a connection to the value and position a start-up can obtain with the number of academia oriented employees it contains? Is it even a positive correlation?
I don't think he's implying you can't be a good company without it, just that there's a lot of hardship and lessons learnt that can be avoided by having a researcher do academic diligence. You can learn those lessons the hard way in practice, but it might be more efficient to do the research instead.
Sure, Google has a policy of employing people with an strong academic background but I kind of think they're mostly grossly underutilised maintaining UI code or doing other drudgery. I'm sure a few get to exercise their academic muscles from time to time but according to friends of mine at google that's the exception rather than the rule.
I think you mis-interpreted the parent's example. Larry and Sergey were academics before they were founders.[1] Their research lead directly to Google's success. I believe Google still licenses Page Rank from Standford. (A huge win for the TTO at Standford)
The fact they developed page rank at Stanford and then needed to licence it seems like a great reason to avoid Stanford. And possibly a great reason to avoid reading any academic research.
PS: 3am here so I am probably missing something obvious.
Probably you are. When the university pays you to develop something, and then only takes a minor cut of the profits, why would you want to avoid the university?
This is the right analogy. Its the same reason you don't always want a "faster" car in the america's cup or in f1. Boring racing. But the product is not "winning", its racing...the "racing and competition" are what sell tickets, attention, and bring in sponsorships. Technology-solutinos is only interesting insofar as it drives "good racing". This is why all kinds of "faster" technology is banned everywhere as "cheating".
> So why are we hiring designers mainly on their Photoshop skills and maybe knowing a few tricks for optimizing conversions on landing pages? What a waste.
> Of all the social sciences, the following seem to be disproportionately valuable in terms of creating and evaluating startups:
> Psychology / Social Psychology
> Internet Psychology / Computer Mediated Communication
> Cognitive Development / Early Childhood Education
> Organizational Behavior
> Sociology
> Education Research
> Behavioral Economics
> And yet not only is no one hiring for this, but having expertise in these areas likely won't even get you so much as a nominal bonus.
The core argument of this article -- that designers at top startups are not hired for their CogSci/etc chops -- is patently false in my experience. Has this person gone actually gone and talked with design leads at startups?
Never underestimate the ability of an "academic" to belittle others in regard to their own perceived ability.
Designers just fuxx around in photoshop. Sure.
Psychology is pseudo-science. N = 1 is no way to conduct a serious scientific endeavor.
Internet psychology? lol
Cognitive development / Childhood behavior - Ever hear of COPA? Many developers/designers/projects will never deal with anything front-facing involving anyone under the age of 13.
Organization behavior - hmmmm
Sociolgy - well....
Education Research - I suppose if your project is focusing on training/education you would want to be practicing best pedagogic practices.
Behavioral Economics - Cereally? I don't know how fundamental we need to get into treating our users as "active agents." Can't we just see them as the people they are and still succeed?
To conclude, all I can say is from my experience T=the best designers are born, not honed in the hoary halls of the academy, divorced as they are from the real world.
Researchers such as John Ioannidis have been making an increasingly good case in the last few years that a substantial proportion of published research in areas such as the social sciences and medicine may be wrong or misleading, though.
Obviously I wasn't trying to make predictions in these posts, let alone predictions that would look correct ten years later, but I think you'll see that I have a pretty good track record of being on the right side of history way before these sites hit their tipping points and became mainstream. But regardless, it's not really about making predictions, it's about knowing what questions to ask in order to better understand the founders and the marketplace. Ultimately you have to decide who to bet on, but I think it would be a mistake to confuse a bet with a prediction.
Does Facebook really rip off that much non-posted comments? I know they advertise Likes, but I haven't seen much more.
This doesn't necessarily detract from the bigger argument which is it is useful to know the research relevant in your field.
By analogy... Many hedge funds don't act like they know current financial theory. (Example: Icann) Others (Example: AQR) base their entire existence on being current on research.
The most likely explanation is that knowing "relevant literature" as proof of "doing homework" simply doesn't correlate with company's success and investors would rather wait to see some validation from the market.
Also, after having read a lot of social science research, the research is pretty crap for the most part. I'm sure there are a few gems in there, but you have to read a lot of positive results from badly-thought-out experiments with obvious holes to get to the few nuggets of truth.
Much, much, easier and faster to conduct your own experiment by building something and seeing how customers react to it.
After something fails, it's usually trivial to go back and see the obvious reason that it failed, and find a professor willing to say so.
Before something fails, it can be very difficult to notice it, and even more difficult to differentiate it from all the other obvious things that will kill it but actually never will.
It's hard to make predictions, especially about the future.
I enjoyed reading it but I can't say I agree with it. There is often an 'Entrepreneur in Residence' or 'CTO' or 'this guy I know' who is consulted by the partners when they are doing diligence on a startup. That person, if they take their job seriously, is abreast of the technical developments and academic research in the area (or can familiarize themselves with it) and apply it to the proposal under consideration. A friend of mine once called it 'technical headlights' which I liked as it has both the utility and limitations that vehicle headlights have on a dark road. Able to bring out obstacles, not necessarily going to light up something that is off road.
There is a difference between research and academia. Academia in an institution, with specific ways of becoming a member (thesis, tenure) and structure to support the sharing of information (journals, conferences). These structures don't fit well with startups.
Behavioral research and drawing insights from huge amounts of social data is definitely useful for the startup industry. But people can do this completely outside of academia where there aren't massive barriers to entry. And they can share their findings using blogs, books, github, consulting, etc.
Yeah, the slow transfer of knowledge between academia is a big problem and there is a need for people who have a foot in both worlds but it's tricky to be that sort of person because people in each camp will see you as somebody from the other camp.
That depends entirely on the culture of the University and Company.
The University of Central Florida's College of Engineering as entire courses taught by real world professionals from Lockheed, TI, Duke Energy, Boeing, Harris Corp, Orbital, NASA, etc etc etc. They also work very closely with students who are working on unique research projects and connecting them with experienced professionals that can help with the real world side of the research.
I'm sure UCF is not unique, it's just what I'm most familiar with.
"Why isn't somebody doing this?" - Why aren't you doing this? Provide a service to VC that answers those questions as part of their due diligence. Sounds like a good idea to me.
In formal, established companies this does exist: it's called "decision support analysis (or researcher)." Whether a particular staff person is steeped in academic research, which they should, and whether a particular staff person provides actionable insight and intelligence that big companies often lack is another matter. The problem is discoverability of results (because there is a vast universe of unstructured data and research out there) and applying it to specific needs: academic journal search (LexisNexis) and regular search engines combined with talented staff might work.
Sounds like there's a startup or two in decision support anyhow.
Your suggesting Academic Researchers should be consultants for VCs. Sometimes they are! but, just not full time. Usually, they might be on a board of advisors, for a small amount of stock, or maybe as an unofficial advisor.
Now let's cover why not. Simply put: academic research often is only tangentially related, and thus of limited value. The people with the most direct expertise in the area in question, are the ones who are actually doing the technology they're developing, on a day to day basis.
Coming from an academic perspective, my knee-jerk reaction to this post is "Awesome, we definitely need this", but after some thought I really don't see this as a necessary job (at least, not for most startups in most areas). I'll try to explain my more ruminative thinking:
Since the article actually specifies behavioral research, I think my background in anthropology and the social sciences might be helpful here. My research for the past ~year has been on the culture of Quantified Self, but I'm also coming from a background of Human-Computer Interaction and I'm going to study HCI at Stanford (sooner or) later this year.
What I generally call "behavioral" research is just too specific to be applicable without an academician him/herself to parse, abstract, and apply this stuff. Worse, you would be hard-pressed to find an anthropologist (or I suspect any other social scientist) who would be able, let alone willing, to make any predictions about the future, even in their own niche. My thesis's discussion section looks at the future of QS culture as it relates to mainstream culture, but I'm not willing to make any predictions at all. The most brazen thing I'm willing to do is highlight some of my observations and follow where those observations might lead. I immediately underscore that these are total unknowns, and that we should all just keenly watch QS culture for how these issues will play out.
That kind of non-committal culture (at least in the social sciences) is favored in academia because it's incredibly difficult to correctly guess or predict the future, especially when humans are the subject of research (and especially when they're aware of the prediction you're making, because they so often seem to want to prove you wrong). You want your research to stand the test of time, and making predictions that don't bear out undercuts your credibility.
So you won't read any journal articles in sociology or anthropology that definitively tell you what you should make your next startup about, and any interpretation between the lines you read will invariably be contentious. For all of my research, I wouldn't bet my lunch on any particular prediction.
Instead, it makes much more sense to have a UI/UX specialist whose job includes knowing the research and academic consensus on stuff. Maybe they should keep their ear to the ground to hear for any trends or new paradigms in user interface design, but whether this person can even shoehorn that stuff into real-world business endeavors is questionable.
All that being said, I think I agree with the idea that a startup should be cognizant of research in the area they're trying to break into. But that sounds (to me, anyway) like I'm advocating that in the process of doing a business plan and analyzing competitors someone should do a cursory search for existing literature on this topic to make sure there are no land mines in the field. If someone wanted to get into medical informatics but had no idea about HIPAA-compliance and the complications that injects, I would steer clear.
> That kind of non-committal culture (at least in the social sciences) is favored in academia because it's incredibly difficult to correctly guess or predict the future
It's not actually that it's difficult to predict the future -- it's just as difficult in industry, but they try all the time!
It's that it's difficult to prove in a peer-reviewed article that your prediction is correct. Academics don't try to say anything that can't pass peer-review.
This filter of peer-review is what limits academics from speculating. In industry, you are free of peer-review. Steve Jobs can predict that the world is moving to multi-touch phones, and it doesn't matter if his peers complain that there aren't any buttons or physical keys. He will be proven right in the marketplace.
I caught a hint of doubt on the "non-commital culture" from GP and I guess I agree with that. If they are specific models of behavior, shouldn't the model come with validating observations? If the new model is very encompassing so that good enough observations are hard to come up with or their specificity would detract from the broad view, It might be excusable. Otherwise, I would think that the paper has to clearly show it's raison d'etre to it's stakeholders, most likely interested industry -- with observations. And why not, sometimes predictions are due, specially when they contradict the status quo. The predictions don't need the pretense to be certainly true, they just need to be consistent (or follow directly) from the model.
I would expect predictions, just like a new physical theory or observation may accompany bold predictions following from it's premises.
Translating research findings into actionable advice for startups is incredibly difficult. You're either bound to find support for just about any idea or find that there isn't enough research about your idea/topic due to the difference in abstraction between academic research and actual design.
VCs don't invest in business models. They invest in the possibility of getting a big payout. We cannot assume that a given business model is immutable. You can only evaluate it's current state, which might be only loosely correlated with financial success.
I'd prefer a startup with traction and a team that might figure something out. I'm pretty sure you'd get more mileage learning how to spot sketchy people, rather than looking if the current model aligns with current-often-vague-and-inconclusive social sciences research.
academicians are outsiders looking in, fascinated by phone usage because it's a relatively new experience and they see how the world is changing.
Kids are the insiders. They don't need someone to tell them that something fascinating is going on in their own world. It's the only world they've ever known. They don't know of anything else.
The literature is written by the reporters. The kids using the technology are on the battlefield. They don't need a reporter to tell them what's going on.
> Investors often wait months before investing in order to let a little more information surface, during which time the valuation can (and often does) increase by literally millions. Given that the cost of doing the extra research for each deal would be nominal...
Not sure about math here. Lets say that average increase is $0.5M and only 1% gets funded. In that case it is around $5,000 per study to break even. I do not think investors could fit reliable evaluation into this money.
This must be a troll ... honestly recommending a mixing of aademics + 'best practices' consultants?
This person has never experienced the ridiculously huge different in productivity between startups/small to medium sized organizations and those big inefficient beasts like banks/telcos/government departments.
I am the learning design lead at Play-i (play-i.com). We build robots to teach kids ages 5+ how to program. I am a cognitive and developmental psychologist. I did my PhD in how early language input from parents affect kids' readiness to learn number and math concepts before a postdoc on applying cognitive science to middle school science education and another postdoc on how 2D and 3D block building affects geometric and spatial cognition and later math performance. I joined my first educational gaming startup in 2011. It imploded within 6 months, but that's another story ;)
This is what I recently recommended to new employees at my company. The three authors are highly respected researchers in the field. Here is a TED talk by Alison Gopnik (the main author) for a sense of her work on babies' and young children's natural readiness and ability to learn: http://www.ted.com/talks/alison_gopnik_what_do_babies_think
Missed the part about being unusual. Unusual being rare or uncommon, yes, but one of the first questions people always ask is if they have a learning specialist on board. This means different things to different people, but for me, I feel really lucky for a lot of reasons to land where and how I did.
It's called R&D. (Or, more accurately, this describes a subset of what R&D should be doing.)
Software culture is, to my surprise, deeply anti-intellectual. Crass commercialism has driven out everything better, and the result is that a discipline (technology) that ought to be focused on improving human life is, instead, focused on helping business assholes unemploy people.
Of course, the cost-cutting anti-intellectual shitbirds don't limit their damage to outside of their companies, so R&D is one of the first things they attack when they need to free up cash for their unreasonable bonuses.
My start-up vocabulary is failing me here so I'm going to have to use an analogy.
---
In boxing, the most profitable fighter is not necessarily the best fighter.
A promoter will use an expert eye for the sound fundamentals of a great fighter at least as much to avoid bad match-ups for his prospects as he will to find those prospects in the first place.
Great fighters are not necessarily marketable fighters and their value falls through the through floor once they take an L.
What the promoter really wants is the right face, a guy with a great story and charisma, someone the people will pay to watch beat up cab drivers - he needs him to be good, but only good enough.
The promoter has all the resources to arrange the rest.
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So, is the issue that the VCs are overlooking / ignorant to these technical factors of great companies or is it simply that great companies are too much effort when they can get rich(er) on status quo games of cash and connections?