Hackers and Startups

Rather good article on starting Startups by Paul Graham, founder of Y Combinator, its a List of Things a Founder Needs to Know. In essence his argument is that much about running a startup is counterintuitive to what peopel have learned to that point in more formal structures - here is the Broadstuff Expergated Version for you lazy lot out there:

1. Don't saddle yourself from the get-go

Trust your instincts about people....one of the most common mistakes young founders make is not to do that enough. They get involved with people who seem impressive, but about whom they feel some misgivings personally. If you're thinking about getting involved with someone—as a cofounder, an employee, an investor, or an acquirer—and you have misgivings about them, trust your gut. If someone seems slippery, or bogus, or a jerk, don't ignore it.

2. Its all about the Customer

The way to succeed in a startup is not to be an expert on startups, but to be an expert on your users and the problem you're solving for them. [T]he characteristic mistakes of young founders is to go through the motions of starting a startup. They make up some plausible-sounding idea, raise money at a good valuation, rent a cool office, hire a bunch of people. From the outside that seems like what startups do. But the next step after rent a cool office and hire a bunch of people is: gradually realize how completely fucked they are, because while imitating all the outward forms of a startup they have neglected the one thing that's actually essential: making something people want.

3. You can't game the startup system

The third counterintuitive thing to remember about startups: starting a startup is where gaming the system stops working. Gaming the system may continue to work if you go to work for a big company. Depending on how broken the company is, you can succeed by sucking up to the right people, giving the impression of productivity, and so on. But that doesn't work with startups. There is no boss to trick, only users, and all users care about is whether your product does what they want. Startups are as impersonal as physics. You have to make something people want, and you prosper only to the extent you do.

Though he makes the caveat:

The dangerous thing is, faking does work to some degree on investors. If you're super good at sounding like you know what you're talking about, you can fool investors for at least one and perhaps even two rounds of funding. But it's not in your interest to. The company is ultimately doomed. All you're doing is wasting your own time riding it down.

4. A startup is for life, not for Christmas

Startups are all-consuming. If you start a startup, it will take over your life to a degree you cannot imagine. And if your startup succeeds, it will take over your life for a long time: for several years at the very least, maybe for a decade, maybe for the rest of your working life. So there is a real opportunity cost here.

And as for starting up while at Uni, its one thing or the other. It may have worked for Zuckerberg & Gates, but they are a smal minority:

Yet when it comes to startups, a lot of people seem to think they're supposed to start them while they're still in college. Are you crazy?

Graham's view on what to dio at Uni is this:

...if you want to be a successful startup founder is not some sort of new, vocational version of college focused on "entrepreneurship." It's the classic version of college as education for its own sake. If you want to start a startup after college, what you should do in college is learn powerful things.

5. How can you tell if you're up to this challenge?

You can't tell. Your life so far may have given you some idea what your prospects might be if you tried to become a mathematician, or a professional football player. But unless you've had a very strange life you haven't done much that was like being a startup founder. Starting a startup will change you a lot. So what you're trying to estimate is not just what you are, but what you could grow into, and who can do that?

6. The way to get startup ideas is not to try to think of startup ideas.

I've written a whole essay on this, so I won't repeat it all here. But the short version is that if you make a conscious effort to think of startup ideas, the ideas you come up with will not merely be bad, but bad and plausible-sounding, meaning you'll waste a lot of time on them before realizing they're bad.

The way to come up with good startup ideas is to take a step back. Instead of making a conscious effort to think of startup ideas, turn your mind into the type that startup ideas form in without any conscious effort. In fact, so unconsciously that you don't even realize at first that they're startup ideas.

7. How do you know if you are working on Real Stuff ?

I can't explain in the general case what counts as an interesting problem, I can tell you about a large subset of them. If you think of technology as something that's spreading like a sort of fractal stain, every moving point on the edge represents an interesting problem. So one guaranteed way to turn your mind into the type that has good startup ideas is to get yourself to the leading edge of some technology—to cause yourself, as Paul Buchheit put it, to "live in the future." When you reach that point, ideas that will seem to other people uncannily prescient will seem obvious to you. You may not realize they're startup ideas, but you'll know they're something that ought to exist.

8. And the Ultimate Advice?

So here is the ultimate advice for young would-be startup founders, boiled down to two words: just learn.

Link at the top takes you to the full article, and I've linked to a further eassy he wrote as well

Kickstarter was hacked - The Verge:

Hackers breached Kickstarter's defenses and stole the information of an unspecified number of customers, the company disclosed today. The company learned of the breach on Wednesday from law enforcement officials, and quickly resolved the breach, Kickstarter said today. It did not disclose how the breach occurred.

No credit card data was accessed, the popular crowdfunding site said, but hackers did gain access to usernames, email addresses, mailing addresses, phone numbers, and encrypted passwords. The company recommends that all users create new passwords for their accounts and any other accounts that use the same password.

Where there's bank account numbers, there will be hackers. Good news is they admitted it, many companies don't.

The issue for any user of any Web service is that the more companies you put your data with, the higher the probability that it will be hacked and identities pilfered. So what to do? A good plan is to leave the minimum data with any company, but companies seem to want more and more data that is largely irrelevant. In the absence of a "minimum data law" or a trusted 3rd party service, or obfuscation services, we think using proxy data wherever you can (ie data that leads to something else, that only then leads to you -eg an email account that is not "you" for example) is the only real option for Joe and Jo Average right now - if anything its going to get worse (see our post on the Dark Side of Open Data - of course this applies to all data, not just Open data)

I can imagine a world emerging where non-digital data is actually valued more than on-line data again, and where private or "Word Of Mouth" networks (WOMNets) make a comeback as the tradeoff between convenience and security shifts.

Further to our earlier post on the incipient unwinding of the UK consumer tech startup scene, it doesn't help that any that do survive will cost significantly more to run than the indstry heavyweights they compete with.

Google's tax rate in the UK is between 2.5% and 0.25% of revenues, depending on whether they make £4m or $4bn out of the UK - Pc Pro.

Google bills all online advertising via its European head office in Ireland, and at the hearing, Google's vice president of operations for Northern Europe, Matt Brittin, said his firm uses tax havens including Bermuda to increase shareholder value, but said the company obeyed the letter of the law. Last year, it posted £395m in revenue and paid £6m in UK taxes; however, a US SEC filing showed it made sales attributable to UK addresses of $4bn (£2.5bn).

Amazon is similar - As PC Pro previously revealed, Amazon.co.uk is considered a "fulfilment" company for the European branch of Amazon, which is based in Luxembourg, and paid £1.8m in tax last year. However, the evidence submitted to the PAC showed £3.35bn in sales were from the UK - 25% of Amazon's sales outside of the US. If all the tax was on UK only revenue that's a maximum of 0.05% (and more like 0.0013% if only 25% of tax paid is from thre UK)

You either have to believe these businesses perform far, far worse than their corporate average, or you have to believe that their tax revenues are underpaid.

Now, compare this with the tax that any UK technology company pays in the UK, which, for a small limited company is 20% on the first £300k and ratchets up to 23% at £ 1.5m. What this in essence means is that any UK tech startup starts the game with both hands tied behind its back vs the major players.

Now, let us make a heroic assumption that a viable startup's taxable income is similar - as a % of sales - to Amazon or Google (in fact it's probably worse). This implies that the UK startup is spending between 10x and 1000x more on it's tax bills per £ earned. This is an "order of maginitude" rather than an exact figure, but it makes the point - the risk of a startup is far higher than that of a major corporate, but the rewards are structurally far less.

This is also an a**e-to-face reward structure, and certainly not the way to give the UK's technology entrepreneurs a boost, especially if you are hoping they will lift the UK out of a depressing recession.....one could (and in my view should) make a case for near zero tax for startups until the position is equalised

A mere week after we noted the Silicon Valley sturm and drang about the decline of Consumer VC funding, following the popping of the Social Media bubble, there is now a sturm and drang around the impact of the cash drain on the booming "startup production industry" as we called it in 2008 (the seed funding competitions, newly minted angels, incubators, optimistic lecture circuitry etc etc), probably started by Y Combinator's discombobulation this weekend just past. Now there is much more handwringing in the blogosphere as it becomes clear the oxygen of cash is receding.

To say this is totally predictable is putting it mildly, heck, we predicted it months ago - but it seems that time after time greed trumps sense. Anyway, a good summary of the basic dynamics acting in the tech startup funding space is well put by Chris Dixon:

Startups sit in the middle of two markets: one between VCs and startups, and one between startups and customers. These markets are correlated but only partially. When the financing supply is low but customer demand is high, entrepreneurs that are able to finagle funding generally do well. When financing and startup supply is high, customers do well, some startups do well, and VCs generally don’t. And so on.

When VCs get too excited, people talk about a bubble. When VCs get too fearful, people talk about a crash. Historically, downturns were great times for startups that were able to raise money because competition was low but customer demand for new technology remained fairly steady. Downturns also tended to coincide with big platform shifts, which usually meant opportunities for entrepreneurs.

These markets shift independently between different stages and sectors, although there are connections. The amount of financing available is relatively constant, because of the longevity of VC funds and the way most VCs are compensated (management fees). Less financing in one sector or stage usually leads to more financing in others.

The stages are related because the early stages depend on the later stages for exits and financings. The result is a bullwhip effect where changes in later stages (the latest stage being public markets) lead to magnified changes in early stages.

What this means is well satirized by The Kernel, as it allows a lot of vested interests to invest in it:

when you flood a market with former user experience consultants and professional “strategists”, each of whom has their own uniquely dreadful idea for a technology start-up (normally something that failed in San Francisco half a decade ago), then throw money at them, proper developers suddenly become hot property.

...There’s no shortage of marketing, public relations and even business development enthusiasts angling for a slice of the Old Street pie. But the sort of hard skills necessary to build digital products aren’t that easy to come by.

That’s because they’re simply not taught widely enough in schools or in universities [Oxford for example admits 10x more historians, economists and philosophers every year than computer scientists - Ed]. Needless to say, governments tend not to invest in higher education and research and development, because it’s a thankless, multi-decade endeavour that obstinately refuses to concord with the electoral cycle.

Instead, governments tend to pootle around with easy wins they can point to in the run-up to polling day. Investment into early stage venture capital and sponsoring drinks parties for luvvies in Shoreditch is an easy, cheap and measurable way to make it look like you’re supporting enterprise.

This creates a wall of hype that suck(er)s in aspirant startup CEOs....

Now consider that glut of start-ups in east London, aided and abetted by that noisy, hyperactive, undoubtedly well-meaning but ultimately insignificant Government department anxious to locate simple, measurable metrics of success – like the number of companies founded, or people employed.

There are aspirational, wannabe entrepreneurs, who foolishly view a tech start-up as a route to easy riches, everywhere. They will always be happy to show up to a sponsored booze-up, to nab subsidised office space and to cling greedily to taxpayer-funded investment.

They represent little more than the middle-class branch of the welfare state, funding themselves and their marketing departments with money from daft angels, a dafter public or, yes, the public purse.

Indeed, when newly minted Angels are stampeding over the Fools and Friends in a rush to the startup pot, you know its time to run far, far way. Sadly for all the startups out there, the "startup production industry" is a lagging indicator of a bubble deflating, i.e. by the time their clay feet are showing the cash tide has long gone out.

Reuters:

When Randy Adams, 60, was looking for a chief-executive officer job in Silicon Valley last year, he got turned down from position after position that he thought he was going to nail — only to see much younger, less-experienced men win out.

Finally, before heading into his next interview, he shaved off his gray hair and traded in his loafers for a pair of Converse sneakers. The board hired him.

"I don't think I would have been able to get this CEO job if I hadn't shaved my head," says Adams, who has founded eight venture-backed companies. He is now chairman of the company that hired him, mobile conference-call service Socialdial, and is fundraising for a new business. Adams has supplemented his makeover by trading in his button-down shirts for T-shirts, making sure he owns the latest gadgets, and getting an eyelid lift.

Forty is definitely not the new 30 in Tech, it would seem:

"I don't think in the outside world, outside tech, anyone in their 40s would think age discrimination was happening to them," says Cliff Palefsky, a San Francisco employment attorney who has fielded age-discrimination inquiries from people in their early 40s. But they feel it in the Bay Area, he said, and it's "100 percent due to the new, young, tech start-up mindset."

They go on to point out that there are some benefits of youth, but it is possibly being over-emphasized now:

In some cases, there are reasons other than bias for preferring younger workers in a startup setting. People with young children can be strapped for time and less able to work long, late hours. Younger workers are more likely to be expert in the newest software programming protocols. Young entrepreneurs, like many others, often move instinctively in hiring from the cohort of those they know.

Yet there are some indications that age bias is now part of the culture in Silicon Valley - especially visible in what Adams of Socialdial calls the "cachet of the young entrepreneur." When young executives like Zuckerberg are successful, their age often gets a lot of attention. Successful older entrepreneurs, on the other hand, take pride in every aspect of their accomplishments - except their age.

[So] When the software company Workday went public last month and raised $637 million, little attention was paid to the fact that co-founder and co-CEO David Duffield is 72.

My own experience and those of other "wrong-side-of-40's" in the industry I know (bearing in mind anecdote is not the plural of data of course) is that no, we are not as up on the intricacies of the latest cool language, but our experience also shows us that the big drivers of success are seldom to do with the tech itself, nor working long and hard instead of smart. It's about managing risk, enthusing people, controlling cash, ensuring delivery quality, attracting customers, managing expectations - and while experience doesn't guarantee success in this, it does increase it's probability, as it's a learning curve thing. Which is why, when the going gets tough, Boards start to want a "grown up in charge" (Google, Facebook...and now Groupon it would seem). Horses for courses, as they say....

And, if I was being exceedingly cynical, I would suspect that some of the preference for youthful startups is their naivete, allowing funders to strike deals that no-one who has been around the block would ever accept.

Interesting piece in the WSJ about an Urban Drfit for technology companies:

For as long as many of us can remember, high-tech industries have flourished in the suburban office parks that are so ubiquitous in Silicon Valley, North Carolina's Research Triangle and other "nerdistans." But in recent years, high-tech has been taking a decidedly urban turn.

Silicon Valley remains the world's pre-eminent center of high-tech industry, of course. But even in the Valley, denser, more mixed-use and walkable places, like downtown Palo Alto, are becoming the preferred locations for start-ups and smaller firms. And many other start-ups—Pinterest, Zynga, Yelp, Square and Salesforce.com, to name just a notable few—are taking up residence in downtown San Francisco.

New York City's Silicon Alley—after a false start during the tech bubble of the late 1990s—is now home to more than 500 new start-up companies like Kickstarter and Tumblr, not to mention the gigantic Google satellite in the old Port Authority Building on Eighth Avenue between 15th and 16th streets.

I recall at the height of the dotcom boom, you couldn't move in San Fran without tripping over a a Blazer'd and Chino'd dotcommer, but Silicon Alley was still mainly Chinatown - so is it just a new Bubbletime, or is it a real shift?

Across the Atlantic, London's once- derelict Shoreditch district—now known as Tech City or Silicon Roundabout—has been transformed into a thriving high-tech district housing 3,200 tech firms and 48,000 jobs, according to a recent report from the Centre for London.

Except that's not really true, the action is more spread out - Soho, London Bridge, and other areas all have their enclaves, but they are still mainly within the inner city Circle line, it is true. So asssuming it is a real trend, what is driving it? Part of it is avoiding the increasingly traffic-jammed commutes to beltway business parks, says Mark Suster (now in LA, but he was a London boy when I knew him), and part of it is other amenities:

There are also the distinct lifestyle advantages of setting up shop in the hurly-burly of real urban districts. Compared with previous generations, today's younger techies are less interested in owning cars and big houses. They prefer to live in central locations, where they can rent an apartment and use transit or walk or bike to work, and where there are plenty of nearby options for socializing during nonwork hours.

"It's not that young people wanted to live in Mountain View in the past," Mr. Suster blogged. "In fact, so many did not that companies like Google & Yahoo had free buses with Wi-Fi from San Francisco to their Palo Alto and Sunnyvale headquarters."

I suspect there is also the shadow of underlying modern economics there, in that I am reliably informed that you can no longer afford a Mountain View house and car on startup money, so if it's to be a bijou pad and bus it may as well be somewhere with decent amenities outside.

But SV and New York and London have long had overpriced housing, so why did people go to out-of-town campuses in the first place?

The answer was cost - companies used cheaper land business park campuses to minimise their costs, while also externalising the inconvenience cost by forcing employees to bear the cost of commuting and car ownership. However, when the majority of employees own the companies (as is the case in a small startup) then that economics is turned on its head and it's far more rational to live as near the shop as you can (or even above it, or in it). Also, its an attractor. A company baesd in central London is easy to get to for a large number of people all around London. Put it out on the beltway, and its becomes inaccessible to 3 quadrants out of 4 without a bad commute. And if they have other options, you've just lost 75% of your potential staff recruiting base.

Also, it would seem the startup and market economics have changed:

An even bigger part of the story is rooted in the changing nature of technology itself. A generation or so ago, the fastest-growing high-tech companies were more like factories. They developed proprietary software systems, designed and manufactured chips, built computers and created the infrastructure that made the Internet possible. Whether it was Microsoft or Apple, they deployed big engineering teams—and they needed big suburban campuses to house them.

The changing nature of technology—cloud-based applications in particular—enable new start-ups to succeed more quickly, with smaller teams and much smaller footprints.

The speed of technology has also accelerated. The companies that succeed are the ones that stay in the closest contact with their end-users and first adopters, as MIT's Eric Von Hippel has shown. When a company is located in a city, many of those end-users can be found right on its doorstep.

At the same time, high-tech products and industries are more multidisciplinary than they used to be. Success often requires excellence in more than one field of technology and in other lines of business. East London's tech scene is led not by tech firms per se but by "digital creative" companies that combine computer technology with music, art and narrative—and musicians, artists and writers cluster in cities.

I'd discount the London thing as an overall trend, London bats way above its weight in media (online and off, it always has, it houses the UK's Madison Avenue, Hollywood, News Media and the BBC plus its multiple spin outs/offs/ins/etc), just as SV does in new technology infrastructure, so I'd say that's a London cluster-specific issue. The rest of the economics of firm size, speed to market and close to consumer issues do ring true though.

The other thing about cities is that, well, they are just fun places for smart people to live in:

Cities are central to innovation and new technology. They act as giant petri dishes, where creative types and entrepreneurs rub up against each other, combining and recombining to spark new ideas, new inventions, new businesses and new industries.

Once you are tired of London (or New York, San Fran, Berlin, etc etc) you are tired of life.

(Incidentally the article is written by Richard Florida, whose major thesis is that liberal urban areas attract the most groovy, smart, creative and interesting people. As a Londoner, I have to agree . As an aside, my experience is that having a big University (or even better, a few) in the town is a huge boost to that vibe as well )

Following on from Part (I), in my opinion this piece, "All Revenue is Not Created Equal: The Keys to the 10X Revenue Club" by Bill Gurley a few months ago sums up a lot of the main issues to think about around the business model, and some areas of customer attraction. I have abridged it below, but the full piece really is required reading.

1. Sustainable Competitive Advantage (Warren Buffet’s Moat)

By far, the most critical characteristic that separates high multiple companies from low multiple companies is competitive advantage. This concept, well explained in Porter’s book by the same name, basically asks the question, “How easy is it for someone else to provide the same product or service that you provide?” If your company has “high barriers to entry,” Wall Street will be super excited, as investors will have confidence discounting cash flows many, many years into the future.

2. The Presence of Network Effects

No discussion of competitive advantages and barriers to entry is complete without a nod to perhaps the strongest economic moat of all, network effects. In a system where the value to the incremental customer is a direct function of the customers already in the system, you have a powerful dynamic that tips towards winner take all. Perhaps the definitive piece on this type of advantage is Brian Arthur’s Increasing Returns and Two Worlds of Business published in HBR back in 1996 [Recommended reading, its an eye opener]. This “second world” that Brian refers to is one where the market leader has an unfair advantage that is reinforced by network effects.

3. Visibility/Predictability Are Highly Valued

For the same reason that investors favor companies with sustainable competitive advantages, investors favor pricing models that provide a high level of predictability and consistency in the future. It is easy to see why revenue visibility would have a positive impact on a DCF analysis. The more certain you can be of future cash flows, the higher premium you will put on a business, and as a result, you will see a higher price/revenue multiple. One obvious example of this is the predictable nature of SAAS subscription revenue. Salesforce.com trades at a staggering 7.5x 2012 estimated revenues. SuccessFactors trades at 7.9x 2012 estimated revenues. Subscription revenue businesses take longer to grow than traditional software businesses, but once you reach scale investors put premium multiples on the predictable future revenue streams.

4. Customer Lock-in / High Switching Costs

If investors value predictability, than retaining customers for long periods of time is obviously a positive. Conversely, if customers are churning away from your company, this is a huge negative. Investors are highly fixated on churn rates, as they should be. Churn has a direct and significant impact on a DCF model. With subscription models, a low-churn customer is quite valuable. In fact, companies with excessively low churn rates (5% annually or less) are very likely to have price/revenue multiples in the top decile. Obviously, high churn rates are really bad for all valuation multiples.

5. Gross Margin Levels

This may seem super-basic or even tautological but there is a huge difference between companies with high gross margins and those with lower gross margins. Using the DCF framework, you cannot generate much cash from a revenue stream that is saddled with large, variable costs. As a result, lower gross margin companies will trade a highly discounted price/revenue multiples. Amazon (20% gross margin), which is certainly among the very best retailers when it comes to execution, trades at a low 1.5x 2012 revenue estimates. Wal-Mart (25% gross margin) trades at 0.41x 2012 revenues. Best Buy (24% gross margin) trades at only 0.22x forward revenues. All things being equal, gross margin percentage should have a direct impact on price/revenue multiple, as there will obviously be more gross margin dollars to contribute to free cash flow. Journalists who quickly apply 10x multiples to all private companies should at the very least consider gross margin levels in their analysis.

6. Marginal Profitability (ie scaling)

Investors love companies with scale. What this means is that investors love companies where, all things being equal, higher revenues create higher profit margins. Microsoft had wonderful scale in this manner for many, many years. Selling more copies of the same piece of software (with zero incremental costs) is a business that scales nicely. Companies that are increasing their profit percentage while they grow are capable of carrying very high valuation multiples, as future periods will have much higher earnings and free cash flow due to the cumulative effect of growth and increased profitability.

7. Customer Concentration

In their S-1, companies are required to highlight all customers that represent over 10% of their overall revenue? Why do investors care about this? Once again, all things being equal, you would rather have a highly fragmented customer base versus a highly concentrated one. Customers that represent a large percentage of your revenue have “market power” that is likely to result in pricing, feature, or service demands over time. And because of your dependence on said customer, you are likely to be responsive to those requests, which in the long run will negatively impact discounted cash flows. You also have an obvious issue if your top 2-5 customers can organize against you. This will severely limit pricing power. The ideal situation is tons of very small customers who are essentially “price takers” in the market. Google’s AdWords program is a great example.

8. Major Partner Dependencies

Investors will discount the price/revenue valuation of any company that is heavily dependent on another partner is some way or form [Which is why we are sceptical of biusinesses based on Twitter or Facebook platforms]. A high profile example of this is Demand Media’s reliance on Google’s SEO traffic. Google isn’t the customer per se, but they can heavily impact the outcomes for Demand. And even if they don’t impact them (the recent quarter was in line with expectations), the mere awareness that they could, can have drastic impact on long-term valuation, and therefore price/revenue multiple. These dependencies are also [usually] disclosed in the S-1 under “Risk Factors.”

9. Organic Demand vs. Heavy Marketing Spend

All things being equal, a heavy reliance on marketing spend will hurt your valuation multiple. Think about this simplistic example. There are two stores in the middle of town. One has a product/service that customers love, and as a result, customers flock to the store day in and day out all on their own. These customers then tell other potential customers, and through this “word of mouth” process, the customer base grows even larger. The second storeowner advertises frequently, and all new customers are a result of this advertisement and promotion (which obviously costs $$). Which business would you prefer to own? Which one would likely have higher cash flows? If you have to “buy” or “rent” your customers, you have a non-optimal business model – plain and simple.

10. Growth

We saved the best for last. Nothing contributes to a higher valuation multiple like good ole’ growth. Obviously, the faster you are growing, the larger, and larger future revenues and cash flows will be, which has direct implications for a DCF. High growth also implies that a company has tapped into a powerful new market opportunity, where customer demand is seemingly insatiable. As a result, there is typically a very strong correlation between growth and valuation multiples, including the price/revenue multiple.

A really good piece, I think its realy worth reading the whole piece and pasting it on the front of any startup's business plan design file.

I was on holiday at the time so I'm a bit late onto it, but this piece in The Economist chimes a lot with my experience:

Firstly, "market research" for new technology startups is nothing like what usually works for more tradtional start up businesses:

Anyone who has tried a hand at starting a high-tech business—seeking to turn a clever research idea into something customers will pay good money for—quickly learns that everything taught in business school is next to useless. The mistake is to think of start-ups as just smaller versions of established businesses. They are nothing of the sort.

Existing enterprises, even so-called SMEs (small-to-medium establishments), usually have no shortage of marketing and financial data. Their success depends on how well they execute their data-driven plans. Start-ups, by contrast, are faith-based organisations that survive on passion and belief—with nothing to go on but a bunch of hunches.

Our experience is its far more about modelling scenarios, what-ifs, probabilities etc and laying down "marker stones" to know where you are, so you can tell which scenarios are probably playing out. For this reason I was very interested that Silicon Valley Entrepreneur Steve Blank has come to similar conclusions, but with a lot more data and experience, and has set up his own accelerator - i-Corps - to do this (I know, I know re Accelerators* - but read on, there is some interesting stuff here):

What distinguishes an I-Corps start-up from a typical university spin-out is the way it forces researchers to stop fixating on the technology they have developed. New ventures, they are taught, are all about finding customers, what distribution channels to adopt, how to price the product, who to partner with, and more. From day one, the mantra is “get out of the lab”. Participating academics have to make countless cold calls to potential customers—something few research scientists and engineers have ever done in their professional lives and most initially find awkward.

The I-Corps programme is based on the premise that all new ventures are little more than a series of untested hypotheses—in other words, optimistic guesses about market size, customer needs, product pricing and sales channels. With so many unknowns, the programme teaches participants to treat their start-up as if it were a typical research project, amenable to the same iterative process of hypothesis testing and experimentation.

Stopping Technology Fixation is IMO one of the absolutely critical issues for Technology startups, the problem is its virtually impossible for techies who are in love with their technology to do - so the second bit, on treating the startup dispassionately as a live project, seems like a very clever way of forcing that dissociation. Anyone who has studied innovation and startups will know that which technology/company/method succeeds is highly unpredictable in the initial stages, and all sorts of factors come into play - exactly because all sorts of factors are untested.

But I was also impressed with the following, because in my experience turning around tech companies, these are usually the most critical issues - making sales and making profits:

Mr Blank’s blueprint draws on two complementary techniques—“business-model design” and “customer-development process”. The first uses a technique pioneered by the authors Alexander Osterwalder and Yves Pigneur in their book “Business Model Generation”. This provides a handy graphical template (called a "canvas") that helps fledgling start-up teams envisage their most likely customers. With the canvas' nine separate blocks covering such things as resources, value propositions, customer relations, cost structure and revenue streams, it captures the complete essence of a business plan. By filling in the individual blocks, the hopeful entrepreneurs are forced into the sort of business brainstorming many are unfamiliar with.

Customer-development process, meanwhile, provides a real-world way of testing the business plan's various hypotheses, as written in the canvas' nine blocks. The testing is done by getting potential customers, suppliers, partners and channel operators to challenge the assumptions. If invalidated, the I-Corps team has to pivot, and revise the entry in that particular block of the canvas. The process is repeated until all reiterations, in all nine blocks, are finally exhausted and the business plan emerges robust enough to be realistic.

There are other methodologies than those suggested here of course, but in my experience the "80/20" impact is the act of focussing on the business model (how you will make money) and the customer model (who will buy). Its damned hard to do, especially for the techies who are struggling with making the new wotsits work, but absolutely critical. You don't have to have the "right" business model initially (just look at Google) but you have to know what a "wrong" one looks like, and what the envelope of success looks like.

Also, they emphasise that there will be significant twists and turns in the business (or "pivots", as the fashion is to call it these days), its a given not a failure

The I-Corps curriculum emphasises that failures which force participants to pivot and change their assumptions are an integral part of the learning process. That can mean rethinking the market, changing the price, even altering the product itself. During the eight-week programme, I-Corps teams repaint their business-model canvases literally dozens of times. The average team confronts 100 or more potential customers while honing its business plan and tweaking its product.

Re: pivoting, I increasingly think of a startup as a bit like a new genetic algorithm, so it has to go through a number of self winnowing cycles before it can navigate the ecosystem its launched into. Another analogy may be a new species that has emerged blinking onto the landscape and has to adapt to its niche.

Its too early to say whether this particular program will work, after all execution is 9/10 ths of the lore, but I think the proposed areas of focus are in the right direction. The one thing this piece does not say, of course, is that for any startup taking money from an accellerator, incubator, seed investors etc - Cave Contract! Get a lawyer to look it over.

*Yes, in the Bubbletime we are also sceptical of any New New Accelerator story, but this piece has some interesting points.

In Dotcom 1.0 there were Incubators. These businesses typically rented space, facilities, admin and backoffice support to startups for some cash and a share in the success (or failure) of the business, typically back to backing it against investment from others who hoped to get into startup portfolio investment. Cometh the Dot Bomb, goeth the Incubators, and they got a bit of a bad name, a recent study by Jared Konczal of the Kaufmann Foundation, showing what everyone suspected empirically - Forbes:

The findings reveal that the effects of incubation are potentially deleterious to the long-term survival and performance of new ventures. Incubated firms outperform their peers in terms of employment and sales growth but fail sooner. These are important findings for policymakers who support incubation as a strategy to increase employment locally and for entrepreneurs who risk their livelihoods in order to earn a decent living.

Claims that incubators are highly successful and serve a significant number of businesses are overstated. The comprehensive process used in this study to identify the largest possible sample of incubated firms uncovered a fraction of the number of incubated ventures that supporters of incubation claim exist. While improvements are likely possible to the methods used in this study, this study roundly refutes the poorly documented and unpublished studies that cite much larger numbers of incubated firms and much higher levels of performance.

Cometh Bubble 2.0, cometh Incubator 2.0 - only they have been rebranded, "Combinator" was tried but never took off, the New New Word is an Accelerator. The business models has also changed a bit- Forbes again:

Accelerators are organizations that provide cohorts of selected nascent ventures seed-investment, usually in exchange for equity, and limited-duration educational programming, including extensive mentorship and structured educational components. These programs typically culminate in “demo days” where the ventures make pitches to an audience of qualified investors.

In other words they are Incubators with a more direct funding link (and often without the benefit of any facilities to help startup companies with). But are they any more effective?

Claims are made by their proponents that they are more effective (eg Grasshopper, here). As Konczal notes, the major criticism of such assertions is there is no "blind test" vs other startups that did not use Accelerators. In essence though, from the data, the main issue that emerges is that you have a huge differences in impact between the Very Early In to any trend (like Y Combinator) that work out very well, and the following horde of me-toos that don't (as was true for Incubators, and the VC game in general). One piece of research is noted by Konczal. Based on the c 120 Acceleraror programs in the seed-db.com database, it shows that by 2012 Accelerators are a massive wealth reduction agents to the end-of-the-line funders. As the chart at the top shows, splitting Y combinator out from The Rest, Y Combinator is profitable whereas The Rest, on aggregate, are massively loss making - $300,000 lost for every startup job created is all you need to know. (The author points out his data is not accurate, but has some sound reasons to suppose it is indicative - ie the non reported costs are probably larger owing to many types of investments being below the radar).

Interestingly, Konczal notes a NESTA (UK) study from last year that I read just after we were developng the Bubble-O-Meter, the NESTA research noted the rapid growth (see graph below), said that early evidence was that they were a positive influence, but noted 4 main risks:

(i) Good companies still fail after accelerator programmes (as Konczal notes we also don't know what the success rate of not going to an accelerator is)

(ii) They exploit startup founders (The amount of equity taken by accelerator programmes has also been controversial - ie they take a lot)

(iii) They attract companies that are already struggling (and this is what usually leads to the effects described above - Good companies still fail after accelerator programmes, as the number of accelerator programmes rises, they will struggle to avoid making investments in B-grade companies.

(iv) They’re helping to create a bubble (If accelerators continue to grow and start producing thousands of small companies, we can expect to see a bottleneck developing and in the event of a crash in confidence in the sector (as happened in the Autumn of 2008)

We've been following the Accelerator trend since 2007, here was what the state of our research c 2008 was:

I would make a few predictions here on the Next Generation of Incubators 2.0 (I'll call them hothouses as its more part of the zeitgeist):

(i) There will be little difference in average outcome between hothoused startups and organic ones, but later hothouses will underperform on average, as they will be lower quality.

(ii) There will be a higher propensity for the hothouses to follow fashion, as following the crowd is an easier sell to funders. This will make them more costly than organic plays which will by and large be earlier in.

(iii) There will be little advantage gained from using youth and inexperience early up, apart from low cost of the initial "throw at wall" phase - if anything sticks, age and guile will be required, and as it has less stake, it will be at premium pricing - or the founders have to give up a large slug of equity.

(iv) The "Next Web" will not be built in the hothouses, as innovation is not really their business model - fast following is.

By 2011, when NESTA was writing their report, we had seen the latest bubble in Accelerators and listed it as No 4 in our Bubble-O-Meter trends.

Looking at the huge growth in Accelerators since c 2006 again now, and juxtaposing the Kauffman data, we'd propose that bubble-like behaviour has indeed emerged here, and the me-too startup count is rising (empirical observation sure, but a lot of them do look similar). If the dotcom era is anything to go by, this implies that anything founded since the "bubbly bit" began in the graph - about 2007/8 looking at the graph, soon after Y Combinator according to the chart - is probably not going to make any money for its funders.

Yesterday I was one of the "response" speakers to Jimmy Wales' talk at the London Mayor's "Technology: Disruption and Convergence" debate. Facilitator Nico Macdonald had asked me to focus on what London had to do to foster Innovation in new technology (and, by extension, startups in London). According to the hype, we have the skills, we have the people, we have the creativity, we have the Accelerators, we even have Tech City.

Hype notwithstanding, we are probably all also familiar with the major barriers the UK has for startups getting big, ie:

- Unadventurous Venture Capitalists, leading to the "Equity Gap" after Friends and Fools money runs out
- A (relatively) small home market, so we can't grow gargantuan companies before going abroad
- Reluctant "small c" conservative public who don't like to try things early
- Higher amounts of "Red Tape" for British SMEs vs the US, making it harder to hire/fire and reward.
- A culture that punishes a failure rather than sees it as painful experience
- An unresponsive environmnet in dealing with other countries' subsidies and indirect benefits (See Games Industry, loss of...)

However, when you look at Wikipedia. it wasn't relying on VCs, its product inspired people worldwide to contribute en masse, wasn't up against subsidised industries, wasn't shooting for "success" and it was hardly a company structure being Not For Profit - so, none of these UK disadvantages mattered.

So, why did JImmy Wales, an ex Chicago currency trader, set this up in the US rather than some UK person set it up here (Heck, we have enough ex-currency traders of our own)?

I suggested 3 hypotheses, assuming our Entrepreneurs were no less creative than anyone else's:

- Numbers - there were just more entrepreneurs in the US, so it was more likely there.
- The Silicon Valley ecosystem - something in the air makes things happen
- A combination of all the disadvantages that I listed above, that becomes a whole raft of "small frictions" and add up to a far lower likelihood of success as they play through.

Wales's view was interesting (bear in mind he is now living in London so has some familiiarity with the scene). He said he wasn't in Silicon Valley, and set up Wikipedia far from the "SV bubble", and that he would have set it up wherever he was. He agreed that the "large number of small frictions" is a factor in the UK, but said one of the biggest risks was.....

.....UK Libel Laws

Wales said Wikipedia still does not put any of its servers in the UK owing to the risks posed by UK libel laws. Its not just that they overprotect and can deliver large damages, but they are also unclear and unpredictable which adds cost, time and hassle and would make it very dfficult to operate Wikipedia effectively.

So, there you have it.

Wales feels the UK/EU laws around content, and its freedom. are major barriers to content based startup success. Which points to an issue for the UK, and London in particular. As another spot speaker, Dean Bubbley, pointed out, there is not much "Silicon" in Silicon Roundabout (or in the UK overall really), and creative content (media, software etc) is where the UK punches way above its weight in (the traditional British succesful startup is a world class rock band, not a world beating Tech company).

And yet, and yet..I am still sitting here wondering why someone - anyone - in the UK didn't do something like this, even if it became an heroic failure...... so, do we need to look at our much vaunted innovative creativity again, or maybe Jimmy's 3 previous failures were what winnowed Wikipedia?

Update - interesting response from El Reg -on British Wikipedias.....

In fact, Britain has had several online encyclopaedia projects that anyone can contribute to. One is the Knowhere Guide, which has been online since 1994. It is archived at the British Library, but doesn't have a Wikipedia entry. Another general-purpose effort is the H2G2 encyclopaedia. Both have trundled happily along for years.

....and on their scaling:

We can see that Britain does have wiki-style distributed user-contributed projects. However, what it doesn't have is a "Wikipedia Cult": our collaborative projects don't have utopian aspirations, and don't claim to save the world. Ours aren't given utopian status by slack-jawed journalists, pundits, management consultants and gabfest organisers. Ours don't have a Messianic leader; Wales styles himself as Wikipedia's "spiritual leader". You could make the case that the British projects are Wikipedia done properly – without The Bullshit.

I think he may have something there, we tend not to boost technology in the UK. I was reflecting on this last night, when on BBC's premier Newsnight analysis priogram neither the Mars landing nor Bernard Lovell's death were covered, whereas the death of an Arts TV prersenter was

(Twitterstream of the event is over here)