Jay Haynes

"Heavy" Startups

I was with a good friend and great entrepreneur this weekend who has recently become a venture investor. He is exceptionally talented and I have a great deal of respect for him. He said something that made me think about startups and the innovation process. I was walking him through the details of our innovation methodology and he said, "that's heavy."

What he meant was that our process might be too detailed for a nimble startup financed with seed capital. But let's look at what any startup will confront, regardless of the model used to innovate. 

Of course, every startup has to ship a product or service that meets customer needs. That's a given no matter what the market. But a startup also exists within a value chain of suppliers, distributors, competitors, OEMs, etc. What this means is that the product or service not only has to meet the needs of the customer (the job executor) but also of the other players in the market who either help create the product or help distribute it. And each one of these players has needs that need to be met as well (i.e. they have jobs to get done). 

If every job has 50-150 outcomes, and every job executor has multiple jobs to get done, and every value chain has multiple players, the number of outcomes that need to be known and quantified upfront is certainly "heavy".  

A startup doesn't get to avoid these metrics simply because the cost of development has decreased. It can choose a "fail fast" strategy with lower levels of funding to try to satisfy needs. But this doesn't mean the needs are less "heavy", it just means that the startup is lighter. 

And there is more evidence today that the light and fast version does not work any better than traditional methods.

Thoughts on Reid's Rules

Reid Hoffman, the Founder and CEO of LinkedIn is a very successful entrepreneur and investor. I am a big fan of LinkedIn and support Reid's efforts to encourage entrepreneurship.  But let's look at his three rules for investing closely in order to make them useful for entrepreneurs.

His rules, in order, are: 1. reach a mass audience, 2. have a unique value proposition, and 3. be capital efficient. All good rules, but the question is how do you actually accomplish these goals? Reid's view (and the view of most venture investors I know) is that an entrepreneur has to figure out how to reach these goals.

I have always found it curious that venture investors will openly tell anyone that what they do is "pattern recognition". They look for similar patterns in opportunities and solutions that have worked in the past in order to predict success in the future. And this is true with Reid's rules: he is looking for distribution patterns, value proposition patterns, and capital efficiency patterns.

But if venture investors are good at pattern recognition (even if 63% of all their investments return less than 1x), wouldn't it be better to explicitly state what those successful patterns are and then (i) devise ways to acquire the data about the patterns and (ii) a objective, quantitative system to validate the patterns? Then entrepreneurs wouldn't waste time guessing about the patterns (e.g. "do we have a good value proposition") and investors would reduce their failure rate.

Let's look at the most important pattern: the value proposition. Without a value proposition distribution and capital efficiency don't matter (so I think Reid should have put value proposition first in his rules).  Of course, every company needs to have a unique value proposition. But what is "value"?  Reid states that "a product needs to be sufficiently innovative to distinguish itself from the pack, but not so forward thinking as to alienate the user." What does that mean? What quantitative criteria can be used to determine if a product is "sufficiently innovative" and "not so forward thinking"? And what is "innovation that is categorically distinct"?  Without a rigorous definiton of what these terms mean, they are almost useless to the entrepreneur.

Here's an example of the confusion: Reid states that Facebook used a "University-centric approach" to be successful. You might call this strategy "Friendster, but for college students". And yet, Reid criticizes "pitches that sound like 'It's a dating site, but for senior citizens.'" Without rigorous definitions for "sufficiently innovative" and "categorically distinct" it is almost impossible to see a priori what is different about "Freindster for college students" and "dating for seniors". How is an entrepreneur supposed to tell the difference?

What is needed is a definition of value from the perspective of the customer. What is a customer need and how do you know if the need is satisfied or not - this is the pattern that matters.  All products must meet customer needs to be successful, and "sufficiently innovative" means that a product meets customer needs better than the existing solutions. So customer needs must by rigorously defined and quantifiable in order to be useful for the enterpreneur. The "pattern" (the customer needs) must be explicit and knowable in advance.

If the customer needs are defined, solutions can be generated to meet customer needs and the value of the solution (from the customer's perspective) can be quantified. If the solution does create enough value for the customer (and the value chain), it is much easier to figure out if you can reach a mass audience and if the business model will be capital efficient.

Cheap is too expensive

Josh Quittner has an article in Time on a new type of startup he calls LILOs for "a little in, a lot out". The essence of the article is that starting a new business now is easy and cheap. The cheap part might be true, but the easy part, not so much.

The article serves as a lesson in what is wrong with venture and startups today. Let's start with Josh's assumption that "It almost goes without saying that many more start-ups fail than succeed." This is very problematic thinking: authors, entrepreneurs, and investors just assume that this is the way startups work: the vast majority will fail so investors should spread capital across lots of companies in order to find one that might succeed.

This type of thinking ends up encouraging failure and risk. And it is why venture returns are highly variable and often underperform. 

For example, Josh writes (quoting Joi Ito): "'The cost of failure is cheap. It's so low, you can swing the bat way more times.' In a bad economy, no one really notices or cares about more failure. That creates a better environment for risk-taking, which is the only way innovation occurs." [emphasis added] 

So according to Josh and Joi: entrepreneurs should take lots of risk in an environment where they can fail again and again and again, until maybe they succeed. This is the standard way to think about innovation: start with tons of big ideas, build stuff fast and cheap to filter out the bad ideas and see which ones work. 

But let's say we thought about the innovation problem differently. Wouldn't it be better to focus on the cause of all these failures? Suppose instead that entrepreneurs were encouraged to mitigate as much risk as possible before any product development in order to succeed consistently. 

What's crazy is that this very logical idea (mitigate risk to succeed consistently) seems crazy at all.

Josh does causally identify the problem to be solved: "All that's required is a great idea for a product that will fill a need in the 21st century." But this begs the question: what is a "need"? Companies don't even agree on what a customer need is. Without a rigorous and quantitative definition of a customer need it is almost impossible to launch a product that meets customer needs.

As a result, it is not surprising, as Josh notes, that "there's often no correlation between the assumptions in a theoretical business plan and reality." But the problem is not with planning, the problem is the type of planning. If there is no agreement on what a need is, planning to fill it will not work. And launching a product to fill the need won't work the vast majority of the time either. 

The goal should be to develop a system that rigorously defines and quantifies customer needs and consistently leads to successful innovation. But with a mindset that encourages risk-taking and failure from the outset, it will be an uphill battle.

Startups Should Take More Risk?

Sarah thinks startups should take more risk: "they are supposed to be doing something that is risky, seems insane and can easily fail. If they aren’t, they’re probably not taking enough risk." 

This is a common myth and just about everyone, even the best in the business just accept it. But it is untrue. Startups should be figuring out ways to lower risk - and lower it dramatically. The problem is the equation that Sara (and just about everyone else) accepts without question: that risk = reward. She is encouraging startups to take more risk because this is the supposed way to create the next big thing. 

This myth is generally based on confusing risk with insight. What Sara should say is that startups should be doing something that is non-obvious because they have better insight into customer needs. Of course, doing this lowers the risk to the startup. Which is the real goal.

If you think you should be taking more risk, get out of your startup now. It will fail.

Four Flaws of Tech Commercialization

Guy thinks there are four flaws. He is right that "it's not easy to productize technology and start a company". The hard part is understanding the customer need. And he is right that patents (and technology) don't make people buy products. They buy products to get jobs done, and it is the job that is the most important part of commercialization. Failure to understand the job is the reason technology commercialization fails. 

Innovation Lessons From The 1930s

Should companies invest in innovation in today's down market? It depends on what type of innovation. In this Forbes article, the authors note that DuPont continued to invest in R&D in the 1930s and discovered neoprene (synthetic rubber), an enormously successful product. But this analysis lacks real data on investing in technology as opposed to innovation. How many companies lost how much in R&D and was it worth it? 

Innovation is creating and validating a solution concept that meets customer needs. It is not investing in R&D. In any market, investing lots of capital in R&D can be (an usually is) extremely risky. 

A better way to invest in innovation is to figure out what the unmet customer needs are and then develop solutions based on known and proven technology first. If this isn't possible, then investing in R&D when the needs are known has much lower risk. So the right question isn't, "should companies invest in innovation?" The right question is "what is innovation?"

Silicon Valley a Systemic Risk?

The WSJ has a good editorial about why venture capital could never pose systemic risk. And I agree, but what is really revealing about this conversation about regulation and risk, is that the prevailing logic on venture and risk is absolutely wrong: everybody thinks risk taking is good. And the more risk, the better.
 
There is a sense that "good old American risk taking" is somehow the goal in itself: "venture capital is exactly the place where we have to encourage risk."
 
I would argue that the goal of venture capital is exactly the opposite: to mitigate as much risk as possible. The best entrepreneurs know this. They use their insight and experience with customers to mitigate as much risk as possible before they start a new venture.
 
The problem is that venture investors and entrepreneurs are not very good at mitigating risk. The dismal venture track record is a result of investments made based on "passion and vision" and gut feel about the market.
 
Don't take risk - mitigate it.

Study Finds Business Plans a Waste of Time

This is a fascinating study. It basically says your business plan doesn't matter for fundraising. Why is this? Not surprisingly, venture investors invest in people not plans. So your connections matter more than your plan or your idea.
 
But this is a problem. The venture success rate is so low because traditional methods lack quantitative tools and techniques to evaluate addressable markets and validate solution ideas. Thus the pervasive "fail fast" technique.
 
It's not surprising that VCs like to say that "passion and vision" are the keys to success - they don't have quantitative tools, so they make qualitative assessments.
 
Here's the basic VC formula: I like you, so go out and develop your product. If it takes off, we will invest, if not, keep failing faster until you succeed. No wonder only 11% of all venture investments get to liquidity.

Ask The VC: Does Addressable Market Matter?

Brad responds to a question about addressable market. Does it matter? His conclusion: "Almost every market sizing presentation is incorrect - by a lot. Enough to make it irrelevant."
 
He is right, of course, about the incorrect analysis. But not about the irrelevant part. Given that 90% of all new products fail and only 11% of all venture investments get to any liquidity, by definition the market sizing by entrepreneurs (and venture investors) is incorrect 90% of the time.
 
But the question should be: what is an addressable market? The big mistake is trying to calculate the addressable market without a rigorous definition. The mistake is defining the terms of an addressable market incorrectly. Most markets get defined by their solution: the auto market, the cell phone market, the software-as-a-service market.
 
But these are not markets; they are solutions. A market should be defined by the customer need and the customer population. And the need is the job that customers are trying to get done (and all the outcomes of performing that job). It is not the solution that helps them get the job done.
 
So yes, the concept of an addressable market matters - it is essential. Fixing the problem with addressable market analysis is the first critical step in improving the dismal success rate for new ventures.

The U.S. Balance Sheet

Pete Peterson's $1 Billion Bully Pulpit.

Imagine a humongous business with assets of $1.6 trillion, balance sheet liabilities north of $10 trillion and off-balance-sheet obligations of $41 trillion. That's debt--whether explicit liabilities, commitments and contingencies, or implicit exposure--that produces a debt to assets ratio of 32-to-1, roughly similar to the late and not-so-great Bear Stearns and the quickly departed Carlyle Credit Corp., which lost a bundle for its well-heeled investors.