Product, Strategy, Business Model and Two ‘>’ Symbols

Quick! Write an inequality equation using two ‘>’ (greater than) signs and

1. Product
2. Strategy
3. Business Model

Depending on where you stand and which articles you read recently there are six possible permutations.  If you had recently read what Fred Wilson, a Venture Capitalist, wrote you are  mostly likely to write down

Product > Strategy > Business Model

Is that all to it?  According to research done by four business schools, this permutation defines only one of two classes of VCs. More precisely, there are two schools of thoughts of how VCs make investing decisions. The second class of VCs believe the right permutation is,

Strategy > Business Model > Product

While Fred Wilson makes a compelling case to get product-market fit correct, then define your strategy and then worry about making money, a VC who falls in the second category will argue, equally eloquently, strategy (making choices about segmentation and needs to serve) first, finding how you add and capture value (business model) is next and what the offering (product) is last.

The two ways of reasoning are called  Effectual and Causal reasoning respectively.

Effectual – Instead of doing market research, competitive analysis, value analysis etc, go build something and keep iterating on it and building a growing customer base. Then worry about strategy and business model.

Causal: Start with customer segmentations and their unmet needs (or jobs to be done).  Make choices on the right segment you should target first and understand its value perception, alternatives and willingness to pay. Define a product version that serves that segment and offer at a price they are willing to pay.

There exists a class of VCs who apply effectual reasoning and there exists another that applies causal reasoning. You can see Fred Wilson falls in the effectual bucket.

So when you have two classes of entrepreneurs and two classes of VCs, the next obvious question is which pair would work together well. The aforementioned research suggests, cognitive similarity (“I like how you think”) was a decisive factor in how VCs decide choose to invest in startups.

Their study was conducted on 49 partners from different VC firms, by presenting them 16 different hypothetical investment opportunities and asking them to rate how likely are they to fund these ventures. From these 784 data points, the researchers employed conjoint analysis to tease out the influence of individual factors on VC’s decision. This is approach is far better than stated preference studies that ask VCs for their rating and data mining studies that succumb to data errors.

 

The number one deciding factor?  How similar the thought process is between the VC and the founder. The researchers call this cognitive similarity, which has nothing to do race, national, education, gender or other physical characteristics. It is how a founder thinks and how similar it is to VC’s thought process. Higher the similarity, greater the chances of getting funding.

Everything else, including the perception of the team, its experience and commitment (human capital) are influenced by VC’s reading of founder’s thought process.

“A founder who demonstrates cognitive similarity with a VC is more likely to be perceived in a positive light, and viewed as better positioned to make effective use of his or her human capital”

All other positive attributes we hear about, the product’s competitive advantage, scalability, founding team’s ability to hustle, their focus etc seem to be bestowed after the fact.

What does this mean to you as a startup founder seeking venture funding?
You are better off seeking those VCs who think like you do in terms of product, strategy and business model. If you think market demand and opportunity size first and pitch to Fred Wilson you are most likely going to come back empty. On the other hand you at least get to play if you think product-market fit first. So knowing how you reason and seeking as venture partners only those who think like yourself saves lots of wasted time and agony.

Will Fred Wilson and other VCs admit to this influence of cognitive similarity in their investment decisions?  More broadly, do VCs know and admit to the influence of cognitive similarity on their funding decisions?

No, they do not recognize this hidden factor. And I expect comments from a few stating so. In the same study that teased out this hidden factor, the researchers asked an explicit question on how much weight VCs place on cognitive similarity with founders.  VCs rated this as the the least important factor, but when they had to place a bet given a profile of venture and its founders, the hidden influence of cognitive similarity came out loud and clear.

Finally, is Fred Wilson right? Is effectual better than causal?  The proponent of this classification, Professor Saras Sarasvathy, goes one step beyond this mere classification.  She argues great entrepreneurs are ‘effectual’. They opt for doing things vs. analyzing things.  I do not subscribe to this latter part of her theory regarding what defines entrepreneurial greatness.

How do you reason?

Startups and Cognitive Biases

When things seem impossible, remember: Apple, Oracle, Sun & Cisco were once just a few people arguing strategy in a cramped room too.

— Aaron Levie (@levie) November 10, 2012

@mtg_law_etc @mattwensing @levie spot on 🙂 except if one understands cognitive biases one wouldn't have started a venture

— Rags Srinivasan (@rags) November 10, 2012

If you are not irrational enough it is highly likely you won’t start a venture.

See also Mind of Analyst.

If you are asking entrepreneurs to be rational

What is the biggest resource an entrepreneur can waste? According to Kevin Ready, author of  “Startup: An Insider’s Guide to Launching and Running a Business, it is not money. Ready says it is time spent trying to keep a start-up live long after its viability has been discredited.

Kevin Ready says,

I call this creature a “zombie start-up.”
… many intrepid entrepreneurs hold on and continue the vision — sometimes for years. Herein lies the true cost and risk of start-ups: Time.

When you hold on to a dead idea at the expense of other possibilities, even though you are not burning cash to keep it alive you are keeping yourself away from what you could be doing elsewhere.

Time is the one resource that we can never recover. The opportunity cost for chasing the wrong idea is immeasurable. What is the cost of a lost year? How about two years? A decade?

Kevin Ready makes a very good point. (Although he says we can’t put a price tag on time lost. We can.)

I would also add a close relative of opportunity cost,  sunk cost. Many are not able to walk away because they have already sunk so much of their time and money into the venture. Doing so may seem like they are wasting their “investment”.

But recognizing sunk cost bias, walking away from what is sunk and taking into account opportunity cost before making choices are rational behaviors.  If entrepreneurs are wired to do scenario analysis, calculate expected value over all possible options, consider opportunity cost of leaving their current job, etc.,  they would not be entrepreneurs at all. (See The Mind of an Entrepreneur and that of an Analyst.)

It  takes an irrational sense of optimism to believe their venture will be a big success when the base rate says less than 3% of the ventures live past their third year.

It is the irrational sense of optimism that makes an entrepreneur.

Don’t ask those irrational optimists to look at opportunity cost.

Fail fast because successful companies failed before they succeeded

There are several versions of this statement, one way or another they glorify failures and in the name of exhorting startup founders these inspirational statements lead one to believe

1. After a few failures success is inevitable
2. You must fail first to succeed
3. Fail fast so you can succeed
4. Failures signal impending success
5. “Failure can be a true blessing in that it educates you and prepares you for success” (from here)
6. “Remember that most successful entrepreneurs fail good and hard before they finally make it” (same source)

All these assertions are happy to point out popular examples. The problem is the assertions are derived from the very examples they are using as evidence.

First let us make something very clear. Success and Failure are the only two possible outcomes for any venture you undertake. But the fact that there are just two outcomes does not mean they are equally probable. It is not the case of tossing a fair coin and calculating the odds of heads or tails.The chances of success and failure can be and are very different. If you take the base rate (looking at the success rate of thousands of ventures and small businesses) the success rate is 3 to 5%.

Second  even if we assume that Success and Failure are equally likely, a series of failures does not mean inevitable success. Take the coin example. The probability of getting 10 Tails in a row is same as the probability of getting 9 Tails in a row followed by a Head.

Lastly the fact that those who succeeded had failed in the past is irrelevant. Those who make such an argument pick only the success stories that are popular, recent and available to them. When you only look at those who succeeded and are still in business you are leaving all those who did finally succeed and gave up or still trying without success. Even in these cited success stories success is mostly random rather than a result of their failures. The fact that those who succeeded had “failed hard” does not mean when you fail you will succeed.

Granted they learned from their mistakes but you do not have to learn from your own mistakes.  You do not have to fail to learn. Failure is not the true blessing. Insane success with hundreds of billions of valuation even when your venture has no real product or clear value add is true blessing.

Those who advise you to fail are not being intellectually honest. Their advices are no different from those advising a gambler to bet on a slot machine that had been coming up empty for the past few hours.

 

One question to determine a startup’s success?

Let us stop looking for a single predictor of success, be it a startup or an established enterprise. I saw a TechCrunch interview of Mr. Peter Thiel, of Clarium Capital.  The TechCrunch post is titled, “Best Predictor of Startup Success Is Low CEO Pay”, and Mr.Thiel was quoted as saying

In practice we have found that if you only ask one question, ask that.  (CEO Pay)

This is the classic single question trap. There cannot be single metric that can be “the best predictor”.  You should ask

1. Does correlation mean causation?
2. Is there cause-fusion – i.e., do successful startups pay low CEO salary?
3. What about all other lurking variables? What if there is another variable that drives CEO’s low pay and success? (Omitted Variable Bias)
4. If low salary is good, is lower salary better? (reductio ad absurdum)
5. What about other startups that have CEOs with low pay and still fail?
6. A startup, hamstrung by lack of resources and low cash flow may pay low or no salary, is that still a predictor of success?
7. What about the congruence between the startup’s strategy and the needs of the market it serves?

Let us not forget  Predictive Analytics slippery slope. If you want to ask a startup questions, here is my list (not claiming predictability):

1. What jobs will your customers hire your products for?
2. Who do they hire now, i.e., who do they have to fire first?
3. What are their alternatives?
4. How much will they pay for it?
5. What budget will that come from and how big is that budget?
6. Where do they post the job opening?
7. Where do they look for candidates and can you go there without considerable costs?
8. What is their hiring process?
9. What will they find compelling about your product’s candidacy?
10. Will the job exist two years from now?

Ten Questions To Ask About Any New Venture

Here are ten questions I ask when I talk to my entrepreneur friends, the questions follow from the framework of business strategy, customer needs and Go-to-market strategy:

1. What jobs will your customers hire your products for?
2. Who do they hire now, i.e., who do they have to fire first?
3. What are their alternatives?
4. How much will they pay for it?
5. What budget will that come from and how big is that budget?
6. Where do they post the job opening?
7. Where do they look for candidates and can you go there without considerable costs?
8. What is their hiring process?
9. What will they find compelling about your product’s candidacy?
10. Will the job exist two years from now?