Warning Label

by Joshua Chuang

Hypothesis-driven, lean entrepreneurship can be the difference between a successful venture and a failed one. This strategy requires one to propose a hypothesis, develop a test around the hypothesis, test it, and learn from it. At its core, hypothesis-driven, entrepreneurship strives to reduce the biggest risk startups face: building a product that no one wants. A powerful tool for entrepreneurs, but potentially dangerous for those who don’t fully understand it or who overlook certain dangers.

The following serves as my warning label to the entrepreneurs out there following the lean startup methodology:

1. BEWARE of AssumptionsPeople tend to presume they understand how things work, when in fact they often don’t. For example, with Cake Financial, the founder and CEO, Steve Carpenter, assumed that the user-interface wasn’t what people cared about and focused his attention on the back-end. He also assumed that Yodlee would be a bad business partner, based on his prior experience. Both are completely valid and, seemingly, reasonable points. However, other plays (like Mint) were able to capitalize on Yodlee’s abilities to create a strong product. Don’t make assumptions/presumptions! Whenever possible, test your assumptions.

2. BEWARE of false positives and negativesConsider the following scenario. You’re friends with many people in the VC and tech industries. You make an assumption that people in this world want a product that automatically folds your laundry (I hate folding clothes, one of you should really make this product). Your friends all love it, and you’re receiving some good press from some famous blogs. All signs point towards making the product, right? WRONG! This is a false positive! While it could be true, it’s not a definitive positive (and you should never read it as one). One might begin building an expensive prototype when, in fact, there was no real demand. So what should you do? When designing your test, create a checklist of potential outcomes and their associated implications. Could I be receiving good press simply because I’m connected to the right VC firm or right advisory board? Are my friends supportive because they believe in me or because they believe in the product? Next time you hypothesis test something, make a checklist first.

3. BEWARE of the “Customer knows best” mentalityPart of the lean startup methodology requires creating minimal viable products, testing them, and improving them based on feedback. Learn as much as you can as quickly as you can. However, what happens when people start asking for numerous improvements/features? What happens when users fundamentally dislike one of your key features? I wish there were a simple rule as to when you listen to the customers and when you stick to your beliefs. Like many things in life, the answer is “it depends”.

In short, my advice is to take your “belief” and test the crap out of it. If the feedback says make changes, but you still wholeheartedly believe you’re right, then try and figure out why they’re wrong. Ask those you trust whether your reasoning makes sense. As I’ve already established, every entrepreneur likes to believe they know best. What I’m telling you is to never trust your gut alone. Prove it if you can. And if all else fails, then make a choice and pray it works out.

Good luck entrepreneurs. You’ve been warned!

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The Grass is Often Greener on Your Side of the Chasm

by Natasha Prasad

A few weeks ago, Fred Wilson and Jeff Bussgang supplanted our usual LTV class with a fireside chat on lean startup methodologies, monetization and VC value-add.  A Fred idea I found particularly compelling suggests that entrepreneurs should be “hunch-driven”, rather than “data-driven” in the early days of a startup.  Indeed, if Jack Dorsey and Mark Zuckerberg hadn’t stuck to their hunches, Twitter would never have gotten past 1000 users and Facebook’s newsfeed wouldn’t exist.

Hunches, however, can only get you so far: most successful startups will at some point face the excruciating transition from early adopter glory to mainstream success.  Founders like Dennis Crowley, who admit to having built products for their own friends, are now struggling to gain momentum with the mass market.  If users outside of NYC, LA and San Francisco lack the vanity-driven penchant for public bar and restaurant hopping, how can Foursquare possibly grow beyond its 6 million strong userbase?  It probably merits some sort of pivot (sorry, at least I held it in till the second paragraph).

Market pivots are painful.  Not simply because you need to get your engineering team, company culture and external investors behind a new vision but because any significant product change can alienate the fanatical userbase that got you off the ground in the first place.  When social news site Digg launched a slightly less geeky version of its product last summer, its nerd powerbase turned hostile, flooding the newsfeed with rival Reddit submissions and quitting en masse.  In fact, any site that crowdsources its content is especially vulnerable to this kind of scale/product quality tradeoff.

So, is it possible to live in the chasm?

Power users tend to be highly engaged, passionately vocal and valuably prescient in vetting hunches; you really don’t want to push them out.  But, barring the success of Second Life, living off a tiny group of loyalists and generating positive cash flow really isn’t easy.  How can you balance these competing tensions?

1. Seed your site with high quality users: Quora has done an impressive job in nurturing an informed and prolific community of contributors as well as encouraging self-governance through norms.  If mainstream users can derive value from “read” rather than “write”, scaling need not lead to deterioration in product quality.  On Wikipedia, for instance, 20,000 users contributed 80% of the content.
2. Know what kind of market you want to serve when you grow up:  Product Market Fit is a fantastic milestone, but the pursuit of this legendary goal tends to emphasize “Product” over “Market” as the active lever; the sooner we recognize the other side of this equation, the easier it will be to pivot in the direction of longer-term alignment.
3. To each his own: Facebook, Twitter and even Foursquare to some extent hold huge appeal in that they are different things to different people.  The versatility of each platform enables users to derive value however they see fit.  Supporting the creation of sub-communities of users based on different use-cases and consumption patterns is one way of ensuring power/mainstream user harmony.  

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The Best Tech Ventures Pursue Vision First and Monetization Later...

…they are in effect social enterprises that are for profit by necessity not by design


by Evan Baehr (blog: http://www.evanbaehr.com)

"[My aspiration is] to change the world," said Dennis Crowley, cofounder of Foursquare.  "If this turns out to be an amazingly big business at the same time, well, that's an added bonus."  This is hardly what you would expect to hear from a founder who raised $20 million in a Series A from all stars including Andreessen Horowitz.  Aren't these guys supposed to be razor focused on monetization?  In a quixotic way, many founders of revolutionary internet companies begin with visions that have no component on monetization.  How can we explain this irony: some of the "best" and "most innovative" internet companies--and therefore those with the highest valuations--are often founded by visionaries who are supposedly indifferent to--you might even say disinterested in--monetization.

Consider Crowley, a dreamer who was fascinated by the idea of bringing a gaming layer to the physical world.  Indeed he even wrote his NYU thesis on the subject.  And it was this nearly-academic curiosity that shaped his vision for the company.  "We just want to get all these things built... and to put as many pieces in place as possible.  After we do that, then we'll try to monetize," he explained.  "And if we can't monetize, at least we will have pushed the world forward a little.  We taught people about check-ins.  We taught them about location services and about life as a game," he offered.  For Crowley, monetization is literally an afterthought.  It is secondary in sequence and importance to product and impact.  To understand Crowley and founders like him, it is critical to understand his personal motivations.  He values teaching society about a concept.  He values helping people build better relationships.  And he values pioneering sociological concepts that enable future companies to realize his vision.  His passion reminds me of Ronald Reagan's line: "It is amazing how much you can get done if you don't care who gets the credit."

Yet this attitude--indifference to ownership and IP, a disinterest in monetization--would seem a poor fit for the model of venture-backed s-corps that nearly all of these companies pursue.  How do we make sense of the essentially communitarian, visionary disposition of innovative founders in the context of venture-backed companies with billion dollar valuations?  Would Martin Luther King have built a megachurch and charged for attendance?  Would Karl Marx have required a subscription for his podcast?  Would Mother Theresa have billed $500 an hour for a hospital visit?  Probably not.

A conversation with Chris Cox, VP of Product for facebook, helped me answer this question.  He said that in certain ways facebook should be a non-profit.  Facebook’s mission--"to give people the power to share and make the world more open and connected"--sounds like it could be the mission of the Reporters Without Borders or the Berkman Center.  So why not run facebook as a nonprofit?  They ran into a little problem: in order to realize the mission, they needed a few hundred of the smartest engineers, pedabytes of data storage, and world class infrastructure.  And to have this, they needed money.  And lots of it.

The essential tension is this: in order to realize revolutionary impact from innovative new technology products--even ones with social, communitarian purposes--the business must have a way to monetize so that it can finance the development, roll out, and support of the product.  Thus for facebook, monetization became a tactic to help realize the vision of the product--monetization was not an end in itself.

We might even go as far as to say that the success of revolutionary internet companies is partly explained by the absence of monetization strategies at their founding.  Monetization ought to emerge—but only as a supporting mechanism to realizing the vision.

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Geniuses Don’t Launch Lean Startups

by Lucas Vargas

Entrepreneurship in the 20th century was about getting a lump sum of capital from professional investors, growing the company to reach as many locations as possible, and imposing the power of scale. Big companies – like AT&T and Home Depot – followed that model. They applied techniques envisioned by Ford enthusiasts, relying on improving efficiency. Such enthusiasts assumed the plant was stable and tried to arrange inputs and processes so that the outcome picked up.

Today we have a different landscape. Barriers to entry – especially in tech industries – have decreased in consequence of the very limited capital required to start a company and create value. Therefore competition has increased and companies in the 21st century see their ability to differentiate themselves threatened. Many enterprises don't have a clear competitive advantage and, to be really successful, companies need to differentiate their products and services significantly, to envision what is unknown and not obvious to the competition and customers. These companies have to offer innovative products and services.

The old Ford model is nearly dead these days because its basic assumptions no longer hold: who said the plant has to be stable and that all we have to do is to make it more efficient? Today, the most successful and respected enterprises are the innovative companies, who are constantly changing the plant, instead of making it more efficient; or launching new products, instead of reducing the price of old products. We are no longer in the age of Fordist efficiency.  We are in the age of post-Fordist innovation.

As the philosopher Arthur Schopenhauer said, “Talent hits a target no one else can hit; Genius hits a target no one else can see.”

Is there a secret formula for creating disruptive products and services? Certainly not; it is very difficult to envision an idea that will become a transformative innovation. Nevertheless, in some places, somehow, some uncommonly exceptional entrepreneurs happen to develop extremely innovative products and services. They are able to see what the others are not. They are visionaries. They are the Geniuses.

‘Talents’ are the ones able to improve efficiency and bring marginal gains to a product or service, or even to make small innovations in existing products or production processes – they are the short-sighted people Trina Spear talked about on “ The Anti Pivot”. ‘Geniuses’, on the other hand, invent completely new products, transform the production plant, achieving major improvements, drastically boosting the companies’ results.

Schopenhauer again: “All truth passes through three stages. First, it is ridiculed. Second, it is violently opposed. Third, it is accepted as being self-evident.”

Geniuses, with extremely innovative ideas, have to go through a long way before probation; only after the distress, their ideas are perceived as palpable. They transform consumer’s interests.  They invent needs and desires that people normally cannot feel or know in the present.  A customer’s centric development process, therefore, might be a good strategy to test a Talents’ ideas, and to bring minor improvements people’s lives. But asking for customers’ opinions on ideas will only contribute to prematurely eliminating Geniuses’ innovations.

Exactly as when people face truth, people will ridicule an extremely creative idea.  Then they will oppose it violently.  And only in the end they will accept it as a self-evident and valuable product or service could bring to society.

If Geniuses are visionaries, bring true innovation, and are neglected by customers, it makes little sense to accept customers’ feedback or to pivot. Geniuses will enhance the plan to achieve great results, not offer what customers want.  They could actually do better ignoring customers’ opinions. The lean startup model does not appear to help the development of their product or service ideas.

It seems that Eric Ries disagrees. On his post “Four myths about the Lean Startup”, on April 18, 2010, he says “Lean, when used in the context of lean startup, refers to a process of building companies and products using lean manufacturing principles applied to innovation.” Is he wrong? I agree that Eric Ries model is appropriate to Talents: it might help get products right, slightly successful, slightly interesting, and slightly good. But his model would probably reject as mistaken and undesirable exactly those very unique ideas which normally bring about the most successful and transformative innovations in the market. Who wants to be a Genius anyway?

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Figuring Out foursquare

by Jeff Bussgang, republished with permission from his blog

I had the pleasure of teaching a new case at HBS yesterday on foursquare that I co-authored with Professors Tom Eisenmann and Mikolaj Piskorski as part of Tom's new course "Launching Technology Ventures".  Foursquare executives Dennis Crowley, Naveen Selvadurai and Evan Cohen were kind enough to allow us to interview them in preparation for the case, which framed some of their current key strategic issues and looked back on the choices they made in the early days to draw pedagogical lessons of lean start-up best practices, building a platform business, network effects and running monetization experiments.

The foursquare team was consumed this week with SXSW preparations, but we were fortunate to have as class guests Charlie O'Donnell, who wrote the original blog post on foursquare that got many in the community excited about the company, and Andrew Parker, who was an associate at Union Square Ventures at the time of their Series A investment. 

As I did with the class a few weeks ago when Fred Wilson visited, I asked the students to pull out their phones and tweet throughout the class.  You can see the rich "dialog behind the dialog" here, using the Twitter hash tag #hbsltv.  Here were some of the takeaways I had from the class discussion framed around three major questions I posed to the students:

1) Why did foursquare succeed as compared to the same founder (Dennis) in a similar venture (Dodgeball) in a different era and as compared to other teams pursuing LBS services in the same era?  

The students concluded that the context around a venture matters tremendously - that smart phones, the explosion of apps and social networking all were important enablers that allowed foursquare to succeed at this particular moment in time.  At the same time, the foursquare team was incredibly skilled at applying lean start-up best practices, specifically:

• Product-obsessed founders:  both Dennis and Naveen were consumed with the product.  Always interacting with users in bars and over Twitter, thinking less about strategy, analytics and monetization and focusing more on a great user experience. 
• Hunch-driven:  they had deep domain knowledge and didn't need outside studies or market research to guide their prioritization.  One of the key takeaways that both Charlie and Andrew emphasized to the students was to be power users in whatever area of focus they choose to develop those instincts.
• Minimum viable product:  they didn't wait years and years to perfect the product but instead got it out there to solicit user feedback.
• Modest burn:  the company only raised $1.35 million in its series A financing and kept the burn rate at less than $100k per month to make he money last.  Dennis wrote a great post at the time of the financing that showed just how product obsessed he was, even after taking the seed money.  There's no bravado or BS - just a list of the great features they're going to roll out as a result of having the extra capital.

2) What was the magic of the foursquare system that drove rapid adoption that so many other consumer Internet companies fail to achieve?

• Game mechanic - students really honed in on the playfulness of the service, both the entertainment value and the addictive nature of competing for badges and mayorships.
• NYC launch - the fact that the service started in such a perfect venue gave it great advantage - a highly concentrated, very social community.
• VC validation - having Fred Wilson invest and promote the company helped provide it credibility with an insider crowd that may have provided some strong tailwinds.
• Win-win for all constituents - unlike many services, the students understood a key insight about foursquare:  the local merchants make the service.  The fact that merchants are so incented to promote, discuss and reward consumers creates a positive feedback  loop that transcends the power of a consumer-only service.
• Online - offline combination.  Another aspect of the magic of foursquare is that it is not an online only service.  In fact, the ability to drive consumers to actually walk into local venues is a special dimension of the service.  As one student pointed out:  "Facebook tells me what my friends are doing.  foursquare tells me where they are and where I can meet them."  This is a unique and powerful aspect of the service.

3) Once a company achieves product-market fit and starts to scale, how do their priorities, and burdens, shift?

• Raising money, scaling the team.  A rich discussion ensued about what it means to raise big money.  When foursquare took $20 million in venture capital at a reported valuation of $100 million, suddently they had transformed the company from a lean, product-obsessed start-up to a company that would need to generate tens if not hundreds of millions of dollars in cash flow to justify a billion dollar valuation.  A product-obsessed management team suddenly had to transition to become an operational scale management team.
• Monetization.  Consumer Internet companies have to decide when they begin to monetize - as part of the lean start-up experimentation or only after they achieve enough scale to attract partners and advertisers.  But it's not a binary decision.  Foursquare has run monetization experiments from the beginning, but to justify the big valuation they will have more pressure to show real financing results, perhaps at the expense of the user experience.  It takes a strong founder to resist that temptation (think Jesse Eisenberg playing Mark Zuckerburg in "The Social Network", sneering:  "No advertising.  Advertising isn't cool.")
• Vision/Becoming a platform.  What does the company want to be when it "grows up"?  To be a generation-defining company and enter the ranks of Facebook and, arguably, Twitter, foursquare needs to evolve from a great application into a platform.  But becoming a platform company requires a whole different approach and set of priorities.  Do you build out your own features or expand your APIs and invest in supporting third party developers to build applications to your platform. One of the students had coincidentally tried to work with the foursquare API to develop an application and complained that it was very rudimentary and limiting relative to the Facebook and Twitter API.  

The verdict?  I ended the class by polling the students - who would buy foursquare stock at a $200-250 million valuation (my very rough estimate of the current trading on the secondary market) and who would sell?  One third of the students were buyers at that price at the end of the class.  Two thirds were sellers.  One student pointed out in a tweet that the voters were unfairly negatively biased because only 10% of their classmates had even tried the application and, besides another tweeted, 3/4 of HBS students apparently wanted to sell Amazon short in 1998!  Another student tweeted that if there was even a 3% chance that the company could be a $10 billion company, it was worth buying at $200 million.  Now there's a future venture capitalist in the making!

Thanks again to the foursquare team for letting us write the case and adding to the HBS community's intellectual capital.

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The Arranged Marriage Mindset

by Mohammed Aaser

After studying entrepreneurship for two years at Harvard Business School (HBS), I’ve been trying to understand what makes some startups more successful than others.   Moreover, I’ve been especially interested in this since I launched a startup a few years back which I eventually had to shut down (http://www.cafexi.com).

I believe that there are two factors that significantly increase the likelihood of success for startups.  These two factors are adopting an “Arranged Marriage” mindset, and the second is having an “Unfair Advantage”.  This first post covers the Arranged Marriage mindset, and my next post will be about the Unfair Advantage.

The arranged marriage mindset assumes you don’t know much

Take a few seconds and think about what life would be like if you had to have an arranged marriage.  An arranged marriage would likely involve getting to know someone for a short period of time, and making a permanent marriage decision based on that.  You would not be able to live with the person before the marriage.  Nor would you be able to date the person at length to get to know everything about them.  There would be no intimacy before your marriage either.  Both couples’ families would  be involved in the decision making process, but ultimately you would have the go/no-go decision on whether or not to marry the other person.

What would you want from your relationship?  What are your expectations of the other person?  What would be your biggest fears?  Now, what if I said that you had to make this marriage work?  Could you do it?

For many of us, this might be a very difficult proposition.  It’s very difficult to make big decisions like this with little information.   But because there is a tight lock on the marriage - it’s incredibly difficult to get out (unless there are abuse issues) - people make it work and could be very happy.  Moreover, as both parties learn about each other, especially early in the marriage, both partners MUST find a way to make it work.  Sometimes one partner adapts more than the other, and other times both adapt equally.   This learning and adapting, is also critical in making a new business succeed.

The love marriage model assumes you know a lot

If you are dating someone right now you might know how hard it is to commit.  ”I really like this person, we’ve been dating for 3 years, but I’m not sure if she’s the one”.  It’s probably because you want to have a perfect match, and you expect the person to stay largely the same over the span of your marriage.  Moreover, you also expect that passion and excitement to remain somewhat constant over time.  If these hold true, then you will remain in love, and your marriage will succeed. However, as individuals enter new life stages, we can change considerably, and this can lead to friction in the relationship. This could spark discussion like:   

• “You’re not the person I married”
• “I’m not in love with you anymore”
• “Where has the love gone?”
• “I’ve found someone else”

While marriage is seen as a commitment between those that are in love, if one party is not in love with the other any longer, it might be seen as acceptable to separate or divorce.  This means that there may not be as much of a forcing mechanism to make the relationship work.

  

If love prevents you from learning, don’t fall in love

According to many VCs and courses at HBS, “Pivots” are critical in the success of startups.  Most startups start with an idea, only to find that the idea is not working.  They continue to gather customer feedback, and ultimately modify their business and start on another idea.  What’s more, last year I had a chance to meet with a co-founder at BlingNation and he shared an interesting fact.  In a conversation with a VC, he found out that 95% of the businesses that were successful were not operating the business plans the VCs had funded.  This means that only 5% of the successful businesses stuck to their business plans, while most had to change in order to operate.  Moreover, a vast majority of the businesses that stuck to their business plans were no longer in business.

Uncertainty is the name of the game with personal relationships and startups.  If I fall in love with an idea or a person, it might be very difficult for me to change when faced with information that shows that the concept or relationship isn’t working.  If I instead commit myself to an industry, and focus on learning as much as I can and adapting my actions, I might be significantly more likely to have a successful.  The commitment and learning that arranged marriages can have, can be very powerful for a startup.

Loss aversion may be the reason why it’s so difficult to adapt when you are in love

The truth is that very few things in life are actually known.  And for those things that are known, they are constantly changing.  For example, imagine that you are Kodak in the late 1990’s and digital photography is picking up?  What would you do?

Well Kodak didn’t adopt a learning culture and now is a fraction of the size they use to be.  They were in love with film, and expected the market to stay the same.  The underlying cause of their failure was their response to loss aversion.  Loss aversion is the feeling that people get when they could lose something they own or love deeply.  When individuals are faced in these types of circumstances, they become mentally “rigid” and it becomes difficult to respond creatively.  This can lead to either dramatic and risky responses or no response at all.

If Kodak had adopted a learning philosophy, they may not have been impacted by loss aversion.  Instead of thinking about what they could have lost, they would have focused on what their market was really looking for (e.g., what they could gain). That’s exactly what Fuji did, and now they have taken Kodak’s place in both film and digital industries.

When responding to situations in our lives or our startups, how often are we thinking in terms of loss aversion, and how often are we thinking about learning and gaining?  If we are thinking about how much money we might lose, or our reputation, this may hinder us from learning. Even in our personal relationships, how often are we motivated by loss aversion (e.g., losing our relationship or worried about problems in the future), when instead we should be thinking of ways to learn and improve our relationships?

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The Cognitive Startup

by Sarah Dillard

“Listen to your customers, but don’t do what they say.” Eric Ries

I’ve been on Quora fewer than ten times.  My impressions of it are thus snapshots, and I have not grown gradually with it.  Each time I’ve visited Quora, I’ve been impressed by the quality of answers to questions about the Silicon Valley ecosystem.

But on the non-Silicon-Valley topics I care about, the questions still aren’t good, let alone the answers.  One only needs to browse through “microfinance” or “emerging markets” for ample evidence.  Meanwhile, each time I go back, the feature set is larger and more confusing—I have followers?  An inbox?  Notifications?  I thought I was just looking for an answer to a question, maybe one I didn’t even know I had.    

I’m not privy to Quora’s iterative process, but it feels like a company that is listening to its current user base rather than thinking about what it will feel like to join as a new user.  For Quora to “cross the chasm,” it will have to be intuitively usable by new users—and it feels like it is getting further from this the more it iterates on its current product without adding new content verticals. 

There are two popular camps in decision-making: the Malcolm Gladwells who Blink and the Michael Maboussins who Think Twice.  In How We Decide, Jonah Lehrer unites the two, explaining the neuroscience behind the decisions where it makes sense to go with your gut and those where it makes sense to step back and think carefully. 

The customer usage data collected through rapid prototyping and iteration is essentially building a limbic system—a gut—that gives feedback on how customers are responding to the product.  But a gut is not sufficient.  Without help from the frontal cortex, the part of our brain we recruit to help us address new situations, the learning machine may suggest regression to the mean or an increasingly elaborate set of features that meet the needs of beta users, as it feels like Quora is doing.  If the limbic system helps you listen to your customers, the frontal cortex helps you decide what to do about what they say.

Startups have historically been long on vision but prone to errors in assessing adoption and usage patterns.  The rapid decline in the cost of building prototypes and collecting data on usage patterns is beginning to create the opposite possibility—that startups  might have little sense of who they want to be and how they add value but reams of data about their users.  A “cognitive startup” gets both pieces right—it has a limbic system that gives it rapid feedback and a frontal cortex that can interpret that feedback.

Dropbox is an outstanding example of a cognitive startup.  As founder Drew Houston comments:

We have features that our power users have been requesting from the beginning that we still haven’t added.  One of the most humbling things we’ve done is bring in people we found on Craiglist to try our product.  They struggled to use it.  We learned then that we need to keep it simple.

And simple it is.  My mother, a physician who into the 2000s didn’t know of the existence of search engines, is already a Dropbox fan.  In its current form, Quora has no such chance. 

But all is not lost.  As Jonah Lerner ends How We Decide, “The most astonishing thing about the human brain [is]: it can always improve itself.  Tomorrow, we can make better decisions.”  Tomorrow, your startup can become a cognitive startup.  And so can Quora.

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A Sprinkling of Unvalidated Vision May Pay Long Term Dividends

by Charlotte Jepps

Conventional wisdom in ‘lean startup’ theory appears to prescribe the following formula:

1.      Sketch out an initial vision

2.      Test these ideas and the resulting products rigorously, engaging users to play with a ‘minimal viable’ version early on as a tool for learning

3.      Use these test results to pivot the product systematically to nestle it snugly into the chosen market niche, ensuring maximum engagement

4.      … and then scale scale scale!!

5.      Follow up with ongoing A/B tests and refinements

“Product-market fit” is the pivotal moment, at the end of step 3, that serves as the trigger for transition from research and development phases to customer acquisition and eventual monetisation.

While convincing as an approach to attain maximum user engagement at launch, I think it is important to remember that “fit” is less of a static formula, but a state of alignment that requires continuous maintenance over the lifetime of a user’s engagement. Whilst the “flow” of new users to a site is important, it is surely the “stock” of loyalists that captures the attention of venture capital and advertisers.

By testing the water with a “minimal viable product” there is surely a risk of focussing solely on attributes that attract initial interest based on their recognised needs (truly ‘lean’ products stripped of all elements that did not appeal to today’s testers), but failing to adequately value elements that might grow progressively in value and drive user stickiness in the longer term.

I think there is an argument for taking pause after step 3 to reintegrate a little more ‘top down’ strategy and vision to the initial offering, even if it means adding a little risk.

Obviously the reasons certain ideas are de-prioritised in user tests is that users do not currently see their value. But I think it an oversight to consider optimal product-market fit as a unidirectional or static concept: a “fit” of one to the other. Rather I believe ventures should aspire toward “synchronisation”, where both products and markets evolve together over time each with the capacity to observe and adapt to each other (albeit after the site has got the user’s attention). After all, surely one of the most exciting attributes of a new technology is the potential to open doors only the visionaries realised were closed – and once users come to value seemingly ancillary initial features they will be increasingly predisposed to explore new features in the future.

As an example, consider a technology product like the Ipod. The user is going to give the team positive feedback relating to their initial needs: something that plays music transferred from a CD via their computer - but I assume Apple already had designs on capturing online music distribution. This ultimate vision involves multiple interlinked products and services which would likely overwhelm the early user, but was clearly worthwhile planning from the outset. Similarly, a user would inherently undervalue product attributes that leverage archives of their own usage data, but this data capture is most valuable if initiated at the outset.

I wonder if there is a way to be lean but avoid focussing too religiously on current “ fit” at launch, stripping the product (and team) down, and thus failing to lay the groundwork to transition smoothly toward a grander vision?

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Think You Know What You Want?

by Mark Datta

The customer is not king. Sounds like heresy, right? Perhaps put more accurately, the customer is not always king.

Two companies we have studied – Dropbox and Aardvark – espouse user-centric design as their guiding design philosophy. Essentially, products are designed around how users can, want and need to use a product – so no behaviour adjustments are required from the user to accommodate the product. It fits well with the lean start-up philosophy, using multiple rounds of iteration based on metric-driven assessments, and neatly embodies the ‘customer is king’ mantra.

But both companies deviate from this philosophy on at least one substantial aspect. Dropbox refuses to allow users to sync any folders which are outside of their local Dropbox folder. Aardvark refuses to maintain a searchable database of previous questions and answers. Neither would be particularly expensive or technologically challenging (from my outside-in impression).

Four possible explanations come to mind:

1.     ‘Democracy’: the wishes of one user group conflict with those of another group, and the loudest or most lucrative group wins

2.     ‘Protector’: customers don’t really know/say what they want, so the company protects them from themselves

3.     ‘Visionary’: founders can be very particular about the core of their product vision, and they’ll compromise on almost everything but this

4.     ‘Money’: when cash is at stake, customer wishes are sometimes trumped by the company’s need cash

We can disregard #1 and #4, because neither feature significantly affects other users, and neither feature would have a materially negative impact on profitability.

#2 seems more applicable to the Aardvark case, if we look at the second-order effects. Making the change may enhance the product in the near term, but it can fundamentally alter the product as it matures and grows. It would become a repository of knowledge – differently organised but similar to Wikipedia or Quora – rather than serving fresh, trusted knowledge to order. It could be argued that the former is a better model, but that is not what Aardvark is. Aardvark’s hypothesis is that customers want what it provides, so they protect that by forcing themselves to renounce the archive model and improve the quality and speed of fresh answers instead.

#3 seems more applicable to the Dropbox case. The vision is a simple product that just works. It should be impossible for users to screw up their computers, publish their credit card details in a public folder or lose track of their files. The feature could cause these problems in the hands of even an averagely savvy user. But, surely the feature could be hidden in an advanced section of the menu with a bold warning? That argument misses the point – perhaps a subtle one – that Dropbox is a location in itself. It’s not just an enhanced backup or file-sharing service. In the end, this comes down to ‘the vision thing’

We often don’t know what we want. So it’s either up to a ‘visionary’ to figure it out in advance for us – Steve Jobs and Vincent Van Gogh spring to mind. Or it’s up to a ‘protector’ to save us from ourselves – step forward Drew Houston of Dropbox, and the sage words of Eminem:

So be careful what you wish for

'Cause you just might get it

And if you get it then you just might not know

What to do wit' it, 'cause it might just

Come back on you ten-fold

Strategies which go against your customers’ desires are ineffective for most companies in most situations. But – like some benign dictatorships and arranged marriages – less choice can lead to a better outcome than we might expect.

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Lean Startups: The Most Efficient Path To Non-Differentiation

by Joris Poort 

In a hypothesis-driven lean start-up environment, lean theory recommends maximizing your learning from customers while minimizing effort.  While the theory sounds great, if lean startups follow lean principles blindly it could lead to unintentionally bland results.  More specifically, if the product vision is truly inspired, lean approaches can drive the development path away from a disruptive new solution and gravitate more toward incremental improvements upon existing products.

Lean methodologies can stifle innovation

Lean principles originated in the manufacturing environment to help reduce waste and focus on value-added activities.  In manufacturing environments however, lean principles are typically only implemented once both the production processes and product are very well defined.  In contrast, in the R&D lab lean principles can inhibit collaboration, creativity and innovation.  To be sure, there are certainly ways to improve the efficiency of the innovation process.  In fact, IDEO has developed their business around ways to achieve this in a repeated fashion.  In an uncertain innovative environment, the value that certain activities bring to the final solution can often only be identified as such in hindsight.

In a start-up, just like in an R&D lab, the product is still not yet fully defined and structured processes can limit the creativity of innovation and breadth of outcomes.  Additionally, iterative continuous improvement principles can severely limit the final product results from lean start-ups to incremental improvements.  If the lean startup methodology is implemented without careful thought, the original vision of the startup will likely be discarded pre-maturely.

Customer feedback can be misleading

A truly disruptive product solves a problem in a creative novel way, and often requires new customer behaviors.  If a customer needs to behave differently for your product to work, customer-centric development and feedback needs to be approached with care.  Customer feedback and behaviors may be skewed toward experiences with existing products.  Thus early adopter customers can give misleading feedback, and cause the product development path to stray away from the original vision – before this vision has even been appropriately tested. 

An ideal visionary customer can perhaps piece together where you are trying to go with your product, but this can be very unreliable.  Real valuable customer feedback comes from a completed product, not half of a prototype and some hand waving. 

Splitting interdependent hypotheses can lead to false results

Disruptive products often have a whole hypothesis composed of a group of sub-hypotheses that are interdependent on each other.  Testing these hypotheses independently can lead to both false-positives and false-negatives.  Just because you couldn’t sell the peanut butter or jelly sandwiches independently, doesn’t mean the peanut butter and jelly sandwich isn’t a great snack.  Customer feedback used to test a hypothesis only becomes valuable with a product that is able to test your whole hypothesis.  Thus if maximum learning really only occurs with all the pieces of a complex product pieced together, then your minimum viable product is really just your first whole product release, just like in traditional product development.

Lean startup methodology is a helpful guide, but not gospel

Lean startup methodology provides great advice on ways to iterate quickly and get customers involved in startup product development.  Ultimately I do believe Steve Blank’s book (Four Steps to the Epiphany) and Eric Ries’ lean startup methodology are extremely effective as a guide – but should be interpreted with care.

Some tips to help avoid these potential lean methodology pitfalls:

·       Don’t stifle early innovation by over-applying lean principles

·       Test interdependent hypotheses with whole products

·       Keep a strong vision and filter customer feedback

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