A lot of discussion on startup and business strategy ultimately comes down to one single piece of advice.
“Build a moat”.
Yes, increasing margins is important. Yes, solving distribution is critical. But before you do all that, you need to build a “moat”.
What’s a moat? Like medieval castles, a moat for your business protects you from competitors and substitutes. It gives you market power, so you can focus on growth, profitability, and all the good stuff.
For many investors, it is the most important thing.
Most of us in the startup community understand the concept of a Minimum Viable Product, or MVP. It’s the most basic version of your product that still delivers your core offering.
Aiming for an MVP helps entrepreneurs (especially first-timers) avoid the rookie mistake – building too much product before validating market need. We all want the ten revolutionary features in our first version. But not only will these features take five extra months to build, most users will also not see them.
So that’s the concept of an MVP. Sounds simple, right?
And yet, we slog for 3 months to build the MVP. And congratulate ourselves on finding out it didn’t work, and then spend another 3 months on a pivot.
Three months is way too long! Why does the MVP take so long?
The reason is that we’ve got the notion of an MVP all wrong.
They are tools that help us understand the world faster and better. Instead of approaching every new problem from scratch.
Simple but powerful concepts, that help us understand situations more clearly, and make quicker yet better decisions.
For example, take this core principle from economics: “There ain’t no such thing as a free lunch“. It reminds us to look at every wonderful business deal with care. What’s the catch? There’s always a catch.
In a way, mental models help us think in a more “modular” fashion.
Modular programming makes software much faster. In the same way, mental models are the modules that soup up your decision-making engine.
Mental models are the modules that soup up your decision-making engine.
Over the years, I’ve written about a few powerful mental models, that have helped me think faster (and better) about business problems.
If there’s any ideology that’s gone from radical idea to article of faith in less than a decade, it’s “Lean Startup”.
When the idea was first proffered by Steve Blank in the early 2000s, it took the world by storm. A simple idea. That generated so much momentum for a startup.
And by 2007, everyone could point to Facebook – or even better, Twitter – as proof that Lean Startup works. Facebook at least scaled with a consistent vision. Harvard → other universities → the world. Twitter was the original clown car that pivoted its way into a gold mine .
I’m a strong believer in starting up lean.
It’s how, in a past life, I iterated my consumer loyalty app to 200K users… with zero marketing dollars. Or how we launched a new lending segment at Indifi, and made it our top segment in 6 months.
So yes, Lean Startup works. And it is an article of faith. The word “lean” is almost redundant today. Of course a Startup has to be Lean. Of course you first build an MVP and test it with customers. Raise serious money only when you find product/market fit.
And then there’s Quibi.
Quibi raised USD 1.75 billion two years before launching its first product.
It then went on to raise another USD 750 million a year after that. Still a relaxed one year before launch.
If you haven’t heard of Quibi, you’d be forgiven to think it was a rocket company to rival SpaceX. But no, Quibi is a mobile content platform (short for Quick Bites), which launched a month ago.
The antithesis of Lean Startup. Will it work? Is this how we’ve got to do it now?
Get Big Fast Baby
The first insight about Lean Startup is that it bootstraps leverage from scratch.
There are only two priorities for a start-up: Winning the market and not running out of cash
Every start-up is in a furious race against time. The start-up must find the product-market fit that leads to a great business and substantially take the market before running out of cash.
That’s where leverage helps. Maximize the ROI on the cash, people, or other resources you bring to the business. Win the market as fast as you can, before you run out of cash.
Now, there are many types of leverage a startup can have.
Proprietary IP / best-in-class technology
Regulatory capture: Microsoft scaled only because of their hilariously one-sided deal with IBM.
The product itself: Instagram has in-built virality. In its early days, Instagram’s core use-case was to touch up photos, and post them on Facebook or Twitter. So, by simply using the product, you were marketing it to your friends.
Network effects: Uber
The revolutionary suggestion of the Lean movement was that the process itself could generate leverage.
That’s how Lean Startup works. Start with a hypothesis: product X solves problem Y for consumer Z. Test it in the most basic way possible, and iterate and refine.
Such a simple process, but generates such strong momentum.
It’s like you try to lift yourself by your shoelaces. You wouldn’t expect it to work, but magic, it does!
Now here’s the thing – the leverage could simply be intuition.
The founder of Quibi is Jeff Katzenberg.
His catalogue of accomplishments is stunning. He oversaw The Lion King (the original), Beauty & the Beast, Aladdin, etc. at Walt Disney Studios. Then he co-founded DreamWorks, and produced Shrek, Kung Fu Panda, Madagascar, and several other massive hits.
Jeff knows more about film-making than 99.9% of the world’s population. Combined.
And the CEO of Quibi is Meg Whitman, ex-CEO of HP and eBay. A tech veteran.
Katzenberg and Whitman have boatloads of intuition, sharpened by decades building large media and tech companies.
“I said to Meg that, until day one, every decision that we make around content will be driven by instinct,” Katzenberg said. “Minutes after we launch, everything will be driven by data.”
And it’s true. They’ve doubled down, extracting every ounce of instinct from their extensive experience.
Everything was so meticulously planned. From the same interview:
A launch date a year in the future (and they were bang on time)
Crystal clear financial model for funding content production
Firm view on pricing tiers for the app
No testing hypotheses with an MVP. Just dive right in. With a few billion dollars in the bank.
What do you do when there’s no leverage?
The second insight about Lean Startup is that it was an answer to a specific question, posed at a specific point in time.
As Steve Blank says, the idea of the Lean startup was built on top of the rubble of the 2000 Dot-Com crash.
Most entrepreneurs today don’t remember the Dot-Com bubble of 1995 or the Dot-Com crash that followed in 2000. As a reminder, the Dot Com bubble was a five-year period from August 1995 (the Netscape IPO) when there was a massive wave of experiments on the then-new internet, in commerce, entertainment, nascent social media, and search.
After the crash, venture capital was scarce to non-existent. (Most of the funds that started in the late part of the boom would be underwater). Angel investment, which was small to start with, disappeared, and most corporate VCs shut down. VCs were no longer insisting that startups spend faster, and “swing for the fences”. In fact, they were screaming at them to dramatically reduce their burn rates. It was a nuclear winter for startup capital.
The Lean movement started during a nuclear winter for venture capital.
When capital is scarce, you have no choice but to go Lean.
When capital is not scarce, it’s worth considering whether other forms of leverage can help you win the market faster.
Well, today, capital is not so scarce. And it’s chasing fewer good deals.
If you can raise the capital, it makes sense to go big, and go fast. Correct mistakes along the way. Figure out product/market fit as you go.
Thin was in, but fat is where it’s at.
It’s tempting to say that Lean will have a resurgence post COVID-19, as the world tips into recession.
But many funders have raised large funds at the top of the market. 10 of the largest 15 VC funds ever raised, have been since 2016.
And tech startups will be especially hot, seeing the resilience of tech in this downturn (NASDAQ is inching back towards its peak!).
So capital is available, searching for “fat” tech startups that can absorb a lot of their capital. The number of seed deals will continue to fall, as they have since 2015.
Let’s talk about Quibi.
OK, we’ve discussed why fat startups like Quibi will be the norm going forward. Now it’s time for the punchline.
I don’t think Quibi will work. Despite all the leverage (or “fat”) it has.
It won’t go bust. But the value of the company will trend towards the value of the content it has bought / licensed. The platform itself will have limited value at best.
Let’s get the obvious first-level problems out of the way.
The battle between every startup and incumbent comes down to whether the startup gets distribution before the incumbent gets innovation.
But the more important reason Quibi will fail is…
What is Quibi’s Seinfeld?
Content follows a Power Law distribution. You can have a million shows, but viewership will concentrate around a few.
I couldn’t find a chart on TV shows, but here’s a chart about movie viewership from Michael Tauberg.
Netflix paid 6 years (!) of its content budget for Seinfeld, because Seinfeld is a “whale”. Like The Office and Friends, this is what people will subscribe to Netflix for. Not for Altered Carbon or Too Hot to Handle or whatever else.
That’s the math of the streaming video industry.
Consumers will pay for 2-3 subscriptions, and you do what you can to be one of them. You need proven hits like Seinfeld, not hit-or-miss new shows.
It’s like the SEO Red Queen Effect – if you aren’t in the first three results on Google, you don’t exist.
Quibi has some solid content. But unless it unearths a Seinfeld or Sopranos or Big Bang Theory in its first try (possible, it’s Katzenberg after all), it’s down for the count.
Well, that’s how the Quibi crumbles.
Related: Teledesic was the original fat startup. Raised two billion dollars for a satellite network… and then didn’t even launch.
As Tren Griffin writes in this short memoir, some investors received many times their original investment. Even though the company never provided service!
[A version of this article first appeared in The Quint.]
As a seed-stage investor at OperatorVC, I see at least 50 startups a month that are looking to raise a seed round. Most pitches aren’t perfect. That’s usually OK – a founder’s core competency should be building, not pitching.
But one of the most egregious mistakes is calling yourself the “Uber of X”, or the “Airbnb of Y”.
The moment you say this, the pitch ceases to remain credible.
This is such a common refrain – and such a rookie mistake – that I can’t help but point it out.
Startups ain’t Star Trek, but I feel Picard’s pain.
I think the “X of Y” epidemic started with Y Combinator’s application process. The How to Apply page mentions that YC likes hearing “X of Y”. It helps them place the startup into the pantheon of successful companies they’ve seen.
It makes sense for YC. When they have to scour thousands of startups in a short time to select a few, a metaphor helps. “Hi, I’m the Uber of bicycles.” Enough, let’s move on.
But most fundraising pitches are not YC applications or Demo Days. Yet, Paul Graham’s words are gospel. So everyone and their next-door founder has adopted this with great gusto.
Even in situations where it doesn’t make sense.
And it’s gotten to a point where it’s almost ludicrous! I’ve heard a startup describe itself as “the BikeBob of X”. Have you heard of BikeBob? Neither have I! [Note: I’ve disguised the real name of “BikeBob”, but trust me, you haven’t heard of it.]
Let’s be clear – this is not a “done thing”. It’s not a “best practice”. It’s a mistake, in most pitching situations. Even if it’s Uber you’re comparing yourself to, and not BikeBob or MotorcycleMary.
Before digging into why it’s a mistake, there’s an even more basic question. Why do we do it? Fierce individualists that we are, why do we willingly attach our identities to something else?
Why do we do it?
Helps explain the product. This is why it’s recommended for YC Demo Day.
Shows a pattern. We all know that VCs are in the pattern recognition business. This just makes it easy for them to realize that you’re the next Uber. They better chase you with their money!
An attractive narrative. Starting up is hard. It’s difficult to justify to your family – and yourself – why you’re abandoning a stable ship. In such a scenario, who wouldn’t like a little ego boost?
[Tweet “Saying you’re Uber of X is awesome. Wouldn’t you love to equate your startup to a unicorn?”]
But the moment I hear it in a startup pitch, it’s hard not to cringe. Why?
Why is it a mistake?
1. Gives the impression that you’re not solving a real problem.
It sounds like you just read about a successful startup’s business model, and applied it to the first sector you could think of.
“AirBnb for cars: rent other people’s cars when they aren’t using them.”
It’s like you went to the neighborhood workshop and bought yourself a hammer. Now everything looks like a nail!
[Tweet “Unless an idea has formed organically from a real problem, it’s probably a bad startup idea.”]
[Side note: this is just one characteristic of a startup idea that sounds good, but is probably bad. Click here for a full list of such characteristics.]
“Do you want a bicycle at this very moment?” “Not really, but your speakers look awesome!”
Sometimes, it’s a real problem all right. But the solution doesn’t make sense.
An “Uber of intercity B2B logistics” is OK from a problem perspective. Manufacturing companies do need intercity logistics.
But do they need it on-demand? No! A huge majority of customers transport loads often, on predictable timelines. They’d prefer negotiating longer-term contracts.
I once thought of applying the Airbnb model to books.
Once I finish a book, it’s lying on my bookshelf. Wouldn’t it make sense to lend it out to others who may want to read it?
The problem is real – I need to buy a book to read it. But is this the best solution at scale? No. Not in a world where book prices are falling, e-retailers offer one-day delivery, and you can download a Kindle book in an instant.
Do I know the problem exists? In some cases, yes. In most cases, no. All I know is that the solution has worked. In another, unrelated sector.
2. It can constrain your imagination.
The moment you start calling yourself “Uber of X”, you constrain your thinking. You fool yourself into believing you have a foolproof playbook. When in fact there are important nuances and differences that are critical to consider.
When Taxi for Sure started, one initial focus area was inter-city cabs. Do you think they’d have discovered the lucrative on-demand taxi market if they called themselves the “Redbus of taxis”?
Oyo Rooms, a successful startup in its own right, could have called itself “Airbnb of hotels”. But would that have worked? Would the founder have made the same decisions? It’s possible. But not probable.
3. It’s another stake in the ground you must defend.
VCs are in the business of pattern recognition. They’ve internalized the patterns of successful startups to a level you never will.
They’ll point out nuances of those playbooks that don’t apply in your case.
I once saw a startup that was building the “Oyo of manufacturing”. Just like Oyo helps hotels use their idle capacity, this founder would help manufacturers deploy theirs. Only two tiny chinks in his plan:
Hotels have average capacity utilizations of around 60%. Manufacturers have much higher utilizations. And moreover, they don’t want to be at 100% – flexibility is important. If a plant has 80% utilization, there’s no idle capacity.
Unlike hotels, production is stable. A plant owner doesn’t want one-off users. He’d prefer someone who promises orders for at least 6 months.
Pattern recognition has a flipside too. An average VC sees 500 pitches every year, to select 3-4. So, they’re far more well-versed in the patterns of bad startups than good ones. Be ready for sweeping statements!
[Tweet “VCs are far better at identifying bad startups than good ones.”]
Successful entrepreneurs, investors and strategy experts all extol the virtues of focus. I have as well, as a strategy consultant, then a founder, a writer, and now as a seed stage investor at OperatorVC.
“If you focus on a small segment, you can own it, dominate it.”
So the conventional wisdom goes.
But there are times when focus can constrain a startup from achieving its potential. When you become a big fish in a small pond, while there are gloriously large oceans just around the corner.
How do you know which is which? How do you know when to focus, and when to extend?
This came up in a conversation with Ankesh Kothari, a fellow entrepreneur and seed investor. He highlighted how a lot of startups focus too narrowly on a small market, and never expand. And we often see the opposite at OperatorVC. Startups trying to solve problems across a broad swathe of consumers from the outset. “Microsoft Office products that solve everyone’s problems”, as I call them here.
Here’s what’s interesting: neither of these is always the right answer.
Sometimes, you have to focus on a specific consumer segment. Make sure you solve a need deeply. At other times, you need to expand your horizons.
If you focus too acutely, you’ll never become a $100 million company.
This is not intuitive. You can’t be deep in the weeds one moment, and flying at 20,000 feet the next.
Great founders can alternate between these two opposite behaviors well. And legendary founders plan for this in advance.
Now, I know what you’re saying. Hindsight is 20:20.
Is this just one of those clichés that you retrofit to success stories? Or is there actually a lesson here for people just starting out?
Is it even possible to be more like Elon Musk?
The Chasm model of product adoption is a great framework to know when to focus, and when to extend.
At the trivial level, we all know this. Tech enthusiasts and early adopters will use your product first. The mass market (the Early Majority or “Pragmatists”) will gradually start using it later.
But the Chasm Model offers two new insights:
There’s a “chasm” between the early adopters and the mass market (the early majority). It’s very hard to make that leap, and many startups die trying.
Unlike the early adopters, the early majority aren’t interested in your tech. They are interested in its application to their most important needs.
And therein lies the way.
When to focus
Focus when you’re crossing the chasm.
Focus on a single narrow niche within the mass market. Understand that niche and its most important needs. Create an application of your technology tailored to that segment’s needs. Find product-market fit, and cement your place there. Own that niche.
Let’s take an example we’ve seen at OperatorVC. Say you’re building an AI based system to help people recover from illnesses. Don’t start coding algorithms for all the million diseases that are possible. Don’t even start with the 100 most prevalent diseases. Start with one disease. Just ONE.
When to extend
Extend once you own that first segment.
Select the next niche(s) in the mass market that you want to own. Again, design applications of your technology for those segments.
This is exactly what Tesla is doing now, working its way down the price segments.
Once the healthcare bot is perfect for that one disease, it’ll be much easier to expand to the next disease. And the next hundred.
[Tweet “Be like Elon Musk. Focus first. And then extend to own the world.”]
So, when you’re starting off, make sure you focus on a segment you can really own. But also be ready to extend later, so you can own the market.
Many of us have heard the saying “What gets measured, gets managed”. A simple, yet powerful thought. With a simple corollary – what doesn’t get measured, doesn’t get managed.
But last week I heard an interesting anecdote that drove home the power of measurement. In reality, the corollary is far more extreme. In the eyes of the person responsible, what doesn’t get measured… doesn’t really exist.
But before we get into that, let’s take a second look at Peter Drucker’s statement.
In just five words, he captures an overwhelming amount of insight. On human behavior, cognitive biases, the power of incentives, and the strength of a goal-driven approach.
If you want something done, measure it. If there’s an objective number representing the outcome of your actions, you (or your team or partner) will automatically work towards improving it. If you’re assessing something subjectively (or not at all), then progress will never happen.
We see scores of examples of this, across our personal and professional lives:
A. Choose an objective metric
If you need to exercise more, then don’t just tell yourself to do that every day. Track your activities. A guy I know walks up and down his office building five times every day, just so he can hit the step goal on his Fitbit.
If you want to increase user engagement on your app, look at your Daily Active Users or Monthly Active Users metrics. Run experiments to increase them. Don’t directly start integrating fun-and-games mechanics without an objective goal.
B. Choose the right metric
If you want to lose weight, don’t just count calories. Instead, count the amount of simple carbs you’re eating. [Aside: this is an excellent layman’s book on the subject].
If you want your salespeople to increase sales, don’t measure the daily hours they clock. Count the amount of sales they make. Else, you’ll have diligent workers… who use Facebook 8 hours a day (9-5, on the clock).
As they say, “track it till you crack it” (it rhymes, so it must be true).
Photo by Russ Hendricks on Flickr (https://bit.ly/32vlBp8)
But I heard a surprising story last week about Indian broadcast media. It underlined the power of the measure, or in business jargon, the Key Performance Indicator (KPI). It showed how, when marketers can’t measure their impact on a market, they all pretend it doesn’t exist. Even though they know full well that the market is substantial.
First, some quick background on the Indian broadcast market.
Traditional audience measurement was flawed
Till recently, TV broadcasters and advertisers in India measured impact of TV programming using an agency called TAM. TAM had special set-top boxes installed in 20K households across India, which tracked data on TV watching habits.
Using this, TAM could tell broadcasters how many people, in which cities, were watching which show. Broadcasters were incentivized to produce content that generated high TAM scores, so they could show this data to advertisers and demand hefty ad rates.
It was a useful KPI, aligning incentives all round. Except for a tiny problem – TAM’s sample was urban-centric. In a market where the rural populace forms a sizeable proportion of TV watchers.
Broadcasters recognized this problem, and fixed it
Since TAM placed disproportionate importance on urban TV viewing, it was clearly unrepresentative. And the powers-that-be knew that. So, in the last two years, the industry created an alternative – the Broadcast Audience Research Council, or BARC.
BARC looks at a much larger sample, including a sizeable rural proportion. The system rolled out just recently, with an objective of giving a clearer picture to broadcasters and advertisers.
Instantly, broadcasters started generating new, “rural-focused”, content
Here’s where it gets interesting.
As BARC launched, more and more shows with supernatural elements started appearing on TV. Even existing shows, whether staid family dramas or comedies, started having occult “tracks”. This is what happened in 2015:
New shows were launched, like Darr Sabko Lagta Hai (“Everyone gets scared”), Naagin (rough translation: “serpent woman”), etc. In fact, Naagin was one of FOUR new shows about serpent-women!
Many ongoing shows started introducing supernatural elements. Not only daily soaps (or saas-bahu shows as we call them in India), but also comedies.
Why did this happen? The reasoning goes – ghosts, serpent-people and others are integral parts of age-old Indian folklore. These beliefs are still a major part of rural lives. Hence we’ve introduced them to create a better connect with the new rural audience.
Disregard the blatant stereotyping for now (we’ll come back to it later). Assuming that this is what the rural audience wants, the logic makes eminent sense.
Why then was television content urban-focused? Why were there no shows targeting the rural populace?
Because rural wasn’t measured.
The only number available was the urban-focused TAM, which was out of step with reality. And producers of TV shows, in full knowledge of this fact, nevertheless used it. There was no other number, so they followed this one. Single-minded and unswerving, like mice following the Pied Piper.
[Tweet “If you can’t measure it, it doesn’t exist.”]
What does this mean for us? We need to be more careful than ever in choosing our KPI – the True North that we set our sails by.
If we don’t choose the right metric (or worse, choose the wrong one), the outcomes will be the antithesis of our objectives. No matter how well-meaning we or our colleagues are.
Coming back to our rural stereotype, we’ll find out how true it is in the coming months. If it isn’t, expect the broadcasters to nimbly eliminate the black magic tracks from their shows. It will be managed adeptly. After all, it’s getting measured now.
Over the last few years, I’ve been quite interested in the startup investing process.
At the trivial level, understanding the investing process could help struggling entrepreneurs (like me) raise funding faster. And, assuming that this investing philosophy does pick winners, this could also teach us what kinds of businesses tend to make it big. And we could then apply those patterns to our own businesses.
It certainly is, according to the conventional wisdom. According to Andy Rachleff, again:
The best investments have high technical risk and low market risk. Market risk causes companies to fail. In other words, you want companies that are highly likely to succeed if they can really deliver what they say they will.
Don’t take market risk – i.e., aim for markets that are already large. Instead, take tech risk – where the product itself is hard to create.
This sounds great, and is a commonly accepted truism. And it also seems to be common sense.
But, again, is it true?
One way to settle this is to look at the performance of venture capital over time. As they say, nothing talks like money. But a quick look at VC returns can be quite sobering.
The Kauffman Foundation reports that VC hasn’t outperformed public markets since the late 1990s. In fact, since 1997, VCs have returned less cash to investors than they invested!
Could it be that this VC approach of taking high tech risk but low market risk isn’t working?
Tech matters (more)
I’ve just finished reading Crossing the Chasm, Geoffrey Moore’s landmark book. He presents technology adoption as a bell curve, with a few “gaps” between segments.
It’s easy to get the innovators and the early adopters. They want to be the first to try new technologies, so they’re primed to be convinced. You start hitting the main market only with the next group, the early majority.
Moore’s key insight is that it’s not natural to move from the innovators and the early adopters to the early majority. That’s why there’s such a huge chasm between these segments in the image above. A graveyard of companies that show great early traction, but suddenly hit a wall and collapse into the chasm.
His model suggests two pointers for technology companies:
Building a version of the tech, and serving innovators and early adopters, comes first.
The real challenge is crossing the chasm. You need to find a specific application to solve the early majority’s existing problems. This market isn’t visible or obvious at first – you need to create / discover it.
Thus, tech companies don’t take tech risk. They take market risk. If they find a big market, they succeed big. If they don’t, they fail.
Whenever VC returns peaked, the driver was high market risk. Would there be a big market for computers (60s, Intel)? Would there be a big market for PCs (70s, Apple, Microsoft)? Would biotech become big (Genentech)? Would the Internet reach the masses, or would it remain a plaything of the elite (90s)?
These markets may seem inevitable today, but that’s just hindsight bias. Ask Ken Olsen. Or Thomas Watson. Or anyone in this article.
In most cases, investors didn’t take tech risk. Often, they found already-working products. Apple’s technology was already working when it raised funding.
Whenever VCs tried to reduce market risk to stabilize returns, they failed. For example, in the 80s, they entered more traditional, massive industries like retail. Result: returns were consistent and stable. But bad.
Thus, VCs didn’t often take tech risk. They preferred technologies that were already proven, and showed promise. And whenever they tried to reduce market risk by entering existing large markets, they failed.
At the end, Jerry summarizes:
The only thing VCs can control that will improve their outcomes is having enough guts to bet on markets that don’t yet exist. Everything else is noise.
Peter Thiel’s Founders Fund adds its own voice to the argument. It highlights how, from the 60s to the 90s, VC was a predictor of the future. Today, though,
VC has ceased to be the funder of the future, and instead has become a funder of features, widgets, irrelevances. In large part, it also ceased making money, as the bottom half of venture produced flat to negative return for the past decade.
When you focus on incremental innovation, for a market that’s here and now, returns fall.
When something is described as a toy, that means it has everything an idea needs except being important. It’s cool; users love it; it just doesn’t matter. But if you’re living in the future and you build something cool that users love, it may matter more than outsiders think. Microcomputers seemed like toys when Apple and Microsoft started working on them… The Facebook was just a way for undergrads to stalk one another.
I alluded to a similar point in a previous article, where I said that you must target a deep need for a narrow population, rather than a shallow need for a broad one.
As a VC friend of mine was quick to remind me when we discussed this, the quality of the team is incredibly important!
But this quality is not theoretical or bookish. It’s not about which Ivy League school you graduated from. Or even whether you have a string of successes under your belt (at least in consumer).
Instead, it’s about three things:
How driven you are. Will you overturn that 99th stone to find the gold mine? Or will the first 2-3 pivots fatigue you? Your initial ideas for tackling a problem will rarely be right. You’ll need to persist: find a new beachhead, and wade in again.
Are you willing to learn? Again, you won’t be right the first time. They say industry knowledge is a great unfair advantage. True, but it’s also a double-edged sword.
Can you execute?
So what’s the conclusion?
Which of these three is the most important?
The ex-consultant in me would answer, “all three”. And he’d throw in an “it depends” for good measure.
But it appears the conventional VC wisdom, of taking tech risk but not market risk, is wrong. As the Founders’ Fund article above says, the current trend of funding incremental innovations and more efficient solutions for existing markets is what has pushed VC returns downwards.
And what does this mean for entrepreneurs? Instead of trying to build something for large markets that VCs seem to be interested in, “swing for the fences”. But not in the conventional sense of aiming for large markets. Instead, try and piggy back on emerging trends that could become waves.
Sure, you’ll probably strike out. But should the market materialize, you will laugh all the way to buying the bank.
I’d love to hear your opinions. If you’re an entrepreneur or startup investor – what’s your stand on market risk vs. tech risk? Do email me at email@example.com, tweet at @jithamithra, or comment here. I’d love to publish a follow-up sharing your opinions.
Thanks to Aditi Gupta and Abhishek Agarwal for commenting on drafts of this post.
 This article is about VC backable startup, and not a small business in general. Many great cashflow businesses (e.g., auto dealerships, general manufacturing) are often not high-growth businesses that can return 20x on invested capital, and are therefore not VC backable. See this article for a great description of such businesses.
Multi-sided business models are a unique phenomenon – unlike standard businesses which offer a product / service to a particular type of consumer, multi-sided businesses don’t offer any product / service. Rather, they provide a platform that connects buyers andsellers.
Think of Uber – it connects cab drivers and passengers, who benefit each other. E-commerce marketplaces are also examples – they connect buyers with sellers.
Such businesses face a natural chicken and egg problem. For the platform to be useful, both sides have to be present. Sellers won’t come on to your platform without buyers, and buyers won’t come either, unless there’s enough choice (i.e., sellers).
For example, people buy video game consoles only if there are games they can play. But game designers make games for a console only if there are enough people who own it. The proverbial chicken and egg problem. How do one solve this impasse?
The above article discussed a few ways in which businesses can break this deadlock. Many readers wrote in after the article, asking if I could create a framework / checklist that they could use to brainstorm ways to scale their own multi-sided businesses.
Towards that end, I recently published this presentation on SlideShare. Check it out, download it, and let me know what you think!
Regular readers of this blog and my newsletter (subscribe here if you haven’t!) know that I’m an avid reader. 2015, for me, was a year of quantity. I read 60+ books, and at least ten times as many articles.
Some of these were bad, some good, and some changed my perspective on work and life.
I could list the top 5 books I read in the year. But instead, let me present the top 5 ideas that transformed my thinking, and the books I found them in.
1. Keystone Habit – One Habit to Rule Them All (The Power of Habit)
I’ve written before about Thinking, Fast and Slow, and the difference between System 1 and System 2 thinking. The former is rapid, automatic, instinctive and judgmental. The latter is slower, more considered and analytical, and more effortful.
In most situations, we tend to use the quick-and-dirty System 1. The more methodical System 2 is quite lazy.
This proclivity to use System 1 underlines the importance of habits. Such sequential, repetitive tasks are so ingrained that we do them without thinking. The essence of System 1.
For instance, do you think when you’re brushing your teeth in the morning? More likely you’re so woozy you can’t walk straight. Still, your teeth are sparkling clean by the end of it.
That’s the power of habits – you can do certain tasks without thinking.
To understand more about habits, I read two books this year – Hooked and The Power of Habit. They talk a lot about the structure of habits, how to build good habits, how to break bad habits, etc.
But the most powerful concept to me was that of the keystone habit. Keystone habits are small, narrow habits in one area of your life that impact several other areas in a significant manner.
As Charles Duhigg says in The Power of Habit:
Some habits have the power to start a chain reaction, changing other habits as they move through an organization. Some habits, in other words, matter more than others in remaking businesses and lives. These are “keystone habits,” and they can influence how people work, eat, play, live, spend, and communicate. Keystone habits start a process that, over time, transforms everything.
A few examples of this are:
Exercise. When you start exercising, even if only once a week, it triggers changes in various other areas. You start eating better. You become more productive and confident at work. You show more patience towards your family and colleagues. All because of a few push-ups once a week. That’s a keystone habit.
Making your bed every morning. It’s a tiny, almost irrelevant change. But studies show that this correlates with better productivity, greater well-being, and more willpower.
Willpower. This is the most important keystone habit. Studies show that willpower in children is the most accurate indicator of academic performance throughout their student lives. Even more accurate than IQ.
At an organizational level as well, keystone habits can have transformative impact. The book cites an example of how a worker safety program at Alcoa ended up not only improving safety, but also turning Alcoa into a profit machine.
How do these small, unrelated habits have such widespread impact? In Duhigg’s own words:
Small wins fuel transformative changes by leveraging tiny advantages into patterns that convince people that bigger achievements are within reach.
So what are your keystone habits at life and work?
2. Rewards and their Unintended Consequences (Drive)
Incentives are strange, powerful beasts. Whether it’s pocket money we give children for doing household tasks or bonuses our bosses give us for exceeding sales targets, incentives play a key role in driving us to perform.
I think I’ve been in the top five percent of my age cohort almost all my adult life in understanding the power of incentives, and yet I’ve always underestimated that power. Never a year passes but I get some surprise that pushes a little further my appreciation of incentive superpower.
Given the immense power of incentives, it becomes all the more important to design them right. If they’re even slightly misaligned, they can “damage civilization” (Munger’s words, a tad hyperbolic).
I read Drive earlier this year – an insightful book on the powers of rewards. The book also talks about the negative influences of incentives, if not designed well.
Incentives can drown out intrinsic motivation, even when you’re doing a task you enjoy. If you receive an incentive for doing something, you also receive a subliminal message that the task is not worth doing without the incentive. End result: incentives transform an interesting task into a drudge, and play into work.
[Tweet “Incentives transform an interesting task into a drudge, and play into work.”]
Incentives can only give a short-term boost. Like caffeine, they’re useful when a deadline looms. But beware the energy crash that will inevitably follow.
Rewards can become addictive. As Daniel Pink, the author, says – Yes, rewards motivate people. To get more rewards.
Incentives do have their uses, but only for process-oriented tasks. In fact, incentives for creative tasks can impede progress. They narrow your focus at the exact moment when you need broad thinking.
The book captures many more interesting and significant implications of an innocuous, innocent incentive.
3. Your MVP can be more “minimum” than you think (Lean Startup)
Most people working in the startup ecosystem are familiar with the Minimum Viable Product. The MVP is the most basic version of your product that still delivers your core offering.
It’s an important concept to keep in mind as you build a product. You don’t want to spend too much time building the first version, before realizing customers don’t want it.
I thought I’d understood the concept well. I congratulated myself as I built my first product in three months, found that people didn’t need it, and junked it. And again when I built my next product in four months, tested it with customers for three, and then pivoted it to its current form.
Then I read Lean Startup.
I realized then that I’d taken far too long to build my MVP. What’s more – so had everyone else I know. Why do we all take so damn long to build an MVP?
The reason is that we’ve got the concept wrong. You don’t need to ‘build’ an MVP. You just need to put it together.
What does that mean?
Let’s say you want to create a website offering fashion tips. You can launch in one day or less.
Buy a domain. 3 hours (the actual purchase will take 2 min. But I know you’ll agonize over names for the remaining 2 hours 58. And no, the name won’t matter.)
Build a landing page with Unbounce where people can ask questions or upload photos. 1 hour.
Run a small Facebook campaign publicizing the site. Or tell 10 friends, and tell them to tell 10 more each. That’s your test audience. 2 hours.
Thus, you can be up and running tomorrow! Even if you’re slow because this is your first time.
[Tweet “Your Minimum Viable Product can be more “minimum” than you think.”]
Many popular products of today hacked together such makeshift MVPs when they started. Check out the article in Further Reading for examples.
4. Pareto Principle & the Minimum Effective Dose (Four Hour Work Week)
Four Hour Work Week, by Tim Ferriss, is THE book to read on personal and business productivity. Unlike most productivity books and blogs, he eschews all the standard life-hacking methods (of the “shake your hips while you brush your teeth, to get some exercise” variety).
All he has to say about traditional time management is, “Forget all about it.”
[Tweet “All you need to know about traditional time management is, “Forget all about it.””]
Instead, he focuses on using the Pareto Principle, or the 80/20 rule. He uses this to introduce the concept of the Minimum Effective Dose – the smallest amount of effort for the most impact.
Whether your customers, your vendors, books you read, anything – choose the few that give you the most value, and forget about the rest.
He should know. He puts the Pareto principle on steroids. Sample this:
In his nutrition products business, he “fired” the least profitable 97% (!) of his customers, to instead focus on the 3% most promising ones and double his income.
He eliminated 70% of his advertising costs and almost doubled his direct sales income.
He discontinued over 99% of his online affiliates.
Eliminating the least value tasks and business relationships helped him free up his time to do more productive tasks. And achieve the Holy Grail of less work but more profit. That’s how you do productivity!
Side note: In his follow up book, The Four Hour Body, Ferriss uses the concept of the Minimum Effective Dose to illustrate how to become more healthy. Check that out too.
One skill I tried to build last year was negotiation and persuasion. I read three great books on the subject. I’m still to have the investor conversations where I’ll use this skill, so I don’t know how much they’ve helped!
But one concept that has stuck is that of the BATNA – the Best Alternative To a Negotiated Agreement. In simple terms, the BATNA is your fall-back option in case talks fall through.
Your BATNA is tantamount to your leverage in the negotiation. It works in two ways.
1. The better your BATNA, the more leverage you have.
Let’s say you’re negotiating the sale of your house with a prospective buyer. Your alternative to this is to (a) rent it out; (b) sell it to a land developer to make a parking lot, and (c) live there yourself. If option (b), say, is the most attractive of these, then that’s your BATNA. The value the land developer offers you should form the baseline for the negotiation.
As long as the buyer’s offer is higher than this, you can reduce your price (after making a big deal of it, of course).
Far more important though, is that if the buyer pushes you below this BATNA, you can and should refuse. This is difficult. We tend to over-invest emotionally in a long negotiation. But with this hard stop in mind, you can overrule your emotions and walk away.
2. The worse you make your opponent’s BATNA, the more leverage you have.
Improving your BATNA gives you leverage. Straightforward. But there’s a more interesting insight here. You can improve your leverage by worsening your opponent’s BATNA.
Let’s say you’re the prospective buyer in the above transaction. You know that your seller is holding out because of the safety net of the land developer.
So, you remove that safety net. For example, you could sell one of your own other properties to the land developer, so he’s no longer making an offer to your seller.
By removing the most promising alternative your seller has, you’re weakening his leverage. And strengthening your own considerably.
[Tweet “Show your opponent he has a lot to lose from breaking talks, and he’ll be surprisingly pliable.”]
6. [BONUS] Focus on strengths, not lack of weaknesses (The Hard Thing about Hard Things)
By default, we are all risk averse. In fact, Loss Aversion is one of the strongest, most deep-rooted cognitive biases there is, squirming deep inside our brain’s reptilian core.
This loss aversion manifests itself in several ways. Holding on to bad-performing stocks in the hope of a turnaround. Not making bets because of high risk, even if the reward is much higher.
In the corporate environment, this results in a preference for well-rounded candidates. We tend to choose such people over others who are spiky in some areas, but middling in others. We choose average programmers with great communication skills over 10x programmers who are introverts. We reject uber-salesmen just because they don’t know much about tech.
As Ben Horowitz says in this book, that’s the exact wrong approach. That’s not how great organizations work. Instead, such organizations look for excellent candidates, who are in the top 1 percentile of their roles. Never mind that they’re not good at other things.
“Identify the strengths you want, and the weaknesses you’re willing to tolerate.”
Your Product team should have the best programmers. Even if their communication skills could be better. For sales, hire the best salesmen out there, even if they’ve not worked in your industry before.
We also tend to paper over the weaknesses and focus on repairing them. Again, not the most optimal approach. Instead, focus on honing your employees’ strengths. Plug the weaknesses (If they’re important. They often aren’t.) by hiring superstars in those areas.
[Tweet “Identify the strengths you want, and the weaknesses you’re willing to tolerate.”]
So, those were the books and ideas that captivated my thinking in the last year. Here’s to many more brilliant ideas and books in the new year. Of course, you’ll be the first to know of any great books I find (sign up here to receive regular updates!).
A few weeks ago, my wife and I were in Galle, Sri Lanka for a much-awaited vacation. We chose a villa with great reviews on TripAdvisor. It seemed a decent place. A little far from the main town, but the hosts were quite friendly.
But we couldn’t get much sleep any of the nights we stayed there, because our room had bedbugs.
After we came back from the trip, we made sure to rate the place. We left not one, but two ratings (one each from my wife and me). Both of them were 5 stars.
Did we enjoy getting bitten by bedbugs?
I was surprised too. Not just at my own rating, but at other ratings on TripAdvisor too. This place was one of the most recommended ones in Galle!
So how did this happen? How did I – and all the other guests – rate inferior customer service so highly?
Do ratings work?
The prevailing wisdom is that ratings work. That’s why they are everywhere. When you open an app on your Android phone, it asks you to rate it on the Play Store. Complete a ride on Uber, and you have to rate your driver. Order something from Amazon, same story. Open your inbox after a long vacation, and what’s the first email you see? A message from either your airline or hotel, requesting you to rate your experience.
I’ve always found the act of rating quite empowering. The equation is simple – if you can rate a service provider in public, he has every incentive to ensure that you get great service. Right?
Well, after that incident in Galle, I realized that ratings may not result in better customer service. In some situations,they may be worsening it.
Wait, how does that make sense?
I’ll explain. But first, let’s agree on two key facts about ratings.
1.Ratings have an impact on service providers.That’s one reason they’re ubiquitous. Drivers on Uber do get blacklisted for low ratings. Top-rated hotels on TripAdvisor do get ten times as many bookings as lower-rated ones.
2.Customers know ratings have an impact.This makes them capricious (this Verge article calls them – us – entitled jerks). To see this, you only need to see a few app reviews. Sample these ratings on Circa (an app that used to provide summaries of important news):
Ratings are supposed to highlight how good an app is. But no, sometimes you get a 1-star for an innocuous review request.
This customer fickleness is not just an app store phenomenon. As the Verge article says,
We rate for the routes drivers take, for price fluctuations beyond their control, for slow traffic, for refusing to speed, for talking too much or too little, for failing to perform large tasks unrealistically quickly, for the food being cold when they delivered it, for telling us that, No, we can’t bring beer in the car and put our friend in the trunk — really, for any reason at all, including subconscious biases about race or gender.
Please the customer, and hope for the best
The fact that we wield a strange amount of power and know it, turns upstanding, proud cab drivers and B&B hosts into fawning, obsequious and servile slaves. You can’t jilt or offend a customer in any way. A single misstep, and you get a 1-star rating. Not a 4- or 3-star. Your last five customers may have given you 5 stars, but this single rating could put you out of business. In New York, Uber delists drivers from the platform if they go below a 4.5 star average!
So what is a service provider to do? Provide honest-to-God great service.And hope that nothing gets screwed up.
But there’s an easier way.
The honest approach is hard, time-intensive and expensive. And it’s subject to random whims of the entitled customer.If a customer expects Hilton service at McDonald’s rates, you’re bound to get 1 star.No matter what you do.
But there is an easier, quicker and more inexpensive way. One of the oldest psychological tricks in the book.
Dr. Cialdini, the author ofInfluence, calls this trick “Liking – The Friendly Thief”. Studies show that if you spend more time with a person, you end up liking her. And if you like a person, you tend to favor her in your dealings.
At a certain level, this is obvious. But that doesn’t make it any less powerful. Malcolm Gladwell cites a great example of this in Blink. Patients don’t file lawsuits when they suffer shoddy medical care, if the doctor is polite. They only file when they feel the doctor mistreated or ignored them.
“People just don’t sue doctors they like.”
So, to get a great rating, all you need to do is: (a) smile a lot and appear likeable; and (b) talk a lot, to create a human connection and familiarity.
Tried and tested. Once you get to know the service provider, you’d be a stone-hearted reviewer to leave anything less than 5 stars.
Nice host + bad customer service = 5 star rating
That’s what happened to us in Galle. Even though I was aware of this cognitive bias, I was powerless to counteract it.
The owner received us with great cheer. He chatted with us for hours. Always smiling and laughing (even when I didn’t crack a joke. And I’m not that funny anyway). I learned a lot about his life. I commiserated on his past troubles, and lauded him on his recent turn in fortunes.
My room still had bedbugs.
But my wife and I didn’t complain. Who can tell off such a nice guy? And when he requested us to leave two ratings on TripAdvisor, how could we refuse?
Talk more. Do less. Get 5 stars. Repeat.
This is just one small episode. But it sets in motion an insidious feedback loop, which could result in worsening customer service over time.
Customer give a 5-star rating despite bad customer service.
Service provider sees this as validation of his strategy. And becomes more chatty, more fawning.
Soon, if he’s smart (our guy was), he realizes there’s no return on actual customer service. It’s much easier to smile and bluster, than it is to clean the room. Over time, he’ll become more talkative, and truecustomer service will degrade.
Woe betide the unsuspecting traveler when that happens.
Thus, ratings may have an impact that’s thepolar opposite of your intention.
How do we break this loop?
Now, I’m sure you want great customer service. So, how can we break this loop?
Just being aware of what’s happening is not enough. You’ll only feel worse, as you continue to give 5-star ratings like a powerless lab rat.
The only way to break this cycle is to have a system of multiple ratings on different attributes, instead of one single unidimensional one.
Why would that work? For three reasons:
It would force objectivity.If you’re rating your stay at a B&B separately on Cleanliness, Quality of Food and Friendliness of Staff, you’re more likely to question the halo around your host’s head, and distill your cheery feeling into its components
It would give the service provider the right feedback on how to improve.
Ratings are here to stay. Let’s make sure they actually improve customer service. Rather than slowly turning us into smiling zombies.