Get Out the Door

“A good plan, violently executed now, is better than a perfect plan next week” - George Patton

A great strategy is something to behold. When Elon Musk references back to his original master plan for Tesla, it’s easy to become stuck in awe. But for every master plan flawlessly executed are countless elegant strategies that never see the light of day. And for more than 9 of 10 startups that ultimately IPO, the strategy and business model they created in their first powerpoint deck changed dramatically by the time they reach the public market. Lyft spent years as a platform for carpooling before realizing that managing the actual ride itself was the way to drive the business forward. Netflix stumbled early on in online video rental before realizing the only way to get to market in a pre-broadband era was to mail DVDs to customers. And Twitter started in podcasting, nowhere close to social messaging at all.

The reality of innovation is that the concept we have of how customers will value our products and services is rarely the way they actually do look at our products when we launch. And unfortunately, without discovering how the world actually looks at our offerings, it’s possible to find teams spending years building the wrong things.

Specifically, if you don’t get your product out the door, a beautiful strategy can find itself with three very common failings.

Problem 1: Nobody Wants the Product You’re Building

The reality is that there is a strong possibility that no one wants your product (in the form it’s built or at the price point required to deliver it). In the bubble that is pre-product release, it’s easy to fool yourself into believing otherwise. Until you can force customers to pay for your product - whether that payment be in the form of attention (minutes spent on a website) or the payment comes in cash form - it’s impossible to know for certain how many people value your product.

The most extreme example of the delusion that can exist inside the pre-release bubble can be seen in the Segway. When Dean Kamen designed the “personal transportation device that would revolutionize the world,” hundreds of investors were willing to believe that Kamen’s self balancing scooter would change the world. They saw a big market, a novel technology, and simply heard the cash register ring. After years of setting expectations high, the market spoke for itself. No one wanted the product.

Unless you have the consumer intuition of Akio Morita or Steve Jobs, odds are the only way of knowing that you’re not wasting your time building something that customers don’t want. Hence, it is key to get early product out there in the hand of customers. And if no one wants your core offering, a beautiful strategy matters for nothing.

Problem 2: The Solution Won’t Scale

For innovators (especially in enterprise software) it can pose a severe challenge if the solution isn’t scalable. It’s immensely easy to think of a complex product that can solve an intractable problem. If you can only crack the technical challenge, customers would pay enormous sums of cash for the solution. “Wouldn’t it be great if I could provide the perfect advertisement for a Big Mac directly to an Apple Watch as you pass by a new location?” Sure. And McDonald’s would likely pay handsomely for such a solution.

This becomes the trap. Too often, innovators turn towards these initial customers as validation that a market exists and can be penetrated. But much of the challenge of building a business becomes repeatability and scale as technical feasibility. In the early days of Netflix’s operations, Reed Hastings envisioned distributing streaming media via the internet. Today, it’s clear that was the future. At the time, it was insanity. Hastings quickly learned that only the Silicon Valley elite had enough bandwidth to stream a movie. He had to abandon that plan for nearly a decade and turn to mailing physical DVDs in order to build a business with enough scale to be viable.

One customer does not make a business. Regardless of how much that customer is willing to pay.

For companies looking to avoid this problem, getting out the door fast helps ensure a few things. First, it forces them to focus on things that many people value. It might take 3 years to build the perfect product for Walmart. When you take it to the next customer, you might find that 95% of the features Walmart required aren’t needed. Second, it forces you to sell the dream instead of the solution. Invariably, if you’re moving to market fast, you’re going to sell the roadmap and vision - not what’s there. Having a hundred conversations about the vision will help you hone in on the features that are most important to solving customers problems. That way, when you do get out the door with a product, it will be with the right one.

Problem 3: The ‘Perfect Business Model’ is All Wrong

Modern business strategies often entail subsidizing one or more products or services in order to build a different revenue stream. This is the case with almost every multi-sided platform product. Facebook provides a free service to its users in order to build its advertising business for marketers. Box offers customers free storage for their personal data in order to make the value proposition of selling secure storage to its corporate customers more appealing. 23andMe subsidizes running DNA tests for individuals in order to build a vast database of genetic information that can be used to develop drugs.

These business models can serve as the foundation for wonderful businesses. Unfortunately, they presuppose a certain level of desirability of the underlying products by different constituents. For instance, if your business is based on reselling data that consumers opt to offer you; you better be certain that consumers value your product enough to agree to the terms and conditions. If they don’t, then your model has to evolve.

For many innovators, changing these strategies can be easy. It could just be a matter of offering cash incentives to a set of customers. It could turn a multi-sided platform strategy into an outright technology sales approach. But until you have product in the hand of customers, you can’t reasonably evaluate your strategy.

Core to determining which direction to move in, is getting out the door.

There are two countervailing forces in product development; the desire to ship product that can best satisfy customer needs and the desire to ship product quickly. It’s critical that, in an age where rapid iteration is easier than ever, teams don’t let the first force - the desire to ship the perfect product - get in the way of getting a good enough product out there in the world to learn what will work and what won’t. Ship fast. Ship often.

It's Harder to Say Yes

This week a colleague and I hosted dinner for a group of VCs in Washington DC. As is often the case, the conversation turned “inside baseball” very quickly. We chatted about down rounds, entrepreneurs’ expectations, newfound pressure from LPs, and the now striking (and somewhat scary) disconnect between the private markets and the public markets. It was very doom and gloom. And very reminiscent of all the conversations I’d just finished having in the bay area before heading east.

That was until one of the investors at the table who’d been relatively quiet to that point chimed in. Normally, folks would all continue talking passed or over each other. But since this particular investor happened to be one of the better enterprise investors on the East Coast, people quieted down.

“Look,” he said. “In this industry, you’ll always be able to come up with reasons to say no to an investment. The hard part is coming up with the right reasons to say yes.”

The conversation kept moving along, as conversations do, and we eventually got to more traditional dinnertime subjects. But since our conversation earlier this week, the comment has sunk in and resonated. Its truth couldn’t be more obvious to me. There are a near infinite number of reasons why startups can fail. That number compounds as investors ask themselves why, even if the startup succeeds, they might fail to make money on their deals.

Every time we look at businesses, it’s easy to spot these risks and argue that a deal doesn’t make sense. In fearful times like these, we’re biased to see these potential risks first. We’re like moths to flames. But the reality is, most of those issues are there in greedy times as well. The key is to avoid both irrational fear and irrational exuberance and come up with the right reasons to say yes.

This is something I’m going to be focused on for the next few months; forcing myself to always ask how a business might succeed instead of talking about why it might fail.


Image Courtesy of Alexandre Dulaunoy

How Big Data Is Changing Disruptive Innovation

Much fanfare has been paid to the term “disruptive innovation” over the past few years. Professor Clayton M. Christensen has even re-entered the fold clarifying what he means when he uses the term. Despite the many differences in application, most people agree on the following. Disruptive innovations are:

  1. Cheaper (from a customer perspective)
  2. More accessible (from a usability or distribution perspective)
  3. And use a business model with structural cost advantages (relative to existing solutions)

The reason these characteristics of disruption are important are that when all three are present, it’s difficult for an existing business to respond to competition. Whether a company is saddled with fixed infrastructure, highly trained specialist employees, or an outmoded distribution system, quickly adapting to new environments is challenging when one or all of those things becomes obsolete. Firing hundreds of employees, upsetting your core business’ distribution partners, writing off billions of dollars of investment — these things are difficult for managers to even contemplate, and with good reason.

Historically, the place we’ve looked for hints of oncoming disruptions has been in the low end of the market. Because disruptive products were cheaper, more accessible, and built on new technology architectures, they tended to be crummier than the existing highest-end solutions. Their cost advantage allowed them to reach customers who’d been priced out of an existing market; Apple originally made a computer that was cheap enough for students to learn on, a population that wouldn’t have dreamt of purchasing a DEC minicomputer. Sony famously made the transistor-based television popular based on its “portability.” No one knew that you could reasonably do that prior to the transistor. New technologies, combined with business model innovation, provide the structural cost advantage necessary to take large chunks of the market over time.

But if you return to the definition above, the fact that low-end entry was typical of a disruptive approach was was never core to the phenomenon. Instead, it was a byproduct. Why? Because any new entrant is hard pressed to deliver superior value to a mature market, where products have been refined over decades.

But although the low-end approach was pretty common, it wasn’t what was holding incumbent firms captive. It was their own cost structures and their focus on driving marginal profit increases that kept those companies headed down the wrong paths. As long making the right decision on a short-term basis (trying to drive more value out of outdated infrastructure)  is the wrong decision on a long-term basis (failing to adopt new technology platforms), CEOs are destined to struggle.

Unfortunately, the focus on the low-end approach of disruption is actually clouding our ability to spot the things that are: cheaper, more accessible, and built on an advantaged cost structure. Specifically, it appears that data-enabled disruptors often confound industry pundits. To get a sense for the point, just look to a few highly contested examples.

Is Uber disruptive? The wrong answer would be to say, “No, because their first product started in the high end of the market.” The right answer would be to acknowledge that the platform they ultimately launched allowed them to add lower cost drivers (in the form of UberX) and offer cheaper, more accessible, transportation options with a structural cost advantage to both taxi services and potentially even car ownership. The convenience of the app is only the most obvious, and easiest to copy, factor.

Were Google’s Android phones disruptive to Nokia? The wrong answer would be to say “No, because the initial smartphones they launched were superior in feature quality to Nokia’s own phones that dominated the global landscape.” The right answer would be to acknowledge that the approach of creating an ecosystem of application development atop its platform allowed them to build far more comprehensive solutions, that were (on the whole) cheaper, more accessible, and structurally cost advantaged over Nokia.

Is 23andMe potentially disruptive to pharmaceutical companies? The wrong answer would be to say, “No, because they compete in completely different verticals.” One in ancestry and the other in drug development. The right answer would be to acknowledge that 23andMe has a vast amount of data that could enable them to start developing drugs in a cheaper, more accessible, and structurally advantaged model.

In every one of these examples, the ultimate end is disruption. In every one of these examples, incumbent managers have a short term incentive to ignore the challenge — making best use of their existing infrastructure. Taxi companies tried to leverage regulation to preserve the value of their medallions and drivers. Nokia tried frivolously to protect its closed ecosystem and preserve employment for their thousands of Symbian focused staff members. And you can be certain that Merck, Pfizer, and Roche have strong incentives to make the best use of their high-end R&D functions before embracing the radically different path that 23andMe might take.

And over the long term, each of these short-term decisions could lead to failure.

The conversation misses that something new is going on in the world of innovation. With information at the core of most modern disruptions, there are new opportunities to attack industries from different angles. Uber built a platform in a fragmented limo market that let it come into transportation and logistics more broadly. Netflix captured your eyeballs through streaming video and used the data it had to blow up the content production process. Google mapped the world, and then took its understanding of traffic patterns and street layouts to build autonomous cars.

There is no doubt that disruption is underway here. These players create products that are cheaper and more accessible than their peers. But it’s not necessarily starting at the low end of the market, it’s coming from orthogonal industries with strong information synergy. It’s starting where the source of data is, then building the information enabled system to attack an incumbent industry.

It’s time for executives, entrepreneurs, and innovators stop quibbling over whether something satisfies the traditional path of disruption. Data-enabled disruption may represent an anomaly to the existing theory, but it’s here — and it’s here to stay. The waste laid to the taxi industry by Uber is example that the new solution had extraordinary cost advantages and that they couldn’t respond. The new questions should be:

  • “How can you adapt in the face of this new type of competition?”
  • “How do you evaluate new threats?”
  • “What capabilities do you need and where do you get them, when data is a critical piece of any new disruption?”

To succeed in this new environment, threatened businesses need a thoughtful approach to identifying potential threats combined with the will to make the right long-term investments — despite short-term profit incentives.

From Active to Passive Marketplaces

Marketplaces are powerful things. Some of the world’s most successful businesses have been built coordinating supply and demand. Southeby’s may be the oldest today, dating back to 1744, but the internet has led to a cambrian explosion in the number of companies that allow buyers and sellers to come together: eBay, Airbnb, Lyft, Etsy, Upwork, Lendingclub, DogVacay, and the list goes on and on.

But the nature of marketplaces seems to be changing a bit. In the early days of the internet, marketplace companies often served as virtual bazaars. Sellers would create profiles and list products while buyers would come and search for their desired wares. They’d both select their products and their sellers. I would characterize these as “active” marketplaces. In other words, marketplaces where participants take active roles in the coordination of commerce.

Today, however, marketplaces are doing more than facilitating commerce. Namely, they’re streamlining experiences. This streamlining of experiences is not surprising. Every day, we generate 2.5 Quintillion bytes of data. It’s constantly growing. In fact, it’s growing so fast that more data has been generated in the last 2 years than over the course of the rest of human history combined. And all that data can be used for optimization. It can be optimizing the price of a product (as Uber does with surge pricing). It can be optimizing the professional selected to service your needs (as Handy does based on available schedules). It could be optimizing the workflow for suppliers (as Crunchbutton does to bring on-demand delivery to suburban markets).

The new marketplaces offer buyers and sellers the same access to commerce as their forebearers but rely on either algorithmic coordination of activity or business model tricks that help abstract away complexity. Instead of actively searching out the right person to provide you with a good or the right person to sell to, that layer of coordination is automated. These marketplaces become far more passive for participants. Instead of thinking, you simply push a button on your phone, beam a signal into the ether, and wait to receive your instructions; “Wait on that corner,” “Pick up this package,” or “Translate this document.”

If nothing else, the transition makes sense. As a species, we relish convenience. Layer any friction into the process of getting something you want, and you might no longer feel that the proverbial “juice is worth the squeeze.” While the early internet enabled coordination at any level, today’s marketplaces enter the fray to streamline that coordination.

As these passive marketplaces emerge and reduce the complexity associated with using a given service, they are also starting to disrupt many existing players. Etsy’s optimized tools for small merchants may not provide access to a marketplace the size of eBay’s, but they are easy enough to use to capture many former eBay sellers. 99designs doesn’t provide the variety of services that can be obtained on Upwork, but it’s a much easier way of finding a design you want than going back and forth with a potential service provider before accepting a bid. And Postmates may only do a subset of what Taskrabbit used to provide, but the fact that I don’t need to coordinate the delivery of anything with individuals has me leveraging the service far more often.

Over the next decade, I believe we’ll see this shift continue. Whether it’s passive marketplaces to deliver standardized goods or service marketplaces (like Uber, Postmates, Handy, etc.) or passive marketplaces that streamline the act of getting non-standard goods (99designs, Crunchbutton, etc.), the more the marketplace itself can reduce complexity for buyers and sellers, the better positioned it will be. Certainly, not all transactions will shift from active to passive marketplaces. But my guess is the portion of eCommerce that shifts will be dramatic.

After all, we all love convenience.

Five Predictions for 2016

Every year, around this time, I try to update my thinking about the world. What’re the most important trends that are going to impact us over the next 5-10 years? On an annual basis, the trends don’t necessarily change year to year. And they’re never comprehensive (mostly because they’re limited by the small goopy mess residing between my ears) -- but for the last 5 years or so, I’ve tried to be systematic this time every year about what’s coming.

Going into 2016 I wanted to make these predictions public. And to go a step further, I also want to follow each with a controversial implication associated with each prediction. I may be far from right or I may be dead on. The one thing I can guarantee is that I believe them to be true and that most investors and innovators wouldn’t agree with them off the bat. If they weren’t controversial, they wouldn’t be interesting.

1. “Developer Tools” will become more interesting than SaaS

Application development has long been a story of hundreds of engineers trying to understand complex workflows and building monolithic services to automate processes. Whether it was something as simple as Excel (building in its own charting and visualization tools) or it was something as complex as SAP (building in calendar management, document rendering, invoice management, etc.), the world of software was dominated by these types of comprehensive solutions.

Today, however, it’s becoming easier than ever to piece together best of breed components in the process of application development. Through APIs, data can migrate easily between clouds allowing developers to rely on other vendors like Google for predictions, Twilio for communications capabilities, or Box for document hosting and rendering. And with these micro-services focused on simplifying the complexity of software development gaining traction, the capabilities of each will improve - increasing the divide in quality between the off-the-shelf component and the build-it-yourself approach.

Going into 2016, I think this microservice conversation is going to come from the periphery to mainstream. And what’s more, my guess is this will be the year that folks realize the next great “IT companies” are going to be developer focused, not CIO focused. All the tailwinds are there. IT organizations are transforming to groups responsible for stewarding digital transformation (whether or not they have the requisite skills). SaaS isn’t interesting anymore, it’s the technology that will enable companies to build new experiences for their customers. As such, the most interesting IT companies in the world will be building the tools to simplify development and streamline assembly. If you’re not convinced, just look at the waves Slack, Atlassian, and Twilio are already making along these lines today.

2. People will start to obsess over “Identity” instead of “Messaging”

Over the last few years, an incredible amount of attention has been paid to messaging and marketing automation services. Effectively, anything that can help a business or an individual reach out to the audience they care about. My observation is that in most of these situations, the subject of communication is known and the only thing that changes is the medium through which the message is delivered.

The stickiest businesses of the last few years have been the ones with strong network effects derived from indirect relationships; value conferred to users by understanding who someone is that they wouldn’t already know. The businesses that create this value tend to offer some sort of solution that captures identity. LinkedIn knows who you are at work. Facebook knows who you are in general. Netflix knows what sort of content you enjoy. Amazon knows what you like to buy.

In 2016, I think that people will start to realize the communications layer of the IT ecosystem is just the front end. Sure, you can add incremental platform capabilities - enabling app development and incremental integrations. But the thing that is going to drive truly differentiated businesses is going to be an understanding of identity. Without that understanding, it’s virtually impossible to create strong recommendations that simplify users lives and tie people into an ecosystem.

For investors and innovators, I think we’ll see some of the darlings of enterprise chat, consumer messaging, and marketing automation struggle to do big things - while businesses and individuals start doubling down on solutions that aggregate information about users and maintain identity.

3. At least one well-funded VR Company goes under, in an otherwise successful year

I am a big believer in the potential of VR. And I believe that 2016 will be a successful year for VR.

However, I also believe that people over-estimate how many early adopters will shell out hundreds of dollars to plug a headset into a small computer and walk around their living room alone. We also estimate how easy it will be to translate content designed to display on a small rectangular screen sitting meters away from our faces to lenses that effectively touch our eyeballs.

My prediction is that in 2016, we see the first profitable VR companies emerge - likely creating short form content for the small number of consumers out there. I’m skeptical, however, that these companies will be the well funded venture backed startups we all know. Instead, I think that (just like mobile gaming) there will be some simple content that create early hits for specific studios and that enables companies to keep producing more and more content. The early revenues will be low, but it will get the ball moving. If I had to make a bet on where early traction would come from, my guess would be early winners would come from puzzle apps. Think Myst for VR.

But while I do believe we’ll have at least one VR content company at a 100M run rate by 2020, I think we’ll see a bunch more corpses first. In particular, while my guess is we’ll start to see real consumer traction in 2016, we’ll also see the first well funded startup collapse. Too many of these companies are investing ahead of the market, burning cash, and creating expensive content targeted at a mass market… in an industry that will be populated by early adopters for some time.

4. Cleantech will become mainstream again

Over the past year, I’ve been surprised at how many companies have built interesting businesses based on sustainability. Whether it’s solar, water conservation, or food production, the opportunity is there. The explanation can probably be found in the dropping cost of the hardware that enables these more sustainable businesses. Sensor costs are dropping, remote monitoring is improving with the use of satellite imagery and drone reconnaissance, and solar cells and EVs are starting to hit a point of parity from a cost perspective. Yet with all of the innovation that is occurring, every entrepreneur I meet strategically avoids talking about “Cleantech” wherever possible. After a decade of getting burned, that makes sense.

But my guess is that 2016 is the year investors realize that 10x improvements in resource efficiency are within grasp in a lot of places. Whether it’s cutting emissions by 1/10th through Tesla batteries and solar cells (Tesla and SolarCity are “clean”), reducing gas and infrastructure costs through ride-sharing (Uber is “clean”), improving revenue by keeping returned goods from going to landfills (Optoro is “clean), or reducing the cost of food by 10x by reimagining the production process (Impossible Foods is “clean), my guess is that 2016 is the year many investors realize that “Clean” is often just business.

(Consequently, investors may also realize that the one fund that had confused “Clean” with ridiculous technology moonshots subsidized by the federal government may have been the one that gave “clean” such a bad name)

5. The most exciting tech products of the year will come from the tech giants (Google, Facebook, Amazon, Apple, and Microsoft)

For years, I’ve always looked to young companies to offer cutting edge innovation that truly wows me. Even if the technology challenges aren’t enormous, I’ve been consistently amazed over the last decade by how deeply companies like Facebook, Twitter, Uber, Airbnb, and Oculus have impacted the way I look at the world.

But as I look out, the most interesting technological shifts underway - innovation in things like artificial intelligence, robotics, telecommunications, machine vision, quantum computing, and the like - are all being driven by the big technology companies with different types of leaders. Larry Page, Jeff Bezos, and Mark Zuckerberg don’t care too much about Wall Street’s expectations. They care far more about using their massive sources of cash and massive user bases to keep their businesses deploying the types of technologies that will change the world. And the amazing thing is that it’s working.

I am sure that 2016 will surprise me. But my intuition is that while we’ll see some unbelievable tech-enabled services pop up in 2016, the most interesting technological innovations of the year will come from the giants.


Photo Courtesy of Jeff Golden

2016 Could be the Year of the Market Correction (That Doesn’t Matter)

I spend a fair bit of time chatting with people about the “bubble.” It’s an interesting enough subject that I’ve even spent some time researching its legitimacy. But the closer we get to 2016, the more I feel that it doesn’t matter one way or another. If we’re on the precipice of a correction, what’s really going to change for the average entrepreneur or investor?

Any self-respecting business school professor would bite my head off for claiming nothing will change. At the altar of the free market, it’s clear that the startup ecosystem will suffer with a contraction. Decrease demand (M&A and IPOs) for these businesses and supply will have to contract (number of businesses being started). And it’s not just academics, LP’s - the pension funds and family offices that provide the capital the startup ecosystem relies upon - also lament the coming correction. For LPs, they look at Cambridge Associates’ VC benchmarking index and realize that fund vintages in times of contraction are the worst. For LPs, contractions mean that average returns will go down. To both sets of onlookers, any change in 2016 seems like one that matters. And I can certainly sympathize with their concerns.

But the fact of the matter is that inside the ecosystem, not much should change. Even in downturns, entrepreneurs will be building great businesses. And when entrepreneurs build great businesses, only the foolish investors shy away due to exogenous factors in the market.

While we spend a lot of time talking about the “bubble,” no conversation about the impact of a correction can exist without talking about entrepreneurs. I started my first web business before I was 20. The last one sucked me in so quickly that I was told I fell off the face of the Earth. At no point in the process of spinning up either endeavor was I thinking about whether the market was right to start a business. It was always just a question seeing a problem worth solving and setting out to do so. Either I was going to build something successful that can sustain itself or I’d fail.

Venture capital is an industry built around supporting entrepreneurs. For individual VCs, what matters most is finding a great company and doing everything possible to help them. While we might think about VCs as portfolio managers, the fact of the matter is that most VCs manage a tiny number of investments. Corrections certainly impact the entry prices VCs pay, the amount of time they may have to hold an investment, and the multiple that a VC will receive on exit - the fact of the matter is that runaway winners typically define the returns of a given fund. So the only relevant question for VCs should be, will these runaway winners be founded in a downturn. If they are, individual VCs will be hunting and investing.

We’ve already established that entrepreneurs will set out to build companies regardless of the macro environment - because the good ones aren’t thinking about optimizing valuation at their seed round, they’re thinking about tackling big problems. Consider Airbnb and Uber. Both companies were founded in the height of the recession. Both companies will define the returns of early investors’ portfolios. It might be easier to get an outsized return through some extraordinary M&A in a frothy environment, but if we assume that there could be the next Uber or Airbnbs popping up over the course of this upcoming correction, we can be sure there will still be great opportunities for individual VCs to swing for the fences.

So where does that leave us?

2016 might very well be the year of a market correction. We might see a contraction in funding, a deflation in prices, and even a handful of “unicorpses.” But the more I think about it, the less I feel any of this matters. With improvements in machine learning, clean energy, and robotics, great companies will be built over the next few years. I’m going to try and spend more time thinking about these things (that matter) and less time thinking about the oncoming correction (that doesn’t).

Making Models Work for You

When you’re out there building a business, the last thing you want to do is waste time. Between building product, finding new customers, and the constant search for qualified new employees, the last things on most young executives’ to-do lists is updating excel models. In my startup experience, budgeting and planning was always characterized as something big companies do after they lose their edge. Not something to waste time on in the early days.

The reality isn’t so clear cut. Wasting time in spreadsheets is as bad as wasting time anywhere. But managing to the numbers and the excel wizardry that comes along with it is often what separates great startups from failed ones. The challenge for entrepreneurs is that - more often than not - people jockeying the spreadsheets aren’t doing it in a useful way. Instead of trying to expose underlying business risk, challenge assumptions around hiring plans, and managing cash, they’re trying to put together pretty charts and tables to placate their managers and investors.

When it’s done right, modeling helps you expose critical business issues and manage them. It tells you what to monitor, what to ignore, and where the threats lie. When it’s done wrong, it keeps your eyes closed to larger issues, it confuses your advisors, and it wastes your time.

Knowing how to make it count can be immensely valuable. So here are a few things that keep me focused on the useful stuff when I’m playing around in Excel, in case it’s helpful.

3 things to strive for when jockeying the numbers.

Know the critical business questions you need to answer

Modeling is useful because it sheds light on what could be. If you’re building out a budget for your next year’s operations, modeling is meant to help you manage your cash. If you’re building a sales plan, it’s meant to help you plan for hiring. To get any use out of the exercise, you need to know how the model will help you make decisions. If someone asks for a projection and you don’t understand how it could be useful, dig deeper. Push them to articulate what the key business question is and how the model will help you make a decision. If you have halfway decent investors, managers, or advisors, there will be a point to the exercise. And if there isn’t a key business issue on the other end of the question, ignore the request.

Build in the complexity you need to manage

If your models don’t reflect reality in the slightest, they’re not useful. My favorite example of this comes in the form of sales planning. Every sales manager under the sun knows that salespeople aren’t productive on day one. But for some reason, early sales managers will consistently turn in hiring plans and sales projections that don’t account for ramp time appropriately. The decision to remove the ramp might simplify the model, but it makes it entirely useless in helping you hit your numbers. Whether it’s forecasting deliveries with no buffer or looking at working capital costs, you need to build in some complexity for models to help you make actual business decisions.

Have an action plan for follow-up in mind

A model helps you build an opinion. It’s not all seeing or all knowing. Have an action plan for follow-up from the beginning. Make sure you use the numbers to hone your perspective and you take action accordingly. If you’re just putting numbers together for the sake of putting numbers together, odds are you’re wasting your time.

3 things to avoid when diving into spreadsheets.

False Precision

If you have an analyst with any sort of banking or consulting background, they’re likely to get “cutsie.” They build all sorts of dynamic capabilities into their models and layer on tens or hundreds of assumptions. The challenge is that when all of these unknowns enter a model, any one of them can lead you astray. You need the complexity in the model that you know exists; things like sales ramp times. But don’t fool yourself into thinking that an assumption is the same thing as a known. It’s not. And any unknown can throw you off. Especially the ones you layer in and don’t keep in mind.

If false precision is rampant, it’s partner in crime is most certainly insensitivity. Even when people know they have a number of assumptions, it’s rare to see people systematically see how sensitive their business is to a given assumption. For instance, whenever my CEOs are going through a financial planning process, I force them to change their assumptions around cash collections. Whatever their policy, it’s not set in stone. And modeling out sensitivities around something so simple often shows them just how valuable it can be to their business to collect payment up front - even at the cost of a substantial discount. When you simply call out an assumption in a table, but don’t test your business’ sensitivity to whatever number you plug in the hole, you’re missing a valuable opportunity.

Unrealistic Expectations
Finally, the killer of all models is unrealistic expectations. As they say, garbage in, garbage out. Too often do we just plug unrealistic numbers into our spreadsheets to placate stakeholders. When that happens, we cheat ourselves of whatever insight they might hold. Push yourselves to put good stuff in whatever model your building. Otherwise you’re just wasting time.
In young businesses, your time is precious. But spending some of that precious time planning can be a wonderful thing. Just don't piss it away jockeying numbers for no reason. Make a plan. And use it to help you make a decision.

Photo Courtesy of Microsoft Sweeden

Good Guys Finish First

First off, I hope everyone is having a wonderful Thanksgiving and spending time with loved ones, away from spreadsheets and email.

This week I had a conversation with Mark Lurie, the CEO and founder of Lofty. But more importantly than his current title or company, Mark is a good friend and has been for many years. Getting on the phone felt great. Unlike many conversations I have with people in the technology world, a conversation with Mark is never transactional. He’s genuinely interested in hearing what others are up to, can appreciate concepts and conversation outside his areas of expertise, and always has thoughtful advice to offer. Basically, he’s a pleasure.

So naturally, when I hung up the phone, I thought to myself that he remains a friend that I’d do almost anything to help. He hasn’t really ever asked for anything. But if it did come down to it, I’d be there.

Over the past few days, I’ve been thinking about that interaction and the feeling it left me with a lot. As I do, it keeps bringing me back to a lesson a professor of mine once, Willy, imparted on me. He would regularly remind us that “a career has a very long tail.” 20 or 30 years down the line, someone you’d never expect might make all the difference to you. Whether professionally or personally, he drove home the fact that you never know how people will help you in the long run.

At the time, I thought that Willy’s motive for reminding us about this fact was to keep us from being conniving, manipulative, and greedy. He wanted to keep us from being the stereotypical MBAs that are represented in movies about Wall Street Bankers. And surely, there were some people in the classroom who were at risk of becoming just that.

Now, I realize that Willy was actually offering advice in the positive, not the negative. He was articulating from experience the value of acting like Mark. When you’re a “good guy,” when you’re the type of person who listens to other people, supports them for no reason other than the act of helping, and are genuinely a pleasure to be around, you’ve got people in your corner.  

This seems pretty straightforward. Be a good person and get treated well. But the reality of business is that we often see people act poorly and get rewarded immediately. Some folks steal meetings or leads from their colleagues. Some folks regularly “forget” to include folks on important email chains. Some people gossip behind the backs of their coworkers to make themselves look better. All of these things might help on a short time horizon. As long as no one notices, you might benefit from the act of being a horrible human being.

Over the long term, however, people always notice.

In technology, I actually see this phenomenon play out pretty regularly. Some investors are constantly out there to help entrepreneurs. They want to change the world for the better regardless of whether they make out like bandits. And over and over those are the folks I see entrepreneurs seek out. Why? Because people sing their praises and push others in their direction.

The same goes for operators. Some people invest immeasurable time in training, mentorship, and helping employees find great places to go when they’ve outgrown their roles. With no clear expectation of return, it’s easy to see the real benefits that accrue. Those are the operators that young prodigies want to work with. Those are the managers that people will work relentlessly and pull all nighters to support.

Every day each of us has countless opportunities to act like Mark. Countless opportunities to be genuinely wonderful human beings. Acting like an asshole might help you in a short term sprint to a closed contract or your next promotion. But in the marathon that is your career, it always weighs you down. Your career has a long tail. More importantly, your life has a long tail. You’d be wise to remember that.

The Need for Irrational Exhuberance

Over the last few weeks, I’ve been spending a lot of time thinking about irrational exuberance in entrepreneurship and venture capital. 

I’m a very careful person when it comes to word choice. So please make no mistake, when I say irrational exuberance, I mean “irrational.”

In 2009, I started my last company. The business was attacking Live Nation’s profitable promotions business from the bottom up (textbook disruption). We grew and had profitable unit economics for some time. But in 2011, we started to see that as the volumes of concerts we coordinated increased our ticket revenue per concert was dropping. Despite the fact that every incremental concert was profitable, the numbers were starting to tell a story that said we couldn’t support our sales model.

This wasn’t the first time the numbers told us to stop. And like every time before, my co-founder wanted to press on. And I’ll never forget the conversation we had as we discussed moving forward. Come hell or high water, Chris reminded me that were going to tackle the market… regardless of all the signs to the contrary. It didn’t matter that our investors were skiddish, that our advisors were changing their tunes, and that we were looking at a long road with no discernable positive outcome at the end. He was all in. The facts be damned. Those would change as he applied more of his blood, sweat, and tears to the problem.

Ultimately, this became the issue we couldn’t overcome. But the more time I spend working with entrepreneurs tackling big problems, the more I realize that every company that’s worth a damn has moments like these. The “Oh fuck” realization where all your assumptions look wrong. At this point, the only options for innovators are to give up and find something more sensible to do or to double down like a crazy person arguing that the laws of gravity only apply to the weak minded.

The rational decision in these situations is almost always to walk away. Your 1% chance at making a few million dollars almost never outweighs the opportunity cost of going to find a safe job at a blue chip company like General Electric. Which is why it’s beneficial to society that so many of us in the industry of innovation share Chris’ irrational exuberance for our ideas. If every human behaved like an economist’s ideal decision maker, nothing interesting would ever get accomplished.

As a group, we’re dependent on a few crazy people ignoring the facts and moving forward. It’s the heart of innovation at some level. Investors may demand predictability out of their companies, but progress depends on irrational drive.

This is part of what makes venture investing so much more difficult than playing in the public markets - and so much more fun. It’s not just about reading the signals, having access to capital, and seeing a PowerPoint. It’s about being bullish about some change in the world that’s impossible to justify on paper alone. When emerged, who would have bet there would be millions of people would start watching eSports on a daily basis? No one. But some foolhardy entrepreneurs and investors set about building a platform for it anyways. Because there was an outside chance that the facts be damned, with enough blood, sweat, and tears they’d be able to help bring that market forward as well.

Today, the problem I see too frequently is people treating entrepreneurship too rationally. Folks with MBAs or Law degrees who want to leverage the option value of a startup as their path to extraordinary wealth. Increasingly, that’s my biggest turn off. Because I am starting to understand the unique paradox - why missionary entrepreneurs are so much more successful than mercenary entrepreneurs. The world that economists teach us about demand rational actors. But you’d be a fool to assume you can know everything coming your way. There is no such thing as an omniscient rational actor. Invariably the “Oh Fuck” moments will arrive. And I want to support the entrepreneurs with the irrational drive to persevere - protecting their employees, customers and investors - and build something great.


Image Courtesy of Tom Woodward

Path Dependency, Infrastructure, and Entrepreneurship

Every day, businesses take action because of infrastructure decisions made long ago. Venture capitalists rely on it. The theory of disruption presupposes that large companies will never look at markets with the eyes of a new organization. Instead, leaders of these organizations look at opportunity through a lens of resource optimization; trying to make the most money out of the least incremental investment.

But despite the handcuffs that tend to come with billions of dollars of outdated investment, attacking huge companies saddled with old assets isn’t always a simple decision. Sometimes the sheer amount of infrastructure in place across a single industry makes it nearly impossible to dislodge any one player. And for anyone setting out to tackle these monolithic industries, it’s important to understand why.

How infrastructure dictates strategy

Everything about who you are today is a result of where you come from. Some of the contributing factors to your position and perspective are more substantial than others - but the fact that your past plays a big role in your decision making process must be irrefutable. Businesses are no different. The decision of a telco to invest in a GSM standard isn’t one that can be reversed lightly - it informs a firm’s strategy for years.

In the mid-1980’s, an economist named Paul David introduced the world to a theory that would describe this phenomena. He called it path dependency. His ideas detailed how investment and standard setting in industries ultimately dictated the future of an industry. Once enough critical mass had been put behind a given technology platform, it was possible to predict the incremental investment companies would make - regardless of the quality of the platform.

The best example of path dependence is the Qwerty keyboard. If you’ve ever wondered why your keys are laid out in such an odd way, you wouldn’t be alone. In the early days of writing’s mechanization, typewriters frequently jammed. When keys were pressed too quickly, the typist would end up with a tangle of mechanical arms instead of a legible sentence. The Qwerty keyboard was developed to slow the process of typing by introducing the least optimal layout of keys. But even after computers became able to handle lighting fast inputs, the keyboard remained the same. Why? We’d invested so much in training people to type on an inefficient Qwerty keyboard that training people to type on any new format was always considered too onerous.

Today, the Qwerty pattern of path dependence holds true in many markets. Car lanes are a certain width because the carts that preceded cars needed to be the width of two horses. Healthcare maintains outmoded process and pricing methodologies because that’s how a wealth of doctors were trained decades ago. And many fortune 100 companies still have COBOL applications in use… a mainframe language that most current computer science majors haven’t ever thought about.

It’s common and understandable. Executives will invest in a production system and then spend years attempting to amortize its cost, regardless of new technologies that might emerge on the scene. Clay Christensen, Willy Shih, and Steve Kaufman called it the threat of marginal thinking. On the increment, the wrong investment seems like the optimal decision. Squeeze every dollar out of what you can - regardless of what advantages new platforms might yield.

But it’s not as simple as building a better business

Unfortunately, as an innovator, the dynamics of path dependence don’t uniformly run in your favor. It’s not enough only to build a disruptive business on the back of a scaleable technology advantage. Depending on what industry you’re sitting in, upending your competitors often requires a whole lot more than you’d imagine. And unless you are prepared to deliver all of what’s necessary, stumbling blocks await.

Consider alternatively powered cars; whether they’re electric, diesel, or biofuel. Companies have popped up and floundered for decades trying to unleash a more fuel efficient, environmentally friendly, vehicle. Until Tesla, none had succeeded. In part, Tesla’s strategy reveals why.

The automotive industry is highly interdependent. Despite the fact that Ford and General Motors don’t own gas stations, their cars appeal to us in part because of the massive amount of infrastructure investment made by gas station owners. A wealth of trained mechanics help us get our cars repaired when we need it - even if there is no conveniently located Ford outlet. And a vibrant reseller market helps us manage our long term costs of ownership.

Introducing a technical platform for a new car requires a lot more than introducing a new car. It requires delivering the same ecosystem of services that make the old platform appealing. This is why Tesla is investing in their Supercharger network, operating showrooms, and helping to manage used car sales. Even though it’s possible for entrepreneurs to predict that Ford and GM will be slow to adopt new platforms, it’s vital to anticipate the same inaction from their ecosystem. Without a strategy to overcome such barriers, it’s hard to topple the status quo.

The reason venture capital tends to flock to biotech and IT is because the industries are fairly modular. Single layers in the tech stack can be replaced easily. When it comes to places like the utilities or energy industry, it’s a whole different story (despite the inevitable march of modularity).

In these industries, the only way disruption can be pervasive is if the new model can grab hold of a small market and grow out. Containerized ships emerged on a single east coast freight route. Containerized ships relied on the rest of the ecosystem to transport their goods - even adapting their early architecture to ships operated during World War II. In order to ensure that people continued to get their goods around the globe, even the most disruptive change to emerge in the history of international freight had to plug into the existing model and slowly grow out. There was no possible justification for complete obviation of the billions of dollars of assets owned by the existing merchant marine. Transformation took decades.

Knowing where you fall on the spectrum

I’ve been spending a lot of time recently grappling with how to look at different markets in relation to this problem. The framework that I’ve come up with is rather simple in explanation and difficult in implementation.

Namely, two concepts that dictate the way disruption will play out in these types of situations:

  1. The fixed cost of deployed infrastructure in the market

    The fixed cost of deployed infrastructure is an indicator of the amount of path dependence in a given market. Things like property, plants, and equipment must be considered here. But other intangible fixed investments must be considered as well (i.e., typing training, etc.).

    In markets where there is a great deal of deployed infrastructure, the decisions of existing players is likely to be more predictable. It’s easier to play traditional disrupter when incumbents are tied to obsolete legacy assets.

  2. The level of interdependence in the market

    The challenge of looking at your competitors’ deployed infrastructure alone is that it often ignores the level of dependence ecosystem participants. When you look at your competitors’ partners, suppliers, and customers - it’s vital to gauge how much they’ve invested in the existing ecosystem. If they’re tied to the fate of the people that you’re trying to displace, it means a harder go of it all.

    Sometimes the burden here can be overwhelming, simply requiring too much investment for any single entrepreneur to overcome. Even if, for example, a company came up with a great alternative to the US highway system. Unless the new solution required orders of magnitude less capital to replace the existing infrastructure or could be deployed in microcosms of the market, it’s unlikely that it would ever dent the market.

When you consider these two influences on the course and predictability of disruption, you get a simplified set of situations. Namely, you find markets where disruption will tend to run rampant where infrastructure costs are high and interdependence is low (i.e., Hard drives). You find markets that require full stack innovators to attack an entire ecosystem, where interdependence is high but infrastructure costs are relatively low (i.e., automobiles). You find markets where both infrastructure and interdependence is high, often resulting in collective inaction (i.e., Utilities). And finally, you find very adaptable markets where there’s low infrastructure and interdependence (i.e., professional services).

Knowing where you sit tells you whether you need to integrate up and down the stack, delivering everything from product to post-sale services. It tells you whether you can expect collusion from incumbents. And it tells you whether venture financing or public investment provide more realistic paths towards rollout. It’s not as simple as just having a superior technology. If you’re in a market where you’re fighting the entrenched interests of the entire ecosystem, having a 10x cost advantage relative to your direct competitors might not even be enough.

Even if they don’t articulate it, investors and corporate financiers are thinking about this the minute you walk in the door. You should be too.