tag:longlogic.com,2013:/posts LongLogic 2017-02-26T17:59:03Z Max Wessel tag:longlogic.com,2013:Post/1134294 2017-02-26T11:20:40Z 2017-02-26T17:59:03Z 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.]]>
Max Wessel
tag:longlogic.com,2013:Post/1001864 2016-02-26T16:43:15Z 2016-02-29T17:01:44Z 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

Max Wessel
tag:longlogic.com,2013:Post/988020 2016-02-07T17:10:32Z 2016-02-12T13:36:30Z 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.

Max Wessel
tag:longlogic.com,2013:Post/977389 2016-01-24T16:22:30Z 2016-01-24T16:22:30Z 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.]]>
Max Wessel
tag:longlogic.com,2013:Post/961144 2016-01-01T02:05:46Z 2016-01-01T02:05:46Z 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

Max Wessel
tag:longlogic.com,2013:Post/957608 2015-12-26T16:33:46Z 2016-01-05T23:30:14Z 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).]]>
Max Wessel
tag:longlogic.com,2013:Post/945025 2015-12-07T04:37:20Z 2015-12-07T04:37:20Z 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
Max Wessel
tag:longlogic.com,2013:Post/939534 2015-11-26T02:55:47Z 2015-11-26T02:55:47Z 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.

Max Wessel
tag:longlogic.com,2013:Post/921676 2015-10-24T16:01:31Z 2015-11-03T23:33:25Z 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 Twitch.tv 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

Max Wessel
tag:longlogic.com,2013:Post/914278 2015-10-08T02:32:48Z 2016-10-05T02:11:28Z 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.]]>
Max Wessel
tag:longlogic.com,2013:Post/910275 2015-09-27T23:52:38Z 2015-09-27T23:56:33Z Buy Right.

Screen Shot 2015-09-27 at 42845 PMpng

Bill Sahlman and Joe Lassiter deserve to be enshrined at Harvard Business School. Choose any entrepreneur or VC across the country and ask if they know one of the two - if he went to HBS odds are that he does and that he sought out advice from one of the two at one point or another. Bill and Joe helped bring the education of entrepreneurial finance to a generation of graduates. For those lucky enough to take their classes, it informed decisions for decades.

Despite the fact that I think about their lessons in entrepreneurial management regularly, one idiom echoes in my head more than any other. Every day, I find myself repeating - "Buy Right, Operate Right, Sell Right."

I remember the first time I heard it. Joe Lassiter was finishing up a class on raising and managing a Search Fund (a financing vehicle that would help young operators find, acquire, and ultimately operate businesses). The case used to teach the class was about the acquisition of an industrial company that made components used in military trucks. Despite the business being operationally complex and traditionally low margin, the entrepreneurs in question managed to buy the company for a fairly low price prior to the 2001. After the US entered Afghanistan and Iraq, volume grew enormously, helping the company make a pretty penny for shareholders.

After chronicling all the challenges in the industry, all of the trials and tribulations of the former operator, I remember Joe Lassiter telling us that we always needed to “Buy right. Operate Right. Sell Right.” And he went on to say that the only thing we could control at the beginning of an entrepreneurial journey was buying right. The two alumni who had started the search fund in question did that. They bought at a low price and rode a tailwind upmarket.

In Silicon Valley, we don’t spend a lot of time talking about industrial businesses. But despite our obsession with rapidly scaling software businesses, those unsexy, lower growth, businesses offer some critical insights. In this case it was that investing in businesses is a actually a fairly rational thing. You can plan for all the synergies in the world. You can forecast out incredible growth. You can model out any number of exit scenarios. But when it comes to investing in businesses, the only thing you can be certain of at the beginning of the journey is your entry price. If you control it well, the benefits are enormous.

Despite the strange economics of software, this dynamic is always in play. Angels can make a pretty penny on an early acquisition if they buy right. Early employees can get screwed on options if they don’t. Buying wrong is what lets investors assemble funds full of big name logos but still yield negative returns for their LPs.

And although you can always grow into a valuation, if you buy right, you don’t necessarily have to.]]>
Max Wessel
tag:longlogic.com,2013:Post/904780 2015-09-13T22:25:35Z 2015-09-13T22:25:35Z Algorithmic Intelligence & Market Resillience

Every day the machines are getting smarter. Better tools for collecting, normalizing, and synthesizing insights from information are emerging everywhere. A decade ago, I remember thinking that recommendation panes on ecommerce sites were novel; the sign of an advanced player in the market. Now simple recommendations are easy to make and we constantly rely on software to make much more complex ones.

The promise of these prescriptions is that every task in the world becomes slightly more efficient. Algorithmic prescriptions are designed to help us make better decisions about where to save our money, what materials to use when we build things, who to hire, how to interact with each other - the list goes on.

But even as a devout supporter of the gains that computer aided decisions will bring, it's important to look for some of the risks. Recently, I've been thinking about one in particular; risks to resilience.

Our situations come about based on a complex system of actions. When we walk into a grocery store, the price we see for a basic food is the result of many farmers looking at weather and soil data and interpreting it differently. Some farmers will vary their crop varietal, others will choose different seeds for the same crop, and still other will manage their use of chemicals and fertilizers differently. At the end of the whole process, the best interpreter of information will likely make the best decisions (and therefore the most profit) in the market. But what we see when we walk into the store is a result of all that chaos.

In this world of disparate predictions, any individual participant might stand to benefit from behaving like the best forecaster in the market. Everyone wants to pick stocks as well as Warren Buffet. And the promise of algorithmic intelligence is empowering each and everyone of us to make decisions as well as the best in our markets. The risk, however, is that everyone will be making the “optimal” decision based on imperfect information.

Unfortunately, in a world of unknown information, it’s impossible to make the “right” decision all the time. The world will throw curve-balls your way. It could be an asteroid, a new disease, or something as simple as a cold snap. Invariably, the best forecasters are wrong. And it’s those situations where we’re thankful we had other people making different decisions based on similar information.

Consider this example. Let’s say growers discover a strain of rice that yields 50x more per acre of alternatives in 99.9% of years. Planters around the world would likely swarm towards producing that variety of rice over any number of alternatives - it has an obvious advantage. Then, imagine that a disease hits that strain. Global rice production could be devastated. Depending on how many people flocked to rice production, global food production overall could be devastated. All because farmers made a very rational decision to optimize their operations.

In the real world, we very rarely see these types of situations where one choice is so much better than another. The example is hyperbole at its best. But it's indicative of a significant point: Variety adds to resilience. And optimization reduces variety.

My worry is that even as we become better at accurately forecasting the world’s future state, our attempts at optimization could decrease our resilience. We get more data about the world by connecting up our devices, monitoring our production output, and measuring everything in between. But at the end of the day, we don’t have perfect information. Which means our predictions can’t possibly be perfect. 

But if human decision makers are all entrusting operations to similar data science, we will rationally turn towards similar behavior. Not the ideal position to be in when things go wrong. In this future, will we be less resilient than before? I’m definitely not one to spend money on bomb shelters, hoard canned food, or even learn to hunt. But if there ever is some sort of disaster, I’d be glad someone had made that decision. And in that case, I'd certainly be disappointed if the algorithms made all those bomb shelters and food stores disappear.

For those of us helping guide the world toward a data driven future, these are important questions to keep in mind. How to we help direct our customers the right way and still ensure their markets benefit from the resilience they’ve had in the past? I don’t know the answer, but I do know it’s a question worth grappling with.


Photo courtesy of episos.de

Max Wessel
tag:longlogic.com,2013:Post/897360 2015-08-25T04:53:56Z 2015-09-09T01:07:35Z The Difference Between Value and Valuable

A few weeks ago, Fred Wilson mentioned that Google was the most important company in the world. He caveated that Google may not be the most valuable company in the world, but that doesn’t preclude them from being the most important. Since that time, I’ve been thinking about the distinction.

The more I consider it, the more important the distinction seems.

Google is a business worth more than 400 billion dollars. In that sense, it’s valuable. The financial worth of the organization today is derived primarily from its advertising business. And while we all enjoy being prompted with recommendations before we even realize we need them, many of us derive the most value from activities that don’t make the company significantly more valuable. Google creates value in the world by extending productivity software at near zero costs through Google Documents. Google creates value in the world by supporting ubiquitous internet access. Google creates value in the world by investing in driverless cars, modular phones, and novel medical technologies.

Even if Google never turns its ancillary activities into businesses that generate significant cash flows for its investors, they will have created enormous value.

As a venture investor and former founder, this difference between value and valuable couldn’t seem any more striking. Every day I meet with hungry entrepreneurs - the vast majority of whom are truly passionate about making a dent in the world through the companies that they’re building. All of them are dedicated to creating value. When I was a founder, I was one of them. The challenge on the other side of the table is respecting their drive to create value in the world and also looking for young companies that can be valuable.

Despite a desire to invest in every world changing organization, venture capital firms succeed or die based on delivering valuable portfolios back to their investors. If the impact of an investment can’t be boiled down to dollars and cents, they can’t be used to raise subsequent funds. So while VCs certainly want to invest in companies that create value, the prerequisite is that they will be “valuable” in the future. Value-ability precedes value creation.

So the question for entrepreneurs is what makes a company valuable? The short answer harkens a required text in every MBA student’s first year strategy course: competitive advantage. But what does that mean?

How to create a valuable business:

Economic theory suggests that in a world of perfect competition, no business will stay profitable for too long. The thinking is that if you - the entrepreneur - discover a new profitable way to solve a problem, others will quickly enter the market and replicate your strategy. As more people enter the market, competition will cause prices to drop or increase the level of investment to acquire customers. The thinking is that profits won’t exist at the end of the process.

You can surmise pretty quickly that we don’t live in a world of perfect competition. Google, Apple, and Microsoft are just a few examples of companies that have created and sustained advantage over an extended period of time. Sometimes building this competitive advantage comes from creating a complementary set of replicable activities inside your firm -- forcing others to recreate your business exactly in order to compete with you (the Southwest Airlines model of competition).

More often in the world of technology, building and sustaining competitive advantage comes from the characteristics of your product itself. When your business creates exceedingly strong network effects, when you maintain intellectual property, or when you have access to asymmetric information, you put yourself in a position to continue outperforming your peers over time. In the words of Brian Arthur, your business puts itself in a position for increasing, not diminishing returns. For example, Apple’s sustainable advantage comes not just from its focus on design but by getting you to put its computing device in your pocket and helping you grow accustom to an app ecosystem for its operating system. As more and more people adopt its infrastructure, it becomes more compelling for app designers, and makes it more difficult for others to enter the market and create price pressure.

Knowing how a business will build increasing returns is critical for figuring out how valuable a business might be. Investors are constantly asking questions about defensibility, cost of customer acquisition, network effects, and switching costs to glean exactly how all this works. It’s not enough to create value for your customers. Because if it’s easy to replicate your model for creating value for your customers, you won’t have much bargaining power when it comes to price and profit. To create a valuable business, you need to solve a big problem in a market where there are buyers waiting - but you also need to do it in a way that is defensible over time.

Why building a valuable business isn’t necessarily the goal:

As an investor, I’m constantly looking for companies that can be extremely valuable. But as a resident on planet Earth, I’m constantly hoping that startups and big companies alike find ways to create real value. Traditional venture funds might not be structured to invest in moonshots, but I’m enthusiastic every time I hear about a new project in the vein.

There are certainly companies that are both creating value and becoming valuable. Facebook is investing in ubiquitous connectivity through drones. LinkedIn is helping to solve unemployment issues amongst veterans. SpaceX is trying to get us to Mars. But creating value at the expense of being as valuable as possible might require making tough decisions. SpaceX is trying to stay private in order to execute on its mission of getting us to Mars, despite its strong profitability. It could IPO, but it’s shareholders would likely push to minimize Mars research. Personally, I’d rather have those brilliant minds focused on the audacious goal of getting to Mars. If population growth continues to push us toward the inevitability of becoming a spacefaring people, the whole planet will look back with gratitude towards the team regardless of how valuable SpaceX becomes. But that’s a question of creating value, not becoming valuable.

Investing in valuable businesses is the goal of investors who’ve signed up to steward capital from people’s retirement accounts. But it’s important that innovators remember that building a valuable business isn’t necessarily their goal. The Bill and Melinda Gates Foundation might not be an investable institution for most people, but it is more important to the world than any startup in the valley at the moment.

Building a valuable business is not the goal in and of itself. I hope people continue to do the bold, audacious, things that create value - even in the absence of becoming “valuable.” The world would be a better place for it. And that’s important to remember.

Max Wessel
tag:longlogic.com,2013:Post/894923 2015-08-18T04:48:51Z 2015-08-18T16:05:32Z The Era in which Everyone Builds the Same Thing

Today, the WSJ featured an article on Slack and Facebook each delivering software that would deliver a semblance of artificial intelligence for use in productivity applications in the office. The article highlighted two companies - but Google, Microsoft, Apple, and IBM are all investing heavily in similar platforms.

Much like the wave of companies investing in autonomous vehicles, the winners in AI will be able to transform a plethora of markets. The implications are vast once software is capable of understanding your situation, your desires, and how to drive outcomes.

It's no surprise that tech companies are investing in the area. But what is interesting is the sheer number of tech companies investing in the space. While there is a great deal of speculation surrounding drones, virtual reality, and 3D printing, there is far less capital being deployed by the big guys. When it comes to artificial intelligence, CTOs are voting with their manpower.

This brute force being used by the world's tech titan's to crack the AI puzzle seems like the best indicator we have that AI is on its way - and that it will be transformative. When we figure it out, hopefully we use it well.

Max Wessel
tag:longlogic.com,2013:Post/892099 2015-08-10T14:55:00Z 2015-08-10T14:55:01Z The Possibility for Outrageous Failure

The startup industry is highly insular. Even if you ignore the homogenous composition of IT (mostly affluent, white, educated, men), the conversation inside the industry often sounds like an echo chamber for the key buzzwords of the day. This much should be clear even to those that only dance around the periphery of the market. 90% of the companies investors are talking about these days have the same key descriptors; they’re marketplaces, on-demand services, SaaS, mobile first, etc.

Over the past few weeks, I’ve been traveling. I disconnected from the startup scene and was able to retreat into a number of books on business history. Not about information technology, but books about the evolution of other major industries. Agriculture. Transportation. Global Logistics.

Their histories are all quite different. But one striking similarity stood out among them all. The most dynamic changes within each stemmed from entrepreneurs and investors setting out to accomplish something, despite an enormous possibility for outrageous failure.

The innovations that reshaped industries weren’t clear cut. Rational human beings could easily question the decisions. And because they could be so easily objected to - the biggest winners required crazy, bold, audacious investments of time, capital, and human intellect.

It makes sense. If everyone is running towards one opportunity, it’s not poised for out-sized returns in that space.

Warren Buffet has famously stressed for folks to be greedy when others are fearful. Clay Christensen has cautioned that profitable markets face the greatest pressure towards commoditization. Even inside today’s tech landscape, we have Peter Thiel appropriately pointing out that there is only likely to be one Google, one Salesforce, one Facebook, one Uber, and so on. The next conquerors of industry are likely to arise in surprising spaces where there isn’t a clear opportunity.

The biggest victories in our industry have illustrated this style of counter-intuitive thesis. Emergence Capital is a firm built on investments in cloud software during an era of complete disillusionment with the cloud. Y-Combinator is an institution built on a bold bet that mentorship and education would provide much greater value in the early stages of startup life cycles in the future. Founders Fund has returned its investors capital by investing in spaceships and electric cars. All highly questionable theses at their onset. But all theses that have shaped today’s landscape as they proved true.

But still, 90% of the conversation in technology focuses on known buzzwords in proven markets. Seems like a strong indicator that 90% of these conversations are irrelevant.

Wouldn’t it be nice if, instead of a constant fear of being wrong, people started articulating bold and counter-intuitive positions about the future? Speculating on a future that might be wrong… but could be right. It seems that conversation would help us hone in on the world changing propositions a lot faster.

Max Wessel
tag:longlogic.com,2013:Post/881909 2015-07-16T05:38:10Z 2015-07-16T05:38:10Z Two Questions that Separate Seed and Venture Investing

This evening, I had a conversation with a close friend building a great business. We were talking about his growth and the company’s current operations.

My friend’s business is growing efficiently but slowly. He’s keeping his burn low and avoiding unnecessary costs as he demonstrates that he can build something pretty phenomenal, using the customers he already has. Unfortunately, when he goes and speaks with venture capitalists about upcoming rounds, they’re skeptical. They’d like to see him demonstrate that he can make some maneuvers to grow even more rapidly.

It’s a more common complaint then you’d imagine. Early in your business’ lifecycle, all you care about is building something that can last. Your early investors harp on you about product-market fit and your constantly terrified of running out of cash. Then, all of a sudden, when you’ve found your product market fit, you start getting asked about growth. People start worrying that the business isn’t scaling as fast as they’d like.

As someone who has bridged seed stage and venture investing (however briefly!), this is an issue I can identify with. When I deal with seed stage businesses, I am often thinking about their viability. Is there a market for them to exist at all? When I am dealing with businesses that figured out there is a market for them to attack, I start thinking about whether they can capture it. One is a theoretical question. The other operational.

For entrepreneurs, the best way to identify with investors is by understanding how they are approaching issues. When you’re early, your investors are asking:

Can you build something people want?

Building something that people want is not a question of efficient use of capital and timing. Assuming that a problem goes unsolved, and your solution is good enough to drive adoption of a new “thing,” then building something people want is rather binary. Either you deliver something great or you don’t. Early stage investors often get involved with businesses before this is established. In order to succeed, they need their entrepreneurs to create great product.

Not running out of cash is an important thing. But running out of cash is inevitable. And growing rapidly is a luxury their entrepreneurs can only afford once they deliver product that is truly differentiated.

If a team is in the right market, with compelling technology, just executing on the building something that people are willing to buy is good enough at the earliest stage of investments.

When you’ve established that you are building a product that could see some real adoption, the biggest risk to your business comes from an inability to execute. The biggest question becomes:

Can you grow the business that provides things people want?

Growing a business is a very different challenge that building something that people want. Growing a business means competing with all the other folks who will copy you. It means spending capital effectively and judiciously, but knowing when to turn the burn up to capture growth efficiently. It means dealing with people issues, negotiating partnerships, and dealing with the mundane reality of things like accounting, legal, and financing.

Once you’ve proven that you have something people want, investors immediately identify these risks as those that pose the biggest challenge to your business. Can you actually overcome the barriers in front of you. At this point, your business is no longer binary. It’s worth something - you’ve proven that. But it’s only worth a lot if you can take it and scale. The faster you can build something big, the more it’s worth to investors. The faster you can build something big, the more likely you’ll see returns in the short run.

It’s here that a lot of early entrepreneurs fall down. After months or years of being questioned on the merits of your idea, this is the point where people start questioning you about things like scaling more rapidly. To your investors, all of a sudden, it makes a difference that you’re growing 6% a month instead of 12% a month. It seems crazy to you at first... but when you dig into the numbers you might realize that change makes the difference between building your revenues by ~4x and ~8x in 2 years. When you’re investing in a real product, those differences matter. And testing that your entrepreneurs can deliver against those slightly higher numbers is critical.

Once you’ve de-risked your business from a product market fit perspective, this becomes a big deal fast. As entrepreneurs, at this point it becomes your job to back solve into the numbers you need to deliver and figure you how you can create a plan to get there.

The challenges of operations before and after establishing product market fit are very different. But the change happens on a dime. It’s often hard to prepare for inside the company - luckily or unluckily, the investors you turn to for new rounds of financing will remind you of this fact. As an entrepreneur, it’s important not to be caught out of the blue by this. Building a great company is a marathon. As soon as you tackle one challenge, you’re off to the next. Product market fit is important. Scaling quickly and efficiently is too. Be ready to create that growth plan and execute against it. Have a hypothesis about the numbers you need to hit to be appealing in new financing rounds relative to your peers. And then make sure you create a plan to get you there.

If you don’t, you’re planning to answer one critical question, but not the other.]]>
Max Wessel
tag:longlogic.com,2013:Post/881057 2015-07-14T16:49:28Z 2015-07-24T14:18:16Z The Moral(e) Danger of Value Inflation

Times are frothy. No one doubts that valuations of startup companies are rising rapidly. In many cases value inflation is causing companies to see prices rising more rapidly than operations justify. But it’s a sellers’ market, and no one can fault entrepreneurs for stuffing their coffers while they can. Capital is ammunition to help attack new markets and grow rapidly. When it’s readily available it behooves you to consider reloading.

However, it’s not all as simple as that.

Recently, I’ve gotten fairly close to a few folks at a company that had raised quite a sum of cash some 18 months ago. At the time, the new investors in the deal were willing to offer an ambitious valuation. They just wanted in. They offered a valuation that the company could grow into.

The good news is that over the past 18 months, the company has grown into the valuation. The bad news is that all they did was grow into the valuation. As the company has depleted its reserves, new investors have balked at offering a meaningful step up in valuation. They’re willing to participate - but only at a marginally higher price than what was offered a year and a half ago.

Normally I wouldn’t write about fundraising during times of value inflation. It’s an over-covered topic and seems somewhat self-serving for venture capitalists. However, I do believe there is a little talked about facet of fundraising that runs the risk of derailing companies in today’s market.

Namely, a perverse incentive problem for early employees.

In public market finance, there is a pretty well known issue of generational discrimination. You and I, as fellow neighbors, might have an incentive to write other communities IOUs for decades - spending far more than we bring in. We might also die before it comes time to pay the bill. Unfortunately, in this scenario, we might have also saddled our grandchildren with insurmountable debt that they had little to do with creating. This behavior is known as generational discrimination and it’s pretty common.

Raising money on too high a valuation, too early, creates a similar problem. Early employees, founders, and investors always have an incentive to get the highest valuation as quickly as possible. If you’re going to raise 10 dollars, you’d rather raise 10 dollars for a company worth 990 (effectively selling 1%) than for a company worth 90 (effectively selling 10%). As a part owner of the business, you want to preserve your stake. You enthusiastically seek out higher and higher valuations to ensure that your dilution is minimal. And in a market like today’s, you can find those exceedingly high valuations rather easily.

The challenge is that once you’ve closed a deal, you saddle new employees with options at the current round’s valuation. If you grow phenomenally, this process works out fine.

If you just grow well after closing a round at a valuation you can’t really justify, it’s more difficult. In that situation employees will find that their hard work, great product development, and strong sales growth doesn’t translate into rising valuations. New employees become frustrated that good performance doesn’t translate into shared upside in your business. How can it? When you’ve raised on a valuation you can’t justify and can only grow into, you’ve already taken that value off the table.

The reality in that situation is that the early generation of investors and employees have preemptively captured the value yet to-be-created by your newest recruits.

In the case of the company in question, people are frustrated and defeated. Morale is low and dropping every day. If they’re not looking already, employees are thinking about leaving. Even though, from the outside, it looks like a great operation.

Great leaders ensure that when the ocean level rises it lifts all ships (old and new alike).  In today’s market, that’s harder than ever. It’s easy to track down enthusiastic investors willing to pay steep premiums to get into some rounds, paying meaningful premiums to be there. The challenge is making sure that you avoid unintentionally taxing future employees. You need your future employees to be happy and motivated. They’re going to help you build a great company. So make sure that you keep them in mind when you raise your next round.

Max Wessel
tag:longlogic.com,2013:Post/877210 2015-07-04T19:04:27Z 2015-07-06T03:21:15Z Broad or Deep in the Shovel Business

It’s a gold rush. No doubt about it.

In the last few years, the number of people opting to build their own startup has grown dramatically. A quick cut of Crunchbase data suggests that outside of California, the number of firms starting-up and finding seed funding grew by almost 700%.

There are plenty of structural reasons for this change. Over the past 25 years the internet has begun to come into a period of relative maturity. The promise of the late 90’s is finally a reality with a good deal of global infrastructure in place. Now more than 40% of the world’s population is on a relatively standard and stable communications infrastructure, allowing entrepreneurs to build digital services that can rapidly affect the lives of billions.

But the change is also cultural. Startups are cool. Entrepreneurs have displaced rock-stars in the minds of many of today’s youth. And many clamor after the pot of gold at the end of the rainbow (a fact we can derive from the swathes of Harvard MBAs heading to Silicon Valley in record numbers).


Without judging the reasons for the gold-rush or taking a position on its sustainability, its easy to agree that it’s underway.

And in any proverbial gold-rush, there is one easy way to make money; sell shovels.1

Selling shovels means delivering critical infrastructure for those attempting to strike it big. And given the massive shifts how we develop applications today, the rapid changes in our macroeconomic environment, and the proliferation of new business models, there is plenty of new infrastructure to be delivered.

Some of the beneficiaries of the second Internet-boom’s shovel selling strategy are already established. For example, AWS is growing substantially on the back of not just enterprise customers but any business looking for infrastructure at scale. Twilio is delivering the critical communications infrastructure that underpins companies like Uber and Opentable. Sendgrid is powering an ever growing array of applications that send you automated emails to confirm purchases or application registrations. But there are many others as well.

Recently, however, I’ve been doing a lot of thinking on this topic with Roy Ng over at Twilio, David Badler from SAP, and a bunch of my teammates at Sapphire Ventures.

While there are an immense number of new opportunities in shovel selling, there is also an increasing risk that the types of projects being undertaken can’t sustain meaningful scale. As many of the core pieces of digital infrastructure start to solidify, many young companies have sprung up building out much more niche solutions; services that enable a much smaller market to flourish. The risk to the entrepreneurs in these spaces is that they think they’re starting a shovel business, when they’re really delivering left-handed pickaxes optimized for miners with vertigo. Something that’s necessary for a few - but won’t support growth.

In attempting to come up with a better framework for entrepreneurs, I find it important to consider two ways a “shovel” strategy can provide the foundation for something great. By delivering something that goes broad or goes deep.


  • A service that goes broad, can deliver value in a variety of circumstances. VOIP, for instance, can be used to enable everything from call center operations to food delivery services. Many of the vendors that developers know today are broad. A developer thinks of AWS, for example, every time they build a new application.

    The challenge with breadth is that the flexibility needed to be broad often requires sacrificing personalization. AWS might be flexible, but it’s not perfect for business data - hence the success of Force.com. This lack of specified capabilities results in commoditization and price pressure. Companies that win with broad “shovel” services understand this tradeoff - focusing on constantly delivering great product at competitive prices.


  • Deep services are those that deliver against critical and specific business process. Checkr, for instance, automates background checks and security screening for on-demand service vendors. If your value proposition is in providing reliable on-demand service, the decisions you make around in-sourcing or outsourcing that screeding capability become core to your business.

    This criticality makes deep services sticky, enabling entrepreneurs to wedge in additional products. For instance, Square has such incredible attention because there is a strong belief that once they’re in the door as the POS provider, Square will be able to provide a bunch of other related services to small retailers. Micros has proven that it’s not so easy to rip out your POS system.

    But the challenge to deep services is two-fold. First, not all services are really sticky. In a world of APIs, it’s easier than most think to replace commodity software. Second, vendors offering deep services to a small number of customers run the risk that those customers will decide to home-grow capabilities for even better configuration.

Since depth and breadth ultimately enable a company’s ability to grow, being thoughtful about how you stack in a shovel business is critical. Companies with broad and deep solutions are few and far between (and most of them didn’t start that way). Companies with a broad strategy need to be the rails, thoughtfully enabling a massive wave of transformation for a wide variety of customers. Companies with a deep approach to the market need to be thoughtful about how they wedge in new products. How can they land some meaningful customers and slowly add incremental services to grow their revenues in a big way.


What entrepreneurs need to avoid is building something basic solutions for a small group of gold-miners. It’s here that you might find a number of early customers, but you won’t find sustainable growth. This is the gimmick. The flash-in-the-pan. The product that won’t scale. The acqui-hire, not the acquisition.

With critical infrastructure being provided daily, the number of obvious holes to fill in are diminishing. But there are still plenty of opportunities out there these days. If you plan on taking a shovel strategy, be considerate of which path you’re traveling and make sure that you go either broad or deep. Avoid being a flash-in-the-pan. Build something great.


  1. Or pick-axes in Chris Dixon’s words

Max Wessel
tag:longlogic.com,2013:Post/870501 2015-06-17T17:12:32Z 2015-06-17T17:12:32Z A Refreshing Take on Identity

Yesterday, I had the great pleasure of attending the Azure Capital Partners CEO day in Mountain View. There were a lot of great discussions over the course of the event. However, one stood out in particular for me; a Yik Yak discussion on identity.

For those of you who don't spend much time in the social media space, Yik Yak is an application that has spread across Universities in the past couple of years like wildfire. The app allows people to communicate with members of their community who are nearby. But in a differentiated manner from other tools that offer social communications, Yik Yak built anonymity into the core offering. And for them, anonymity has worked. They've had extremely successful adoption across the university landscape, kept their conversations mostly positive and humorous, and successfully built a war chest from seasoned investors including Sequoia.

But Yik Yak's early success isn't what made the conversation so interesting to me. It was that their founders, Tyler Droll and Bruce Buffington, had a unique and refreshing take on identity.

Over the course of a 45-minute long fireside, Bruce and Tyler explained how Yik Yak emerged. They articulated a product that was designed to give everyone equal voice - and regardless of how you approached it, identity almost always impacted who had the most voice. On Facebook, your personal brand impacted how you expressed yourself and what you'd be willing to say. On Twitter, there was always the additional challenge of a unidirectional broadcast. Until you depersonalized the speaker, you couldn't equalize the contribution.

Until yesterday, I hadn't thought of the positive attributes of anonymity when it comes to conversation. Frankly, I've always seen apps that leverage anonymity instead of pseudonyms as foolish. Anonymity, in my mind, always had too high a risk of falling victim to misbehavior.

But now the wheels are turning. I actually believe that in a lot of situations, anonymity could be critical to empowering people to participate. With the right community management systems, values, and cultural norms, some powerful tools might emerge.

Max Wessel
tag:longlogic.com,2013:Post/866147 2015-06-05T19:27:42Z 2015-06-05T19:31:10Z Start Breaking the Rules
Who was the last company that successfully out-designed Apple? The last company that out-overnighted FedEx? The last company that out-“everyday low prices” Walmart? The reality is that when a vendor pops up that outperforms a respected global business at what they do best, they are few and far between. It happens occasionally, but not often.

Why? Because it’s much more difficult to win a game when playing by the rules that the experts adhere to. It’s much easier to break the rules. The problem: too many builders expect to play by the same rules as everyone else. And when they do that they destin themselves for mediocrity.

To drive the point home, consider a more practical example. Let’s say you wake up stranded on a desert island. There is one, and only one way off the island; a bridge that will crumble after its first use. You’re there and Ussain Bolt is there. You know that whoever makes it to the bridge first just 150 meters away, will live. The other person won’t make it. Do you try to out sprint Ussain? Or do you step onto the conveniently located teleporter that will take you directly to the finish line?

Building businesses that can topple incumbents is all about playing by different rules. It requires building the teleporter. That’s the key to disruption, business model innovation, or any number of the buzz-words floating around the world of management these days. As someone setting out to do the impossible, you want to give yourself every possible advantage. You’ll never have the deep operational expertise and financial backing of the people you’re competing with -- so you need to ensure that the way in which you create value for customers is different than the way that others create value.

Often, competing differently requires walking away from valuable segments of the market. There was no way, for instance, that Amazon would have ever been able to provide the concierge experience that luxury shoppers required in the late 90’s. However, their virtually limitless selection enabled them to win the hearts and minds of budget shoppers and long-tail book lovers in a way that their incumbent competitors simply couldn’t match. For the race they entered, they broke the rules.

While we commonly associate this type of competition with digital disrupters, it’s not simply a byproduct of businesses native to the era of the Internet. Many industry stalwarts have carved their name in stone by doing things their peers believed unreasonable. Take the following list of companies that won their era by playing by different rules as an example:
  • Apple - Deeply integrated software and hardware in an era where everyone was modular
  • Southwest - Walked away from interstate travel to avoid federal regulation
  • Toyota - Abandoned I-Beam based car chassis to lower costs for small vehicles
  • Carmax - Ditched negotiated prices in a market defined by sleezy negotiations
  • Netflix - Offered unlimited rentals while their competitors sold 3-day rentals, one at a time
  • Dell - Determined that you didn’t need in-store distribution to sell an expensive computer
  • AirBnB - Rents world’s largest number of hotel rooms, without owning a hotel

If you want to do something great, break the rules. Care excessively about adding customer value, but don’t worry about industry dogma.

Max Wessel
tag:longlogic.com,2013:Post/858038 2015-05-19T12:11:39Z 2015-05-19T12:11:40Z The Physical Side of the Job-to-be-Done

Last Friday was a big day for me. Specifically, it was my last day formally with SAP.

I was lucky enough to couple the big event with a strong experience that both echoed and reenforced my emotion; my younger sister's graduation from medical school. After years of focus, both of us are setting off on journeys in new areas. More than just setting out on those adventures, the ritual of meeting, drinking, and reminiscing seemed appropriate. It even convinced me of the merits of setting out on a drive across country. The physical, mental, and emotional pilgrimage is a tribute to what I feel to be leaving some of the good people I've worked - and it's also a experiential representation of the journey to a new location and industry.

The trek west will be the real thing. More than the intellectual experience of deciding to uproot, it's the most primal representation I can force on myself.

Over the last two days, I've been thinking a lot about this. Why it seems important? And what it's importance means?

I keep coming back to the concept of the Job-to-be-done.

The theory of "Jobs-to-be-done" is a rather straightforward one. Humans have a basic set of jobs. They want to be good parents and providers. They want to communicate effectively with their loved ones and colleagues. They want to beaccomplished and appreciated. And so on.

Over time, the theory suggests, that the products we hire have changed, but the jobs stay the same. For instance, while I might have hired a buck knife to "Get me safetey" in the 1800's, today I might hire a satellite phone for the same job.

The basic understanding of what a job is probably feels like it has no relevance to the journey west. But it's the next level of the theory that's helpful. Bob Moesta and Clay Christensen, who developed the theory of Jobs-to-be-done, often say that understanding the job is only the first step. Once you understand the job, you can start to outline the experiences required to complete the job. These experiences fall into three buckets:

  • Functional
  • Social
  • Emotional

For instance, the Satellite phone I might hire to get me to safety may not need to be any bigger than a pen... but for it to have the right emotional appeal, Iridium may want to house its antenna in a large rubber device that feels indestructable to me.

Many marketers have written on the non-functional characteristics of products and services. Ted Levitt (who famously coined the "You don't buy a quarter inch drill, you buy a quarter inch hole" line) used to talk about the difference between the product and the "whole" product. With the theory of the job-to-be-don, Moesta and Christensen gave us all a framework for understanding what we needed to put in the "whole" product.

To me, the physical drive west seems more and more to satisfy a part of the emotional job of transitioning. While posting to Facebook, Tweeting to the world, and writing good bye notes do me some good, there is something truly different about subjecting yourself to a real experience outside the confines of a computer screen. There is something real about sweat, about discomfort, and about effort. Without it, the respect I'd hope to show (whether it's rationally necessary or not), just can't be enough.

It's a very primal thing. Physical representation supercedes digital displays of emotion.

And that makes sense. We humans are simple things that evolved to exist in a physical world. As complex and brilliant as we come, it will take millenia of evolution (or at least few decades of borg like digital reprogramming) to change that.

But despite the sensibility of the statement, I get the sense that modern products and services are evolving without enough consideration for some of our anamalistic tendencies. Worse yet, the trend is only poised to continue as more of our commerce, communication, and community is brought online. As this change occurs - it's vital that we recognize the value of physical experiences. We need to remember the job that we're doing for our customers and get beyond what they need on paper, appealing to their basic humanity. It might not be the most cost efficient option, but providing tangible experiences can be critical in getting the job done right.

So the questions I'd pose to all the entrepreneurs out there are:

  1. What jobs are you doing for your customers? 
  2. And how can you enhance the emotional and social experiences they require by engaging through their physical world?

Max Wessel
tag:longlogic.com,2013:Post/856044 2015-05-14T15:36:01Z 2015-05-14T18:53:05Z 5-years is too short

Successfully building new things requires a mental model of the future. It doesn’t matter whether you’re investing your time, your labor, or your your mind to do so.

Anyone who angel invests, works at a startup, or even helps to build products and services at enormous companies needs to be able to accurately gauge what the future is going to look like. People at Procter & Gamble need to understand how folks will buy soap and wash themselves in the future. Folks at McDonald’s need to understand how health trends will impact their customers diets. And companies like Hertz need to successfully forecast the role autonomous vehicles will play in the transportation market.

But more often than not, when I see people predicting what the future holds, it’s on an awkward 5-year planning horizon. It’s my belief that 5 years is just about the worst planning horizon you can choose.

For most people, 3-years is incremental. 5-years feels long. And 10-years seems unfathomable. If most people are changing jobs every decade, the thought of planning their pursuits around a vision of the world that far in advance may feel ludicrous.

So we end up in 5-year planning cycles.

But the problem is that we think we can see 5 years in the future. We feel like we have enough insight into what changed and how it played out in the last 5 years to successfully project how the world should work from here. We work forwards, not backwards.

On 5-year timelines the world seems linear. You remember buying your first iPhone. You remember looking down at your pocket. And you remember imagining, wow… this thing is going to be really cool. On 5-year timelines, we feel like we can forecast change.

Just take a look at the below chart (US GDP growth quarterly from 2010-2014). None of those growth rates looks too big. The US Economy wasn’t growing more than 5% annually during any quarter in the past 5 years. And in some quarters it’s even been negative.

It’s not dramatic growth. It’s slow and steady.

The problem is that over time, change compounds. It’s exponential, not linear. And it’s incredibly difficult to forecast out the future from an expectation of incremental, linear change.

Just look at US per capita GDP from 1920 to today. That same incremental growth that seems so easy to predict has led us to GDP per capita that is almost 10 times larger in just a 90 year period. If we follow the same trajectory, we'll see that number close to 500K annually. Every American could own a Tesla, a loft in Manhattan, a beach house, and so much more.

It sounds fantastical. But it’s probably not too far from the truth. With the advances in robotics, machine learning, and networking that we’re seeing today, it’s not unreasonable to imagine a world of abundance. (Obviously, we’ll have some social challenges along the path - but that’s an entirely different challenge).

When you start thinking about the ways the world will change on a 10, 20, or 30-year time horizon, it stops looking linear. We know that 30 years from now, driverless cars will be a reality. On that timeline, we can very clearly see a path towards using renewable energy to power our transportation and our homes. We presume that even the smallest household items will be networked.

And when you start planning based on that world, you have a very different perspective. The questions you ask yourself are fundamentally different. You’ll question whether your business, strategy, or profit model are at all relevant. You’ll challenge yourself on the types of talent needed in this future economy. You’ll force yourself to think about how the very lives of your consumers will evolve.

On a 5 year timeline, we miss all of that.

We might slightly underestimate the the scope of change on a 5-year time horizon if we start imagining based on the world that exists today. But we drastically underestimate the scope of change 20 years from now if we start at that same point.

Max Wessel
tag:longlogic.com,2013:Post/854416 2015-05-11T14:17:16Z 2015-05-16T15:00:08Z Your SaaS business probably isn’t being “disrupted”
Every company desires to win profitable customers. The bigger the contract, the higher the margin, the better. And that’s why companies across the board are drawn to “upmarket” customers.

Upmarket customers are the ones that are simultaneously the most demanding and most profitable. As a CEO, upmarket customers are the ones with the biggest problems your company can solve. For that reason, they’re willing to pay you the most for your solutions. They typically have needs that are more complex than much of your base – forcing you to quickly build new capabilities to satisfy them.

When it comes to the world of SaaS, these are the customers with huge MRR. One upmarket customer can make up for a hundred volume customers. They're the logos you put on your website. They're the Global 2000 - businesses that everyone recognizes. You constantly feel their allure as you grow your business.

Figure 1 - Revenue per customer over time (sample public companies)

But, as anyone who has read The Innovator’s Dilemma can remind you, upmarket customers come with their own risks. Listening too exclusively to your most profitable, most demanding, customers often causes companies to build features and distribution models that simply can’t compete over long periods of time. Listening to the demands of these unique customers often provides managers a false sense of confidence that they're headed down the right path.

Over time, upmarket customers unintentionally lead businesses astray - opening the doors to disruption.

For all these reasons, it’s been easy for Venture Capitalists to predict the constant cycle of disruption in technology markets. Not only is technology changing at an ever more rapid pace, but we're also seeing a slew of cloud software vendors march upmarket - increasing their revenue per customer by winning large enterprise contracts. The gut reaction of most observers then is to believe these vendors should be constantly subject to disruption. That's certainly been the sentiment shared by a number of bloggers, investors, and pundits who focus on the software sector.

Unfortunately, it's not quite that simple. And VCs heralding continuous disruption in SaaS should keep that in mind.

There are thousands of ways companies can fall victim to attack by new market entrants. Disruption is a specific one. It also happens to follow a powerful pattern – when the pattern of disruption begins it’s difficult to change the end result. But when companies follow the siren’s song of their upmarket customers it doesn’t necessarily mean all the other conditions that facilitate disruption have been satisfied. Just one.

What actually enables disruption – an Extendable Core

In 2012, Clay Christensen and I published an article in the Harvard Business Review discussing how to forecast the extent to which disruption would impact large businesses. To any sort of recommendation, we had to be pretty prescriptive about what actually drives disruption. So we spent a lot of time discussing what we called the extendable core.

The extendable core of a disruptive business is the technology or business model innovation that allows a disruptive entrant to enter a market and scale up their operations in ways that incumbent players can’t replicate. It’s a way of operating that allows them to improve their product or service but maintain an intrinsic structural advantage.

Originally, SaaS companies found their extendable core in multi-tenant cloud architectures. They could write code once, deploy it to infrastructure they purchase at scale, and manage it in a more efficient model. It wasn’t just the revenue model of subscription – anyone in the license software world could have changed the billing process for their products.

When Marc Benioff coupled his subscription software with a means of delivering software that made it cheaper and easier to manage, he hit the disruptive home run out of the park. His extendable core allowed him to deliver basic software to overlooked members of the market (small and medium sized businesses that couldn't have shouldered the burden of high implementation costs). But the business' extendable core also provided the same cost and service advantages as he slowly crept upmarket. As he added features and functionality to compete with offerings like Siebel CRM, he still maintained an intrinsically advantaged position.

Textbook disruption.

Low Cost Doesn’t Mean Disruption

There is a large difference between price competition and disruption. Consider economy hotels.

Why? Any traveler can attest that no one really needs the luxury that brands like the Ritz, the Four Seasons, or even the Marriott offer most customers. What most people truly need when traveling is a bed and a lock on the door to make certain your goods aren't stolen by the random marauder. Everything else is bonus.

Because millions of travelers choose to opt out of the luxury options available, a slew of options exist for the more fiscally conscious traveler such as Econolodge, Holiday Inn Express, and so many more. But just because those hotels serve downmarket customers at a lower price point doesn't make them disruptive. It just makes them cheaper.

The reason? Each of the low cost vendors share the same basic business model as their upmarket competitors. They own and manage a physical inventory of rooms. Because the underlying foundation is similar, for each of the economy hotels to move upmarket they must adopt the same cost structures as their upmarket competitors. As they add the luxurious spas, pools, and restaurants, they lose their ability to under-price their competitors -- effectively losing their competitive advantage.

When Salesforce adopted a multi-tenant cloud model, they changed the game. They could improve their product, add functionality, build their sales organization, and still maintain many advantages that traditional on-premise software vendors could not compete with.

That extendable core is what made their inevitable victory so perfectly predictable.

Companies without this core can still carve out strong positions. Their entry into markets, however, simply can't be trumpeted as the inevitable downfall /  disruption of their upmarket brethren. Just because Xero is cheaper than FinancialForce, doesn't mean that FinancialForce is being disrupted. They could be out-producted, out-executed, out-marketed, or out-maneuvered... but they won't be disrupted.

In today's SaaS landscape, there are definitely some disruptive entrants (e.g., Zenefits with a profit model that enables the company to subsidize free software). But there are also numerous examples of simple price competition (e.g., Zoho). And when you're managing a business, it's vital that you know the difference.

Three implications for the SaaS CEO

If the cycle of price pressure in technology isn't resulting necessarily from disruption, the question is what does that mean for SaaS CEOs? With an eye towards three things, this can actually be quite empowering.

1) Know the Competition’s Business Model

If disruption finds its roots in being able to sustainably scale an advantaged position, knowing the strength of your competitors (and your own) business model is key. If you’re a burgeoning SaaS executive, it’s your job to know how your competitors operate. Understand their profit model and their technological foundation.

If you have someone nipping at your ankles you need to be aware whether they're playing the same game as you, or if they're playing a different one. What about an entrants model would allow them to maintain a cost or quality advantage over as they scale.

For example, just because Workday is selling larger and more complex HCM contracts in the cloud along with the bread and butter contracts that helped them grow through their IPO, doesn't mean that an entrant can just walk in and steal their base. But they should keep an eye out for Microsoft, Netsuite, and FinancialForce, who are all trying to win greater share of the ERP market by offering deep integration with the front office applications they own.

Keep an eye out for new technologies, programming styles, or business models. Ask very deep questions when someone emerges like Zenefits giving your core product away for free. The key is to dig deep and understand whether these competitors can keep their position as they move upmarket.

2) Pursue Different Models for Different Customer Segments

Being disrupted is a terrible thing. When it starts in reality, you can't expect to hold the low end of your market without a different model. But when you're facing simple price competition - as is the case in most SaaS environments - part of the challenge is ensuring you address your different types of customers with the sustainable models.

As young technology firms add the features and functionality to appeal to large enterprises, it’s enticing to increase focus on winning contracts in that segment. It can be a grind to sell 30 contracts at 10K in annual value each to medium-sized businesses. To those businesses, the 10K is often a large commitment. That commitment drives difficulty in the sales process. It’s often easier to trade that high volume, lower value, focus for a focus on lumpier (but far more valuable) enterprise sales where your average contract value may be 300K. Each contract in that segment might drive 30 times the revenue but only be 15 times as complex to close, meaning the overall job is easier.

But just because SMB and mid-market sales are a grind doesn’t mean they’re not worthwhile. The chairman of Taiwan Semiconductor once said, US CEOs love to talk about improving margin, but “so far I have not found a single bank that accepts deposits denominated in ratios. Banks only take currency.” He advocated pursuing any ROI positive sale and simply building piles of cash. If you have a population of customers that clamor from your services, it can be quite lucrative to manage different go-to-market models for those segments.

Both Netsuite and Salesforce.com represent shining examples of this practice. Each is driving ever larger contracts in large enterprises and corporate subsidiaries around the globe while continuing to grow their volume base of customers. It requires true discipline and a willingness to do things differently for different customer segments. But with the right sales ops team and good channel and ecosystem, it’s definitely possible.*

Figure 2: Estimated Recent Netsuite and Salesforce Revenue per Customer1

3) Listen to Everyone

Disruption sneaks up on those that stop listening. And more specifically, it sneaks up on those that stop listening to ALL of their customers. Even as your business builds capabilities and breaks into new segments of the market, keep listening across your portfolio. Understand why new products appeal to different members of your customer base and respond accordingly.

Andy Grove famously said that only the paranoid survive. He’s right. If you’re not fearful of the types of businesses that are starting to appeal to even your least valuable customers, you’re creating a chink in your armor. Anyone can execute you out of your pole position if you give them the opportunity.


1 Customer count estimates for Salesforce.com derived from Jeff Grosse. Should be directionally correct, though not perfect.

*The added benefit to not retreating from your base is that you can often use your volume to improve your ecosystem. Channel partners and ISVs flock to platforms with high numbers of potential customers. When you have volume, you’ll find yourself with extensions to your solutions that go a long way in defending all segments of your market.

Max Wessel
tag:longlogic.com,2013:Post/850725 2015-05-04T02:32:30Z 2015-05-06T18:27:37Z Bet on "What Could Be," not "What Is"

A few days ago Tesla unveiled their ambitious home battery. Since then, I've had many conversations with friends, family, and colleagues about Tesla's potential to transform the energy markets. I even ended up having a small debate with Clay Christensen and other members of my former think thank on the topic.

Now, I should caveat that I travel very deeply in technology circles. I'd guess that about 20% of the folks I interact with have either founded or worked for venture backed software companies. Typically, they're at the bleeding edge of early adoption. So I was deeply surprised when so many folks echoed the same response back when we started discussing Tesla: "Tesla is incredibly overvalued."

The statement itself isn't what's surprising. It very well might be true. The surprise is that so many folks made the statement quite nonchalantly. As if it were blatantly obvious that Tesla was a company that investors shouldn't be touching with hundred foot poles.

When I pushed each of them further on their thinking, it became obvious that many of the folks I'd been discussing the company with shared a similar characteristic; they sought to rationally justify a $26 billion dollar valuation for one of the world's smallest mass-producers of cars.

And there was the rub. They were analyzing what was directly observable. They were asking themselves how much profit every Model S might generate and what they thought Tesla could produce 3-years down the road. They weren't asking themselves what the world of transportation and energy production might become... and who would be successfully positioned in that future state.

"What Is" can change fast...

Many people regularly estimate what the future will look like based on what they see today. It's a simple way of forecasting. And humans naturally gravitate towards simplification. So it is perfectly understandable that when we are asked what to expect from a person, project, or corporation, we have a tendency to look to the past few years and extrapolate out a few more.

That approach is more than reasonable in some situations. When we're looking at companies that are positioning themselves as leaders in a world that hasn't quite arrived, we do ourselves a dramatic disservice by thinking too short term and too linearly.

Companies like Tesla, Uber, AirBnB, Box, Twilio, SendGrid, and so many more are impossible to value or evaluate based on an evaluation of the current business. Because the business environment that's there today will change fast.

Part of the reason for this change is that often these types of businesses are dealing with compounding growth. Today, they might be have small absolute numbers for revenue and profit. But with growth, that could all change. And growth has a habit of sneaking up on folks quickly.

Take Tesla for instance. This year Tesla is forecasting to sell around 55 thousand vehicles (or roughly a sales volume increases of approximately 50%). Even, if you estimate dramatic decreases in annual sales growth, Tesla can become a fairly significant player fairly quickly. Consider the below scenario

  • 2015 -- 55K (50% Growth)
  • 2016 -- 77K (40% Growth)
  • 2017 -- 100K (30% Growth)
  • 2018 -- 125K (25% Growth)
  • 2019 -- 150K (20% Growth)
  • 2020 -- 173K (15% Growth)

Even cutting Tesla's growth rate dramatically over the next 5 years, we find ourselves with a car maker that is close to as large as Porsche was in 2014.

Many people look at these types of growth numbers and suggest that it makes sense on paper, but it's not realistic. But the truth is that we live in a world where observing this type of exponential growth repeatedly is increasingly more feasible. In today's business environment, companies have access to global pools of capital, production resources, and distribution channels from day one.

We see the trend everywhere. It takes less time than ever before to see great technologies adopted around the world. Where it took nearly half a century for a quarter of the US population to see their homes electrified, it took just 7 years for the same diffusion of the Web.

There are certainly true operational challenges related to growth for young companies. But it's quite conceivable that if a company can overcome those hurdles, its founders can build a truly global organization in less time than it takes most professors to win tenure at Universities.

When you're working with compounding growth and new technologies, it truly is realistic for numbers to get big fast. And in these types of situations it's almost never appropriate to judge what a business might achieve by starting with what exists today.

Starting with "What Could Be" and working backwards...

In my experience, the better way to judge businesses in these rapidly growing markets is to start with what the markets could become and work backwards.

Namely, whenever I'm approached with a question about a company like an AirBnB, Zenefits, or Tesla, I generally force myself to analyze three things:

  1. The Problem(s) the Company is Addressing
  2. The Size of the Problem Space
  3. Potential Barriers to Growth / Profitability

The first step is to determine what problems each company in question is actually addressing. Uber, for instance, is creating an on-demand solution for transportation. They don't just compete with taxis and limousines, but they successfully position their drivers as an alternative to private carpools, public transportation, and even personal car ownership. When you look at Uber as a transportation company, it's opportunity space becomes far larger than simply as a substitute for hailing a cab.

It's not about what aisle a company's product sits in or what search terms its products show up underneath. Understanding potential opportunity is all about understanding the scale and scope of the problem being solved.

The second step I take in evaluating the potential of a business is judging the upper bound of its success.

If, for instance, you were starting a company company that made the perfect food substance (e.g., Soylent), the upper bound of your success might be serving three meals a day to all humans on the planet. Perhaps it might be even larger because maybe your perfect food substance were actually also suitable for animals.

We all know that an assumption like this is unrealistic. But setting the upper bound helps paint the picture of all the value and players in a company's market. For Uber, for instance, setting the upper bound would force you to think about all the situations where people are transporting themselves from one location to another. It would force an investor or potential employee to identify different types of situations where on-demand transportation might be sought out. Only once that complete set of circumstances had been laid out, would it be possible to start winnowing down the opportunity and making a more realistic estimate.

Finally, comes the "real" work. Consultants and bankers revel in modeling out complex market scenarios. They determine how distribution or sales might be impacted by any number of macro-economic issues or competitors in their clients' markets. Unfortunately, these highly paid MBAs almost always add this layer of computational complexity to the wrong foundation.

When you start to look at businesses by determining "what could be," it's a lot easier to peel back the onion. It's almost impossible to guess what a market's growth rate will be 7 or 12 years from now. It's a lot easier for someone to think logically about what geographies would be less susceptible to Uber's model because population density is too low - removing that segment from the upper bound of Uber's market. Similarly, it's a lot easier to think about impediments to Tesla's transformation of the energy and transportation markets than it is to accurately forecast how many cars they'll ship in 2023. 


And that brings us back to the impetus for writing this piece. The Tesla conversations of this week reminded me how common it is for folks to forecast markets based on what is directly in front of them. It's the natural tendency. But despite the apparent simplicity and defensibility of predicting what will come based on what's there today, starting with what could be is a much better approach.

It's not clear that taking this approach would lead folks to come to any other conclusion on Tesla. The company may well still be overvalued. But I'm certain of one thing in particular...

If you really thought long and hard about the topic, the answer wouldn't come so easily and so nonchalantly.

Max Wessel
tag:longlogic.com,2013:Post/849749 2015-04-30T21:42:18Z 2015-04-30T21:42:18Z Heading West to Play the "Long" Game

4 years ago my life took a particular twist. At the time I was running nuevoStage.com, a company dedicated to helping young performing artists get on stage. It was a wild ride, but a difficult one. More on that later.

But towards the end of our adventure with nuevoStage, I was randomly invited to join one of my idol's, Clay Christensen, in his think tank. I skipped giddily into the experience knowing very little about what I was getting myself into. It turns out that it was probably the best experience of my life. We researched, we wrote, and I met extraordinary people. I built a tiny blog following with the HBR and went heavy into the rabbit hole that is twitter. I sucked up books left and write. And I thought. I built a perspective; oddly, something I'd gone my entire life without having. More on that later too.

And as someone with the eyes of young entrepreneur in consumer technology, I really started to see a bunch more of the world.

Enterprise software was one of the areas I saw. I got involved with SAP and ultimately was brought into the company to be one of its youngest Vice President's in history. It was a big business and a wild ride. My charge was to help them think about the long term. To obviate disruption and invest in meaningful programs over a 3-10 year timeline. It was an incredible experience. But -- as it is with all good things -- it is now coming to an end.

After years with the business that touches more than 70% of global GDP, I realized it was time to start applying that perspective that I'd picked up and grown so passionate more broadly. Really... with the ultimate goal of helping to fill in the gaps around the future. Asking myself, "what type of change can I embrace and accelerate?"

So we're picking up and heading west. To the land of software companies doing incredible things.

But with the change in location, I also wanted to change some of my vehicles for communicating with you: the world. Over the last two years, I've really retreated to writing only for the HBR. It's great from a reach perspective to some degree... but it's also incredibly limiting. One medium means boundaries. Multiple mediums allows for creativity.

So here we go. I am rekindling the personal blog. (Technically, retiring the old personal blog and starting this one fresh). Expect frequent updates and a lot of stream of consciousness... but hopefully some good thoughts sprinkled in the mix.

Max Wessel
tag:longlogic.com,2013:Post/849723 2015-04-30T21:16:18Z 2015-04-30T21:18:29Z Why Data is Tripping up Old Businesses

Co-authored with James Allworth & Aaron Levie

This post was originally published by the Harvard Business Review in April of 2015

Ask anyone in technology. Sometime soon, the world around us will be smart. Everything frommugs to mailboxes will be context-aware. Our email inboxes will guide us to the highest priority action items. Online investment portals will automatically advise us to optimize our tax returns with the accuracy of the best financial advisor.

Despite the inevitability of this “smart” future, today only a small portion of businesses regularly merge data and physical products. Most large companies struggle to get the most out of the vast amounts of data they’ve collected. That’s because even after they determine the right ways to use information to delight their customers, managers must address one equally important challenge.

They must update decades-old management systems so they can embrace new digital opportunities.

In this article we will present three ways that information-based competition is challenging existing management practices. We’ll also offer some examples of how digitally native businesses have addressed these challenges. But the solutions described won’t be comprehensive. What’s important is that your management team is aware of these issues and can use that understanding to develop a solution that fits your business and allows you to deliver the most value to your customers.

The Challenge of Investing in Digital Assets

Almost any business school professor will explain to her students that there are differences between managing organizations that are capital-intensive and those that are not. That fact becomes apparent when you juxtapose the balance sheet of a company like Microsoft with the balance sheet of a company like Siemens. To adjust for these differences, managers of capital-intensive businesses have developed all sorts of tools and heuristics to help ensure that they’re building their balance sheets in the right way. If they accomplish the task, their businesses will pay dividends for years to come.

Unlike their industrial peers, managers of asset-light businesses focus little on the balance sheet. Instead, they’re taught to focus on their income statement and optimize their operations around preserving profitability. It’s as simple as that.

The challenge? While we have tools and financial statements that help us manage investments in physical assets, we don’t have the same for digital assets and information. There’s no line item for information on your company’s balance sheet — despite the fact that we know information can be extremely valuable. There’s no depreciation schedule for data — despite the fact that we know data can become obsolete over time. And there are certainly no “digital ratios” to help your shareholders value your business’s future earnings potential.

Combine all of those missing managerial components together and the natural reaction is for executives to under-invest in information. On a short-term basis, the only thing they can expect in return for focusing on data is the headaches that follow from explaining, justifying, and evaluating their operations to colleagues and investors.

Yet, we know there is also clear value in information. Consider the 2.4 billion dollars invested in Facebook during its growth phase. Where did that investment impact its traditional financial statements? It didn’t acquire factories, milling machines, or property. It didn’t generate profits or preserve margins…just losses. The most significant asset it did acquire was user data. And today, the nearly two billion user profiles it captured serve as the backbone for one of the largest advertising businesses ever created. But before those records were converted into advertising revenue, there was no spot for them in any financial statement. Even today, with more than $200B in market capitalization largely derived from that same data, investors struggle to value the company’s information.

Where we land is firmly in the face of a management paradox. We know that information can be used to create value. But the tools we have to evaluate and reward managers point them away from the strategies that leverage information. So we’re left in a situation where information-based strategies rarely get the attention they deserve (or require).

What our teams need are the same sorts of techniques that we use in capital-intensive businesses to monitor and evaluate our asset value. We need to mark our information assets to market or depreciate them as they become obsolete. We need to have an ongoing understanding of what’s being used and what’s not. We need to have investment plans put against different types of information and also run pilot programs to test the usefulness of newly targeted information. Just like procurement specialists will make sure that expensive CNC machines are tested by factory managers before they’re rolled out across a manufacturing organization, we need the same rigor applied to investments in information infrastructure.

Often, venture capitalists help young, digitally native businesses achieve this rigor by identifying key metrics surrounding user activity, registration, and engagement that will help approximate the value of data over time. Things like lifetime customer value are closely monitored so data can be appropriately re-evaluated over time. As such, you rarely see lengthy discussions of traditional financial statements in board meetings. Instead, there is a new focus on the acquisition of return on digital assets. It’s this type of focus on information that needs to become more common inside established businesses.

The Challenge of Determining What’s Core

For years, management consultants have encouraged executives to understand and focus on what’s core to their business. Often, the last thing managers are encouraged to do is think outside of their industry. They’re reminded that conglomerates with diverse industry focus tend to underperform in their markets (at least in industrialized nations) as compared with focused firms. However, determining what’s core and what’s not core is getting more difficult in an era where information is serving as a basis for competition.

Take FedEx for example. Everyone knows FedEx as a logistics behemoth. Its global scale and distribution makes it a critical service vendor for businesses around the world. But since FedEx also has records of its customers’ shipments, it knows how order volumes change based on the date, the weather, and past growth patterns. It’s not far-fetched to imagine this data allowing FedEx to deliver compelling sales forecasting software to its customers.

So would FedEx’s use of its data be a core or non-core activity?

Today, FedEx has some software offerings — but they all revolve around shipping solutions. FedEx isn’t in the business of optimizing supply chain activities using global benchmarks. But there’s no doubt that FedEx’s data would be valuable in the task. And the type of information that FedEx has in this respect isn’t readily available to any of the major players in the supply chain software business.

Honestly, there is no clear answer as to whether this type of opportunity is close enough to core to pursue, or too far away to try out. Similarly, ten years ago, it would have been impossible to predict or justify Amazon becoming the leader in cloud computing simply as a consequence of its own scale in online retail.

The best response is to recognize that the rules used to determine which activities our organizations should pursue are less relevant these days. Some companies will make thoughtful decisions to monetize their digital assets by simply charging for access to data. Some companies will expand into new industries using the information they naturally collect from their traditional business operations as a foundation.

But to optimize your business, you must acknowledge that your information should change what you consider to be adjacent markets — and your business leaders need to make active decisions about which of these “information adjacent” markets to pursue and how.

The Challenge of Building an Ecosystem

At the beginning of the twentieth century, even basic tasks were fairly complex. Figuring out how to send bars of soap efficiently from Ohio to New York required excellent managers who were well versed in the most modern operational techniques of the day. Over the course of the century, businesses slowly mastered the arts of managing the production of physical things to the point where consumers across the globe were able to find products of all variety with costs kept low due to fierce competition. But in the information age, the world has changed again – in particular for businesses that leverage information as core to their competitive position. Instead of using traditional tools to compete in an environment of clear customers, suppliers, partners, and competitors, we find ourselves in an era of “Co-opetition.”

Every modern business operates in a highly networked economic environment. In this economic environment, managing product becomes a small facet of our overall challenge. Among other things, managers also need to manage the development of ecosystems. Ecosystems that require investment, profit sharing, and ongoing care. Ecosystems that can’t be measured based on traditional unit economics. And ecosystems that often require information to be shared across porous corporate borders.

Information is malleable and scalable — but it’s also defensible. Often, after we finally convince our organizations to capture and experiment with information that is useful for satisfying our customers, we find ourselves wanting to keep that information all to ourselves. We especially don’t want to share it with competitors. But in an era of information, sharing what we have is regularly the only way to get people to join our ecosystems — using, enriching, and growing the value of our products.

Consider Bloomberg. For years, Bloomberg has been been building an empire on the back of its real-time market information. Bloomberg terminals are a staple of financial institutions — their comprehensive market intelligence has been what’s differentiated their performance. However, as information becomes ever more accessible via the Internet, lower performing (but good enough) competitors have started to emerge, innovating around the types of core financial data that has long set Bloomberg apart.

As a forward-thinking institution, Bloomberg embraced this change in 2012 and worked to start opening their information treasure troves to a new wave of partners via the Bloomberg API. Bloomberg realized that the ease of information sharing made innovation in consumption a key form of differentiation in the industry. And even if you have access to the best real-time data, it’s impossible to compete without an ecosystem of partners building around your information. Getting that ecosystem meant sharing the data that had powered the core business. So the media giant took its market information and standardized a programmable interface, allowing others to access and enrich the data with other functionality. Its openness streamlines innovation for its customers, but runs contrary to the “walled-garden” strategy that has dominated the industry for years.

Companies in legacy industries as different as retail and financial services all have major opportunities to take the data that is generated by customers and partners to securely help them build new digital experiences. But these opportunities will require openness in many situations. Alliances between partners and competitors will often need to be struck in order to deliver the most value from data. And while these kinds of partnerships are starting to happen more and more, they’re nowhere near the scale that is possible.

In this era of information-based competition, sometimes sharing today is core to profiting tomorrow. And sharing a critical competitive asset is not something we’re used to doing. Developing the systems to help you determine how to build the case for when to share, what to share, and when to stop sharing is vital for managers trying to win in the information economy.

Information is a challenge for your management team because it’s intangible, difficult to quickly value, and can quickly lead you into adjacent markets. And once you have unique data assets that differentiate your business, it’s often tempting to clutch them too tightly, assuming that the value of monetizing those data directly is more than the returns to sharing it and growing your ecosystem. Sometimes it is — but often it’s not.

Every day, people are finding ways to use information to improve our lives, let our machines know us as we approach them, automate basic decisions in our organizations, and improve our relationships with our customers and employees. But while data offers endless possibilities, it also offers real management challenges. To take advantage of data’s opportunities, managers must get out in front of these problems.

Max Wessel
tag:longlogic.com,2013:Post/849681 2015-04-30T20:27:19Z 2015-04-30T20:28:16Z Stop Worrying About Consensus
This post originally appeared in the Harvard Business Review in October of 2014

Consensus is a powerful tool. When CEOs set out to conquer new markets or undertake billion-dollar acquisitions, we’d hope they’d at least sought out some consensus from their trusted advisors. We hope they’d be as sure as possible that their teams are ready, that their strategies are sound, and that they’d done their diligence.

The problem with consensus is that it’s expensive. And while it’s worth the cost of consensus in the pursuit big, bold moves, it’s often crushing to small experimental ones.

Consider the story of Nick. Nick is a typical manager at a one of the world’s most successful widget companies. He’s well respected, but far from the top of his organization. The good news for Nick’s company is that Nick has some great ideas; ideas for new ways of producing and distributing widgets that have never been thought of before. Nick’s company is also lucky that Nick has read The Lean Startup. Nick readily grasps the value in testing his ideas before asking for any full-scale operation.

Like a good student of the lean start-up, Nick plans out a cheap test for his latest idea, “Widget 2.0.” He determines that he can take just $10,000 to determine if Widget 2.0 has legs. If the test goes well, he’ll figure out the next step. If not, he’ll get back to his day job.

Inside most companies, this is where the problem kicks in.

Nick’s company is like most companies — only a small number of key executives have real authority to distribute cash and try new things. Everyone else is happy to defer responsibility (generally terrified of approving a failed experiment). But like most hierarchical organizations, Nick’s managers and their managers expect to be informed of his ideas before they make their way to the big boss. Even though there is only one check writer, there are a lot of potential naysayers. So Nick sets out to convince his key “stakeholders” to support his test plan for Widget 2.0. He has meeting after meeting and slowly gets people on board. Finally they approve his $10,000 dollar test.

The test fails, and Nick goes back to his day job. Success, right?

Not really.

In the last few decades executives have started to get wise about the value of systematically testing new ideas. Whether it was Rita McGrath explaining the importance of identifying risk in inherently risky ventures, Rosabeth Moss Kanter encouraging leaders to let their small experiments proliferate, or Eric Ries and Steve Blank teaching us the value of systematic experimentation and innovation accounting, the message has been clear: constantly testing new ideas is vital in the search for organic growth.

The reason testing is so vital is because it minimizes the investment required to eliminate uncertainty. In so doing, you increase the speed of innovation and decrease the cost of failure.

In the case of Widget 2.0, Nick’s company appeared to understand the value of his experiment… but their process got in the way. Consensus didn’t just slow Nick down, it dramatically increased the cost of his test. If Nick made $120,000 a year and he spent just a month trying to drive consensus around the project, the cost of his salary during the month of meetings doubled the cost of the experiment. If Nick had a small team working for him, seeking consensus may have quadrupled the cost of the experiment. And that’s not even accounting for the executives’ time that he had to sit down with.

Again, consensus can be a powerful tool. Consensus can be used to ensure multiple perspectives are looked at in any decision process. Consensus can help us honor fiduciary responsibilities. But it’s is slow, it’s messy, and it’s expensive. It eats away at the value of experimentation.

Milton Friedman once argued that the beauty of private capital is that it streamlines the act of experimentation in a capitalist society. Instead of driving consensus, “the market breaks the vicious circle [of having to convince a variety of stakeholders].” Individual entrepreneurs only need to persuade a few empowered parties that their ideas “can be financially successful; that the newspaper or magazine or book or other venture will be profitable.” To drive those same benefits inside our firms, consensus needs to be sought only where necessary.

So the challenge to managers is determining how to manage the consensus tax. How do you avoid investing in mediocre ideas, but still act with the speed and efficiency that helps you increase your ROI and get more at bats?

1. Acknowledge that not all investments are the same. Some investments are inherently complex and difficult to test systematically or at low cost. Often, these investments require that we drive consensus and be as sure as possible before we experiment. Others, however, are far less risky. If I can spend $10,000 for a one-day experiment that will tell me if a product won’t work in the future — that’s cheap. (That’s basically the same cost as the pro-rated salaries of a 100-person business unit on a 90-minute call.)

Managers in the modern organization need different processes for different types of investments. If your organization has one pathway for funding you’re doing it wrong. Either, you’re not considering the complex investments deeply enough or you’re crushing the small ones.

2. Push decision authority as low as possible. Senior executives are busy. As much as they want to control everything in the organization, it’s simply not realistic. To be nimble and innovative, part of the key is pushing decision authority as low as possible (but not lower).

What’s as low as possible? That’s going to change from situation to situation. But the key is acknowledging that the more senior you make your decision makers, the more waste you’ll require of those looking to experiment. It’s much better to have a slightly less qualified decision maker that is empowered to act on a much shorter timeline than to force decisions all the way to the top. If the latter is your approach, the only thing that will happen is your execs will end up drowning in a sea of meetings and nothing will ever get done.

To push decisions down, you need to limit your downside. Make sure that you hire smart people who you’d trust to make a good decision (not just order-takers). Make sure that you clearly define what success is for an experiment. And make your corporate mission and boundaries well known and well defined. If you do each of those things and distinguish between experimental investments and more meaningful operational investments, you’re already going to be in a good spot.

3. Don’t punish failure. Punish waste. Most executives are happy to point up the chain in order to avoid retribution. They’d rather not make a decision, because decisions can fail to pay off. It’s a lot easier to coordinate an additional meeting than to take the heat for another investment.

If you truly want to innovate, it’s important not to punish failure. Similarly, it’s not alright simply not to punish people at all. The type of punishment that I’ve seen work well is punishing waste; those who waste resources by failing twice the same way or those who waste time by being satisfied sitting in meeting after meeting without getting anything done. If you have an intrapreneur out there pushing the boundaries, learning new things, and adapting, you’re likely to have success in the future.

As Joe Bower once explained to me – “In pursuit of the novel, small is beautiful.” I’m more convinced than ever that he’s right. In part because small limits downside. But in part, because it also limits the need for consensus. In your search for innovation, it’s vital that you use consensus with some discretion. It’s a powerful tool, but it’s not for every occasion.

Max Wessel
tag:longlogic.com,2013:Post/849679 2015-04-30T20:21:59Z 2015-04-30T20:23:25Z Say no to "Innovation in General"

This post originally appeared in the Harvard Business Review in January of 2014

I had just arrived at a conference on entrepreneurship and the only panel I wanted to see was starting. I looked down at my watch and realized that I was already 5 minutes late so I dropped my bags and ran to the next building.

The subject was intrapreneurship and it seemed like the organizers had collected an all-star panel; two Googlers, an early Facebooker, one of the recent additions to the Paypal team, and one of the IBM leads on the Watson project. For over an hour, the panel discussed all of the innovative projects they’d worked on — spanning projects from Google Fiber to ad bidding technologies at Facebook.

Now, while I can’t speak for everyone else in the room, I found myself leaving the discussion disappointed.

Yes, all of the panelists were speaking broadly on innovative projects. But innovation is a word that means a wide variety of things to a wide variety of people. Without more specification, “innovation” is simply too broad to execute against. It’s like talking about creating art, without specifying between medium. Are you painting, sculpting, filmmaking, or rapping?

At its highest level, innovation is simply where ideation meets commercialization. Innovation is both the new color of Crayola crayon as well as the iPad app that completely replaces the need for Crayola crayons in the eyes of children everywhere. Because of the vast space between these, the astute manager shouldn’t simply aspire to innovation in general. It doesn’t give his team enough to go on. One employee might come back with a thousand different colors for new crayons, while another suggests strategic adjacencies with construction paper, while the final suggests a partnering with Adobe to deliver a drawing application. Yes all three are innovative. But simply claiming that they are innovative projects neglects the point that they really are entirely different in nature.

Without differentiating between things like sustaining and disruptive innovations, the conversation never directs managers to the nitty-gritty details where new products and services live or die.

It’s no wonder there is such widespread backlash against innovation today. Everyone from the Wall Street Journal to Techcrunch has an opinion on innovation overload. But I’d argue that the real problem with our innovation zeitgeist isn’t that the quality of ideas is diminishing, it’s that we’re talking about the bold audacious bets in the same way we’re talking about the unheralded incremental ones. We’re considering little league and Major League baseball the same, just because they’re both baseball.

In the research world, innovation is a term one rarely hears in a vacuum. Instead of rolling off the tongue by itself, academics modify the term innovation with all sorts of other words that specify exactly what phenomenon they’re talking about. And while not all lessons from academia do apply to the business world, this is certainly one place that hard-nosed managers and pointy-headed intellectuals should agree; because when it comes to innovation, our muddled-generic language represents muddled-generic thinking — not the clarity of thinking that should be driving multi-billion dollar investment decisions.

It’s easy to poke fun at the lengthening list of specific types of innovation, from Continuous to Reverse to Sustaining to Disruptive to Platform and beyond. But as we accept that leadership comes in many forms, from managing crises to coaching employees, we need to do the same when it comes to innovation.

Our lack of thoughtfulness on the subject has kept us from investing and concentrating on the innovations that matter most. Increased attention on innovation by businesspeople has led to millions more executives with “innovation” in their sights, but far fewer with a deep understanding of what the word means.

Innovation simply isn’t one thing. It’s a wide variety of things. It’s the sustaining innovations that will drive profitability across your core business units. It’s the continuous technological innovations that will exploit your fixed asset base. It’s the disruptive innovations that will help you drive your business into the next era of your industry’s evolution. It’s the reverse innovations to help you penetrate new markets and return lessons from different geographies.

And your business needs all of it. But each aspect of it needs to be managed distinctly. Build a shared language for innovation in your organization, set up the structures to pursue each type of innovation correctly, and invest in the team that can guide you through the process.

If you’re feeling burned out on innovation, don’t let your new years resolution be to say no to innovation… let it be to say no to innovation-in-general.

Max Wessel