It’s been exactly 60 years since Peter Drucker published The Practice of Management, bringing professional people management into the world of social science. And over the last twenty years, it’s gotten cheaper and easier to build a company, companies that are more often led by non-traditional managers with more leeway to try new things. Together, these forces are leading us into a golden age of people management.
In the history of organized work there has never been such a diversity of management tactics and structures. From holacracies to adhocracies to flat structures to four day weeks, entrepreneurs and managers are trying new ways to get things done and keep people happy at a faster rate than ever before. Just look at the headlines on Hacker News — you’re almost always able to find a couple front-page pieces on a new org chart or management hack.
I don’t agree with many of these tactics. Most won’t work. But some will, and aspects from others will get incorporated into more traditional management canon.
There’s been a lot of negativity floating around the tech world these days. This post isn’t about that. But it is about always seeking to do things better and iteratively improving the world around us, and in that spirit I’m optimistic.
In their December newsletter, University Ventures declared Bridgepoint’s licensing of Forbes’ brand to create the Forbes School of Business to be education’s “Mickey Mouse moment”. The letter compared the deal to Walt Disney’s creation of high-quality, branded theme park experiences that out-competed the questionable and unreliable carnies of decades past.
Brand crossovers in education have happened and will continue to happen. But this trend won’t result in high-quality experiences any more than blockbuster movie crossovers create high-quality video games.
From the letter:
For in a world where universities take centuries to establish themselves and their brands, there are myriad brands that currently have nothing to do with higher education but that could be very useful for higher education institutions interested in developing high quality programs that produce higher ROI for students and that clearly communicate those values to the marketplace. These brands could provide prospective students with shorthand information about the value proposition in a market where prospective students are crying out for better information about the likely return on their investment in a degree program.
Unfortunately, “quality” and “value proposition” are not unidimensional metrics that translate across industries and products. Brand crossovers in this industry have made a splash when education meets the self-help aisle but rarely beyond this. Think Tony Robbins and the Learning Annex; The Apprentice and Trump University. In those cases, students are looking not for a long-term skill set but for inspiration and a silver bullet, for which brands that communicate “immediate success” are highly valuable.
Unfortunately, licensed brands are often used as a stand-in for product quality rather than an indicator of it. The games industry offers a cautionary tale. For years, TV/movie/event IP was licensed to create new game titles, generating a bunch of famously terrible games.
Eventually, the tide turned. Games journalists looked for reasons to attack the next big-budget shovelware, framing the entire category as corporate garbage. Today, the entertainment-crossover-into-games genre is effectively dead, with interactive studios investing their biggest budgets in game-specific IP rather than licensed brands.
Education offers an even harsher environment for brand crossovers. Unlike games, education is typically viewed as an investment rather than consumption expense. Customers — especially those precious 10% whose tickets aren’t subsidized by the federal government — are suspicious and discerning. And unlike the late-90s gaming industry, the education space features hundreds of existing brands specialized in a variety of learning outcomes.
There’s value to the Forbes/Bridgepoint deal and think it will quite likely work out well for all parties involved. But brand crossovers are hardly a new thing, and it’s far too early to claim a watershed moment. The for-profit education theme park is still run by the carnies.
One distinguishing factor between inexperienced and senior software developers is their ability to answer the following question about an application they’ve built:
“As usage increases, what’s the first point of failure?”
Knowing which query or resource will need to be rewritten or replaced soonest is a meaningful — albeit simplistic — indicator that an engineer understands what he or she has built.
I like to apply the same heuristic to entrepreneurs. Experienced founders can be differentiated from novices by their ability to answer the following:
“As the business grows, what’s the first bottleneck you’ll encounter?”
Or stated another way, what problems will be need to be solved at each stage of the business’s growth? Let’s take a child’s lemonade stand. In this example, we have a particularly enterprising child who notices that the local supermarket can only supply 100 lemons per day, which equates to approximately 200 glasses of lemonade. At $1 per glass, that’s only $200 per day! The child thinks, “If I want to grow my business beyond that size, I need to buy wholesale” and begins spending time researching suppliers. But in this case, supply may not be the primary bottleneck. If only 100 cars come down the stand’s street every day — and only a percentage of those buy lemonade — s/he doesn’t need to find a wholesale supplier before finding a new location, or perhaps training an employee and opening a second stand.
It’s useful for an entrepreneur to think about their job less as growth and more as de-risking — identifying and working through the primary risks of the business. This is especially true if the entrepreneur wants to raise money. For the lemonade stand, the ability to buy wholesale isn’t a major risk — many small businesses do that with ease. Growing the customer base and scaling to multiple locations, on the other hand, is a problem worth tackling.
“Scaling prematurely”, “hiring ahead of the curve”, and “capital inefficient” are all phrases that VCs use to describe companies that tackle the wrong issues in their business’s growth. Entrepreneurs rarely err by implementing poor solutions to the right problems but rather by solving the wrong problems.
By this point we all know things are bad in PIGS. But how bad, and why? Matthew O’Brien at The Atlantic included a simple graph in his argument that Spain is Beyond Doomed, charting the growth the long-term unemployed in Spain:
Anyone who has tried to do business in continental Europe — particularly Spain — knows that firing employees is effectively impossible. This can make businesses much more skittish when it comes to hiring full-time employees in boom times, favoring instead unprotected part-time contract labor.
And when I saw that chart, I was reminded of another:
This one isn’t as dramatic, but the underlying problem is the same: a regime that protects a group of established individuals creates a “permanent underclass” of those on the outside looking in. In Spain, permanent workers are almost impossible to fire or downsize, just like tenured faculty in the US higher education system. The result in Spain is an underclass of indignados chronically under- and unemployed; the result in higher education is an underclass of poorly paid adjunct faculty with few prospects of advancement.
Neither system is sustainable. Both discourage effort and innovation, driving talent away. In academia, many of the best students flee research and end up in industry. Leaving a country isn’t as easy.
In the spirit of eating your own dog food, I took General Assembly’s Intro to Rails this past fall. The whole process of learning Rails by trying out pretty much every online tool available led me to a few thoughts:
0) Prior knowledge is rarely clear-cut. I’ve done some combination of front-end development, game development and transactional SQL in the past. Most of which didn’t help and possibly hurt my efforts to learn Rails. Many people I meet have similar quasi-technical backgrounds and are never sure where to start learning. It’s important not to skip things just because you think you’ve seen it before.
1) You have to be passionate about what you’re building. I don’t think anyone can learn to code in the abstract, bouncing from one generic example to another. But…
2) You can be too passionate. Your first, second, third and twentieth attempt to build something will all suck. It may be easier to get started if you’re not building the end-all-be-all personal project to end all projects. Instead, build something to solve a really simple personal problem without any (obvious) commercial potential.
3) Embrace de-leveraging. You can’t walk in with a mindset that you’re just going to learn enough to know how to hire someone to do the hard work. While you may end up doing that, for the moment, you’re de-leveraging and writing the code yourself.
Great businesses are known and grown by the communities that use their products. Apple’s brand was reinforced by the hip designers and musicians that used it through the company’s worst days. Facebook’s initial band of affluent college students proved more sustainable than MySpace’s crowd. Entrepreneurs have noticed, and I’ve seen many try to carefully architect the initial community that uses their product and comes to speak for their brand. This is absolutely the right intuition, as great communities reinforce great products reinforce great businesses.
Unfortunately, I see many entrepreneurs go about this in the wrong way, attempting to curate a seed community by limiting user acquisition channels to only those with a similar brand or a “premium” audience. In addition to being unsustainable, this strategy hamstrings the business and opens the door for competitors.
Your brand’s community is chosen by your product. If you have crafted your product to speak to the community you want, you need not resort to user acquisition jiujitsu to keep the good crowd in and the bad crowd out. If you are relying on targeted marketing rather than a great product to build your community, you are resigning yourself to a giant game of whack-a-mole as you try to stay ahead of the wave of “bad” users which will inevitably descend if you have any aspirations to scale. Good products shuffle bad users away from the spotlight, a “clean handling” that keeps the quality of the core community intact. Great products extract business value from bad users all the same.
Once your product and your community jibe, user acquisition marketing can be a powerful tool to grow the business. But user acquisition at scale is a messy game, and without smart product decisions it can end in disaster. MySpace had brilliant email acquisition marketing run by some of the best in the business, but users acquired through these channels are the kind of users that will set fifteen music videos to auto-play on page load if you let them. By letting them — that is, by not making the product decisions that elegantly handled these types of users — MySpace blew it.
Don’t blow it. Choose your community through your product; scale it through user acquisition marketing.
## A note: Some folks from the old-school advertising world may be a bit confused here. Some decisions traditionally in “marketing” — logo, colors, fonts, name — actually go in the “product” bucket in many web- and mobile-focused companies, and this is the way I classify them in my writings. Here, “marketing” is more specifically “user / customer acquisition”.
If you haven’t read Slate’s article on the economics of New York’s taxi medallion system, it’s worth the time. The tl;dr version is that the city government of New York has created an artificial set of rent-seeking assets — taxi medallions — where none should have existed in the first place. Specifically, the harm done to passengers and drivers by the economic rent extracted by medallion owners outweighs any possible benefit to putting an artificial quota on the number of cabs. Anyone who has tried to hail a cab in NYC between 4 and 5pm can attest to this.
Rent-seeking assets — explained quite well here — can be positive or negative for society. Many would agree that taxi medallions are a net negative. Carbon credits, on the other hand, are an artificial class of rent-seeking assets that could be quite beneficial. If economic theory is right, carbon credits will use an auction system to allocate the right to pollute to the firms producing the most economic value per unit of pollution.
So what makes a rent-seeking asset a good thing? I would argue that three criteria need to be hit to justify this kind of asset:
- Negative externality of supply (the costs of pollution are not naturally born by the polluter)
- Lack of differentiation among supply (your ton of carbon is just as bad as mine)
- Destructive Nash equilibrium (naturally, all profit-seeking firms will pollute as much as they can get away with)
Unlike carbon credits, most products do not meet one or more of these criteria. I would argue that taxis do not meet the second and third criteria. While there may be a negative externality of supply — namely, pollution and traffic — there is certainly supply differentiation (some cabs are comfier, cleaner and friendlier than others), and there should not be a destructive Nash equilibrium, as in a free market taxis should only work the streets as long as it is financially sensible for their owners and drivers. Without these three criteria met, it’s not appropriate for government to create a rent-seeking asset class like taxi medallions.
Supply quotas and rent-seeking behavior go hand-in-hand. The City of New York limits the supply of taxi medallions to 13,000, which leads to a fair market price for a medallions of just over $1 million. But limiting supply doesn’t have to mean a quota. Professional certifications — such as the bar and CFA credentials — are great examples of meritocratic supply limitations. This kind of limitation is appropriate when supply is highly differentiated. In this case, not all lawyers and financial analysts are the same. These merit-based systems attempt to differentiate those truly able to provide services from the unqualified.
This kind of merit-based qualification can also work within a quota system. High-end college admissions is one example of this. There are only approximately 1,500 spots in each class at Yale, but those 1,500 are newly allocated each year on a (mostly*) merit-based system.
But even if those spots were simply sold to the highest bidders, it wouldn’t be a very good example of a rent-seeking asset. Specifically, Yale acceptances are missing a key characteristic of this kind of asset: transferability.
Imagine, for a moment, that a group of 1,500 people were given the right to admit to Yale anyone of their choosing per year back when the university was founded in 1701. Yale never built an admissions office -- it simply filled each class by taking one name from each of these "Admission medallion" holders every year. Of course, since the University would greatly outlive the medallion holders, the holders were given the right to transfer or sell their Admission medallion to anyone of their choosing.
Over the course of time, the vast majority of Admission medallions were acquired by various investment funds and private equity firms, such as Admission Financial. Each year, these huge firms auction the 1,500 spots off to the highest bidders. With some parents willing to pay north of $5 million to get their kids into Yale, the Yale admissions business brings in north of $7 billion per year in economic rent to massive holding companies -- essentially a transfer payment from aspiring families to wealthy investors and funds.
This is a silly example, but it paints a picture of how insane this kind of rent-seeking asset model would seem for more obviously differentiated products. Medical licenses are an even more extreme example: obviously, medical licenses should not be assets simply to be auctioned off to the highest bidder and subject to transfer or sale without restriction like carbon credits or taxi medallions.
Unfortunately, higher education accreditation often functions as a rent-seeking asset. While accreditation should in theory be a quality assurance mechanic — licensing schools as Bar Associations license lawyers, for instance — in practice accreditation is an asset that can be bought and sold, accumulating rent for its owners. Extremely challenging to acquire and just as difficult to lose, the treatment of accreditation as an asset rather than a qualification has played a significant role in the sad state of higher education today. Much like Medallion Financial buys and sells taxi medallions, financial institutions have seen an opportunity doing the same with colleges and their accreditations.
I do not believe that economic rents are always bad things. Rent-seeking assets have their place. But identifying that place — and where merit may be a more appropriate filter — is more critical than ever.
*From an economic perspective, things like athletic recruitment and legacy status count as “merit”, as the spots aren’t simply allocated to the highest bidder as it would be in a rent-seeking economic model. Although I’m sure there is a certain level of donation beyond which my kid is pretty much guaranteed to get in, so “mostly” applies.
In conversation, the terms accuracy and precision are used interchangeably. But they mean different things, and the difference can play a big role in the growth of a business. Before getting into early stage companies I spent most of my time in a science lab, which couldn’t have put me in a worse position to understand how accuracy and precision affect startups.
In science, precision is valued above accuracy. In this case it’s called repeatability, and being able to run the same experiment multiple times with the same results is a good thing. After all, most fields of science expect results with 95% confidence, which means that your error rate can be no higher than one in twenty. So controlling for all possible variables and demonstrating repeatability are of utmost importance.
In startups, this kind of thinking will get you killed on two fronts. First, achieving 95% confidence is impossible in business. If you can collect enough data to be right 60% of the time you’ll get buildings named after you. You can’t possibly control for all variables; you’re lucky if you have the time and money to even understand what they are. This can be summarized with with the old business adage “it’s better to be generally correct than exactly wrong.”
Second, running a variety of experiments that yield different results is a positive thing. If all of your business experiments look similar and yield similar results, you haven’t learned very much, and you certainly haven’t explored the full set of possibilities. In all likelihood there is a better outcome elsewhere, open for a competitor to find and exploit. In other words, you don’t want to optimize toward a local maxima while missing a bigger opportunity.
Take marketing strategy, for instance. Good entrepreneurs usually try a number of diverse strategies — perhaps PPC, plus SEO, plus events or social media — to get a few data points around what works and what doesn’t. Thinking about this as a fractal and trying a few diverse strategies within each of these categories can pay dividends as well. While most of these experiments will likely fail, they can provide multiple starting points from which to drill down and test further, or provide guideposts to the right answer.
So while the precision of experiments is not so critical, accuracy is key. With all your experiments, you want to be close enough within range to triangulate the right answers through experiments. While precision without accuracy is dangerous, being neither precise nor accurate is useless. Trying five wildly different social media engagement strategies for a beta product may yield a false negative if social media isn’t the right acquisition channel; picking a wider variety of tactics may have generated more interesting results.
Business isn’t science, but you can be scientific about it. Having the right experimental framework can go a long way to saving time and money.
One of my favorite essays of all time is accomplished game designer Greg Costikyan’s account of attending the pay-to-pitch New England Venture Summit as a first-time entrepreneur raising money. Coming from the self-described subculture of “science fiction fandom”, Greg illustrates the conference as “[a] variation on that basic [subculture] motif”.
His opening observation on subcultures is worth repeating. Like Greg, I grew up as a part of a subculture. It happened to be online gaming, although the particular choice doesn’t really matter; subcultures are ubiquitous online and off. Now I’m part of a different subculture — scalable startups*. And it’s just as much of a subculture as anything else.
This isn’t just a semantic point. Lots of people casually refer to this community of entrepreneurs as the startup “industry”. But it isn’t an industry; it’s a subculture. Like any subculture, it has its own unique vocabulary, memes, and shared historical narratives and ideologies. It has its own heroes and villains, values and virtues. Healthcare, education and telecom are industries — within them they share trends and players, but from a social perspective are diverse and decentralized.
From the perspective of someone seeking a job at a startup, this distinction means that admission is granted to the startup subculture through a different means than if it were an industry. This is especially relevant to anyone who is trying to land a job at a young tech company but lacks programming or design skills. Submitting a resume will get you next to nowhere. Spending time meeting people and reading up on topics startups care about (which can easily be found on Hacker News) is a more efficient way in the door.
This doesn’t mean you need to be part of the scene. It just means you have to use different means than typical; means that may seem more analogous to a journalist wiggling into the long-haul trucker subculture than a recent college grad trying to get a job. So when someone approaches me looking for advice on getting a job at a startup, I tell them to think of the problem less like getting hired by Goldman or McKinsey and more like getting established as a writer or artist. After all, one could say that what many entrepreneurs are doing is a new kind of art.
* I specifically refer to the subculture as “scalable” startups to differentiate from, say, the affiliate marketing and lead gen world (which is a fascinating subculture in and of itself). But it’s a total different feel, with its own vocabulary and values.
Up to this point I hadn’t thought much about the macro reasons behind Occupy Wall Street, assuming it was driven by a general disaffection with economic inequality. But when I checked out We Are the 99 Percent this weekend, I saw a clear common thread among the protesters: the presence of overwhelming student debt.
Student loans are a unique kind of financial instrument. They are the only kind of debt that can’t be forgiven through bankruptcy, even when the loans come from private sources rather than government-affiliated institutions (like Sallie Mae). These loans have been a pretty standard part of the American education system for the past decade, especially among private, for-profit universities, where 96% of students graduate with an average of $33,000 in debt [PDF].
The past 70 years of American education have been built around a simple social contract: go through four years of liberal arts education, and there will be jobs waiting for you on the other side. You can even take on an otherwise unconscionable amount of debt to do it — after all, education is an investment, not just an ordinary expenditure.
Over the past three years, that social contract has been broken. The jobs that used to be available to young people with passion and drive but no appreciable skills are gone, and the graduates who would have taken those jobs are unemployed. But they still bought into the social contract, accepting suffocating amounts of student debt to get the education that didn’t give them the skills they actually needed to get a job. And just when these young people should be at the height of productivity — working hard, inventing things and starting companies — they are left deep in debt with no marketable talent.
So they’re angry, although without the channels or eloquence to express that anger in a meaningful way. So they lash out at the faceless financial-industrial complex — the people who ostensibly have created and maintained this destructive environment from behind the curtain.
But reality is much more complicated. While the folks on Wall Street have managed to hack the system, manipulating a need for liquidity and market inefficiencies to drive incredible financial returns, they’re hardly the only group at fault for a badly broken educational framework.
As a first stop, the frustrated graduates should take a look at the for-profit university administrators who adopted shady, over-promising marketing practices or the government officials who allowed often well-intended laws to be hijacked to saddle students with unforgivable debt. Or perhaps they should take a look at the state education heads and politicians who have resisted a move toward more practical, vocational education for some segments of Americans.
I maintain that unemployment is not high due to a lack of jobs — General Assembly, for one, has plenty of open positions. Rather, it is high due to a colossal mismatch of skills and market needs resulting from a dated and broken educational system.
The protestors at Occupy Wall Street are right to be angry. But articulating the problem is the first step in fixing it.
[T]here are known knowns; there are things we know we know.
We also know there are known unknowns;
that is to say we know there are some things we do not know.
But there are also unknown unknowns – the ones we don’t know we don’t know.
- Donald Rumsfeld
I first heard the word “de-risked” from a Silicon Valley VC as he passed on the GoCrossCampus deal a few years ago. I’ve heard it a number of times since, always in the same early-stage investment context. It’s an odd word. It has always reminded me of the Rumsfeld quote, at once mixing political doublespeak with a certain higher-level truth and meaning.
And in a way, Rumsfeld and the venture capitalists are saying the same thing, although I think Rumsfeld said it more meaningfully. At the simplest level, de-risking has two components:
- Converting the unknown to the known
- Converting unknown unknowns to known unknowns
That is, de-risking is about taking the unknowns of a business and turning them into knowns. But it’s also about discovering what we don’t know; it’s about cataloguing the unknowns and scheduling them for future exploration.
I think this has some significant implications for the entrepreneur. I’ve found that much of the work an entrepreneur should do prior to seed funding is not simply “proving things out” but rather exploring the key unknowns that stand in the way between the entrepreneur and massive success. Said another way, I see entrepreneurs doing too much work discovering and not enough work figuring out what they should be discovering.
Doing this will enable a healthy incrementalism and structure, bringing the spirit of a scientific experiment to an otherwise qualitative exercise in guesswork. As unknowns are converted to knowns in a deliberate fashion, the business is “de-risked” and the door is opened to more significant relationships with partners and investors. Without this discipline, the entrepreneur risks wasting time exploring things that aren’t all that meaningful – or worse, will lead to the wrong conclusion about where the business should go.
And from a purely practical perspective, an entrepreneur may be surprised at how well a list of the unknowns in their business – framed as a robust list of the things that must be proven out with the money they are raising – will go over with any investor.
There are a lot of philosophical divisions among entrepreneurs: bootstrappers versus fundraisers, platforms versus content, lean versus fat, et cetera. But one has struck me as particularly underappreciated: those who build user flows as a series of deterministic paths and those who don’t.
Paths are best understood in the context of user flows. In a path-driven business, each experience that a user — especially a first-time user — encounters is designed with the singular purpose of pushing a user to the next experience and perhaps collecting some information along the way. In the case of web businesses, each “experience” is a page. To generalize, a path is deterministic in nature; a subject’s destination on any particular page has been determined by the page’s design.
Free Awesome is a great example of a purely path-driven business. While there are plenty of links, there are really few options to leave the path, which presents the user with an alternating series of instant-win games and lead gen. This enables simple mathematical modeling and optimization of the business.
Don’t get me wrong — plenty of businesses aren’t driven by paths. General Assembly is about as far as you can get from a path business — we’re building value in a brand rather than a platform or cash flow — but we still think of large pieces of it in a path context.
But some of the best companies create products that feel like robust experiences but are actually just deterministic paths. Mint.com was a great example of this. While it felt like a comprehensive site, Mint really just guided the user down an inevitable path toward high-value lead gen offers, such as credit cards. That outcome was baked into the site’s raison d’etre at the highest level: users were ostensibly on the site in order to optimize their expenses and save money. So Mint would lead them down a path, collecting sensitive financial information along the way, with the eventual outcome of providing the user with an opportunity to get a low-APR credit card from Discover.
From a psychological perspective, Mint was brilliant. The “saving” component was the carrot hanging in front of the user the whole time. So when the user finally ended up on a page filled with the same credit card offers they get in the mail every week, they viewed those offers as opportunities to save money rather than just more ads.
Some entrepreneurs may look at path-driven thinking as limiting. After all, building your experience as a path discourages users from exploration and tends to focus the business on quantitative — rather than design-driven — decisions. It’s not for everyone. But I do recommend the path approach to many of the first-time entrepreneurs I meet for the following reasons:
Paths kill scope creep If you are designing your site as an experience that contains a bunch of different things that users can do, it’s awfully tempting to build yet another shiny thing for your users. This leads to scope creep, frustrating developers and pushing out timelines. When you are building a path, feature creep makes little sense: something either helps your user get to the next page or it doesn’t. Details can be A/B tested after launch.
Paths simplify evaluation As an early-stage entrepreneur, you want to figure out whether your idea flies as soon as possible. If you have a path, figuring this out is easy and requires little more than Google Analytics: either the conversion data adds up or it doesn’t. If you have a complex multi-dimensional user flow, it’s challenging if not impossible to figure out why the dog food isn’t getting eaten.
Paths end debates Passionate debates about design are one of the most painful parts of the early-stage startup process. As they simplify evaluation, paths make many of these debates far less necessary — if something is in contention, there is a clear quantitative conversion metric on each page to test it against.
I’m not arguing against design. But good design is hard, and design outside of the constraints of a deterministic path is really freaking hard. And if you’re a founder of an early-stage company, your job is already hard enough.