Tag Archives: marketing

Microconf Takeaways

Rob Walling and Mike Taber at the kickoff of microconf 2014

Rob Walling and Mike Taber at the kickoff of microconf 2014

Just had a great time in Vegas with some other small startup guys talking about how to create something that has real value for people — how to help folks in the world. As a side-effect, the goal is to work from home, spending lots of time with your family. It’s no get-rich-quick scheme: everybody has to find their own path. But there are a lot of common things too. Most of us use the internet, most of us either used to program or program now, most of us are part of something called the Micropreneur Academy, and most us, well, are nerds.

Here are the three things I learned (or re-learned) about myself this year:

I don’t know enough about the customer. Yes, I know the job of people I’m helping. Yes, I know the subject area I’m trying to teach. But while I have general and in-depth knowledge, that ain’t cutting it. I need to climb inside my customer’s head, spend time with them doing their work from their point of view, not mine. I keep wanting to jump ahead to the business-building part of things, instead of product-market fit. If I get the right product-market fit, the market will “pull” the rest of the business from me. People will be clamoring at the door demanding that I take their money. If I don’t? Then I’m building something and trying to beat people over the head with it. Don’t do that, Daniel. It hurts.

Hey, I actually know this stuff. Since I’m trying to help people create, maintain, and optimize their to-do lists (backlogs), it would help if I knew what I was talking about. The more I interacted with fellow startup guys, the more I realized that I actually could help these folks too. I’m actually on to something very useful across a broad market. In fact, because book 3 is going to be on backlogs and startups, I can start “eating my own dogfood” and use the things I know in the work I’m doing. It sounds like I am an idiot for not knowing/doing this already, I know. But a lot of times there’s really obvious stuff right in front of you that you miss because you’re in the weeds. Jesse Mecham gave a great talk yesterday about this. He was running a profitable startup for years and still afraid to quit his day job because of his desire for security. It took going to a minister for somebody to convince him he had the answer all along.

Teach more to make more friends. This is one of those things that I understand intellectually, but I don’t think I really get it. Plus, as somebody who took years to learn a few things, I’m seeing these guys become experts in stuff that took a month or two, and then overgeneralizing what they know and saying things that aren’t necessarily true. This makes it tougher on the next guy who comes along who tries to take the reader to the next level. But I understand that taking somebody on a journey of learning with you is good for both of you. I need to keep banging this against my head until it sinks in.

My three action items:

Start talking to people on the phone. Once they sign up for the email course, ask them if they have a few minutes to chat. Get to know why people are interested in learning more about helping Agile teams. There’s no agenda: I’m not trying to sell or push products. Simply trying to gain as much loosely-formatted and unstructured data as possible that I can then go back and find themes and put some structure around.

Use my backlog principles to organize my own startup work. Hey, if the goal here is to complete a series of books that wraps up value creation from customer development to 20,000-person enterprises, time to put the stuff in book 3 to the test personally, instead of just reading about it and watching it. The startup part is probably part of the series I’m weakest on, so nothing like the present to fix that. Not only does this make sense, it’s only an hour or two of work, maybe every month or two. No biggie. (Which is one of the beauties of getting this out to folks, it should take a tough thing and make it much easier)

Revamp my email strategy. Right now I have an Agile Tune-Up email series that runs every week over a period of a year. The purpose is to get to know folks, start a conversation, let them know who I am and that I know some stuff that could help them. That’s about it. I really should 1) offer a free multi-part course or something else of value in return for folks joining the list, 2) re-vamp my weekly series so it’s more useful to the readers, 3) manually test out the emails that go out before I automate the process so that the formatting, message, and timing is exactly what I want, and 4) add in a bit of data around segmentation when people join the list so I can help them better. Are they coaches? Guys working at a big corporation? A startup? I need to create a trial scoring system and hook that into the people I interact with. Powerful idea from Brennan Dunn yesterday. Looking forward to implementing it.

As soon I finish creating the 17 clones I will need to do all of this.

But wait! There’s more! I have a couple of strategic bonus problems that need to be solved right away.

Videos or books? I’m halfway through Backlogs 2, and I only have an early version of the first of eight videos completed for the Backlogs 1 series. Looks like completing either of those two projects should take a solid 3 months. I can’t do both — or rather if it’s possible I don’t understand how. So what to do? Finish the video series so that folks can have the hard-nosed, detailed, deep-dive down on personal and team backlogs after they finish the first book? Or go ahead and continue the story with Smith and the plant, giving people more entertainment — perhaps even finishing the final book — then swinging back for the videos? Maybe neither? Maybe I just stop now and go start marketing the hell out of the book I’ve already completed. Beats me, and I’m the one supposed to be figuring this stuff out.

All-in-all, it was a great conference. Lots to think about, great folks, and some terrific tactical advice that I didn’t even get into here. Good stuff.

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Life, The Universe, Startups, And Everything

Recently I finally figured out what I’m doing in my startup.

Not how to succeed — growing very large is still ahead of me — but how to know what to do next. Here’s what I learned.

I have two theories to test, a value hypothesis and a growth hypothesis.

Value hypothesis: if I present this to you, in this format, you will exchange with me something that I find valuable. Perhaps money. Perhaps your time.

Growth hypothesis: if I do these things, I will be able to present my value proposition to X number of new people.

One of these is called sales, the other marketing. But do not be concerned with business-sounding words. You don’t have to start reading tons of business blogs or building imaginary worlds with spreadsheets. In fact, that can be very dangerous, as it causes you to emotionally bake-in ideas that most likely are completely fallacious. Just look at it like all you have is these two very tenuous theories.

Your job is to make very precise and defined hypotheses — if I do X, Y will happen — then run a test on them to see if they hold up. You are a scientist studying a completely unknown field of study. Come up with two hypotheses, one value, one growth, then test them. If they fail, change the hypotheses until they pass. A failure is a good thing! But it means you need to decide whether to give up or pivot. Most new people to startups build some huge product — one hypothesis — and never really test it. Good startups build dozens of testable hypotheses and test rapidly. Bad startups take forever to get to a test. Or they run out of money long before they ever get around to it.

Here’s the critical thing: The goal is the passing test, nothing else.

Value hypothesis: if I show a bunch of people a bushel of apples while they are at the flea market, 5% of people will buy one for one dollar.

Growth hypothesis: if I give you half-off an apple in return for your wearing an “I bought the best apples ever at Joe’s Booth!” badge, you will bring by two other people who will also buy apples.

By creating and continuing to define these hypotheses, you build a self-sustaining system of creating value, or a business. One way to break down your two theories into finer hypotheses is like this:

lean-canvas

But there are others. As you make your hypotheses more and more detailed, you start creating a very defined structure to the test. This structure is your business model. A business cannot succeed — or fail — without creating and testing hypotheses. If you’re not testing hypotheses, you have an expensive hobby, not a business.

Want practical value? Create a Kanban board around the hypotheses you are testing, color-code your tasks to match up to what you are testing (Trello is really nice for this). Then you’ll know that every thing you do each day is for a reason. You’ll also be able to prioritize your time and energy better.

Write these down. Put them in a public, visible place for you. Everything you do — go to seminars, learn how to sell, read a book on startups, watch a video on programming, life, the universe, and everything else for a startup — everything fits into this model.

Use it.

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Startup Standup Startup

standup-iconsI’ve been coworking at a nearby town and a couple of us decided to try to help encourage each of us in our startups.

Being a startup junkie and an Agile Coach, I thought, “Why not a startup standup?” Each week we meet in person. There, each of us announces what they accomplished in the last week, what they’re planning in the next week, and what they’re number one problem is. No classes, no group-gropes, no fluff. Immediately after the ten-minute standup we can each help each other if one of us has an obstacle that we know about. Plus we can help each other position our work mentally in order to focus more on the right stuff and less on the wrong stuff.

So how to describe what we should be talking about?

I pulled down a couple PG essays, a blog on the Lean Startup concept, and some notes Derek Sivers made while reading the Lean Startup book. But heck, it was still too much verbiage. Put together, it was WAY too much to expect noobs without context to plough through. I decided to cut a bit. So here’s an effort to make a crash course in what you should know and talk about during a weekly report of your activities in a startup. I liberally edited for clarity and brevity.

1. What is a startup? (From PG’s 2012 essay)

Not every company is a startup. Millions of companies are started every year in the United States. Only a tiny fraction are startups. Startups are companies that make something people want that have the ability to scale rapidly. They may or may not involve technology.

For a company to grow really big, it must (a) make something lots of people want, and (b) reach and serve all those people. Barbershops are doing fine in the (a) department. Almost everyone needs their hair cut. The problem for a barbershop, as for any retail establishment, is (b). A barbershop serves customers in person, and few will travel far for a haircut. And even if they did the barbershop couldn’t accommodate them.

Writing software is a great way to solve (b), but you can still end up constrained in (a). If you write software to teach Tibetan to Hungarian speakers, you’ll be able to reach most of the people who want it, but there won’t be many of them. If you make software to teach English to Chinese speakers, however, you’re in startup territory.

Most businesses are tightly constrained in (a) or (b). The distinctive feature of successful startups is that they’re not.

 

2. Do you need a cool idea?

No, you do not.

3. What are you concentrating on and talking about while you are developing your startup? You are creating and testing value and growth hypothesis. A value hypothesis is a concrete way to determine what you are doing has value to your customer. A growth hypothesis is a concrete way to determine how you gain new customers. These are both measurable, and you have to have real results that indicate success or failure for your hypothesis. That means heavy, direct interaction with the people you are supposed to be making things that they want. More Lean Startup goodness from Sivers’ notes:

Startups are human institution designed to create new products and services under conditions of extreme uncertainty.

The stories in the magazines are lies: hard work and perseverance don’t lead to success. It’s the boring stuff that matters the most.

Startups exist to learn how to build a sustainable business. This learning can be validated scientifically by running frequent experiments.

The goal of a startup is to figure out the right thing to build – the thing customers want and will pay for – as quickly as possible.

Too many startup business plans look more like they are planning to launch a rocket ship than drive a car. They prescribe the steps to take and the results to expect in excruciating detail, and as in planning to launch a rocket, they are set up in such a way that even tiny errors in assumptions can lead to catastrophic outcomes.

The customers failed to materialize, the company had committed itself so completely that they could not adapt in time. They had “achieved failure” – successfully, faithfully, and rigorously executing a plan that turned out to have been utterly flawed.

Instead of making complex plans that are based on a lot of assumptions, you can make constant adjustments with a steering wheel called the Build-Measure-Learn feedback loop. Through this process of steering, we can learn when and if it’s time to make a sharp turn called a pivot or whether we should persevere along our current path.

Validated learning is the process of demonstrating empirically that a team has discovered valuable truths about a startup’s present and future business prospects. It is more concrete, more accurate, and faster than market forecasting or classical business planning.

Learning is the essential unit of progress for startups. The effort that is not absolutely necessary for learning what customers want can be eliminated. I call this validated learning because it is always demonstrated by positive improvements in the startup’s core metrics. As we’ve seen, it’s easy to kid yourself about what you think customers want. It’s also easy to learn things that are completely irrelevant. Thus, validated learning is backed up by empirical data collected from real customers.

Learn to see every startup in any industry as a grand experiment. The question is not “Can this product be built?” In the modern economy, almost any product that can be imagined can be built. The more pertinent questions are “Should this product be built?” and “Can we build a sustainable business around this set of products and services?” To answer those questions, we need a method for systematically breaking down a business plan into its component parts and testing each part empirically.

One of the most important lessons of the scientific method: if you cannot fail, you cannot learn.

A true experiment follows the scientific method. It begins with a clear hypothesis that makes predictions about what is supposed to happen. It then tests those predictions empirically. Just as scientific experimentation is informed by theory, startup experimentation is guided by the startup’s vision. The goal of every startup experiment is to discover how to build a sustainable business around that vision.

A minimum viable product (MVP) is simply the fastest way to get through the Build-Measure-Learn feedback loop with the minimum amount of effort. The goal of the MVP is to begin the process of learning. Its goal is to test fundamental business hypotheses.

Most entrepreneurs approach a question like this by building the product and then checking to see how customers react to it. I consider this to be exactly backward because it can lead to a lot of waste. First, if it turns out that we’re building something nobody wants, the whole exercise will be an avoidable expense of time and money. If customers won’t sign up for the free trial, they’ll never get to experience the amazing features that await them. Even if they do sign up, there are many other opportunities for waste. For example, how many features do we really need to include to appeal to early adopters? Every extra feature is a form of waste, and if we delay the test for these extra features, it comes with a tremendous potential cost in terms of learning and cycle time. The lesson of the MVP is that any additional work beyond what was required to start learning is waste, no matter how important it might have seemed at the time. [Which may include actually building anything at all]

(Dropbox:) To avoid the risk of waking up after years of development with a product nobody wanted, Drew did something unexpectedly easy: he made a video. The video is banal, a simple three-minute demonstration of the technology as it is meant to work. It was all he needed at first to test a value hypothesis. Many entrepreneurs refuse to spend any time in development at all until some initial value and growth hypotheses have been tested in the real world and they have real metrics from the tests. (Anecdotes, like “I showed it to twenty people and they liked it” are not real metrics)

MVP can seem like a dangerous branding risk. Easy solution: launch the MVP under a different brand name. Experiment under the radar and then do a public marketing launch once the product has proved itself with real customers.

Prepare for the fact that MVPs often result in bad news.

The solution to this dilemma is a commitment to iteration. You have to commit to a locked-in agreement – ahead of time – that no matter what comes of testing the MVP, you will not give up hope.

A startup’s job is to
(1) rigorously measure where it is right now, confronting the hard truths that assessment reveals, and then
(2) devise experiments to learn how to move the real numbers closer to the ideal reflected in the business plan.

The failure of the “launch it and see what happens” approach should now be evident: you will always succeed – in seeing what happens. Except in rare cases, the early results will be ambiguous, and you won’t know whether to pivot or persevere, whether to change direction or stay the course.

Entrepreneurs need to face their fears and be willing to fail, often in a public way. In fact, entrepreneurs who have a high profile, either because of personal fame or because they are operating as part of a famous brand, face an extreme version of this problem.

I recommend that every startup have a regular “pivot or persevere” meeting.

Remember that the rationale for building low-quality MVPs is that developing any features beyond what early adopters require is a form of waste. However, the logic of this takes you only so far. Once you have found success with early adopters, you want to sell to mainstream customers. Mainstream customers have different requirements and are much more demanding. A pivot is required.

Startups don’t starve; they drown.

Startups have to focus on the big experiments that lead to validated learning. The engines of growth framework helps them stay focused on the metrics that matter.

Companies using the sticky engine of growth track their attrition rate or churn rate very carefully. The churn rate is defined as the fraction of customers in any period who fail to remain engaged with the company’s product. The rules that govern the sticky engine of growth are pretty simple: if the rate of new customer acquisition exceeds the churn rate, the product will grow. The speed of growth is determined by what I call the rate of compounding, which is simply the natural growth rate minus the churn rate.

Focus needs to be on improving customer retention. This goes against the standard intuition in that if a company lacks growth, it should invest more in sales and marketing. This counterintuitive result is hard to infer from standard vanity metrics.

4. So formulating and reporting on hard metrics resulting from direct user contact that prove or disprove our value and growth hypotheses is what we should focus on. Once we do that, what are some common mistakes? (From PG’s 2005 essay)

  • Release Early. get a version 1 out fast, then improve it based on users’ reactions. By “release early” I don’t mean you should release something full of bugs, but that you should release something minimal.
  • Keep Pumping Out Features. I don’t mean, of course, that you should make your application ever more complex. By “feature” I mean one unit of hacking– one quantum of making users’ lives better. [Which should directly come from your hypotheses testing results]
  • Make Users Happy. There are two things you have to do to make people pause. The most important is to explain, as concisely as possible, what the hell your site is about. How often have you visited a site that seemed to assume you already knew what they did? The other thing I repeat is to give people everything you’ve got, right away. If you have something impressive, try to put it on the front page, because that’s the only one most visitors will see. Though indeed there’s a paradox here: the more you push the good stuff toward the front, the more likely visitors are to explore further.
  • Fear the Right Things. Most visible disasters are not so alarming as they seem. Disasters are normal in a startup: a founder quits, you discover a patent that covers what you’re doing, your servers keep crashing, you run into an insoluble technical problem, you have to change your name, a deal falls through– these are all par for the course. They won’t kill you unless you let them.And in any case, competitors are not the biggest threat. Way more startups hose themselves than get crushed by competitors. There are a lot of ways to do it, but the three main ones are internal disputes, inertia, and ignoring users. Each is, by itself, enough to kill you. But if I had to pick the worst, it would be ignoring users. If you want a recipe for a startup that’s going to die, here it is: a couple of founders who have some great idea they know everyone is going to love, and that’s what they’re going to build, no matter what.
  • Commitment Is a Self-Fulfilling Prophecy. I now have enough experience with startups to be able to say what the most important quality is in a startup founder, and it’s not what you might think. The most important quality in a startup founder is determination. Not intelligence– determination. [In fact, intelligence, like funding, can be counter-indicative of success.]Time after time VCs invest in startups founded by eminent professors. This may work in biotech, where a lot of startups simply commercialize existing research, but in software you want to invest in students, not professors. Microsoft, Yahoo, and Google were all founded by people who dropped out of school to do it. What students lack in experience they more than make up in dedication. You can lose quite a lot in the brains department and it won’t kill you. But lose even a little bit in the commitment department, and that will kill you very rapidly.
  • There Is Always Room. So for all practical purposes, there is no limit to the number of startups. Startups make wealth, which means they make things people want, and if there’s a limit on the number of things people want, we are nowhere near it. I still don’t even have a flying car.
  • Don’t Get Your Hopes Up. This is another one I’ve been repeating since long before Y Combinator. It was practically the corporate motto at Viaweb.Startup founders are naturally optimistic. They wouldn’t do it otherwise. But you should treat your optimism the way you’d treat the core of a nuclear reactor: as a source of power that’s also very dangerous. You have to build a shield around it, or it will fry you.The shielding of a reactor is not uniform; the reactor would be useless if it were. It’s pierced in a few places to let pipes in. An optimism shield has to be pierced too. I think the place to draw the line is between what you expect of yourself, and what you expect of other people. It’s ok to be optimistic about what you can do, but assume the worst about machines and other people.This is particularly necessary in a startup, because you tend to be pushing the limits of whatever you’re doing. So things don’t happen in the smooth, predictable way they do in the rest of the world. Things change suddenly, and usually for the worse.

    Shielding your optimism is nowhere more important than with deals. If your startup is doing a deal, just assume it’s not going to happen. The VCs who say they’re going to invest in you aren’t. The company that says they’re going to buy you isn’t. The big customer who wants to use your system in their whole company won’t. Then if things work out you can be pleasantly surprised.

    The reason I warn startups not to get their hopes up is not to save them from being disappointed when things fall through. It’s for a more practical reason: to prevent them from leaning their company against something that’s going to fall over, taking them with it.

  • Speed, not Money. The way I’ve described it, starting a startup sounds pretty stressful. It is. When I talk to the founders of the companies we’ve funded, they all say the same thing: I knew it would be hard, but I didn’t realize it would be this hard.So why do it? It would be worth enduring a lot of pain and stress to do something grand or heroic, but just to make money? Is making money really that important?No, not really. It seems ridiculous to me when people take business too seriously. I regard making money as a boring errand to be got out of the way as soon as possible. There is nothing grand or heroic about starting a startup per se.So no, there’s nothing particularly grand about making money. That’s not what makes startups worth the trouble. What’s important about startups is the speed. By compressing the dull but necessary task of making a living into the smallest possible time, you show respect for life, and there is something grand about that.

I could probably tighten this up a lot further given some more time, but it’s definitely decreased in size from the 50 pages it started out as!

Links/Sources:

So 1st, definition of a startup: http://www.paulgraham.com/growth.html

Here are some notes from the book Lean Startup. Good stuff in here. http://sivers.org/book/LeanStartup

Value Hypotheses. http://thesquigglyline.com/2012/03/05/creating-and-testing-a-leanstartup-value-hypothesis-creating-and-testing-a-leanstartup-value-hypothesis/

Finally, some common mistakes. http://www.paulgraham.com/startuplessons.html

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Everything I Knew About Startups Is Wrong

Here’s a short list of the things I thought at one point which aren’t true.

  • Startups are about high technology. False. Startups are about making things that people want that scale. Yes, technology can help you scale, but it’s not required
  • Startups are all about hard work. False. Yes, startups require hard work, but there is also a luck element too (This is the main reason most of the other things I knew to be true weren’t)
  • You have to have a cool idea to make a lot of money in a startup. False. “Business Porn” has been sold to me since I was a teenager. The idea that cool businesses are also are very dramatic — great idea, super-cool founders, overcoming impossible odds, having something special about them that nobody else has. Hollywood and the book industry love this stuff, and it’s ruined millions of people’s ideas of what startups and business is all about. Most all of the time, it’s just work. Sure, it’s work you love, but lose the dramatics and focus on execution. Ideas are useless. It’s all execution.
  • Venture Capitalists accept plans over the net. False. Ask some VCs when the last time they took a bet on something they got over the net. Like never. If anything, they keep these web forms open as a way to figure out who to ignore. if you fill one out, they know that you have no idea how funding works, so they can permanently forget about you.
  • VCs actually know what the hell they are doing. False. Stats show that your company is no more likely to be alive after five years if you take VC money or not. Sure, if you take the money you might grow. You’ll have to grow or die. Most exercises in funding are social in nature. That means you know somebody. Some professor you know refers you to a fund, or you go to Y Combinator and make the rounds. VCs make money based on what all the other VCs are thinking and doing. Raising money is a cross between a beauty and popularity contest.
  • If your friends like the idea it’s pretty good. False. Your friends are your friends because they say nice things to you. This is true whether they’re hackers or not. What you need is customers, not friends. Get as close to the customers as you can. Live with them. Find out what they think.
  • Facebook, Twitter, and Apple can help you grow. True and False. Yes, if you win the lottery (or spend a huge hunk of time learning how to social engineer a great product), these services will let you gain a lot more traction than just being out there on the web. But apps are a sucker’s game: for every one guy posting how he made 100K there’s a thousand guys making nothing. Even if you succeed wildly, you lose. The owner of your walled garden is just going to incorporate your app into their base product.
  • Most startup founders will not tell you how they succeeded. Mixed Bag. The technology startup sector is tremendously more open than any other sector, so it’s false. Startup founders are usually more than willing to go on at length about how they did it. The crazy part is that most all of it is so unique to their particular idea, team, location, and time period. You’ll be lucky to listen to ten hours and pull 2 ideas out. Are there folks who will look at many startups and try to generalize for you? Sure! Several dozen folks. All with books, or podcasts, or seminars, or classes. There’s an entire industry out there based on you wanting to have a startup. It will bleed you dry and you’ll be no closer than when you started. Don’t be the fat guy reading Running World buying 300-dollar sneakers.
  • Most successful  startup founders know how they succeeded. I do not believe this to be a true statement. They know what worked at that particular time. They probably know why it worked. But once again, this is so contextual and people are so prone to overgeneralizing that the signal-to-noise ratio here is massively lower than it appears on the surface.
  • The best way to vet an idea is to ask other successful startup founders. Here’s where we take what we already know — there’s a lot of luck involved, advice is highly contextual, and don’t ask your friends — and add it together. The worst thing you can do with an idea is listen to others. Take the same hour you would ask and receive advice and go ask a potential customer. Find somebody who might want what you’re making. Do they like it? Would they give you money for it? If the answer is “yes”, then it doesn’t matter what all the successful founders in the world tell you. If the answer is “no”, then ask why and get real feedback from the people you’re trying to help. People can stand around the internet water cooler all day long and speculate on what might work or not. But you’re not getting anywhere. Developing a startup is about learning from the marketplace. What are you doing to learn from where it matters?

ADD: You might think that this post is terribly pessimistic. It’s not meant to be. In fact, I think the social nature of hanging out with other founders might drive out huge benefits for the new entrepreneur. I’d just be careful confusing implicit knowledge and social contacts with explicit knowledge and tactics. We focus on the explicit, the tangible, the teachable. I don’t think that’s where the good stuff is.

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Why I Finally Joined Mixergy

I’ve been looking at the mixergy site for a year or two now with a jaundiced eye. Mixergy is a site created by Andrew Warner, self-made millionaire. Its goal is to have a site dedicated to people forming their own startups. It’s a fee site. You can pay so much every month or an annual fee.

The reason I’m so skeptical? 1) Everybody and their brother wants to charge me for making my startup awesome. By painful experience, most of these sites and applications do not live up to their hype. 2) Andrew seemed like a nice guy, but, frankly, another rich guy with a successful startup wanting me to join in on his next successful startup didn’t seem like so much fun.

But I have changed my mind.

Why?

As it turns out, this is a good lesson for all startup founders.

Warner has been doing interviews of other founders and people in the startup community for a while. Every time he does an interview, he sends it out free to community. But if you want the older interviews and content, you have to join the site. So every so often, the people on his site consume his content and share it. That means I’ve been constantly exposed to his work.

Eventually, every now and then, I’ll click over and consume the content. Each time I do that there’s a small chance I’ll look around.

After a year or two of coming over now and then, consuming content and looking around a bit, I decided to take a look at his interview archives.

Jiminy Cricket! There’s almost 700 interviews in there. While “getting rich quick from your startup” has been done to death, 700 hours of interviews with successful founders is something I’d really like to take in. Even if their advice never directly makes a difference in their startup, just listening to their stories can help me get a better sense of context for where I am in my startup. And that’s worth money.

But the bigger takeaway? It’s one thing to have an idea and chase after it for a while. People see what you’re doing and say “That’s interesting, but are they really serious? I don’t think so”

After a while, though, it starts sinking in to potential customers that you’re not going anywhere. Then they start taking your seriously. For transactions involving money, just being out there isn’t enough. You have to be committed.

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The Copycats at HackerNews

I’ve been a regular on a site called HackerNews for a few years now. It’s supposed to be a place where technical folks can talk startups, but mostly it’s kind of evolved into a sharing place for stuff that interests hackers.

But damn, the place has grown. From just a few hundred members, the site regularly gets hundreds of thousands of people viewing per day.

Over all this time I’ve noticed one clear trend: the rise of the copycat. Whatever you do or say that might be popular, there are hundreds if not thousands of people ready to jump on the bandwagon.

About 18 months ago I got tired of having to create lists of books for people to share on HN. Lots of new folks wanted to know what the best thing to read was. So I thought: why not make a site where we list only the best hacking books and people can create and share lists of them? hn-books.com was born.

But it wasn’t alone. I spoke about my intentions online while I was building it. Within the next month there were a dozen book sites spawned by the members of HackerNews.

I’m not saying it was my original idea, simply that once it was mentioned there were a zillion deployments of the same idea.

At first this was really cool. When the community discussed the need to have some app to strip websites of all the annoying visual garbage on them, wham! A bunch of different really cool sites do that now. (Which I think is awesome.)

But it has a dark side. The problem here is that while ideas are cheap, having 100 people all trying the same idea puts an extra amount of time pressure on an entrepreneur that normally isn’t there. Everything that is mentioned is copied a hundred or a thousand times. It’s as if you, a non-painter, decided to paint a picture of a house. So you set up your easel and get out your paints in front of a nice-looking house and start to puzzle over how to start. Suddenly 500 other people all arrive — some of them who actually know how to paint — and set up all around you. Not only is it annoying, it’s also distracting. And it can lead to a kind of herd mentality where everything is attempted, but nothing is really tried. Next week all the same noob painters are all setting up around a nice-looking barn. Repeat and rinse.

It’s gotten so bad that mentions of a specific business strategy on HN have become counter-indicative of the prospects of your successfully trying it out. The more directly-instructive an article was, the more folks that were going to go out and follow the directions, especially if there’s no cost involved.

It took me a while to figure this out. I finally understood it by observing what was not being done: founders were not giving specific details of their business model execution at the level where others could actually use it. So you’d get a great blog article about how some guy made his startup, and how awesome it was, but somewhere in his actual business would be a few tricks he used that he’d never mention. After all, who wants a thousand people all using your tricks? You’d be crazy to publish that stuff.

It actually happened to me once. About three years ago I came across something very unique: a step-by-step guide on how to set up an internet business online that was written by somebody who was not trying to sell me something. I found it on some obscure user’s group online — I don’t even remember the search terms. At the time, I was willing to try anything. What could a month or two trying this hurt? So I tried it.

Did it work? Yes and no. I learned something very useful from this exercise. Whatever you do for a startup is going to take a long, long time. Take however long you are willing to work, then multiply it times three. It requires a lot of dedication and attention to detail that I (and most others) probably don’t have. As it turns out, getting good at painting is more about the attention, dedication, and mentoring you receive in your work, and not so much about the house you choose to paint. But good luck learning that the first time out. Most folks never learn it.

Most of us are great at thrashing around for a few months! Tell us an idea about an app that mines Facebook data and makes money and there will be a hundred guys tomorrow firing up their code editors. Sure, in a few months most will be gone, but expect to see everybody and his brother coming out with the same idea in a short amount of time.

I get a lot of SEO spam on the blog and in emails. Some of it is automated, but I actually get a lot of people following me because I’ve dealt with SEO in the past. For most all of these people, SEO is a shortcut to riches. Write some crap, make a landing page, then script up enough code so that you generate links back and start making conversions. Sure, Google might shut you down in a few months, but you’ll be thousands of dollars richer and will have used fake credentials anyway.

It’s the ultimate in ADHD money-making. Crap + Code + Conversions = money.

Here’s the crux of the matter: there are people who actually invent an iFart and make hundreds of thousands of dollars in a month, there are people who sit down to paint and make something that sells right away, but odds are overwhelmingly that you aren’t that guy. Odds are you will generally develop as most other startups develop; over a long period of time as you assemble these various business execution ideas into something workable that supports some grand idea (what the grand idea is — not important. The less you focus on that the better.)

We’d all would like step-by-step instructions on how to make a million dollars in a month. But if somebody published it, guess what? Everybody would be doing it and it wouldn’t work. The system is rigged so that the easier it is to connect effort to money, and the more that know how to do it, the less likely it is for a newcomer to make it happen.

That’s not saying that short projects are a waste of time. I love short projects that stand on their own and compete for my attention. Do something for 2-4 weeks and then be done with it. Move on. But don’t expect to see any results for a few years, if ever. What I learn from these exercises is being able to repeat the entire span of startups: idea, execution, business model, marketing channel, and so on. If you ask me, anybody who wanted to teach startups would have people actually learning all of these things with “practice” ideas, over and over. As they gain competence through trial and error and repetition, they’ll develop a voice and style that will carry over to a working business.

So if you want to be a copycat, fine. Go for it. But pick your poison: pick one idea and stick with it for a year or two, or do the micro-startup idea thing I did for a while where you develop something new every couple of weeks. Whatever you do, don’t fall into the death zone. Don’t “fall in love” with an idea, screw around with it for 4-6 months, then give up. That’s the worst of both worlds: you’ve picked something and stayed with it long enough to get really emotionally attached, yet you haven’t given it the attention it needs to actually grow (or die). Then when you finally switch to something new, it comes as a failure.

And whatever you do, don’t follow along with some idea mentioned on a popular website like HackerNews — unless you like learning through pain. The only thing that’s going to happen is that you’re going to be reading about somebody else who tried the same thing and is now living the high life — without telling you exactly what they did that you missed out on. That’s not a learning experience, that’s self-torture.



tl;dr: because of both the mixed messages we send and the size of the HN audience, we’ve actually created something we didn’t mean to: an environment where lots of copying goes on, but not many are really working in a way that generates good learning about startups. Instead it’s much more of a copycat, cool-for-a-day, chase-the-herd atmosphere.

That hurts. Don’t do that.

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Welcome to the Ice Cream Factory

Ben and Jerry's Ice Cream Cone

When I worked for Pitney Bowes in Connecticut, one weekend the family took a trip to nearby Vermont. No trip to Vermont is complete without visiting Ben and Jerry’s — the world-famous place where they make all the yummy ice-cream.

We saw the strangest thing.

You could walk right in on the workers. I kind of expected an overview of the way ice-cream was made, perhaps a free cone (which, in all honesty, was one of the big reasons we visited), but a big part of the plant had glass walls. We could walk right up and watch everything they were doing in there. There were no secrets at all!

I didn’t understand how they could do this. Didn’t they have trade secrets? Things they had learned over the years to make their ice cream the best? If people could just walk around and watch everything they did, how could they run a business? Hell, how could they concentrate enough to run a business? Having all these clowns hanging around everyday would drive me bonkers.

A couple of years later I was working for the Federal Reserve. Great gig in downtown Washington, D.C. Right on the national mall. We could sit in the lunch room and watch buses pull up and thousands of tourists get off and start taking pictures. I would be checking in at my hotel and suddenly 300 Koreans would walk in the door — all with that “Wow! Take a look at that!” look on their faces. Whatever I was doing, wherever I was, there would be tourists.

At work the tours weren’t too bad — after all, it was only every now and then, and it wasn’t as bad as the Ben and Jerry’s deal. It was actually kind of flattering. But still, I didn’t see how anybody could run a business with tourists underfoot all of the time. I could deal with seeing these folks from time-to-time, but hell if I could put up with them in my office where I was programming.

Many years later in the startup world, I look around and it’s not unusual for people to share everything they are doing. Popular blogs show how ideas were found, markets discovered. There are even lots of guys who publish weekly sales and profit numbers. Ideas are cheap, they say, information has to be free! The more eyeballs the better.

I’m still struggling with this — something about this seems a bit too facile — but I’m getting better. One of the things I’ve learned is nobody much cares about anything you are doing anyway. No matter how level-headed you are, you always consistently overestimate the degree to which anybody actually gives a hoot about your startup idea.

In a world of apathy, the best you can hope for is to write an interesting blog article. Then, if you’re lucky, some smart people may drop by and offer you some advice that you really need. This is a key element of the startup experience — serendipity. It can’t be planned and it can’t be forced. It’s what makes a Silicon Valley work — lots of politely-interested strangers providing bits of advice and informally seeing what combinations they can make to the community in general. Because people don’t care personally about what you are doing, but they do feel part of a larger community that likes to help folks. This is the thing that is so hard to replicate about SV. You can dump a ton of money and build a hundred incubators, but you’re nowhere near having an environment where you can walk a block to Starbucks, ask the first ten people in line what they think of your app, and end up with half-a-dozen great pieces of advice. The culture just isn’t there. It has to grow.

And sorry, I still don’t think people share as much as they make out to be sharing, at least publicly. Yes, every day I will see dozens of articles titled something like “How I got 100 thousand subscribers in one week!” These articles will tell me all sorts of generalities about getting celebrity endorsements and such. But most of the time I leave the blog just as ignorant as when I arrived. The critical details are always missing. Big ideas are always worthless, but a very small number of tiny ideas are priceless — and perishable. You’ll very rarely ever see these tiny ideas being published. If so, it’s always a mistake.

For instance, if you knew that famous reporter X was a big photography fan and loved to chat and write about pictures, and then you pitched a story about your business which had a photography angle, would you be blabbing about it on your blog? Or would you file that piece of information away until the next time you needed a story? The reason why we keep reading all of these overnight success stories without actually learning anything is that the authors skate over the tiny details that make the entire thing work. Most of the time the readers don’t know enough to realize what the authors are doing to them — painting some broad attractive picture of amazing fame and fortune while ignoring the key tiny little tidbits that went into making it happen. So you get the general feeling that you’re seeing something, but there’s nothing really there. In a lot of ways it’s like a magic trick: look over here while I do something over there. Interestingly, these tiny tidbits are exactly the kind of thing that you might share with somebody over coffee — but you’d be an idiot to publish them.

Even Ben and Jerry’s probably was this way, I was just too ignorant at the time to notice. After all, making ice cream isn’t much of a secret — no more than “How to speed up your website” or “Unknown magic of C#” — all that stuff, while appearing to be important is just mundane technical details. The real secret is business relationships, marketing plans, how to approach new distributors, strategic plans, all the little detail work that goes into making and popularizing a company logo such as the one shown above. This is the good stuff, and no matter how intently you stare at them making ice cream, you’re not going to see it.

So lately when I’m doing something like setting up a landing page for my new e-book on being a ScrumMaster, I go ahead and blab about it even though — gasp! — i’m actually still working on the page. Here I am making the ice cream. Here you are staring through the glass. Who knows? Maybe somebody will take a look and offhandedly suggest a great improvement to what I’m doing. Maybe you’ll see something that will help you dramatically improve what you’re doing. We’ll never know unless we try.

So welcome to the ice cream factory! Just don’t peak under the office door over there.

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Management by Statistics

Almost as soon as you start aggregating numbers, you start making cognitive mistakes. For instance, look at these two scenarios.

1. Women are roughly 50% of the population, yet they are only 10% of your workforce. Is some sort of management intervention necessary?

2. Your manufacturing plant has a robotic process which has been stable and measured for many years. Last week it deviated outside the 3 sigma range. Is some sort of management intervention necessary?

In the manufacturing example, we have a defined set of inputs, a stable, limited-variable process, and a defined way to measure output. Yes, something is going on. As managers, let’s take action based on the math.

In the first example, we are asked to reason by correlation and simile. Because something occurs at one rate in one place, we are asked whether or not a similar thing should occur somewhere else. No, the math does not say with certainty one way or another. Sure you might have strong moral feelings one way or another, and you should definitely act on them, but from a measurement standpoint there’s really just nothing there to show you one way or another. As managers, if we take action we must be clear that we are taking it based on something besides math. Perhaps intuition, or our best judgment of how a workforce should look statistically. (These are very good reasons to take action)

Yet we persist in treating both of these scenarios exactly the same way. Somebody presents us with numbers, and asks us to decide. After all, they’re both just statistics, right?

In the Monty Hall problem, making a choice actually changes the odds, something that is totally counter-intuitive to most people. The history of statistics is full of stories like this. When the Monty Hall Problem was first asked in Parade magazine, over 10,000 people — of which over 1,000 were PhDs — wrote in to the magazine insisting that the mathematically correct answer was in fact incorrect.

People do very badly with statistics. This has not gotten any better over time. And it impacts a hell of a lot more than just math problems in Sunday magazines.

I spent four hours with the Monty Hall problem the first time I saw it. I finally realized you should always switch, but I was still uncomfortable with the answer. Others seem to find the answer quite easily. Likewise, there are mistakes people make with statistics that I seem fairly good at pointing out, while others struggle. I have a high aptitude for math, so my inclination is to believe that different types of problems engage different emotional centers of the brain in different people. Not sure. It would be interesting to see a psychological study of some of these problems framed in various ways for different audiences. I probably shouldn’t hold my breath, though. About 20% of psychology studies that have been examined by mathematicians show serious errors in, you guessed it, statistics.

sigh

One of the reasons why I led this piece with a political-type example is that this type of reasoning is common there and we’re all familiar with hearing political-type statistics. Lots of folks play fast and loose with statistics to make political points. If I told you the United States has lost most of its manufacturing jobs, is that a problem? What if I told you the United States manufactures the most in the world, but manages to do so with the fewest number of people? (Much like how the U.S. produces the most agricultural goods, but uses very few people to do so) Would you still think that is a problem? You could argue this either way, of course, but the point is that the same observable reality can be presented in various ways, thereby slanting the story. As the guy said, there are truly lies, damned lies, and statistics.

Yet we are stuck with them. In business, any time we have to make decisions inside a large organization, we are going to be presented with statistics. 91% of people who visit our website come back. Is that a great number? Sure! Is there anything we can do with that? Not really — watch it as we continue to change things. That’s about it. The number itself gives you zero information about causation, which is really what matters when you’re running a business. It just shows a great aggregate metric. Most businesses would assume that the combination of things they are doing creates the metric, but the reality is that it’s the things the business does, plus the unique situation of all the users. There’s a lot in that number that we don’t know. In fact, the hard number “91″ actually gives us a sense of security that is not warranted at all (without being given more information, of course)

Facebook made money because their team was able to generalize huge pieces of the way most users’ brains worked and combine them in such a way to make a sticky app. Aside from the delays caused by switching costs, if any piece of this generalized model proves fragile another model will replace it. People say that Facebook is a great app because the site’s stickiness is good, but that’s wrong. It’s the other way around: the site’s stickiness is good because it’s a great app. “Stickiness” is an aggregate number, it represents the result of the quality of the app. It’s a result. It’s not a cause. The statistic shows you some kind of vague, generalized, mashed-up result. It never gives you causes.

So when people start throwing statistics around, be very careful about what kinds of assumptions and leaps of faith you are being required to make. Statistics are terrible at providing insight, although they might be terrific in terms of feedback. “Sales is up 10%” is good feedback that things in general are better than before, but it tells you absolutely nothing about what has changed in the world to cause the increase. And of course, that’s the most important information to know!

Website designers have had this problem for years. You put up a site, instrument it up, wait a while and promote it for a while, and then what? Tons of statistics, that’s what. Anybody that has used Google Analytics or one of the other packages has seen the pages and pages of reports, graphs, and statistics those packages can generate. Page A has more people spending time on it than Page B, but Page B has greater click-through. Is that a good thing for page A? Or page B?

Some website owners are lucky — they have landing pages and the only thing they care about is getting people to click-though (down the “sales funnel”) to an order. In this case, they’ll make two entry pages, page A and page B, and compare how each performs. Each page is instrumented, and they carefully look at how changes in the funnel change the behavior of visitors. This is called A/B testing.

Most website owners, however, are not so lucky. They are content creators, and their goal is to provide engaging and sticky content. There are lots of ways to measure that — we don’t have easy things like funnels to help us out. There is no one universal metric that makes sense. Maybe a ten million people visit regularly, but only once a year. That’s a great site, but those statistics tell you absolutely nothing about why or how to make it better.

Whether you have a funnel or not, statistics get in the way much more than they help. The critical skill of a good businessperson is selectively looking at certain statistics and making guesses about the market that they then quickly test. Bad business people make no guesses, or they make all the wrong guesses, or the guesses they make take too long to prove out. Out of all the startup skills I’ve studied, this one — effectively inferring intent from reams of numbers — is probably the most difficult. That’s why they tell founders to directly and physically interact with customers as much as possible. It’s as hard as hell to get anything out of a statistical report.

But still, I wonder if A/B testing might be useful in a lot more places than just sales pages, from regular content sites to industrial statistical process control to politics and economics. It’s a tool, once again, that we technologists have had to mature out of necessity. It should find wider use and acceptance. Because we ask ourselves this same question over and over again in business and life without realizing it. Can we identify which one thing, if changed, has the impact we want — what is a cause of change? If we’re serious about diagnostics in the rest of our world, we probably should be doing a lot more A/B testing in all kinds of places.


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Yes, I know about multi-variate testing. This article is meant just as an introduction to some of the general startup issues around statistics

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Startups: The Alternative Factor

If you ever want your own startup it’s time I told you something you might find uncomfortable: you are probably living in the wrong universe.

Most people live in a universe where smart people study hard to get a good job that’s steady and provides for them and their family. There are a set of rules to follow in life, even though nobody ever comes out and tells you them directly. Those who don’t follow the rules are to be pitied or politely shunned. Among academics there are one set of rules; among business people another. Among laborers there is yet another. We collect and share these rules in clans which take the shape of churches, civic groups, political parties, or professional organizations.

Most people will never have a startup. Worst yet, they have no idea what it means to form and run a startup. Their value system, their experiences, their social structure — everything about their life has purposefully designed them not to understand the startup world. They live in another universe.

It’s difficult to explain this at the level it needs explaining. They’re not wrong — in their universe they are existing and doing things as they should. Or as someone once said, they’re not even wrong. You can’t be wrong if you are acting in a natural way as best as you know how.

I’ve had a passion for startups for several years. I used to think that forming and running a startup would be like learning a new skill, say C++ or flying airplanes. Apply enough hard work, pour yourself into the subject matter, find some examples to copy, then work until you reach your goal.

How wrong I was.

Instead what I’m finding is that all (or at least most) of the things I have learned before I started working on startups have conditioned me to do exactly the wrong things in my startup. Want to write good, solid, bullet-proof code? Excellent goal — become a true craftsman. Only it has jack shit to do with startups and can easily prevent you from ever having a successful one.

I thought at first perhaps this was an isolated incident: that there were a couple of things that work one way in the corporate world yet another way in startup land. But then the examples kept coming. Want to build a vision of utopia — a field of dreams — for your users to come visit? Never works that way. Want funding so that you can develop for a year or so and build a solid product? Forget it — you’re clueless. Want to educate people with your startup about some cool social cause? Bad idea. It’s a startup, not a charity. Want to build a business and flip it? Wrong thing to be thinking right now. Want to take some new technology and do really cool stuff with it? Great. You’ve got a hobby, not a startup. Want to do some stuff to impress fellow hackers? Wonderful. You’re now in a popularity contest, not a startup.

It goes on and on.

That’s not saying that there are exceptions to each of the conclusions above — there are plenty of folks who make a startup around a social cause and do quite well, and there are folks who take cool new tech and make a workable startup around it — but they are the exception rather than the rule. There are even people who don’t believe any of what I’ve said who have crazy successful startups. These people are an example of selection bias: a person with random attributes who gets lucky and then associates their success with one of those attributes. Who knows how much harm these folks have caused simply trying to help other entrepreneurs.

The startup world is effectively its own universe: a place where the normal rules don’t apply.

Paul Graham (a person who studies startups and runs a startup “bootcamp”) said something once along the lines of “We used to think that you had to be smart to be a founder, but we found through trial and error that wasn’t a reliable indicator at all”

From what I can tell of their latest selection strategy, it’s somewhere between a beauty contest and just finding people who are too stubborn to give up and able to figure things out on their own. In a way this doesn’t solve the underlying problem at all — what makes for a good startup — but it works, at least more than other systems do.

The interesting thing I’m finding in my personal journey is that the more I learn about startups and figure out where I’m going, the less I am attached to the old universe.

For example, I was helping a large corporation out a while back. One of the projects they had completed was a huge repository of job instructions and process descriptions for how they develop technology. As an organization that built things, this made total sense: how could you build something without a clear set of rules? But as a startup person, I had two concerns. First, I don’t know what might be useful or not. (I also had some concerns about prescriptive process, but that’s not relevant for this discussion.) Second, unless we’re doing something that actually has value, we should stop doing it. That means measure whatever you do and stop doing things that don’t help anybody.

To me this seemed very natural — after all, I have a dozen ideas around startups. I could spend from here to eternity working on things I find cool. But instead of trusting my “coolness factor” or my own sense of self-confidence for something, I’ve learned to rely on the people I’m trying to help to tell me what I can do for them. That’s the only true metric I can trust — not my instinct or some huge body of knowledge I might have absorbed about some topic or another. But to the folks I was helping, this seemed odd, strange, threatening, and perhaps even rude. Why would we want to do things this way? Are you dismissing all this hard work we’ve done? Shouldn’t we be telling folks stuff? (even if nobody listens) How will people know what to do unless we provide them instructions? All great questions, by the way — but the assumption is that somehow we could sit around and reason what might be useful or not, then never check back with the folks we are actually trying to help. From a startup perspective, it’s just the opposite: assume you know nothing, form a hypothesis, then check. Repeat and rinse.

I could go on with these examples, but I’m afraid it’ll sound like I’m criticizing folks, and that’s not my intention. We just live in different universes.

I’ll close by sharing with you my comment to a teenager who made several hundred thousand dollars in his own business before being shut down by a legal threat. He had described his problems online, and received a sound thrashing for it by people who have never done anything like that in their life. Note the completely different value system I suggest than the “normal” universe:

Notes to people wanting to hustle and form a company/startup.

Note 1: Never underestimate the ability of the press and your fellow citizens to trash whatever you are doing. Because if you are providing value and making money, you are doing more than 99% of the people out there. They will punish you for this.

Note 2: Always expect a lawyer to call. The other 1% who are providing value have learned that the best way to keep making more and more money isn’t to innovate; it’s to use the political and legal system as a club to kill the little upstarts. Be ready for the club.

Note 3: People who end up making a lot of value usually don’t think anybody would much want what they have. First sale comes as a nice surprise. People who have grandiose dreams of killing the market usually wander off into fantasyland and never produce anything anybody wants.

Note 4: It’s all marketing and distribution. Know your customer and be able to get close to them. If you can do that, you can experiment with things until you find something that works. The market comes first, the product second. Great founders weren’t guys with genius ideas who went forth in some heroic journey: they were guys who were able to grok markets; to deeply understand the people they were trying to help.

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Software: More Battlestar, Less Gunsmoke

When I was a kid growing up in the 1970s, we had a show on TV called “Gunsmoke”

Gunsmoke was a western, which meant folks dressed like cowboys. Our hero, Marshall Matt Dillon, struggled every week with capturing bad guys, cleaning the town up, and just generally doing cool cowboy stuff.

Gusmoke had been running on TV for 20 years by the 1970s. It went on to run another 10.

Even though I was just a kid, it didn’t take me long to figure out that Gunsmoke was mostly empty of content — every week it was the same old rehased plots, with guest stars showing up and always the same kind of ending to the show. Folks loved it, but there was nothing new happening. The guys at Gunsmoke were simply trying to see how many television shows they could make and sell before somebody shut them down.

This past week, major networks in the United States announced that they were shutting down a couple long-running soap operas. These things had been going for decades. “All my Children” ran for 41 years. “One Life to Live” ran for 43.

There’s a new type of show concept, however, used in “Babylon-5″ and “Battlestar Galactica” The show has individual episodes, but each episode is part of a long serialized story. The story has a beginning, middle, and finally, an end.

What a great thing it is to watch one of these shows! It’s something like a cross between a movie and a long novel. Over a period of years and dozens of hours, a long, intricate story plays out. When the end finally comes, it’s really neat.

As a small business owner, I used QuickBooks. I upgrade every few years, because QuickBooks makes me upgrade: they simply make their program break. If I want to continue using it, I have to pay. Doing business accounting hasn’t changed that much in the 15 years I’ve been a customer. After all, a double-entry bookkeeping system and chart of accounts are pretty standard stuff. But QuickBooks makes me pay anyway.

Likewise my tax program requires me to shell out money every year. While the tax code is always changing, completing taxes is basically running an expert system against the data I input. Such a system could easily be maintained in the public domain and would provide a useful service to everybody. Whatever I’m getting, by the 15th time I’ve purchased it, it’s doesn’t feel like it’s worth the money I’m paying.

Microsoft is making tens of billions of dollars from Windows and MS Office. Every couple of years, folks pay hundreds of dollars — for what? To continue to write letters? To have a file system with programs that run in a window when you click on them? Maybe really cool for the 1990s. Perhaps even a bit novel for the 2000s, But at some point enough already. The extra purchase isn’t worth any extra benefit.

I thought about this the other day as I listened to a friend of mine Tweeting about what a pain it was to install program X. He was convinced there was some great value to be had taking 3 or 4 hours of his time doing the upgrade. That may be true, but it got me to wondering: what if I tallied up all the time I’ve spent upgrading various pieces of software. Let’s forget the money for a second, assume I’m made of cash, what about the time involved?

Before I started the list, just thinking about it, it was pretty depressing. All those versions of SQL Server. All those versions of Windows. Of Office. Of various programming languages. Of various programming toolkits. Of various graphics programs and toolkits.

Wow! It could easily run into the hundreds of hours. Over a decade or two, perhaps thousands of hours. Each of those installs promised some new and shiny future: faster query times, better debugging, being able to mail merge a list of friends. These features sounded pretty cool when I read about them in a magazine or imagined how awesome they would be. But inevitably what I used them for was pretty much banal stuff: writing a letter, coding up a business tier, creating a button for a website. If I had a list of all the cool new features from each of those hundreds of installs — a list that would run into the tens of thousands of items — what, exactly, would I be using today to make somebody’s life better?

Somewhere there’s some guy who is able to create an application in 10 minutes and 3 lines of code with one arm tied behind his back using his favorite toolkit. This guy spent ten thousand dollars and three months learning how to do this. With this cool new awesome super-power, he will write exactly 1 app (if he’s lucky), and then next year it’ll be all new stuff. He will start over.

In between that time, there will be a lot of “noise”. Customers will have requirements. He’ll have to maintain existing systems. Perhaps he’ll be doing sales, or tweaking a website to bring in more contacts. New people might have to be trained. There will be seminars and business development assistance, customer relations, re-architecture discussions, and patches and upgrades to existing code.

I’m not the sharpest knife in the drawer, but it occurs to me that all of this “noise” is really what business is all about. It further occurs to me that in software, if you are making a solution for somebody, it pays to never make them completely happy. People are making a lot of money distracting us from the real purpose of what our technology tools are supposed to be doing. There is always be some magic bullet they’re brining out next quarter. All to do the one simple thing that we were basically happy with 20 years ago.

Everybody wants to do Gunsmoke and nobody wants to do Battlestar. They want to get on the gravy train, find the cash cow, and then milk the hell out of it. That would be a hoot, except I’m beginning to feel a lot like the cow.

Enough of this already. Write it up, make it configurable, publish the spec, and move on. End it. Do the right thing. Treat people as you would want to be treated.

More value, less flash. More substance, less glitter. More solutions, less fantasizing.

More Battlestar, Less Gunsmoke.

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