On failing to enter a partnership

I recently explored a business partnership opportunity that was quite exciting.  I had met the possible partner a few years ago.  He has technical chops (a software developer) and runs a company in a sector I’m very interested in.  He had a SaaS application that had real traction–users, revenue.  It wasn’t profitable, but looked like it could be shortly.  If we could find a way to work together, I could own the technical side of things and let him focus on selling and marketing.

However, it didn’t end up working out.  No blowups, thankfully, just a failure to find an arrangement that worked for both parties.

It was quite the emotional roller coaster ride for me.  A business partnership is like marriage without the sex, and so we were both cautious, but it was very easy to get excited about working together and building a big business.  It was all the more exciting to me because he’d done this before.

Here’s what went right:

  • We had open conversations about each of our financial needs.
  • He built a budget and business plan.
  • We used Skype for conversations so that non verbal cues were available.
  • We worked together for a month before hand, which gave us some context.
  • We checked references and had our spouses meet.
  • We planned to get together and work face to face.
  • We used Google docs, which was a great way to share spreadsheets and documents about the business.
  • I reached out to a few mentors to get advice.  Every single person said: “write your expectations down”.  Every one.
  • On the advice of one of the mentors, I read the Nolo books about LLCs, partnerships and business buyouts.  These were tremendous.  Not only did they lay out scenarios I had never considered (what if one of the members of the partnership is disabled?  what if you want to bring someone new in?  what if you want to give time rather than money in exchange for equity?  and many many more), they also give you sample agreements.
  • We set deadlines, both for documents and for coming to a final decision.  We stuck to those.
  • We parted amicably.

And here’s what went wrong:

  • We put off explicitly valuing the existing company until late in the game.  Then it became clear we had pretty different numbers in mind.  We should have done this as soon as we were both interested.
  • We didn’t really know each other, the month of working together notwithstanding.  Just as for investing, I am beginning to think that partnerships work best with lines, not points.
  • The budget and business plan were limited in scope (one year out, then some major assumptions about future years).  Hard to make more detailed predictions about the future, especially since the plan called for major new products.
  • I was in a different state than he was.  This would have made finding common service providers (CPA, mediator, etc) difficult.  No real fix for this, other than one of us moving.
  • Valuing an ongoing, non profitable bootstrapped business is really hard, because most of the value of the business is in the future.  I found some articles, but didn’t find much about this particular scenario.
  • We didn’t really nail down whether this was a partnership, a buy in to an existing business or a valued employee relationship.  Each of these have different equity implications.
  • I didn’t sell myself as well as I should have.

All in all a great experience.  I learned a ton.  Of course, I would have been happier if we could have reached agreement, but I understand why we ended up where we did.


Helping a friend gather data and reach prospects with gentle intros

coffee photo

Photo by My Aching Head

I had coffee with a friend the other day, and he shared a business idea. I thought it was an awesome idea–I certainly saw the need in the marketplace and believed he had the skillset and resources to execute on the idea.

He’s still in the exploratory phase, so I offered to send gentle intros to people in my network who I thought would benefit from his idea. (The target market is anyone with a custom web application that makes money, or anyone who builds custom web applications and is looking for a way to provide ongoing support–if that is you, contact me if you would like to learn more.)  I asked him to write a small spiel that he’d feel comfortable with me sharing.  If you are thinking of doing this, make your friend write a spiel for you.  If they can’t write a spiel, chances are they won’t be good at follow up and your intros will be wasted.

Then, I went through my LinkedIn network and put contacts into categories:

  1. this person (or the company for which they work) might want to partner with my friend
  2. this person (or the company for which they work) is a possible client for my friend’s offering
  3. this person might know people who are in categories 1 or 2.
  4. this person (or the company for which they work) is not a good fit for what my friend is working on
  5. who is this person?

And then I sent soft pitch emails to almost everyone in categories 1, 2 and 3.  The content varied based on which category someone was in, but for category 1, the email was something like:

I have a friend who owns a hosting company who is looking to talk to consulting companies about a possible new product he is thinking about offering.  Here is his spiel:

 

[…spiel from friend …]

 

I wasn’t sure if this kind of software maintenance was something that your company wanted to keep inhouse, or if you would be interested in discussing this with him.  I wanted to check before I did intros.    Is this something you think is worth learning more about?

This way, my friends and contacts on LinkedIn don’t get spammed from someone they don’t know.  Instead, they get an informative email from me, asking if they want to learn more.  If they do (and about 10% did), I do mutual introductions, and then the ball is in their court.  (Side note: here’s a great intro email etiquette guide.)

Why did I do this?  Well, there were a couple of reasons.

First and foremost, because I thought it would be a win win for both sides.  My friend gets more data about his offering and how the market will react to it.  My contacts/friends on LinkedIn learn about a new product from a trusted source.

Second, I was able to do some social network housecleaning.  I was able to ‘unlink’ with all people in category #5–it’s always nice to clean up your social graph.

Third, I reached out to people and had some interesting conversations.  Some folks I hadn’t talked to in years.  It’s good to reach out to people, and always better to do so with something of use to them, rather than a plea for work.

This was a fair bit of effort (a couple of hours).  I can’t imagine doing this monthly, but once a quarter seems reasonable, especially if I’m reaching out to a different segment of my network each time.  And I don’t have to do the whole process every time–spiel, linkedin, soft pitch, intro.  I actually like scanning news sites and simply sending interesting articles to old contacts: “Thought you might be interested in this <link> because of XXX and YYY”.  Those are super simple to send, and again, provide value and raise your profile.

Next time you talk to a friend who has a great idea, who can execute on it, and who will follow up with anybody you introduce them to, consider reviewing your social graph for prospects.  Gentle intros can benefit all three of you.




Denver Bootstrappers Lunch

boots photo

Photo by liftarn

My friend and former colleague Corey Snipes has been working to get a Bootstrapper’s meetup off the ground in Denver. This is a small group (limited to 12, I believe) of people who are building products (typically software) and self funding. I believe most of the members are in the solopreneur mode (I know Corey is).

I imagine this kind of support group would be fantastic–certainly I had a similar group when I was a consultant in the past, and bouncing ideas off of others in similar situations made the struggle much easier.

I’ve not made this meetup yet because, a) I’m not sure I’m bootstrapping (and you know what, if you aren’t sure you’re bootstrapping, you aren’t bootstrapping!), b) I live in Boulder and Boulderites have a hard time leaving the Boulder Bubble, and c) Wednesdays in general are tough days for me to do anything outside of the house.

If you are a bootstrapper in the Denver area, take a look.


Open Source, Consulting and Building SaaS Products

construction photo

Photo by JD Hancock

I was browsing Hacker News the other day, and ran across this article, lamenting how difficult it was to support a company with an open source project and that insomuch as one could, consulting generated far more revenue than selling SaaS services like hosting.  For the record, I’ve never touched LocomotiveCMS.  From a brief glance, it looks nice.

While I feel for them, I think that they have alternatives:

  • Sell premium support.  Right now, it appears the only way to get premium support is to host with them, and it seems that many clients are more interested in self hosted solutions.  Makes sense–if you are a rails developer (the target market for this CMS) you already have a hosting solution.  But if premium support was offered separately, they could hire someone (possibly part time) less skilled than Didier, the primary developer, and have them take care of tier 1 support.  And still offer a warm fuzzy feeling for harder problems, which would escalate to Didier.  Companies like to pay for that kind of service, even if they don’t always use it.  This strategy would also decrease the amount of revenue needed to hire someone to help Didier (customer server folks are less expensive than developers).
  • Sell an ebook (or a couple).  These are far easier to create and sell than a SaaS product.  (I use leanpub!)  It could be an ‘authoritative guide to LocomotiveCMS’ or just focus on one part.  Since Didier knows which questions he often answers for people who have paid him money, he’s probably got a very good idea of where the pain points are.
  • Someone suggested this in the comments, but a marketplace for plugins to LocomotiveCMS seems like a natural way to go.  Again, i don’t know that community, and marketplaces for CMSes can be hard to kick start, but this is worth evaluating.
  • I’m sure there are others.  Here’s an exhaustive list of business models, courtesy of the AVC community, so if I were them, I’d review and see what was a fit.

In my comment on the HN post, I talk about how products often face a “round peg in an elliptical hole” problem. I meant that products often solve 80% of the problem for 80% of the users.  They also require users to change their processes (more crystallization).  Typically there’s just enough offset that people feel cognitive drag.  (Of course, the same thing usually happens with custom solutions, you just don’t know that until you are done.  Doh!)

Especially in crowded markets, like CMSes, it is far far easier to sell enough hours to make a living customizing a solution than it is to sell enough products to make a living.  Brennan Dunn covers this ground well.  Every consulting company I’ve ever seen or been a part of, and every consultant I’ve ever known (except the ones who were contracting for one client and really were employees with more flexibility), dreams of transitioning from non scalable consulting by the hour to scalable product sales.  One friend even had a name for it–the “von MacIntyre machine”, which would make money while he slept.

But it’s hard.




#TBT: Precision and Accuracy in Software

I originally wrote this in Dec of 2004. I still think that having someone who can answer engineers’ questions authoritatively increases productivity (of the engineer). However, now I’d emphasize that developers need to spend some time learning their domain to gain some intuition, and truly great business software engineers will learn when to bump a question up to a business person and when their intuition can be trusted.

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Back in college, when I took first year physics lab, there was a section of the course that focused on teaching the difference between precision and accuracy in measurement. This distinction was crucial in experimental physics, since measurement is the bedrock of such experimentation. Basically, precision is how many digits of a measurement actually mean something. If I’m measuring the length of a room with my stride (and found it to be 30 feet long), the precision is less than if I were to measure the length of the room with a tape measure (and found it to be 33 feet, 6 and ¾ inches long). However, it’s possible that the stride measurement is more accurate than the length found with the tape measure, that is, it reflects how long the room actually is. (Perhaps there’s clothing on the floor which adds tape measurement, but which I stride over.)

These concepts aren’t just valid in physics; I think they’re also useful in software. When building a piece of software, I am precise if I build what I say I am going to build, and I am accurate if what I build actually meets the client’s business needs, that is, it solves the business problem. Almost every development tool either makes development more precise or more accurate.

The concept of precision lends itself easily to automation. For example, unit testing is rapidly gaining credence as a useful software technique. With unit testing, a developer writes test cases for each part of their code (often at the method level). The running of these tests ensures that code is actually doing what the developer thinks it is doing. I like writing unit tests; it gives me comfort to know that corner cases are taken care of and that changes to code can be fairly easily regression tested. Other techniques besides unit testing that help ensure precision include:

Round tripping: using a tool like TogetherJ, I can ensure that the model (often described in UML) and the code are in sync. This makes it easier for me to verify my mental model against the code.

Specification writing: The more precise a spec is, the easier it is to translate into code.

Compilers: the checking that occurs at compilation time can be very helpful in ensuring that the code is doing what I think it is doing–at a very low level. Obviously, this technique depends on the language used.

Now, precision is needed, because if I am not confident that I understand what the code is doing, then I’m in real trouble. However, accuracy is much more important. Having a customer onsite is a great example of a technique to ensure accuracy: you have a business domain expert available all the time for developers’ questions. In this situation, when a developer stumbles across a part of the business problem that they don’t quite understand, the don’t do what developers normally do (in order of decreasing accuracy):

  1. Ask another developer, which works great if the target audience is developers, but not so well otherwise.
  2. 2Best approximation (read: guess at the correct answer).
  3. Ignore the issue. (‘I’ve got a lot more code to write before I can go home today, and we’re shipping in two weeks. We’ll just let the customer discover it and deal with it as a bug.’)

Instead, they have a real live business person, to whom this software really matters (hopefully), who they can ask. Doing this makes it much more likely that the final solution will actually solve the business problem. Other techniques to help improve accuracy include:

Issue tracking software (I use Bugzilla): Having a place where questions and conversations are recorded is truly helpful in making sure the mental model of the business user and the programmer are in sync. Using a web based tool means that non-technical users can participate and contribute.

Specification writing: A well written spec allows both the business user and developer to have a sense of what is being built, which means that the business user can correct invalid notions at an early stage. However, if a spec is too detailed, it can be used to justify precision at the cost of accuracy (‘hey, the code does exactly what’s specified’ is the excuse you’ll hear).

Spring and other dependency injection tools, as well as IDEs: These tools help accuracy by decreasing the costs of changing code.

Precision and accuracy are both important in software engineering. Perhaps the best way to characterize the two concepts is that precision is the mapping of the programmer’s model of the problem to the computer’s model, whereas accuracy is the mapping of the business’ needs to the programmer’s model. However, though both are needed, accuracy is much harder to obtain. Knowing that I’m building precisely what I think I’m building is beneficial only insofar as what I think I’m building is actually what the customer needs.



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