It seems like the most devastating career risk people face is getting stuck doing one thing for too long without branching out. As a result, they become unemployed or underemployed, doing work that is not challenging, poorly paid, or nearing obsolescence. To this end, I have a framework that I currently use to think about the next few years of career development and being proactive about learning. I think about it mostly from the software contracting and business consulting perspectives, although it could be applied to other disciplines. I think the big differentiator is how quickly the field changes and how much one feels a need to hedge their career options.

It’s useful to note that all of the following stages are generally in play at any given time. If you focus only on the future, you might starve. If you focus only on the present, you might become short-sighted and hurt long term results. The idea is that one should have:

• a list of skills that have general value today,
• a list of skills that are becoming obsolete, and
• a list of skills that just might become very useful in the near future.

Essentially, it’s skill diversification, much like people diversify stock holdings.

The Cash Cow

This is something that you are very good at and is currently in hot demand. It differs from a core competency because this is something that you can make money doing for the near foreseeable future. This is web programming (and others) in the late 1990s. This is probably Ruby (and others) today. It might be something else tomorrow. Hopefully you will have learned enough about tomorrow’s cash cow in the second phase (small bets) to be good at it when it changes.

There are different kinds of cows. It could be that COBOL programming is the thing you are best at and can easily find a variety of work for. This would fit the criteria that I laid out. You might have some that are solid, and some that are getting to be less profitable.

If you follow this general process, you will eventually have multiple focused competencies that can be used in the future. This helps ensure losses in one area can be absorbed in another. For example, if for some reason the technology that you are working in suddenly comes into huge legal problems, you are alright because you have other skills that are useful.

It helps to have some competencies be similar so that you can leverage what you know, but it also helps to diversify. In either case, being able to quickly shift what you know and learn something new is going to be a benefit. If dinosaurs could adapt to changing climates, they would have been in much better shape.

Small bets for the future

The race is not always to the swift, nor the battle to the strong, but that’s the way to bet.

~ Damon Runyon

It’s hard to predict the future. If you had a time machine, it would be pretty easy to beat the stock market (see Back to the Future: Part II.) What people commonly do today is to spread their investments out with the expectation that while any one of them might not do well, when all of the investments are taken into account they will be better off than if they held the investment money under their mattress. They also take on less risk than putting all of their money into one investment.

Likewise, the point of this phase is to place small bets on skills that you think will be big at least in the next few years. This satisfies the need to explore and contribute to new initiatives, while limiting the downside that new things may bring. For example, putting all of your investment in learning a proprietary technology and doing projects with it might be a good choice if it takes off. However, if it doesn’t take off, you might be out of a lot of time invested. Generally I’d rather invest than not invest because you end up learning something you can use later, but there is an opportunity cost to consider. Maybe you could have gotten a little better at something that would be more useful.

Later, when the future is clearer, you can double-down on the things that worked well. You gain information due to being an early adopter, and win out by having more experience in a given area. This could be working with Rails in 2006, or maybe some HTML5 + Coffeescript experimentation today.

Investors might be successful if they just diversify, but some do analysis as well to try to pick better stocks. With limited capital (time, attention, energy), it pays to think about what technologies might gain wide adoption in the future. Also, there is the added consideration of: “what skills do I want to have?” If mobile development does not appeal to you, it makes less sense to learn more about it than another hot technology.

A good example of some analysis in this regard is the Thoughtworks technology radar. They give an in-depth look at what technology choices to stick with, adopt, and move away from. You might agree or disagree with their choices, but if you are at least aware that a choice exists, you can potentially make an investment.

The earlier you invest in a technology the more likely that that investment will pay out over time. Instead of four good years, you might get six. Although on the flip side, you get more information as the technology gains adoption. However, as I previously wrote, being first in the mind is enough benefit to risk trying a few technologies publicly, even if they fail. Some of the time things don’t pan out, but the rest of the time it looks like you can predict the future. :)

Branching out

At the same time, it is possible to learn more about surrounding fields and seemingly completely tangential ones. This is the longest view possible and also has larger potential gains. It takes a long time to become an expert in one field, and it’s helpful to understand other fields to try to be at least oriented in a certain field. Again, this branching out takes into consideration that short term and medium term needs also need to be fulfilled for success.

If I am a specialist in software development, it helps to branch out to related fields, like project management and gaining experience with running a business. These are clear wins. If I am interested in using some newer software techniques, I might want to learn more about bioinformatics to make the most of the tools that already exist, or more about the hard sciences to see what the open problems are so I can contribute to them. Basically wherever it makes sense to steal concepts or work with a certain industry.

These are likely long-term studies. One does not become better at them without sustained effort. But half an hour a day for five years adds up (about 900 hours if you take some holidays off.) For some, this might be continued formal education, for others, self study. Regardless, it adds up to more interesting work and increased options.

The nice thing about studying something mostly new is that the return on investment is significantly higher than learning a little more about something you’re already an expert at. If a professional programmer spends twenty hours reading a programming book, will she even move the needle on their professional skills? However, if this same hypothetical and clearly stereotyped-as-introverted programmer reads about how to interact better with others, this has a potentially huge benefit.

Synthesis

I’ve been trying to work the career calculus link in all post, but failed thus far. Now I feel better. This one is all about learning every day.

I think the overall goal is to maximize long-term value creation and ensure cash flow stays at an adequate level. I think opportunities should be evaluated for their lifetime value and short term impact. Value could come in terms of financial compensation, contacts, experience, work environment, and more. If someone wants a Fortran programmer and I’d like to move away from that technology, the other aspects of the project had better be good enough to justify having more knowledge about Fortran and not being able to do something else.

I’ll have more to say on formal skill models on Thursday.

How do you think about opportunities and skill acquisition? What did I miss or overgeneralize? Thank you for reading and leave a comment with your thoughts!