Last week I posed the question, How can you build a budget before you know the work involved?

Yesterday I wrote about one strategy, working in phases. Today I’ll take up a second strategy. (Remember, don’t read anything into the order in which I’m writing about them.)

Strategy 2: Utilize Risk Premiums

Let’s start with a reductio ad absurdum example. I bought a ginormous (my daughter loves that neologism) garden stake the other day at Home Depot. I had to ask two “associates” — floor salespeople in less pretentious times — where they were; the first didn’t know, but the second walked me to them, while telling someone who called on her walkie-talkie cellphone that she couldn’t do whatever it was they wanted right now because she was walking a customer to the gardening area. Once there, it took us together a couple of minutes of they-must-be-here-somewhere time to spot them.

Other customers just go get them, being smart enough to figure out where they’re likely to be.

It cost Home Depot considerably more to support my $4 purchase than it costs them for other garden-stake customers. Should they have charged me more?

Obviously, stores don’t work that way. If they can solve the problem and make money, other industries can learn from the example.

How does it work? Obviously they average into the price the general cost of servicing a purchase. Some customers are more work than others. And sometimes a customer will make you work for one item but self-serve on ten others, which is what I did. You build up your data, take your best shot, and recognize that if you got it right — or at least didn’t get it wildly wrong — you’ll make your profit over the long term.

Apply the same method to pricing legal services. If delivering service X costs you $50K on average, almost always costs between $40K and $60K, and occasionally but rarely costs $10K or $100K, you have a distribution curve, sometimes inaccurately called a bell curve or Gaussian distribution. The risk premium is the difference between the average or median cost and an amount that offers at least a bit of protection against outliers on the high end, the $100K deliveries. Thus you might price service X based on a cost of $55K or even $60K.

There is a difference between median and average that I won’t get into here in detail. Basically, median discounts outliers, most often high-end outliers, while average factors them in somewhat. An outlier is a data point that is well away from the bulk of the data points in your data set. For example, at one point in my work at Microsoft, I was in a conversation with three folks who were roughly my peers plus Bill Gates. The average net worth of those in the conversation was billions of dollars, but I guarantee the only one in the group with an 11-figure net worth — or 10 or 9 or probably even 8 figures — was Bill. Choose wisely between average and median; the basic starting point is whether you want the outliers to be incorporated into the number or want to handle them separately. In the service X example, to say nothing of the net-worth example, I’d probably want to examine outliers separately and thus choose to talk about median rather than average.

Summary

This method is a toolbox requirement for value-based billing a/k/a alternative fee arrangements, in particular flat or fixed fees. I have written other articles that offer more detail, and you can find more information in my book Legal Project Management. I also spend considerable time detailing this method at seminars and Master Classes.

Of the five strategies, this is perhaps the most “technical,” requiring the kind of analysis law firms aren’t renowned for undertaking. I believe it’s time for that to change; this strategy can pay huge rewards to firms that implement it effectively.

Note: I’m traveling the rest of this week, at LegalTech/West in Los Angeles, where I’m speaking Wednesday. I’ll post more in this series as I get a chance this week, but I expect the bulk of it may go up next week. Stay tuned, and here’s to your financial as well as project success. Financial and project success go together like Keith Richards and Mick Jagger — who, incidentally, was a student at the highly prestigious London School of Economics until his own side project — a/k/a The Rolling Stones — became a going concern. So I bet Mick understands this stuff. (Exercise for the reader: Insert at least five project-management puns based on Rolling Stones song titles — starting, of course, with Time Is on My Side.)