I’ve been thinking about what makes a good business analyst, and in general the soft knowledge is harder to pick up in many cases than explicit knowledge like accounting or marketing. To that point, here are a few of the rules of thumb I try to follow. None of them is particularly sophisticated, but I include them because they are the issues that people tend to neglect when rushing to finish a project or a deliverable. These more ambiguous thought processes are often what separate good analysts (and for that matter decision-makers) from great ones.
The 80/20 rule
Most people have heard about the 80/20 rule (otherwise known as the Pareto rule), but it’s often ignored in practice. Consultants in particular, myself included, often have a hard time not throwing every analysis and every recommendation against the wall. Throughout your work, always ask yourself what will truly make the biggest difference and focus on that. Do your best to ignore other issues, or at least put them in an appendix (literally and figuratively) where they won’t distract people from the top priorities.
Be skeptical
I’ve come to realize that whenever I come up with an amazing conclusion while working on a project, there’s about a 50% chance that it’s an error. It could be due to bad data, a spreadsheet goof, or just not fully understanding the context of the situation. So, the more astounding your conclusion is, the more you should treat it with skepticism. Double-check your work and try to poke holes in your logic. There’s nothing worse than showing off your idea to your boss or client as a crowning achievement only to realize that it’s just a mistake.
The same is true when talking to people. Everyone in an organization has an agenda (shocking, I know), and many of them will try to feed you biased information to support their cause. The more you want to believe it because it’s “interesting,” the most you should take it with a grain of salt and try to confirm it.
Correlation does not imply causation
When I show a number based on customer interviews to clients, one of the questions they like to ask is whether it’s statistically significant. It’s not a bad question to ask, but if often misses the bigger point. The biggest risk isn’t that you don’t have enough data points, it’s that there’s some confounding factor that’s the true cause rather than the data you’re analyzing. Like epidemiology, business analysis is messy, and it’s very tough to be sure you know the real cause of something based on statistics. Look at the data, but don’t forget to rely on judgment as well.
Unintended consequences
Always ask yourself how recommendations may play out in real life differently from how you have planned. People will always try to game the system, and any change will almost certainly have unintended consequences. If salespeople get quarterly bonuses, you can be sure that some of them will knock it out of the park for three quarters, make enough money to be happy, and then mail it in the fourth quarter. If you offer customers a service for free, they will often use it even if they don’t really need it. Anticipating these consequences is by definition difficult. Rather than trying to eliminate them, try to make sure you can live with the ones that seem most likely.
The initial reaction to unintended consequences is to try to make processes more complicated to keep people from gaming the system. Unfortunately, that often does not work, confuses people, and results in a more bureaucratic organization. Which leads me to my next point.
Complexity cost
For every bright idea you come up with, consider the level of effort people will need to go through to comply with it, not just the financial cost. The ultimate example of ignoring the cost of complexity is the IRS tax code, which single-handedly keeps millions of people employed dealing with its more byzantine aspects. Don’t create industries within your company or your clients’ companies devoted to adhering to your processes unless it’s truly worth the cost. If your recommendations do add a significant amount of complexity, perhaps you need to figure out a way to simplify other processes in order to keep things in balance.
Of course, this isn’t intended to be an exhaustive list. What other rules of thumb do you keep in mind when thinking about business problems?