“Life is really simple, but we insist on making it complicated.” ― Confucius
It seems that simplicity has always been embraced. Confucius, Leonardo da Vinci (“Simplicity is the ultimate sophistication”), and Albert Einstein (“If you can’t explain it to a six year old, you don’t understand it yourself”) are but a few of the world’s great thinkers who have emphasized the virtues of simplicity.
Simplicity is comfortable. People simplify the world around us into easy-to-understand “rules” to help cope with the myriad of decisions we must make each day. Managers (being people) also like to simplify. They like simple easy-to-understand data analyses and simple answers. Somewhat paradoxically, it seems that senior managers like even simpler answers (This observation is based on how often we hear clients make the request to “dumb it down to a one-pager so that senior execs can understand it”).
Frequently, a data analysis can be boiled down to a few simple easy-to-understand metrics like “average.” Or we can use simple measures of the relationship between two phenomena such as “correlation.” And since human brains like simple patterns, we can assume the world is linear and use linear regression to predict future outcomes (and fool ourselves into believing that since we’re using “sophisticated” analysis methods, the prediction will come true).
But sometimes, simple measures are misleading. Averages aren’t very helpful when the underlying data has a lot of variation, or when the data doesn’t fit a normal distribution or “the classic Bell Curve” (e.g. bimodal distributions can reveal natural market segments). Linear regression isn’t very helpful when the goal is to solve for an optimal point (e.g. what is my optimal marketing budget?)
Sometimes we simply need to use complex analysis approaches to identify the best solution to a problem. Perhaps another quote (also attributed to Albert Einstein) better expresses our data analysis goal: “Everything should be made as simple as possible, but not simpler.”
And sometimes, even a series of in-depth analyses can leave us more baffled … that’s a topic for another blog.
“If you’re not confused, you’re not paying attention.”
― Tom Peters, Thriving on Chaos: Handbook for a Management Revolution