Accuracy and Precision
In conversation, the terms accuracy and precision are used interchangeably. But they mean different things, and the difference can play a big role in the growth of a business. Before getting into early stage companies I spent most of my time in a science lab, which couldn't have put me in a worse position to understand how accuracy and precision affect startups.
In science, precision is valued above accuracy. In this case it's called repeatability, and being able to run the same experiment multiple times with the same results is a good thing. After all, most fields of science expect results with 95% confidence, which means that your error rate can be no higher than one in twenty. So controlling for all possible variables and demonstrating repeatability are of utmost importance.
In startups, this kind of thinking will get you killed on two fronts. First, achieving 95% confidence is impossible in business. If you can collect enough data to be right 60% of the time you'll get buildings named after you. You can't possibly control for all variables; you're lucky if you have the time and money to even understand what they are. This can be summarized with with the old business adage "it's better to be generally correct than exactly wrong."
Second, running a variety of experiments that yield different results is a positive thing. If all of your business experiments look similar and yield similar results, you haven't learned very much, and you certainly haven't explored the full set of possibilities. In all likelihood there is a better outcome elsewhere, open for a competitor to find and exploit. In other words, you don't want to optimize toward a local maxima while missing a bigger opportunity.
Take marketing strategy, for instance. Good entrepreneurs usually try a number of diverse strategies -- perhaps PPC, plus SEO, plus events or social media -- to get a few data points around what works and what doesn't. Thinking about this as a fractal and trying a few diverse strategies within each of these categories can pay dividends as well. While most of these experiments will likely fail, they can provide multiple starting points from which to drill down and test further, or provide guideposts to the right answer.
So while the precision of experiments is not so critical, accuracy is key. With all your experiments, you want to be close enough within range to triangulate the right answers through experiments. While precision without accuracy is dangerous, being neither precise nor accurate is useless. Trying five wildly different social media engagement strategies for a beta product may yield a false negative if social media isn't the right acquisition channel; picking a wider variety of tactics may have generated more interesting results.
Business isn't science, but you can be scientific about it. Having the right experimental framework can go a long way to saving time and money.