Idea in Brief

The Problem

Algorithms are essential tools for planning, but they can easily lead decision makers astray.

The Causes

All algorithms share two characteristics: They’re literal, meaning that they’ll do exactly what you ask them to do. And they’re black boxes, meaning that they don’t explain why they offer particular recommendations.

The Solution

When formulating algorithms, be explicit about all your goals. Consider long-term implications of the data you examine. And make sure you choose the right data inputs.

Most managers’ jobs involve making predictions. When HR specialists decide whom to hire, they’re predicting who will be most effective. When marketers choose which distribution channels to use, they’re predicting where a product will sell best. When VCs determine whether to fund a start-up, they’re predicting whether it will succeed. To make these and myriad other business predictions, companies today are turning more and more to computer algorithms, which perform step-by-step analytical operations at incredible speed and scale.

A version of this article appeared in the January–February 2016 issue (pp.96–101) of Harvard Business Review.