The Limits of Neuroscience in Business
Before investing in products or services that claim to provide business insights based on brain research, managers should understand several key issues with neuroscientific solutions.
Topics
Frontiers
Neuromarketing. Neuromanagement. Neurofinance. Attempts to inject brain science into the business world have been nothing short of comprehensive — and, quite possibly, oversold.
Proponents of neuroscience in commercial settings argue that it can provide key insights that help explain consumer and employee behavior — insights that can ultimately be used to develop more appealing products and services. While that may be true to a certain extent, managers considering such applications aren’t served by broad claims that gloss over important caveats concerning the practical application of brain science.
Get Updates on Transformative Leadership
Evidence-based resources that can help you lead your team more effectively, delivered to your inbox monthly.
Please enter a valid email address
Thank you for signing up
This article aims to help managers critically evaluate vendor offerings based in neuroscience. In particular, there are three very significant issues that business leaders must understand if they hope to make informed decisions regarding investments in such products.
Issue 1: Proxies
One high-profile example of neuromarketing involves researchers who used brain data from individuals watching movie trailers to predict ticket sales. This led to claims that brain imaging could be used to refine marketing practices and boost box-office revenues.
To understand why such claims are questionable, let’s explore the problem with proxies.
A proxy is any indirect measure used to predict the outcome of something that is otherwise difficult or impossible to measure directly. For instance, baseball scouts often use minor league on-base percentage as a proxy to predict how frequently players will get on base in the majors. This indirect measure allows teams to make educated guesses without spending millions of dollars calling up every encouraging prospect.
For a proxy to be considered meaningful within any given field, it must meet three specific criteria:
- Reliability: Because correlations inferred from small data sets often prove inaccurate or erroneous, good proxies are derived from very large pools of data.
- Validity: Because it’s theoretically possible for any single experiment to generate highly variant outcomes (like when the European physics laboratory CERN erroneously detected particles moving faster than the speed of light), good proxies have been independently replicated.
- Utility: Given the finite nature of resources and capital, good proxies deliver a comparatively favorable cost-benefit ratio.
In baseball, minor league on-base percentage is reliable because it has been derived from thousands of players over several decades; it’s valid because it has been replicated using player data from dozens of independent international leagues; and it’s useful because it costs little to measure yet correlates well (0.53) with major league on-base percentage.