HBR STAFF

You’re sitting at a Very Important presentation related to a Very Important decision. The presenter is trying to convince senior management in your company to invest in a large, expensive project, say setting up a new robotic production line in one of your plants. Given that your company has always used more traditional manufacturing techniques and that you’ve just watched the latest Terminator movie, this seems like something of a departure, and you are naturally wary.

And then the presenter shows a graph to illustrate their point about increases in manufacturing capacity. It’s not particularly fancy. It has only a few words and numbers, and two bars. One is clearly higher than the other.

Suddenly, this prospect seems a lot more attractive—there’s clearly data to back it up! And before you know it, the company has decided to pour millions of dollars into an uncertain future.

Graphs have a bad reputation for being used as a cheap means of impressing an audience—whether they communicate meaningful information or not. While the anecdote above is extreme, it nevertheless illustrates this common, but previously untested, wisdom. Our recent research at the Cornell Food and Brand Lab, published in the journal, Public Understanding of Science, actually bears this out: the presence of even trivial graphs significantly enhances the persuasiveness of the presented claims.

You and Your Team Understanding Analytics Get over your fear of data.

In a series of studies investigating promotional messages for medication, participants were randomly assigned to graph or no-graph conditions. In both cases participants read about a new medication that boosts immune function and reduces occurrence of the common cold, ostensibly developed by a large pharmaceutical company. They were presented with information about the medication’s function and its performance in tests. (The information given was minimal, akin to what might appear in a company’s press release or advertising.) They were then asked to rate the medication. Including a graph increased its perceived effectiveness by as much as 23%. In another study, 96.55% of those who saw the graph believed the medication would reduce illness, versus 67.74% of those who did not see the graph. (Here’s a visual representation of some of our results: do you trust me now?)

An initial, exploratory study for business decisions revealed similar effects. The percentage of people willing to invest in a costly change to the service department of a hypothetical company increased from 90% (the investment was fairly attractive from the outset) to almost 100% (98.6%). (While this may seem like a small change, the results couldn’t be any bigger because the graph condition reached the top of the scale. We suspect that starting with less appealing prospects might produce larger changes, but further research is needed.) More notably, the amount participants were willing to spend on the improvement also increased by almost 50%, from $860K to $1.2 million dollars.

The likely reason? Graphs have a scientific halo—we associate them with science and objectivity. As a result, graphs give an aura of truth to the information they accompany. We found the same to be true for chemical formulas (and other research has shown that brain scans and scientific jargon operate in a similar way). Our effects were stronger for those who expressed a greater belief in science, too, which reinforces the fact that people connect science with veracity. The higher participants’ agreement with the statement “I believe in science,” the greater were the effects of graphs on ratings of medication effectiveness.

One of the most striking things about our results is that the graphs were simple to understand, and added nothing beyond the information that was provided in writing. (The chart below duplicates what participants read: that the drug reduced the incidence of illness by 40%.) The graph’s presence did not improve comprehension or retention of the information presented (yes, we checked), but did increase belief in the effectiveness of the promoted medication. In other words, graphs do not need to be impressively complicated, or even informative, to have a persuasive effect. It’s possible, though not proven yet, that graphs that do impress or add substance might have an even bigger impact.

Naturally, the impact of graphs is likely to vary based on context. For instance, if someone leans towards accepting the associated claims from the outset, the presence of graphs may reinforce what they already believe. And conversely, they may be less persuasive when someone suspects the source of the information. If you give a presentation that sounds dubious in other respects, graphs might not save you.

What does all of this mean for presenters and consumers of graphs? Awareness of the persuasive power of such devices is a good first step. It’s important for audiences to assess the more objective elements of the information rather than being swayed by heuristic devices. Is there scientific support for the claims being made? What is the graph telling you? Remember that sometimes, a graph is just a graph.

Presenters attempting to win people over should use graphs sparingly, restricting their presence to the illustration of truly necessary information. Before including a graph or other scientific element as support for your argument, ask yourself: does this add anything beyond flair to my presentation? Does it make the information clearer?

My intention is not to argue against the use of graphs as a rule. Graphs can help decision makers understand and utilize information. Many people are visual thinkers, and can better absorb and comprehend pertinent information when it’s presented graphically. Graphs can be used in support of a verbal argument and provide additional evidence that may be more easily processed visually.

Despite the usefulness of graphs, managers should be cognizant of the biases that predispose people to believe them because they “look scientific.” Considering the information offered by graphs and using them to assist understanding is not a bad thing. But don’t let their signaling of scientific credibility sway you in favor of unmerited business decisions.