Between a sitting US president who refused to accept he lost an election and millions willing to label COVID-19 a “hoax,” 2020 was a banner year for those who reject data and objective facts. Some have gone so far as to assert that we are living in a “post-truth” era.

Even in business, an area where you might expect the role of accurate data to be critical, there is often a reluctance to embrace data.

Why is that—why would a CEO reject information that she needs to make critical business decisions? And how do those of us who value data get past such rejection?

The reasons they resist

Business leaders resist data for a variety of reasons. Sometimes, like everyone else, they simply get overwhelmed with all the data and information that 21st-century life throws at us. Even with a topic as grave as COVID-19, daily tallies of new cases and deaths can become numbing over time. It’s not even conscious rejection — more a kind of avoidance, or data fatigue.


Other times business leaders actively mistrust data, often because the numbers disagree with their existing beliefs. For example, imagine a company’s human resources department has for years told the executive team that the company scores high on employee surveys. If you present them a detailed data analysis showing a higher turnover rate than their industry average, they may reject it because it seems contrary to what they have been told all along. Related to this is the very human tendency to cherry-pick data to support the opinions we already hold, and ignore data that might contradict our established views.

Perhaps the most challenging (but nonetheless common) scenario is that a CEO is not ready to take in what the data say. Typically there is some motivating business need behind the initiative to gather data in the first place: the company wants better sales conversion on its leads, or insights into hiring. But that doesn’t guarantee that the people who need to act on the data are prepared to do so, much less that they have a plan of action. This is especially true for decisions that are difficult or painful to make, such as replacing a department head or killing an unsuccessful product line.

In this scenario, executives may perceive, consciously or unconsciously, that data actually harms their position. It’s one thing not to act because you don’t know the underlying reality. But if you do know the underlying reality and still don’t act, then you risk being held accountable. It reminds me of the classic line from A Few Good Men:  “You can’t handle the truth!”


When confronted with these obstacles, neither the quality nor the volume of data matter much. If you don’t believe a news story, you’re not going to be persuaded if someone hands you ten more copies of it. Similarly, no amount of methodological tweaking or longitudinal analysis is going to move leaders off of their positions. 

So how can professionals convey what they need to, in the face of passive or active resistance? What follow are the techniques my data firm uses, which can be adapted in a variety of business settings.

Emphasize data are a means, not an end

When a company sets out to collect data, there is typically a quantifiable problem or question for which they are trying to solve; e.g., “Have we made our hiring more diverse in the last year?” But the data gathered around that question isn’t itself the ultimate solution. Whether the answer to that hiring question comes out yes or no, that doesn’t answer the more important questions “Why?” and “What do we do to improve?”

It’s natural for those who collect data to think of their product as an end, but it will only ever be effective if it is a means. Making sure that every relevant party understands this distinction is crucial to the success of a data-driven strategy. Data is only meaningful when paired with the will and resources to act on it. So, to continue with the hiring diversity scenario above, the company needs a plan to improve recruiting if the answer is “no,” or, if the answer is “yes,” to figure out what changed and whether to double down on those efforts. 

Ditch the dashboard mindset

Almost everyone in business has been seduced by the data dashboard, the single magic window onto a website’s or business’s performance that conveys all the information users need to know. While of course dashboards are helpful, they assume that the user knows the context for the data, which is rarely the case. 

Instead of thinking about data as merely a stream of numbers or updates to splash onto a dashboard, it’s far more effective to harness data into a story. And just like a powerful novel or movie, a data story should have a beginning, a middle and an end. Good data storytelling requires anticipating how major stakeholders will respond to the data, and building those reactions into the narrative. This also means focusing not merely on “what the data say,” but also on what specific actions the data impels decision-makers to take. 


And remember: ever since the original prehistoric cave drawings, humans have learned from visual aids. The field of data visualization has grown by leaps and bounds in the last decade; look to major newspapers like The New York Times and Wall Street Journal for inspiration on turning data into effective stories and visual experiences.  

Use data as a pain-reliever

Most business leaders, no matter how data-fatigued or data-adverse they might be, will respond to appeals to their bottom lines. Especially in cases of inertia (see above), data need to be framed with leaders’ self-interests in mind. Make it clear that data can help remove pain points from their business, and help the enterprise succeed in the future. 

To return to the diversity in hiring example above, leaders may well be numb to stats showing lack of diversity among management or senior leadership. Simply harping on those numbers may merely yield indifference or active mistrust. However, emphasizing the bottom line impacts of improved diversity — from better financial returns to greater employee satisfaction and enhanced recruiting — can improve receptivity to data findings and, more importantly, lead to concrete action.  

When you present data in the business world to make an argument, you won’t win every time, because you are up against fundamental qualities of being human. But you will increase your odds of victory by understanding why your listeners want to fight the data, and demonstrating to them how accepting data will help their business. Ultimately, data is a tool to help people see the truth and, in turn, create a better future — provided we’re willing to use it.

Ryan Wong is an engineer turned CEO of Visier, a people analytics company.