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The Psychology of Dangerous Knowledge Storytelling: Why Folks Misinterpret Your Knowledge

The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
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Introduction

 
Why do individuals misinterpret your information? As a result of they’re information illiterate. That’s your reply. Executed. The top of the article. We are able to go dwelling.

 

The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
Picture Supply: Tenor

 

Sure, it’s true; information literacy continues to be at low ranges in lots of organizations, even these which are “data-driven”. Nevertheless, ours is to not go dwelling, however to stay round and attempt to change that with the best way we current our information. We are able to solely enhance our personal information storytelling expertise.

If you’re seeking to refine the way you wrap information in narrative, with construction, anecdotes, and visible enchantment, take a look at this information on crafting a formidable analyst portfolio. It presents sensible ideas for constructing information tales that really resonate along with your viewers.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Realizing all this, we are able to be sure our information is known the best way we supposed, which is, in fact, the one factor that issues in our job.

 

Cause #1: You Assume Logic All the time Wins

 
It doesn’t. Folks interpret information emotionally, by means of private narratives, and have selective consideration. The numbers gained’t converse for themselves. It’s important to make them converse with none ambiguity and room for interpretation.

Instance: Your chart exhibits the gross sales have dropped, however the head of gross sales dismisses it. Why? They really feel the gross sales crew labored tougher than ever. This can be a basic instance of cognitive dissonance.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Repair It: Earlier than exhibiting the chart, present this takeaway: “Regardless of elevated gross sales exercise, gross sales fell 14% this quarter. That is probably on account of lowered buyer demand.” It offers context and explicitly supplies the doable purpose for the gross sales decline. The gross sales crew doesn’t really feel attacked in order that they will settle for the chilly truth of the dropping gross sales.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Cause #2: You Depend on the Unsuitable Chart

 
A flashy chart may seize consideration, however does it actually current the info clearly and unambiguously? Visible illustration is precisely that: visible. Angles, lengths, and areas matter. In the event that they’re skewed, the interpretation will probably be skewed.

Instance: A 3D pie chart makes one finances class seem bigger than it’s, altering the perceived precedence for funding. On this instance, the gross sales slice appears the largest on account of perspective, although it’s precisely the identical dimension because the HR slice.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Repair It: Follow utilizing chart varieties which are simple to interpret, similar to bar, line, 2D pie chart, or scatter plot.

Within the 2D pie chart under, the scale of the finances allocation is far simpler to interpret.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Use fancy plots solely in case you have an excellent purpose for it.

 

Cause #3: Correlation  Causation

 
You perceive that correlation shouldn’t be the identical as causation. After all, you do; you analyze information. The identical typically doesn’t apply to your viewers, as they’re typically not that versed in arithmetic and statistics. I do know, I do know, you assume that the distinction between correlation and causation is frequent data. Belief me, it’s not: two metrics transfer collectively, and most of the people will assume one causes the opposite.

Instance: A spike in social media mentions of the model (40%) coincides with a gross sales enhance (19%) in the identical week. The advertising crew doubles advert spend. However the spike was brought on by a preferred influencer’s unpaid evaluate; extra spending didn’t have something to do with it.

Repair It: Label relationships clearly with “correlated,” “causal,” or “no confirmed hyperlink.”

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Use experiments or extra information if you wish to show causation.

 

Cause #4: You Current Every part at As soon as

 
Individuals who work with information are inclined to assume that the extra information they cram onto a dashboard or a report, the extra credible {and professional} it’s. It’s not. The human mind doesn’t have limitless capability to soak in info. In case you overload the dashboard with data, individuals will skim by means of, miss vital information, and misunderstand the context.

Instance: You may present six KPIs directly on one slide, e.g., buyer progress, churn, acquisition price, internet promoter rating (NPS), income per consumer, and market share.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

The CEO fixated on a small dip in NPS, derailing the assembly whereas utterly lacking a 13% drop in premium buyer retention, a a lot larger difficulty.

Repair It: Be a slide Nazi: “One slide, one chart, one foremost takeaway.” For the sooner instance, the takeaway might be: “Premium buyer retention fell 13% this quarter, primarily on account of service outages.” This retains the dialogue centered on an important difficulty.

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

Cause #5: You’re Fixated on Precision

 
You assume exhibiting granular breakdowns and uncooked numbers with six decimal locations is extra credible than rounding the numbers. Mainly, you assume that extra decimal locations present how advanced the calculation behind it’s. Nicely, congratulations on that complexity. Nevertheless, your viewers latches onto spherical numbers, tendencies, and comparisons. The sixth decimal of accuracy? Complicated. Distracting.

Instance: Your report says: “Defect price elevated from 3.267481% to three.841029%.” WTF!? Folks will get misplaced and miss the truth that the change is critical.

Repair It: Around the numbers and body them. For instance, your report might say: “Defect price rose from 3.3% to three.8% — a 15% enhance.” Clear and simple to grasp the change.

 

Cause #6: You Use Imprecise Terminology

 
If the terminology you employ is imprecise, or the metric names, definitions, and labels aren’t clear, you permit the door open for a number of interpretations. The fallacious one amongst these, too.

Instance: Your slide exhibits “Retention price.”

 
The Psychology of Bad Data StorytellingThe Psychology of Bad Data Storytelling
 

The retention of who or what? Half the crew will assume it’s buyer retention, the opposite half that it’s income retention.

Repair It: Say “buyer retention” as a substitute of simply “retention.” Be exact. Additionally, at any time when doable, use concise and exact definitions of the metrics you employ, similar to: “Buyer retention = % of shoppers energetic this month who have been additionally energetic final month.”

 
Why People Misread Your DataWhy People Misread Your Data
 

You’ll keep away from confusion and in addition assist those that might know what metrics you’re speaking about, however aren’t fairly certain what it means or the way it’s calculated.

 

Cause #7: You Use the Unsuitable Context Degree

 
When presenting information, it’s simple to overlook the context and current the info that’s overly zoomed in or zoomed out. This will distort notion; insignificant adjustments may appear vital and vice versa.

Instance: You present a 10-year income pattern in a month-to-month planning assembly. Nicely, kudos for exhibiting the large image, however it hides a smaller, far more vital image: there’s a 17% drop within the final quarter.

 
Why People Misread Your DataWhy People Misread Your Data
 

Repair It: Zoom into the related interval, e.g., final 6 or 12 months. Then you may say: “Right here’s the income within the final 12 months. Observe the drop in This fall.”

 
Why People Misread Your DataWhy People Misread Your Data
 

Cause #8: You’re Too Centered on the Averages

 
Sure, the averages are nice. Typically. Nevertheless, they don’t present distribution. They disguise the extremes and, thus, the story behind them.

Instance: Your report says that the common buyer spends $80 monthly. Cool story, bro. In actuality, most of your prospects spent $30-$40, that means that only some high-spending prospects push the common up. Oh, yeah, that marketing campaign that advertising created primarily based in your report, the one concentrating on the $80 prospects. Sorry, it’s not gonna work.

Repair It: All the time present distribution by utilizing histograms, field plots, or percentile breakdowns. Use median as a substitute of the imply, e.g. “Median spend is $38, with 10% of shoppers spending over $190.” With that info, the advertising technique may be considerably improved.

 
Why People Misread Your DataWhy People Misread Your Data
 

Cause #9: You Overcomplicate the Visuals

 
Too many colours, too many shapes, too many labels, and legend classes can flip your chart into an unsolvable puzzle. The visuals needs to be visually interesting and informative; hanging the stability between the 2 is nearly a murals.

Instance: Your line chart tracks 13 merchandise (that’s 13 strains!) over 12 months. Every chart has its personal coloration. By month three, nobody can observe a single pattern. On prime of that, you added information labels to make the chart simpler to learn. Nicely, you failed! The info labels began resembling Jamie and Cersei Lannister — they’re disturbingly intimate.

 
Why People Misread Your DataWhy People Misread Your Data
 

Repair It: Simplify the charts. Present the highest three or 5 classes, group the remaining as “Different.” Present vital info solely; not all information you might have deserves to be visualized. Depart one thing for later, when the customers need to drill down.

 
Why People Misread Your DataWhy People Misread Your Data
 

Cause #10: You Don’t Inform What to Do

 
The info shouldn’t be the objective in itself. It ought to result in one thing, and that one thing is motion. You need to at all times present suggestions on the subsequent steps primarily based in your information.

Instance: You present churn has risen 14% and finish the presentation there. OK, everyone agrees the churn rise is an issue, however what needs to be performed with it?

Repair It: You need to pair each main perception with an actionable suggestion. For instance, say “Churn rose 14% this quarter, primarily in premium prospects. Advocate launching a retention supply for this group throughout the subsequent month.” With this, you’ve reached the last word objective of information storytelling — making enterprise selections primarily based on information.

 

Conclusion

 
As somebody presenting information, you could be an novice psychologist generally. You need to take into consideration the individuals you current to: their background, biases, feelings, and the way they course of info.

The ten factors I talked about present you ways to do this. Attempt to implement them the subsequent time you current your findings. You’ll see how the opportunity of misinterpretation decreases and your work turns into a lot simpler.
 
 

Nate Rosidi is a knowledge scientist and in product technique. He is additionally an adjunct professor instructing analytics, and is the founding father of StrataScratch, a platform serving to information scientists put together for his or her interviews with actual interview questions from prime firms. Nate writes on the most recent tendencies within the profession market, offers interview recommendation, shares information science tasks, and covers all the pieces SQL.


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