Pop Quiz: Guess What This Chart Shows

Reposted from September 2022

Go ahead and make a guess from the options below. Then scroll down to see how your response compares with others’ and what the answer is!

Keep scrolling!

The answer: The decline in child poverty in the U.S.


As reported in The New York Times, “the sharp retreat of child poverty represents major progress and has drawn surprisingly little notice, even among policy experts.” Read the article (and view the detailed line chart) to learn more about the role of government aid in lifting children and families out of poverty.

I share this chart with you—in this way—for a couple of reasons:

1) It’s an engagement strategy you can use. Rather than present a list of stats to your audience, you can engage them in your data by first quizzing them on an interesting, fun, or counterintuitive finding from your data.

2) Bad new bias. Bad news is more likely to be reported than good news, possibly because bad news sells, according to this article citing various research. Perhaps because of that bias, we may be more likely to assume a chart is telling a negative story. This chart is a reminder of the importance of taking a broader view to gain a more balanced understanding of an issue.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Make Data Viz Accessible

Data visualization is the translation of data in the form of words and numbers to a visual format, using color, size, shape, and placement to convey trends and patterns in the data which can be much less apparent when looking at tables of numbers or words. Thus data viz communicates best to those with full visual capabilities. To make charts, graphs, and maps accessible to those with visual impairment, we must translate the meaning of a visualization back into words, which can be a challenge. Amy Cesal's article, Writing Alt Text for Data Visualization, can help us address that challenge.

Alt text is a brief description meant to provide the meaning and context of a visual item in a digital setting. And although Cesal notes that, in most cases, it’s impossible to write something short that conveys the whole meaning of a visualization, she maintains that an incomplete description is better than none at all. Here are Cesal’s simple guidelines for alt text for data viz:

Chart type: It’s helpful for people with partial sight to know the chart type. This information provides context for understanding the rest of the visual. Example: Line graph.

Type of data: What data is included in the chart? The x and y axis labels may help you figure this out. Example: number of clients served per day in the last year.

Reason for including the chart: Think about why you’re including this visual. What does it show that’s meaningful? There should be a point to every visual and you should tell people what to look for. Example: more clients are served during the winter months.

Cesal also suggests that you include a link to the raw data somewhere in the surrounding text.

For a deeper dive into this topic, checkout Image Description Guidelines from the Diagram Center.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Create Data Stories That Actually Engage People

Here’s a sneak preview of a workshop I’m doing on September 26th. I’m sharing the first few slides below. Click on the right to advance through them.

Presentation Preview by Amelia Kohm

To tell a story in a way that humans can understand and get behind, it helps to understand humans’ powers and challenges when it comes to consuming data. Then we can make better charts, maps, and graphs (aka data visualizations) and present them in a way that humans can absorb.

I hope you can join me on September 26th, 8:00 am - 9:00 am PT | 11:00 am - 12:00 pm ET. Click HERE to register.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Add This To Make Your Charts Memorable

Copy of 60-SECOND DATA TIP_3.png

Reposted from October 2019

Look at the two images below.  Which catches your attention? Which do you think you are more likely to remember?

Edward Tufte and other data viz gurus have warned us against “chartjunk” which is anything that is not necessary to comprehend the information represented on a chart, map, or graph. The idea is to get rid of distractions and focus attention on the data.

But some research by Michelle Borkin and colleagues points in a different direction.  In an experiment, they showed participants charts with and without various elements that might be construed as chartjunk like photos and drawings. They found that such images not only did not hinder memory or understanding of visualizations, they appeared to serve as “visual hooks into memory.”  Such visual hooks are important because what we perceive is based, in part, on what we expect to perceive due past experiences.

The idea of not loading up a chart with a lot of junk competing for attention is still a good one. But some images, if they are closely related to the data and connect with what folks already know, can help viewers to focus on and absorb information.

For more on how to capture attention with data visualizations, check out this data tip.

Sources:

M. A. Borkin et al., "Beyond Memorability: Visualization Recognition and Recall," in IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 1, pp. 519-528, 31 Jan. 2016.

 P. Kok et al., “Associative Prediction of Visual Shape in the Hippocampus,” in Journal of Neuroscience 1 August 2018, 38 (31) 6888-6899.

 Photo by Nery Zarate on Unsplash

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Charts That Changed The World

This week’s tip is to check out this video from The Royal Society in which Adam Rutherford shares five data visualizations that have changed the world. Admittedly, this will take you more than 60 seconds to watch (it’s 6 minutes). But it’s worth it. Rutherford shares four classic charts. Two of them clarified a problem so well that they led to solutions. He also shares a chart that drives home the dangers of visualizing lies and thus making them look legitimate. If you’d like to learn more about these charts, I’ve included links below the video. Enjoy!

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Improve Your Organization’s Time Line

Reposted from March 2022

Here’s a simple data viz idea. Next time you make a time line showing your organization’s milestones, size those milestone markers (usually circles) according to some key measure. Voila! You are not only showing what happened but also your progress along the way.

The data for such a viz is super simple. Something like this:

Screen Shot 2021-08-24 at 9.01.48 AM.png

I connected the data shown above to Tableau Public (the free version of Tableau) to create the time line below. Vertical time lines not only suggest an upward progression but also work better on phone screens.

Dashboard 1 (3) (1).png

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Make Big Numbers Tangible

Reposted from March 2022

We’ve talked about the problem with big numbers before. Most recently, we considered the difficulty humans have digesting large numbers and how “perspectives” — simple sentences that relate a large number to something more familiar to us — can help us to understand, assess, and recall numbers. (For more on this, check out the data tip.)

I’m returning to the big number problem today and offering up some new tips for dealing with them. The inspiration for these tips came from the data-driven documentaries of Neil Halloran, specifically his first documentary called The Fallen of World War II. If you have a few more minutes to spare after reading this 60-second tip (and are not among the 13 million + who have viewed it already), I highly recommend that you check it out. It’s 18 minutes long, but the techniques listed below all appear in the first 7 minutes.

Halloran uses the following techniques to make large numbers understandable. And you don’t need to be a filmmaker to use them. You can apply them to simple data presentations on websites, reports, and PowerPoints.

  1. Use shapes or icons (rather than bars) to represent one or more people, programs, etc. Halloran uses a human figure shape to represent 1,000 people.

  2. Show an aggregate and then break it down by subgroups and time periods. Halloran shows aggregates, such as the total number of U.S. soldiers who died and then, using animation, redistributes the human figures to show how many soldiers died in the European and Pacific theaters and then how many died over time. The animation is cool but not necessary. You can do the same thing with a series of static images. See example below.

  3. Juxtapose photos and charts. To keep the discussion from becoming too abstract, Halloran reminds the audience what actual soldiers (rather than icons) look like by incorporating photos into his presentation. Again, animation is not necessary. Static photos can be placed alongside charts.

  4. Walk your audience through the data. To give the audience a sense of scale, the video progresses from smaller to larger numbers. Halloran first walks us through casualty stats for the U.S. and European countries. These numbers seem quite high so by the time Russian stats are shown, we are blown away.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Visualize Cycles

Reposted from April 2022

Every organization experiences cyclical or seasonal patterns. Understanding how funding, participation, volunteering, and other factors change in predictable ways over time can help us to plan for the future. The problem is that we don’t always see these patterns. We get caught up in current issues and crises, and it’s hard to step back and see what’s coming next. Visualizing your data can reveal cyclical or seasonal patterns in helpful ways. This often involves aggregating data from multiple years by specific time periods such as season, quarter, or day of the week. Here are some examples.

Working with a statistician named William Farr in the 1800s, Florence Nightingale analyzed mortality rates during the Crimean War. She and Farr discovered that most of the soldiers who died in the conflict perished not in combat but as a result of “preventable diseases” caused by bad hygiene. Nightingale invented the polar area chart (shown below), a variant of the pie chart, meant “to affect thro’ the Eyes what we fail to convey to the public through their word-proof ears.” Each pie represented a twelve-month period of the war, with each slice showing the number of deaths per month, growing outward if the number increased, and color-coded to show the causes of death (blue: preventable, red: wounds, black: other). The New York Times showed the seasonal pattern of COVID cases using a somewhat similar chart.

Source: Wikipedia

In the dashboard below, Curtis Harris reveals not only patterns in taxi rides by time of day but also by day of the week. We can see, for example, that few people are using taxis between 2 and 3 am, particularly at the beginning of the week. (Click on this viz to see interactive version.)

Source: Curtis Harris on Tableau Public

This varsity-level viz (below) by Lindsay Betzendahl shows the seasonality of the flu. Each dot represents one week in a particular year. Each “ray” consists of dots for the same week of different years. So the ray at the 12:00 position represents the first week in January for each year between 2007 to 2018. The size of the dots show the number of influenza cases. So we can see that cases surge during the winter weeks, in general, but we also can see outbreaks during other seasons in particular years. Betzendahl explains how to create such a chart in Tableau here.

Source: Lindsay Betzendahl on Tableau Public

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Recognize and Reform Vanity Metrics

Reposted from March 2022

Vanity metrics are like cheap, trendy sunglasses. They may help you to look cool, briefly, but they don’t last long and do little to improve your eyesight. You’ve seen vanity metrics, even if you haven’t used this term to describe them. They are those flashy statistics (sometimes called “big ass numbers”) and charts showing how many services an organization has provided or people they’ve served or some other seemingly impressive stat. The problem is that these metrics don’t help you to better understand your current work and improve it. In this tip, I’ll give you some quick advice on recognizing and reforming vanity metrics.

How To Recognize A Vanity Metric

This Tableau article suggests three questions to ask to identify a vanity metric. I’ve put a nonprofit spin on each:

  • What decision can we make with the metric? If the metric can’t help you to make a decision, it’s probably a vanity metric. For example, does knowing how many meals you delivered help you to decide who, what, where, when, or how to deliver meals in the future? Or do you need a more specific metric such as the gap between need and service provision for various subgroups of clients?

  • What can we do to intentionally reproduce the result? Did some random event produce the big number? For example, did you see a bump in the number of participants last year because another organization, providing a similar service, closed down? If you cannot consistently reproduce the same result next year, this isn’t a helpful metric.

  • Is the data a real reflection of the truth? Let’s face it. There are always ways to misrepresent the truth. You can tell the world that attendance at all of your programs last year totaled 3,237. Sounds good, but that’s probably a “duplicated number” and can be misleading depending on what you want to understand or broadcast to the world. Some people likely attended more than one program. So the total number of individuals who participated in any program could be much lower. The central question to ask yourself when considering a metric is whether or not it will help your organization achieve its goals. If your goal is to reach more folks, this metric is not helpful.

How To Reform A Vanity Metric

  • Provide context. The metrics that are worthy of your attention and your stakeholders’ attention are those that are directly related to your goals. You may have overall goals for all of your participants, clients, audiences, services, programs, etc. But you also might have specific goals for subsets of those groups and for specific time periods. Present your metrics in relation to the goals. And compare metrics for subgroups to each other to see where you are making progress and where you are not.

  • Use more than one statistic. Sometimes what you want to improve cannot be measured with just one metric. For example, if you aim to improve the diversity of your staff, you may want to look at a set of metrics together including number, tenure, and seniority of staff by race/ethnicity, gender identification, age, etc.

Sources: Moving Beyond Vanity Metrics, Stanford Social Innovation Review and Vanity Metrics: Definition, How To Identify Them, And Examples, Tableau.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Visualize What Could Have Been or Might Be

In English, there are three verbal moods:

  • The indicative used to express factual statements or positive beliefs;

  • The imperative used to express direct commands, requests, and prohibitions; and

  • The subjunctive used to express hypothetical situations or conditions which are contrary to fact or uncertain.

When we are visualizing data, we often settle into the indicative, the realm of facts. But what if we want to show what might happen if action is not taken or what might have been had action not been taken? In other words, how can we visualize the subjunctive? I’d like to offer up four examples to inspire you. The Flattening The Curve chart shows the impact of COVID mitigation (social distancing, masking, etc.) on the healthcare system and should bring back memories of 2020. The other charts may be new to you.

 
 
 

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Emphasize The Shape of Your Data

“There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.” – Henry D. Hubbard in the preface to William C. Brinton’s Graphic Presentation, 1939.

Data visualization translates words and numbers into visual cues such as color, size, position, and shape. Humans can process such visual cues much more easily and quickly than words and numbers. Today, I’m here to talk about shape because I don’t think we turn to shape often enough to engage and educate with data. The three area charts below provide a great example of the power of shape. The charts show estimates of the distribution of annual income among all world citizens over the last two centuries. By considering the change in the shape of the data across the three time periods and in relation to the poverty line, we learn a lot. Most significantly, we learn that, over the 215 year time period, the majority of people went from living below the poverty line to living above it. We learn even more by considering the shape of the distribution for each color-coded region.

So consider taking a page from this playbook. Rather than showing change over time in one chart. Consider using shape to tell the story by showing the distribution of something (e.g. income, course grades, number of clients) at different time periods in adjacent area charts.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

This Is A Teenager: Showing The People Behind The Data

My tip this week is to check out This Is A Teenager by Alvin Chang at The Pudding. It’s a visual essay that traces the paths of hundreds of teenagers, starting in 1997, to see how their childhood experiences relate to their life outcomes. You can view it in video form (see below) or as a scrolling visualization HERE. The actual teenagers behind the data* don’t get lost in aggregates represented by bars, lines, and circles. Instead, we see them as individuals whose lives tend to follow the paths of other individuals with similar childhood experiences.

* The data is from the National Longitudinal Survey of Youth.

Source: The Pudding

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Create More Diverse, Equitable, and Inclusive Data Visualizations

Reposted from February 2022

When we visualize information, we make a series of decisions which affect the way that viewers process the information in our charts, maps, and graphs. Sometimes they don’t feel like decisions at all. We go with the default settings in the application we are using. Or we just do something the way it’s usually done. But a more diverse, equitable, and inclusive approach to presenting and visualizing data requires us to make those decisions more consciously and deliberately. Jonathan Schwabish and Alice Feng of the Urban Institute provide some helpful tips, based on the Urban Institute’s own style guide, which you can apply the next time you present data.

Here is a summarized version of Schwabish and Feng’s article.* And here is my 60-second version of their recommendations:

  • Use people-first language in titles, text, and labels associated with charts, maps, and graphs. For example, use “people with disabilities” rather than “disabled people.” Also the Urban Institute does not refer strictly to skin color. For example, they refer to “Black people” not “Blacks.”

  • Order and present groups purposefully. The first group shown in a table or the first bar in a chart can affect how readers perceive the relationship or hierarchy among groups. For example, if the first group is “Men,” then it may appear that men are the default group against which other groups should be compared. One way to prevent viewers from making certain comparisons is to display groups in side-by-side charts (aka “small multiples” charts) rather than on a single chart. In general, make ordering and grouping decisions to promote certain comparisons and prevent others.

  • Point to missing groups. If certain groups are missing from the data, explain why in text boxes or footnotes. Also add information on groups included in “Other” categories and consider providing a more specific label than “Other” which can have an exclusionary connotation.

  • Do not use color palettes that reinforce gender or racial stereotypes. This one may seem obvious, but it bears repeating. Also, the Urban Institute’s color palette is accessible to people with certain color vision deficiencies, and the contrast between those colors and white and black text meet basic accessibility guidelines.

  • Depict a variety of races and genders when using icons and avoid icons that make inappropriate depictions of people or communities or reinforce stereotypes such as showing traditionally feminine icons to depict nurses or traditionally masculine icons to depict bosses.

  • Find ways to show the people behind the data. Data visualizations are, by definition, abstractions of larger realities. But in the process of abstracting, we may obscure the lived experiences of the real people whom the data represent. Visualizations can remind viewers about the individuals behind the data by, for example, depicting them as individual circles rather than aggregating them in a single bar.

* The full paper has been published as an OSF Preprint and can be accessed here.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

The Power of Substraction

“Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.”

―Antoine de Saint-Exupéry, Airman's Odyssey

If you have heard of any data viz guru, it’s probably Edward Tufte. And if you know one thing about Tufte, it’s probably the data-to-ink ratio. The data-to-ink ratio is the amount of ink (or pixels) that convey the data divided by the total ink (or pixels) used in the entire chart. The ratio, according to Tufte, should be as close to one as possible. In other words, most of the ink/pixels should be conveying data, and you should remove as much non-data ink/pixels as possible. Click through Joey Cherdarchuk’s slides below for a great example of what Tufte is talking about.

Source: Darkhorse Analytics

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Presenting Data Fast and Slow

Reposted from May 2022

Sometimes we approach the challenge of sharing data with others as if we were trying to con a pet into taking a pill. We think that our audience is too busy, disinterested, or distracted to focus on the data. So we wrap it in something that attracts their attention and feed it to them as quickly as possible. The problem with this approach is that it may get the data into their brains—momentarily—but it won’t stay there long. See where the pill ends up in this video.

If we want others to LEARN from the data — which involves not only retaining it but also drawing knowledge from it and applying that knowledge in the future — then we need a different approach. Daniel Kahneman’s Thinking Fast and Slow can help us.

First a little background on how the brain works, according to the evidence Kahneman presents. For learning to happen, information first must get past System 1 of our brains. This is where fast thinking happens. System 1 is the harried gate keeper, madly processing all of the information that comes in through our senses, pitching most of it, keeping only what is deemed necessary. But making it through the gate is only half the battle. Once in, information confronts System 2. This is the part of the brain that allows for conscious thought or slow thinking. The problem is that System 2 is lazy. Conscious thought is hard, and System 2 is always looking for an excuse to avoid it. However, if System 2 engages with information, the resulting knowledge can find its way to long-term memory and learning happens.

So the challenge when presenting data is to make it past System 1 AND engage System 2. Let’s consider a series of vizes from Harvard Business Review (HBR) that I think meets both parts of this challenge. Yes, it’s an example from the for-profit world, but could easily work with nonprofit data. See snapshot of the first viz in the series below .

How to get data past System 1

Getting data past the System 1 fast-thinking gate keeper is all about grabbing attention. We process images much more quickly than words and numbers, so images are a great foot-in-the-door. The HBR viz does it with bright colors and a cool-looking, somewhat unusual chart. There’s plenty of information out there about how to attract attention, including the use of images with:

  • Stand out colors and textures

  • Human faces (we are wired to focus on them)

  • Novelty (images that are unusual in size, placement, etc.)

Data visualizations can use color as well as images to draw attention. But getting past System 1 is not nearly enough. For learning to happen, the viz also has to engage System 2.

How to engage System 2

System 2 is smart but lazy. So we need to pique its interest. The HBR viz starts with a title that poses a question. When confronted with an interesting question, we may be more likely to stick around for an answer. Then the viz leads you through the answer in a visually engaging way (see interactive version of the viz HERE). These are two great ways to slow down and engage the brain with data. Here’s a list of ways to engage System 2:

  • Ask a question in the title as the HBR viz does—questions beg answers.

  • Make it personal. We may be more likely to engage with data when we have a personal connection with it. This New York Times viz, for example, allows you to enter in your county to see what the barriers to COVID vaccination are in your area.

  • Highlight a surprising finding. Many of us love the counterintuitive and the creative. If you draw attention to something new that the data suggests, you may have a better chance at hooking System 2. For example, this viz from The Economist shows that China emits far less greenhouse gas per person than Western countries at the same stage of economic development. Or check out this viz by Dimiter Toshkov showing that small countries can be big players in development and good governance.

  • Hand draw it. There is some evidence that making information harder to consume, for example by presenting it with harder-to-read fonts, makes the brain slow down and engage in effortful and analytic processing. Although the jury is still out on this, I do find myself more likely to engage in hand-drawn vizes like two of the winners of the World Data Visualization Prize in 2019. Perhaps it’s simply the novelty of hand-drawn charts that engages me. Anyway, it’s something you might consider, and all you need is a pen and paper.

  • Walk them through it. A great way to slow down your viewers is to set the pace by walking them through the data as HBR does in the example. I love how HBR presents what the data might look like if our assumptions were confirmed followed by what it actually looks like.

Sources: Veritasium, Visual Content Space, MIT News, Springer Link,

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Present Data on Slides

“It’s not the mere presence of data that gives the presenter power,” notes Joel Schwartzberg in his Harvard Business Review article on presenting data, “It’s how that data is presented.” Below is my 60-second review of Schwartzberg’s helpful tips. But before you scroll down, see how much you already know. Take a look at the “Before” slide below and consider what changes you would make to it. Then advance to the “After” slide (by clicking on the right side of the image) to see a revised version that follows Schwartzberg’s guidelines.

  • One point per slide. Have one key takeaway for each slide and write a slide title that reinforces your point rather than something generic like “Performance by Quarter in 2023.”

  • Visually highlight “Aha” zones. Use a bright color to direct attention to a key data point and gray out the rest.

  • Make charts readable from across the room. If you have to say “You probably can’t read this but it shows that . . . “ then it needs revision. Don’t use font sizes smaller than 18 points.

  • Labels are clear and intuitive. Your audience needs to decode your chart in a few seconds. Make sure axis and data labels are understandable.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Ideas You Should Steal From This Viz (Installment 11)

“Every artist gets asked the question: ‘Where do you get your ideas?’ The honest artist answers, ‘I steal them.’ . . . What a good artist understands is that nothing comes from nowhere. All creative work builds on what came before.” —Austin Kleon in Steal Like An Artist.

Today I offer up another steal-worthy interactive viz that I came across in the Tableau Public Gallery.

Source: Kizley Benedict on Tableau Public

Here’s what I suggest you steal from this viz:

  • Beeswarm Chart. The beeswarm chart at the top allows you to easily compare several countries and to see the overall distribution along the Gender Inequality Index among large and small countries. For more on beeswarm charts, see this tip.

  • Highlight a Country. For users who want to know about a particular country, the dashboard provides a search tool which highlights the selected country.

  • Overall Then Zoom In. After getting a sense of the overall distribution from the beeswarm chart, the user can zoom in and make comparisons among and within regions with the maps along the bottom of the dashboard.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Check Your Data Blind Spots

You’ve heard it before. We see what we want to see. It’s called confirmation bias, and we are all susceptible. Confirmation bias is a big problem to those presenting or consuming data (i.e. all of us.) How can we draw our own and others’ attention to the data that does NOT fit our existing beliefs? How, in other words, can we check our blind spots?

The great thing about your blind spot when it comes to driving is that you know it exists. Your rearview mirrors do not show you an area next to and behind your car. So you learn to check that area in a different way. Experienced drivers do it by rote. Wouldn’t it be great if we also could remember that we have data blind spots and learn to check them automatically?

Here are some ideas for making your blind spots visible. All of them involve doing something before you look at data (in the form of a spreadsheet, table, chart, map, or graph) to help you look at the data with fresh eyes.

  1. Make predictions before looking at data. To prevent seeing only the data that confirm our beliefs, we can make predictions before looking at the data. In Staff Making Meaning from Evaluation Data, Lenka Berkowitz and Elena “Noon” Kuo suggest that, before sharing data with program staff, “have them spend 10 minutes writing down predictions about what the data will say. This exercise helps surface beliefs, assumptions, and biases that may otherwise remain unconscious.” This can involve drawing a predicted trend in the data or jotting down guesstimates of key data points. Then look for differences between your predictions and the actual data and consider:

    • What may have contributed to the differences,

    • What more do you need to know to take action, and 

    • What actions might you consider immediately?

  2. Consider your “null hypothesis” before looking at data. This approach is a variation on strategy number one.  Rather than making a prediction, you pose this question to yourself: If what I expect is NOT true, what might I see? This is analogous to how researchers conduct experiments.  Rather than trying to prove that a hypothesis (e.g. A is affecting B) is correct, researchers aim to collect sufficient evidence to overturn the presumption of no effect, otherwise known as the null hypothesis. It’s sort of like innocent until proven guilty. The idea is to take the opposite view to the one that you hold and then look for evidence to support it. If you can’t find that evidence, then your assumption might be correct. This approach makes you think more critically and perhaps more dispassionately when encountering data.

  3. Set decision criteria before looking at data. “Many people only use data to feel better about decisions they’ve already made,” notes Cassie Kozyrkov in Data-Driven? Think again. To avoid this, you can frame your decision-making in a way that prevents you from moving the goalposts after you’ve seen where the ball landed. Before considering the data, determine your cutoffs for action. For example, you and your colleagues might decide that program participation below 150 in any given month requires investigation and possible action. Let’s say that twelve-month data show participation below 150 in six months. The pre-established cutoff can prevent you from only focusing on the worst months when participation was below 75.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How and Why to Visualize Variability

Every dataset includes variability. The people and things we measure differ from one another in many ways. And visualizing data always involves some decisions about how much of that variability to show. There are tradeoffs:

  1. If you show too much variability, you obscure patterns and trends. To understand anything with data, we usually need to reduce its complexity. We can’t extract meaning from a table full of numbers and letters. So we summarize the data through such activities as grouping people, concepts, and time periods; calculating averages; or organizing individuals or groups in a rank order. This process allows us to detect patterns and trends within the data. Patterns and trends become even more apparent when we visualize the data in the form charts, maps, and graphs by assigning visual cues such as color, size, and shape to groups and values. However, too many colors, sizes, and shapes make discerning the patterns and trends more difficult.

  2. If you show too little variability, you obscure reality*. Overly simplified visualizations do not show just how complex and messy the data actually is. And the viewer may mistake the simplified, summarized version of the data as reality.

You can find a great example of problem #2 in Eli Holder’s article Divisive Dataviz: How Political Data Journalism Divides Our Democracy. He describes the danger of red and blue political maps in the U.S. in this way: “there’s no such thing as a “red state” or a “blue state.” Consider Texas, which is often called a “red” state. In the 2020 presidential election, more Texans voted for Joe Biden (5.26 million) than every other “blue” state, except for California. Even New York, a Democratic stronghold, had roughly 20,000 fewer Biden voters than Texas. . . . While popular election maps accurately reflect the ‘winner-take-all’ dynamic of the electoral college, they create the misimpression that state electorates are monolithic blocks of only-Republicans or only-Democrats.”

And the misimpressions such maps engender have real-world consequences. Holder describes an experiment in which people were shown either dichotomous maps or continuous maps (see examples below). Those shown dichotomous maps were more likely than those shown continuous maps to feel that their state was dominated by one party and thus that their votes mattered less because the election outcome was a foregone conclusion.

So when deciding how many shades of gray or circle sizes to show, consider how much summarization is needed to make patterns and trends perceptible without misleading the viewer with an oversimplified view of the data. Take, for example, these three versions of a map. They each show the same CDC chronic illness survey data with a “diverging color palette” in which blue states ranked high on health indexes; orange states ranked low; and gray states were in the middle. The maps differ in the degree of variability shown. Which map allows you to see corridors of good and bad health without oversimplifying the matter?

*More specifically, the full reality of the data. This 60-second data tip doesn’t get into the nature of reality in general!

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

One Dataset, 100 visualizations

Today’s tip is to check out the 1 dataset, 100 visualizations project. It shows 100 different ways to visualize this simple dataset:

 

It’s fun to compare the different charts and see how they provide different perspectives on the data. For example, to visualize this data, many of us would create a stacked bar chart like this one and call it a day.

 

But look at how this chart allows you to better understand each country’s relative position in relation to number of world heritage sites between 2004 and 2022. We can more easily see, for example, that Denmark leapfrogged Norway.

 

These 100 charts make a strong case for visualizing your data in a number of different ways before selecting one which provides the perspective needed.


To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.