Managing Amid Uncertainty: What You Can Know and Show

Does your organization feel like the guy in the picture above? Heretofore, you and your colleagues have been climbing a challenging mountain. The journey has been daunting at times but despite occasional setbacks, your trend has been upward. And just as you were ready to take on the next steep incline, you encounter a cliff — or at least what feels like a cliff. The path ahead is foggy and uncertain.

How to deal with the uncertainty that the pandemic had brought into most aspects of life, including our work? One response is to try to bring the present and possible future into focus through charts, maps, and graphs. “In many ways, data visualization has been instrumental to how we’re processing COVID-19,” writes Stephen Gossett at Built In. “The Washington Post’s animated-dots simulation became the paper’s most-viewed article ever.” But Gossett goes on to describe the dangers of visualizing uncertain data. As I wrote in an earlier data tip on “Low-CAL” data, data visualizations can make situations appear more certain than they actually are. We should look for the fine print that describes Context, Assumptions, and Limitations and be wary of visualizations that lack this information.

So what can you confidently know and show about your organization now?

• Your past efficacy or impact. It’s a good time to dust off old charts. Or better yet, revive past data with new and improved visualizations that show your staff, board, and current and prospective supporters how well you have done in the past and thus how worthy of investment your organization is.

• Your ability to adapt. For extra credit, show your stakeholders how well you have adapted to changes in the past, particularly unexpected ones. Show in charts how you resurged after a cut in public funding or how you built new programs to address unexpected needs in your community.

• Your current efforts. Show how much money and person hours you have invested, how many people you have served, how many funds you have raised, or how you have redirected resources to new programs.

Even amid all of the uncertainty, there are some “known knowns” (in the words of former US Secretary of Defense, Donald Rumsfeld). While we are waiting for the “known unknowns” and the “unknown unknowns” to come into focus, we can move forward by showing what we do know.

 To see past data tips, including those about other chart types, click HERE.

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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.

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A Cure For Bad Charts

Hey Everyone: This week’s quick tip is to check out “Great Graphs: Design Principles,” another excellent course from Ann Emery. This is the only week of the entire year that you can register. Registration ends this Friday, May 1, 2020. Click HERE for more info and to register. And stay tuned for another 60-second data tip on an interesting type of chart coming soon!

Beware of Low-CAL Data During Pandemics (And Always)

We are all trying to make sense of how we got here and how we are going to get out — often with the aid of numbers and charts. The most common coronavirus numbers and charts fall into two categories: 1) those with actual data, which is often limited, and 2) those that predict what might happen based on assumptions. Many of the numbers and charts I’ve come across have reminded me of the dangers of Low-CAL data which is any data presentation that is low on clearly articulated: Context, Assumptions, and Limitations. Let’s talk about each one:

Context: Listening to President Trump’s daily briefings, I am reminded of the appeal of BANs (big ass numbers). Trump uses them a lot. For example, on March 23rd, he said that FEMA is distributing 8 million N95 respirator masks and 13.3 million surgical masks across the country. Sounds like a lot, but is it? Numbers, by themselves, have no inherent meaning. You have to put them in context. How does the supply compare to the need?

Assumptions: We make predictions about the future using assumptions which are based on currently available data and data about similar situations in the past or in other places. It’s the best we can do. That’s fine. But the assumptions and the rationale for the assumptions need to be clearly stated. For example, some predictions assume that the spread of the virus will slow down during the summer, but at the time of writing, we do not know how safe that assumption is.

Limitations: The data we have about the coronavirus is limited at the time of writing. We do not fully understand what factors promote or impede the spread of the virus nor do we fully understand how widespread it is. Many sick people have not been tested making it impossible to calculate a reliable death rate (number of deaths caused by the virus divided by the total number of cases.) Most data sets have limitations. To fully appreciate the implications of data, we must know what those limitations are.

Scholarly journals require that authors clarify context, assumptions, and limitations. But websites, tweets, blog posts, newspaper and magazine articles do not. I urge you to be a smart consumer on the lookout for Low-CAL data presentations. And when presenting data yourself, consider adding something akin to the drug facts label you find on medications to your charts, graphs, and maps. Somewhere in or near your data presentation include information on context, assumptions, and limitations so that viewers fully understand what the presentation does and does not show.

To see past data tips, including those about other chart types, click HERE.

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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.

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Why You Should Know About Pictogram Charts

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This is the seventh in a series of tips on different chart types. The idea is to fill up your toolbox with various types of charts for making sense of data. This week, I give you the pictogram chart.

Active Ingredients (What is a pictogram chart?)

Pictogram charts use icons instead of bars or circles, usually to show how many units are in a group. Probably the most common icon is the stick figure used to represent a person or a group of people (e.g. each stick figure represents 100 people.)

Uses

Pictogram charts can be useful when bars or circles just seem too abstract, and you want to emphasize that you are talking about people, animals, apartment buildings, or whatever it is that you are measuring. Pictogram charts also come in handy when you want to clarify confusing statistics. Back in data tip #77, I used the pictogram chart below to compare the attendance of students in classrooms with attendance monitors to the attendance of students in classrooms without monitors, assuming 10 students per class. The chart was designed to clarify this statement: “54% more students with monitors improved attendance than students without monitors.” That sounds like a lot until you look at the chart below. The 54% stat is a “relative difference,” which is calculated as the absolute difference divided by the “standard” which, in this case, is the class without monitors. So 4.0 minus 2.6 divided by 2.6 or .54, which when expressed as a percentage is 54%. But the chart makes it clear that we are talking about 4 students vs. 2.6 students, which sounds much less impressive than 54%.

Warnings

Avoid showing too many icons. They are hard to count. Remember that one icon can represent a larger number. Also, don’t display partial icons. If you need to show a number with a decimal, consider showing the whole icon and coloring in just part of it, as in the example above.

Fun Fact

You can find free icons to use in pictogram charts at The Noun Project or at Flaticon.

To see past data tips, including those about other chart types, 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.

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Why You Should Know About Gantt Charts

This is the sixth in a series of tips on different chart types. The idea is to fill up your toolbox with different charts to make better sense of data. This week, I give you the gantt chart.

Active Ingredients (What is a gantt chart?)

A gantt chart shows the start and end date of a list of activities or tasks. Each row represents a task and each column represents a time period. Here is a gantt chart I made for Thanksgiving. In this case, the tasks are dishes. I used color to show different stages (preparation, cooking, refrigeration, and reheating) for each dish.

Here’s a gantt chart that may be closer to something you’d want to create for your organization:

Uses

Gantt charts provide a great way to show the different components or tasks in a project or program, how long each task is going to take, which tasks precede or follow others, and which tasks occur simultaneously. In the Thanksgiving chart, I was particularly interested in which dishes would be cooking at the same time since I have limited space in my oven. Similarly, a gantt chart can clarify if you have enough staff and other resources to conduct simultaneous tasks. You might consider adding a reference line to show the current date, shading portions of the bars to show what is completed and what is left to do, or adding arrows to show which tasks are dependent on each other.

Warnings

As with so many chart types, they can get overly complex and difficult to read. So keep the overall gantt chart simple to give a view of the entire project. If you need to show more detail, you can make related charts that zoom in on subtasks for each of the major tasks on the overall chart. Also, remember to update your gantt chart as timelines and tasks change.

Fun Fact

The gantt chart is named for its inventor, Henry Laurence Gantt, a disciple of Frederick Taylor, the great promoter of scientific management in the early 20th century.

To see past data tips, including those about other chart types, click HERE.

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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.

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Can spreadsheets actually be fun?

Hey Everyone: This week’s quick tip is to check out Ann Emery’s excellent course on extracting the full power of spreadsheets. This is the only week of the entire year that you can register. Registration ends this Friday. See more information below and stay tuned for another 60-second data tip on an interesting type of chart coming soon!

Simple Spreadsheets: From Spreadsheet Stress to Superstardom

Data Analysis Techniques & Time-Saving Secrets for Busy Number-Crunchers

What We’ll Cover: 14+ Hours of Content--The Equivalent of Taking a 2- to 3-Day Workshop

We’ll go broad and deep. You’ll learn about everything from concatenate to sparklines to pivot tables to vlookup. There’s even an entire bonus module on data visualization! You’ll get access to 14+ hours of training, which is the equivalent of participating in a 2- or 3-day workshop.

This online course is all about data analysis time-savers. Spreadsheet skills are the foundation of good data visualization. You need to be able to pour through huge datasets and find the gems that are worthy of visualizing. You need to manipulate your tables, rows, and columns to get formatted juuuuuust right. And most importantly, you need to be able to analyze data quickly and without mistakes.

Registration Period for Simple Spreadsheets

This data analysis course is *only* open for enrollment between Monday, February 24th and Friday, February 28. When it's open, it's open. When it's closed, it's closed.

LEARN MORE AND ENROLL HERE!

You’ll be on your way from spreadsheet stress to superstardom in no time.

Why You Should Know About Bullet Graphs

This is the fifth in a series of tips on different chart types. The idea is to fill up your toolbox with various charts to make better sense of your data. This week, I give you the bullet graph.

Active Ingredients (What is a bullet graph?)

A bullet graph is a bar chart with context. In the example below, the orange bars show the number of enrollees in the Child Health Plus Program in five New York counties. The black vertical lines and the gray bars provide context. Each black vertical line shows the (fictional) goal for each county. The dark gray shaded bars show 60 percent of the goal, and the light gray bars show 80 percent of the goal. So we can see that Queens has surpassed its goal whereas Kings hasn’t reached its goal but has surpassed the 80 percent mark. These gray bars are called “performance ranges” and can be any amount that makes sense for the data and organization. Sometimes these ranges are labeled poor, average, and great.

Data source: https://healthdata.gov/dataset/child-health-plus-program-enrollment-county-and-insurer-beginning-2009

Uses

Charting your data allows you to see the overall picture, patterns, and trends in your data. But without context, it’s difficult to really understand the implications of your data: where do you need to invest more time and resources, which groups might serve as models for others, etc. Bullet charts provide that context. You can quickly see which groups are meeting, exceeding, or falling below goals and by how much.

Warnings

As with bar charts, it’s usually best to display your bars in descending or ascending order. And use a limited number of performance ranges, usually no more than three.

Fun Fact

Data viz guru, Stephen Few, invented the bullet graph as an alternative to dashboard gauges and meters.

To see past data tips, including those about other chart types, click HERE.

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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.

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Why You Should Know About Histograms

This is the fourth in a series of tips on different chart types. The idea is to fill up your toolbox with a variety of charts for making sense of data. This week, I give you the histogram.

Active Ingredients (What is a histogram?)

Histograms look like bar charts. Along the X-axis are “bins,” which each represent a range of values. The Y-axis shows how many units fall into each bin (as long as bins are equally spaced. See warning below.)

Uses

A quick look at a histogram shows you where values are concentrated, what the highest and lowest values are, and whether there are any gaps or unusual values. As such, histograms provide a snapshot of the shape and distribution of the data. Histograms are a great way to get to know your data and give you a much clearer picture than a simple average of your values would.

The series of histograms below provides a snapshot of how 87 students are doing in school. We can see that:

• Absences, referrals*, and F grades are all relatively rare. A lot of kids fall into the zero bin.

• Although missing assignments were also less common, most kids had some.

• Reading and math test scores (MAP) were more “normally distributed” meaning lots of scores concentrated in the middle of the range, with the remaining scores trailing off symmetrically on both sides.

Source: http://www.storytellingwithdata.com/blog/2019/2/21/various-views-of-variability

Warnings

If you make your bins too big or too small, it will be difficult to see the underlying pattern of the data. There’s no rule of thumb about how to size your bins. Play around with it to see what makes the overall pattern clear.

Technically, histograms are based on the area, not the height, of bars. The height of the bar does not necessarily show how many units there are within each bin. Instead, the height times the width of the bin gives you the number of units in the bin. However, most histograms that I run across have a standard sized bin, and under these circumstances, the height of the bin does reflect the number of units.

Fun Fact

Histogram = histos (Greek for mast) + gram (Greek for something written or recorded). So maybe the term was applied because the chart looks like a row of masts.

*I assume this means discipline referrals.

To see past data tips, including those about other chart types, click HERE.

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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.

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Why You Should Know About Treemaps

This is the third in a series of tips on different chart types. The idea is to fill up your toolbox with a range of charts for making sense of data. This week, I give you the treemap.

Active Ingredients (What is a treemap?)

As with so many charts, it’s easier to show you one than to describe it. So here you go:

Data source: https://catalog.data.gov/dataset/performance-metrics-family-support-services-homeless-shelter-system-monthly-utilization-8d7ff/resource/3f5b8d3d-bafe-4dfd-87ae-54f4797d1e46

This treemap shows the number of shelter beds used by individuals and families in various years in Chicago. There are two primary or “parent” categories: interim shelter beds and overnight shelter beds. Each of these categories is assigned a rectangle area with subcategory rectangles nested inside of it. In this case, the subcategories are years. The area of each rectangle in a treemap is in proportion to a quantity, in this case number of beds. The area size of the parent category (bed type) is the total of its subcategories (years). The parent categories, in this case, are also distinguished by color: red/orange for interim shelter beds and yellow for overnight shelter beds. Further, darker shades show more beds.

Uses

Treemaps provide a clear view of the structure of your data and allow you to compare the size of parent categories and subcategories. With the example above, we quickly can see that there were many more interim shelter beds than overnight ones. We also see a similar numbers of beds in all years except 2016, when there was a lower number of interim shelter beds.

Warnings

The treemap doesn’t look like a tree or a map, really. So why do we call it that? Well, the treemap shows a hierarchical structure (categories and subcategories) like a tree diagram (aka organizational map). But a treemap doesn’t show the different levels of the hierarchy as clearly as a tree diagram. So if you are trying to focus attention on a hierarchy with several levels, consider a tree diagram instead.

Fun Fact

A “tiling algorithm” (included in data viz programs like Tableau) determines how the rectangles are divided and ordered into sub-rectangles in a treemap. The most common is the "squarified algorithm," which keeps each rectangle as square as possible.

To see past data tips, including those about other chart types, click HERE.

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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.

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Why You Should Know About Bubble Charts

This is the second in a series of tips on different chart types. The idea is to fill up your toolbox with a variety charts for making sense of data. This week, I give you the bubble chart.

Active Ingredients (What is a bubble chart?)

A bubble chart is really just a souped-up scatterplot. Like the scatterplot, it’s a graph with plotted points that show the relationship between two sets of data. Here’s a scatter plot showing the relationship between the height and girth of black cherry trees:

We can see that there is a relationship between height and girth. As trees get taller, they also tend to get wider. The scatterplot becomes a bubble chart when we size the points according to another measure, in this case the volume of the trees.

Black cherry tree data: https://vincentarelbundock.github.io/Rdatasets/datasets.html

Now we can see that as height and girth increase, the volume of black cherry trees also tends to increase. Sometimes folks add another measure or dimension to bubble charts using color, such as in this example.

Source: Smartphone Sales Growth Worldwide | Mekko Graphics

Uses

Use a bubble chart when you want to show the relationship between two measures plus a bit more. In the bubble chart above, we can see that as the cost of smartphones (position on X-axis) increased, the growth in sales (position on Y-axis) decreased AND that sales were particularly high in China, Emerging Asia, and North America in 2017 (size of bubbles) AND that the boom markets with cheap phones were mainly emerging markets (color of bubbles). That’s a lot of information in a fairly small space.

Warnings

When you cram too much information into bubble charts, viewers struggle to see core relationships and trends. So don’t use too many data points, too many sizes, or too many colors. Scroll down to the end of this tip to see a bubble chart that confuses more than elucidates.

Put your most important measures on the X and Y axes. Remember that humans are really good at discerning position along a common scale. So viewers are most likely to comprehend the relationship between the X and Y measures first.

Show your less important measures or dimensions with size and color. Humans can only make general comparisons when it comes to size and color. We are hard pressed to say if one shade is twice as dark as another or if one circle is three times the size of another.

To see past data tips, including those about other chart types, click HERE.

There’s too much information in this bubble chart!

Source: European Beer Consumption | Mekko Graphics

I found most of these bubble charts on Grafiti.

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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.

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Why You Should Know About Heat Maps

My 2020 gift to you? A quick and dirty introduction to a bunch of different chart types. Over the next several weeks, each 60-second data tip will introduce (or re-introduce) you to a particular chart type. I’ll give you need-to-know information in a format akin to the “Drug Facts” on the back of medication boxes: active ingredients (what the chart is), uses (when to use it), and warnings (what to look out for when creating the chart). I’ll also add some fun facts along the way. The idea is to fill up your toolbox with a variety of tools for making sense of data. We begin with the heat map.

Active Ingredients (What is a heat map?)

A heat map is a chart that uses variations in color to show differences among categories (e.g. people living in different zip codes) or differences across a scale (e.g. people with different income levels). In a lot of cases, it’s simply a table with color added to the cells.

Uses

Consider adding color to a table to quickly see patterns. Tables have a least one advantage over charts. They cram a lot of data onto a single screen or page. But it’s hard to see patterns when looking at a regular table on a spreadsheet. Take a look (but only for a few seconds) at this table showing the number of shelter beds used by individuals and families each month in Chicago.

Source: https://catalog.data.gov/dataset/performance-metrics-family-support-services-homeless-shelter-system-monthly-utilization-8d7ff/resource/3f5b8d3d-bafe-4dfd-87ae-54f4797d1e46

Are any patterns jumping out at you? Now take a few more seconds to look at this version, which uses color instead of numbers — aka a heat map:

Are patterns more apparent now? In a few seconds, this is what I saw:

• More variation by year than by month.

• Shelter bed usage was particularly high in 2015.

• Less seasonal variation than I’d expect. I expected darker colors during the winter months.

With a little more time, more patterns might emerge. And more questions too. This heat map shows number, rather than percentage, of beds used. So, perhaps, more beds were used in 2015 because the number of beds available increased. After more examination and exploration, you might decide to use another chart, which zooms in on a subset of the data. But the heat map is a great first step to understanding data.

Warnings

When creating heat maps, you will use discreet colors to show differences among different categories and a color scale (light to dark) to show differences among different levels, from low to high values. Sometimes folks use the stoplight color system (red, yellow, and green) to show the categories: good, okay, and bad. For example, fundraising amounts over a certain number might be considered good. The problem with this approach is that it doesn’t work for people with red-green color-blindness. If you want to draw attention to good or bad amounts, it’s better to just highlight the good or bad numbers with one color and not color the others.

Color provides only a general understanding of differences in data. To provide a more specific understanding you may want to add numbers, as well as color, to cells as in the chart below. And, in general, don’t use too many colors in your heat map palette. It will be easier to read if you keep it simple.

Fun Fact

Heat maps are thought to have originated in the 19th century. Loua created this chart in 1873 to show the characteristics of 20 districts in Paris.

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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.

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Invisible Assumptions Driving Your Organization

People and organizations have ideas about what leads to what. We are aware of some of these ideas. But others are so ingrained that we mistake them for facts of life.

Psychologists call the visible ideas explicit theories and the invisible ones implicit theories. Both explicit and implicit theories affect how we perceive and act in the world. If, for example, we believe—either explicitly or implicitly--that hard work leads to success, we are more likely to perceive evidence that supports our theory (aka confirmation bias) and to work hard ourselves and encourage it in our offspring, clients, and employees.

If this idea is explicit, then we are more likely to examine it, compare it to the ideas of others, and even test it. However, if it’s implicit, then it will probably never occur to us to examine it because we are not fully aware that we believe it or that things could be any other way. (For more on implicit and explicit theories, check out this.)

Implicit theories also affect what data we gather and use. If we have an implicit hard work theory, we might gather data to assess what type of work or effort is most likely to lead to success but, unless we make the implicit theory explicit, we are not likely to collect data to see if clients who put in more training hours actually had more success.

Every organization has implicit theories. Do any of these seem familiar?

• Meetings make people feel included/empowered.

• With more money, we could be more effective.

• Special events help to cultivate new donors.

Some of these assumptions might be true, at least under certain circumstances. But no matter how data-driven we are, we are not going to collect data to test ideas we are not fully aware of.

Staff meetings are great places to listen for implicit theories. Next time your colleagues and you are discussing an issue, see if you can detect a few of them. What assumptions lie behind your assessments, decisions, and actions?

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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.

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Photo by PoL Úbeda Hervàs flickr.com/photos/polubeda/

Top 3 Things You Should Know About Rankings (And How To Visualize Them)

1. We love lists, listicles, and rankings in particular, because they make assessment easier. We hate information overload. Ranked lists show us what information is most important and so ease decision-making.

2. We are more likely to remember items at the top and bottom of the lists and forget the items in the middle. So shorter lists are easier to retain.

3. People also BELIEVE shorter lists more than longer ones.

 3 Ways to Visualize Rankings

1. Bar Charts (like the one above)

2. Rank Charts (which are good for showing how ranking changes over time)

3. Stacked Bar Charts (scroll down to see the mother of all stacked bar charts showing the top 100 colleges by diversity)

For more on the power of rankings, check out this podcast from  the Kellogg School Of Management At Northwestern University. And here is the full version of the viz shown above:

You can find the ARTICLE in which this viz appeared on the World Economic Forum website.

I found this chart on Grafiti.

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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 Squeeze MUCH More Information From Your Surveys (Repost)

Surveys are such a common data source for nonprofits. And I get so many questions about how to make better use of survey data, that I’m reposting this tip which originally appeared in June 2018.

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Surveys provide answers to many nonprofit questions.  How do participants like this program? What are barriers to enrollment? What types of services do community members lack and need?

It’s easy enough to create a survey on Survey Monkey or the like. It's harder to get an adequate number of responses.  And even when you do, the respondents might not fairly represent the larger group you want to know about. But let’s say you get past this hurdle. There’s still a major hurdle ahead of you: extracting meaning from your data.

Surveys include different types of questions. Perhaps the most common one is the Likert scale question. You have seen them a million times. Respondents are asked to indicate how much they agree or disagree with a particular statement using a five to seven point scale.

Let’s say you want to know participants’ feelings about a program. Your Likert scale statements might be; “I feel that I can ask the instructor for help when I’m confused” or “I feel comfortable interacting with the other participants in the program.” Survey Monkey will give you each respondent’s rating of each statement and will also give you the average rating. What meaning can you extract from these numbers?

Many organizations will use just the averages to determine where they are doing well and where they need to worker harder or differently. But there is so much more information in those numbers than averages can tell you, including:

The extremes: Averages can’t tell you what were the lowest or highest ratings on any given statement.

What most respondents said: Averages also can’t tell you if the average is three because most people responded with a “3” or because half responded with a 5 and half responded with a 1.

What subgroups think and feel: Even though the overall average might be high, the average might be low for some subgroups within your group of respondents. Perhaps respondents from a certain neighborhood, for example, had very different opinions than the group overall.

You can extract and show this information using data visualization tools like Tableau that allow you to interact with your data. The viz below shows the range of responses to each survey statement and the proportion of responses for each rating. Moreover, the interactive version allows you to “drill down” into the data and see how the results change overtime. We could also construct the visualize to show us results for different subgroups.

If you are going to go to the trouble of conducting a survey, make sure to squeeze all of the information you can from the data you collect.

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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.

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See other data tips in this series for more information on how to effectively visualize and make good use of your organization's data.

When to (and NOT to) Use a Map

Maps can be a powerful way to show your data. But not always. Maps work best when . . .

1) Your audience already knows the geography.

Most Americans have a basic understanding of the size, demographics, land use, weather, and history of different regions of the U.S. It’s that foundational knowledge that makes maps like the following so effective. We think: wow, cows would take up all of the midwest if we put them all together, and urban housing would require only a portion of New England. Or, if only white men voted, just a few states in New England and the Northwest would go Democratic.

Source: Bloomberg

Source: Brilliant Maps

But when we are not familiar with the geography, maps are much less illuminating. For example, if you don’t know Ireland well, then this map does not shed much more light on the matter than the simple bar chart in the upper left hand corner. It tells us which clans are most prevalent, which is all the map also shows us unless we know more about the different regions.

Source: Brilliant Maps

2. You are showing the significance of proximity or distance.

Even if your audience is not familiar with the geography (and sometimes especially when they are not familiar with it), maps can be an effective way to show proximity or distance. This map of the Eastern Congo shows us how close armed groups (in green) are to internally displaced people (in purple). Just naming the cities or regions where these two groups are would not be effective for audience unfamiliar with the geography.

Source: Brilliant Maps

I found all of these maps on Grafiti.

Data Viz for Nonprofits helps organizations to effectively and beautifully present their data on websites, reports, slide decks, interactive data dashboards and more. Click HERE to learn more about our services and HERE to set up a meeting to discuss how we can meet your particular needs.

How Data Viz Can Save Your Thanksgiving

Your next data challenge may involve turkey. And I’m here to help. This week we take a break from nonprofit data and consider Thanksgiving data. If you are in charge this year, and you have a medium to small oven and fridge, you have to be strategic. When should you cook, chill, and reheat each dish to make the most of your time and oven/fridge space?

I give you my color-coded gantt chart. I used it last year, and it worked like a charm. I took all my recipe data and came up with this chart to make sure I had my timing right. Made it in good old Excel. Nothing fancy, but it did the trick. Feel free to adapt it to your recipes or perhaps your next fundraising event!

Happy Turkey/Tofurky Day.

Data Viz for Nonprofits helps organizations to effectively and beautifully present their data on websites, reports, slide decks, interactive data dashboards and more. Click HERE to learn more about our services and HERE to set up a meeting to discuss how we can meet your particular needs.

Embrace Redundancy

Redundancy gets a bad rap. It’s almost always mentioned as something to avoid. Graphic novelist Nate Powell cautions. “As a visual storyteller, a lot is learning what to include so you're not being redundant between images and text.”

But some research by Michelle Borkin and colleagues points in a different direction. They found that “redundancy was helpful in improving visualization recall and in improving viewers’ understanding of the data being presented. This was true whether it was data redundancy (like labeling your bar chart values, or dual-encoding data) or message redundancy (including the same message in a title, an annotation, a label, a pictogram, etc.)” (Quote from: “How to get people to remember your visualization” by Mike Cisneros and Lilach Manheim.)

Other psychological research also suggests that redundancy can be a friend to memory. (See this research, for example.) And it makes intuitive sense. Perhaps redundancy is good for the same reason you want it on the space shuttle: if one component doesn’t work, it’s good to have a back up. Perhaps it’s just the power of repetition. In either case, it’s a good way to make sure your primary message gets through.

Check out the example below. The main message is that there are a lot of vaccines in development. This is communicated by the title, the number of circles, and the data labels.

Source: https://beta.grafiti.io/facts/1048338

And for more on how to capture attention with data visualizations, check out this data tip and this one and this one too!

Data Viz for Nonprofits helps organizations to effectively and beautifully present their data on websites, reports, slide decks, interactive data dashboards and more. Click HERE to learn more about our services and HERE to set up a meeting to discuss how we can meet your particular needs.

The Most Important Element of Any Chart

After you have chosen a chart type and labored to make it clear and engaging, you still haven’t done the most important part. You haven’t given it a title. And it turns out that “YOUR TITLE IS SUPER IMPORTANT. It’s the thing people look at for the longest, the thing they build the strongest association with, and the thing they’re most likely to remember” according to data visualization research described in “How to get people to remember your visualization” by Mike Cisneros and Lilach Manheim.

So don’t give the title short shrift. Consider what your viewers/readers might want to know. What would capture their attention? What would make them want to learn more? Below are some visualizations posted on Grafiti. The “before” images show their original titles. The “after” images show my new and improved titles. See what you think.

And for more on how to capture the attention with data visualizations, check out this data tip and this one too.

Data Viz for Nonprofits help organizations to effectively and beautifully present their data on websites, reports, slide decks, interactive data dashboards and more. Click HERE to learn more about our services and HERE to set up a meeting to discuss how we can meet your particular needs.

Add This To Make Your Charts Memorable

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 perceived is based, in part, on what we expect to perceive due to memories of 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.

And for more on how to capture the attention with data visualizations, check out this data tip.

Data Viz for Nonprofits helps organizations to effectively and beautifully present their data on websites, reports, slide decks, interactive data dashboards and more. Click HERE to learn more about our services and HERE to set up a meeting to discuss how we can meet your particular needs.

 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

Data TMI? It's A Thing

TMI* is a problem in many realms. It has become a parenting truism to only answer the question asked when our kids ask about sex. “Don't tell the kid every single thing you know about a topic; keep it pretty simple and let them ask you for more detail if they need it,” says  Dr. Carol Queen, a sexologist.

I think the same principle applies to data dashboards. Those of us who create dashboards have a tendency to add too many charts, too many filters, too many measures, too many dimensions. The idea is to anticipate almost any question the user might have and make it answerable with the dashboard. But usually, that’s TMI. We overwhelm the user. It’s not clear why or how to use the dashboard and so it’s not used at all.

So listen to the sexologist. When designing dashboards, focus each one on just a few questions that your intended users have. Then beta test them with a few of those users. If they want more detail, they will ask for it.

Data Viz for Nonprofits help organizations to effectively and beautifully present their data on websites, reports, slide decks, interactive data dashboards and more. Click HERE to learn more about our services and HERE to set up a meeting to discuss how we can meet your particular needs.

* too much information