Get to the Point
HOW GOOD DATA VISUALIZATION IMPROVES BUSINESS DECISIONS
Whatever presents itself quickly and
clearly to the mind sets it to work,
to reason, and to think.”
- William Playfair,
inventor of the pie chart, line graph and bar graph
Contents
4 Introducing Datavis
5 Why Data Visualization?
6 Visual Learning
7 THE VISUAL PERCEPTUAL PROCESS
8 Three Keys to Effective Data Visualization 9 Data Visualization Types
10 LINE CHARTS
12 BAR CHARTS
17 PIE CHARTS
18 GEO-SPATIAL CHARTS
20 CHOOSING THE RIGHT CHART
21 Conclusion
22 RESOURCES
Introducing Datavis
In a data-driven world, leaders
must communicate data clearly to help their organizations recognize trends and drive decisions.
Data visualization (“datavis” for short) improves this communication. It is an effi- cient, effective way of improving how data is consumed, then acted upon, inside an organization.
When turning data into images, there are some core tenets to keep in mind. To get great, compelling visualizations you need to understand why datavis works.
You need to know how to make your data visualizations simpler and more effective.
You want to tell a clear story. You want to get to a key takeaway that will compel your organization into the right actions.
Using effective data visualization prac- tices, companies can turn data into good decisions. Let us help you use it well and save time and resources in the long run.
Why Data
Visualization?
Leadership is a difficult, often a lonely proposition. When you are making busi- ness decisions the livelihoods of employ- ees and stakeholders are in your hands.
Sound decisions require communication both up and down the chain: you have to get your leadership and your team to buy in to your decisions, first in order to carry them out at all, and then to carry them out effectively.
Data visualization accomplishes this.
It allows multiple parties to look at the same rationale behind a decision. It helps you share understanding across departments. We believe a more united company is a more efficient company, and in that sense, sound data visual- ization techniques pay off well into the future.
Why does data visualization work so well? The answer lies deep in your brain.
WHICH TRIANGLE DID YOU UNDERSTAND FIRST?
A plane figure with three straight
sides and three angles.
How much more quickly does
the brain take in images?
Visual Learning
There are three types of learners:
kinesthetic, auditory and visual.
Everyone has some mix of those three, so using them in combination is powerful. Richard Mayer and Valerie Sims, educational psychologists, have found that data materials that use both words and pictures are more effective than words alone.1
HEAR IT
3 days later you’ll remember 10%
SEE IT
3 days later you’ll remember 65%
John J. Medina, a molecular biologist who researches learning, makes simi- lar claims. In his book Brain Rules, he explains that half of our frontal cortex is devoted to visual processes, and that they are the most powerful learning tool we have.2
Data visualization takes advantage of our predisposition toward visual learning.
Effective data visualization does so in a way that maximizes its potential.
John Medina, Brain Rules, 2008
THE VISUAL PERCEPTUAL PROCESS
Maximizing visual learning is about understanding how we perceive images.
Ryan Kumpfmiller from Zencos Consulting3 explains that the mind visualizes in three phases:
When creating data visualizations, keep this process in mind. Distinguish general categories of information from each other by color or form, so that they become clear even at the first perceptual stage.
Accommodate step two by making key pieces of information stand out from the pattern in some way. And remember that working memory can hold a limited amount of information at once; elimi- First, it picks up general at-
tributes, like form or wheth- er an image is divided into sections.
Next, it examines each sec- tion individually, scanning for patterns and noticing incon- sistencies.
Only then does the brain begin to analyze a picture in detail, committing elements of it to long-term memory.
nate all unnecessary information (called
“chart junk”) so that you can speed up the analysis process in step three.
Once you know how to use visual learn- ing in your communication, it’s time to clarify why you’re communicating in the first place. As you create your data visu- alization, ask yourself: what story are you trying to tell?
Three Keys to Effective Data Visualization
Before you share a piece of information or an idea with another person, first answer a few questions.
1.
WHAT IS YOUR ONE BIG IDEA?
Data visualization reveals relationships within the data, and those relation- ships lead you to your point. If your audience looks at a chart, graph or map, what one thing would you want them to learn?
2.
WHO IS YOUR AUDIENCE?
Determine how familiar your audience is with datavis techniques, and present data accordingly.
Just as you might teach a subject differently at a high-school or college level, you would present data differently to an employee versus an executive.
3.
HOW CAN YOU MAKE IT SIMPLE?
Users should look at your chart, graph or map and see a representation of the data, not the presen- tation method.
Data Visualization Types
We are taught to think about data as numbers. Sometimes we fail to understand that numbers tell stories.
They show causes and help others rea- son through issues. Tricia Aanderud of Zencos helps business leaders develop strategies to effectively present data. In her paper, How to Become the MacGyver of Data Visualizations, she details differ- ent types of data visualizations and how to use them most effectively.
LINE CHARTS
• Keep intervals in order
• Connect the dots
• Mention missing data
SHOW RELATIONSHIPS OVER TIME Line charts use the x-axis for time series, such as year, month, hour, or even min- ute. The following line chart is the perfect way to show the arrival rate for consum- er complaints by product. This datavis shows that consumer complaints about mortgages have decreased, while credit reporting complaints doubled and kept going. The line chart makes following the trends easy to understand because it dis- plays information in a linear fashion and connects each data point.
FREQUENCY 5,000
4,000
3,000
2,000
1,000
CONSUMER COMPLAINTS ARRIVAL RATE BY PRODUCT
BANK ACCOUNT OR SERVICE CREDIT REPORTING MORTGAGE PRODUCT:
01/13
02/1303/13
04/1305/13 06/13
07/13
08/1309/13 10/13
11/13
12/1301/14
02/1403/14 04/14
05/14
06/1407/14 08/14
09/14 10/14
11/14 12/14
HOW TO CREATE AN EFFECTIVE LINE CHART
• Start with 0 on the y-axis
• Change the y-axis to add drama
• Use one chart for the trend and one for the big picture
To give the user a clear picture of the data, begin with a y-axis at 0. You can then play with the y-axis to add a clarity to trends. Consider the following graphs and how much more dramatic the trend seems when we changed the y-axis value. The reported product issues are arriving at a dramatic pace, indicating
a product with many issues. When we place the y-axis back at 0 it is easier to understand that there is a flow to the arrival that may even be seasonal. This is an example of using the y-axis to zoom in on a trend and re-setting it at 0 to see the big picture.
2,600
2,500 2,000 1,500 1,000 500 0 2,400
2,200
CONSUMER COMPLAINTS ARRIVAL RATE FOR CREDIT REPORTING
01/2014 02/2014 03/2014 04/2014 05/2014 06/2014 07/2014 08/2014 09/2014 10/2014 11/2014 12/2014 01/2015 02/2015 03/2015
01/2014 02/2014 03/2014 04/2014 05/2014 06/2014 07/2014 08/2014 09/2014 10/2014 11/2014 12/2014 01/2015 02/2015 03/2015
BAR CHARTS
• Start the y-axis at 0
• Limit the number of bars displayed to 10 or fewer
• If there is an “Other,” it should be a low percentage
CHOOSE BETWEEN A BAR CHART AND A LINE CHART
Bar charts provide more detailed infor- mation than line charts. This datavis type makes it easier to compare exact quan- titative categories. There are two types of bar charts: vertical and horizontal.
Vertical charts compare categories while horizontal charts work especially well for ranking.
300 250 200 150 100 50 0
300 250 200 150 100 50 0
HOW MANY CONSUMER LOAN COMPLAINTS WERE RECEIVED?
Mar2012 Apr2012 May2012 Jun2012 Jul2012 Aug2012 Sep2012 Oct2012 Nov2012 Dec2012 Jan2013 Feb2013 Mar2013 Apr2013 May2013 Jun2013 Jul2013 Aug2013
Mar2012 Apr2012 May2012 Jun2012 Jul2012 Aug2012 Sep2012 Oct2012 Nov2012 Dec2012 Jan2013 Feb2013 Mar2013 Apr2013 May2013 Jun2013 Jul2013 Aug2013
In the following figure, you can more easi- ly see how the line chart allows the eye to see the trend while the bar chart shows a specific value.
HOW TO CREATE AN EFFECTIVE BAR CHART
• Keep white space between bars
• Use like colors for like data sets
• Avoid patterns on the bars
Web
Referrals
Postal Mail
Phone
Other
WHICH CHANNEL DO CUSTOMERS PREFER?
10%
0% 20% 30% 40% 50% 60%
Referrals Postal Mail Phone Fax Email Other
Which Channel do Customers Prefer?
10%
0% 20% 30% 40% 50% 60%
Web
Referrals
Postal Mail
Phone
Other
WHICH CHANNEL DO CUSTOMERS PREFER?
10%
0% 20% 30% 40% 50% 60%
Referrals Postal Mail Phone Fax Email Other
Which Channel do Customers Prefer?
10%
0% 20% 30% 40% 50% 60%
REMOVE EXTRA LINES AND COLORS Below is a bar chart makeover. You can see how much easier it is to read and understand the simpler chart on the bottom. In addition, the “Other” category was more appropriately handled. In the original the Fax and Email categories appeared to contribute almost nothing.
Moreover, there was no value in having different colors for the categorical values;
that extra information simply distracted the eye.
WHEN TO USE STACKED BAR CHARTS Use stacked charts to reveal the whole and show how each part contributes.
In the following figure, you can see a stacked chart both horizontally and vertically. Notice that the percentages
100,000
CHANNEL
MORTGAGE CREDIT REPORTING BANK ACCOUNT OR SERVICE 80,000
60,000
40,000
20,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
100,000 CHANNEL
MORTGAGE
CREDIT REPORTING
BANK ACCOUNT OR SERVICE
80,000 60,000
40,000 20,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
100,000
CHANNEL
MORTGAGE CREDIT REPORTING BANK ACCOUNT OR SERVICE 80,000
60,000
40,000
20,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
100,000 CHANNEL
MORTGAGE
CREDIT REPORTING
BANK ACCOUNT OR SERVICE
80,000 60,000
40,000 20,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
are sorted, which ranks the values. Even with values not shown as percentages, you get a sense of how many more com- plaints are about mortgages than about other categories.
WHEN TO USE GROUPED BAR CHARTS Grouped charts are easier to compare across categories. Notice that the white space is between Product instead of Channel. Your eyes pick up the visual clue that those items are related within the grouping. This chart doesn’t give you a sense of overall counts but it does
show the Web channel as the most popular contact method. You also see that almost no one uses postal mail to complain about his or her bank account, but it is a popular method for the other categories.
50,000
CHANNEL
MORTGAGE CREDIT REPORTING BANK ACCOUNT OR SERVICE 40,000
30,000
20,000
10,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
50,000 CHANNEL
MORTGAGE
CREDIT REPORTING
BANK ACCOUNT OR SERVICE
40,000 30,000
20,000 10,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
50,000
CHANNEL
MORTGAGE CREDIT REPORTING BANK ACCOUNT OR SERVICE 40,000
30,000
20,000
10,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
50,000 CHANNEL
MORTGAGE
CREDIT REPORTING
BANK ACCOUNT OR SERVICE
40,000 30,000
20,000 10,000
0
STACKED VERTICAL BAR CHART (Part to the Whole)
PHONE POSTAL MAIL REFFERAL WEB
WHEN TO USE HORIZONTAL BAR CHARTS
Horizontal bar charts assist with making comparisons, but are also useful to sim- plify long labels. Notice in this example the difference in the labels. The slanted labels are difficult to read because they are too long. By turning the chart on its side, the values become much easier to understand.
0 1000 2000 3000 4000 5000
5,000 4,000 3,000 2,000 1,000 0
Con’t att
empts collect debt o
wned Communications tacticsDisclosure v
erification of debt False stat
ements or representation
Improper contact or sharing of inf
o Taking/threat
ening an illegal action
Con’t attempts collect debt owed
Communications tactics
Disclosure verification of debt
False statements or representation
Improper contact or sharing of info
Taking/threatening an illegal action
COMPLAINTS ABOUT DEBT COLLECTORS COMPLAINTS ABOUT DEBT COLLECTORS
0 1000 2000 3000 4000 5000
5,000 4,000 3,000 2,000 1,000 0
Con’t att
empts collect debt o
wned Communications tacticsDisclosure v
erification of debt False stat
ements or representation
Improper contact or sharing of inf
o Taking/threat
ening an illegal action
Con’t attempts collect debt owed
Communications tactics
Disclosure verification of debt
False statements or representation
Improper contact or sharing of info
Taking/threatening an illegal action
COMPLAINTS ABOUT DEBT COLLECTORS COMPLAINTS ABOUT DEBT COLLECTORS
PIE CHARTS
• Use pie charts sparingly
• Start with 100% and display parts of a whole from there
• Limit the number of variables you display to 4 or 5
• A good, simple pie chart won’t need a legend
BE CAREFUL WITH PIE CHARTS Look at the pie chart below. Is it effec- tive? The answer is no. When there are too many variables to display and a user has to look from the legend to the graph, the point is lost. Here, the horizontal bar chart is the more effective datavis.
0 20,000 40,000 60,000 80,000 100,000 Credit Reporting
Credit Card
Bank Account or Service
Debt Collection
Student Loan
All Other
WHICH PRODUCTS GENERATE THE MOST CONSUMER COMPLAINTS?
WHICH PRODUCTS GENERATE THE MOST CONSUMER COMPLAINTS?
Bank Account or Service Consumer Loan Credit Card Credit Reporting Debt Collection Money Transfers Mortgagae
Other Financial Services Payday Loan
Prepaid Card Student Loan
Product
0 20,000 40,000 60,000 80,000 100,000 Credit Reporting
Credit Card
Bank Account or Service
Debt Collection
Student Loan
All Other
WHICH PRODUCTS GENERATE THE MOST CONSUMER COMPLAINTS?
WHICH PRODUCTS GENERATE THE MOST CONSUMER COMPLAINTS?
Bank Account or Service Consumer Loan Credit Card Credit Reporting Debt Collection Money Transfers Mortgagae
Other Financial Services Payday Loan
Prepaid Card Student Loan
Product
GEO-SPATIAL CHARTS
• Ensure geography is part of the data story
PLOT REGIONAL RESULTS
In the following figure, the markers indicate where tornadoes with an F5 strength occurred. A Geo-Coordinate map allows the datavis to show the exact location at which an event oc- curred, an issue that you can imagine particularly concerns users. It also helps the user understand where in the county the event is most likely to occur.
COMPARE REGIONAL AREAS
Using a Geo Region map, you can place a value over the entire region, such as a country or a state. In this datavis, you can see the associated property damage for the tornadoes. The darker the color, the more damage the storm caused. The storm events appeared to have been in- tense in the southern states, but surpris- ingly Kansas and Ohio had a more costly impact.
COMBINE DATA WITH A BUBBLE MAP You may find yourself not wanting to compare the previous maps but instead want the data on a single chart, which is what a Geo Bubble Plot allows. The size of the bubble represents the frequency of events, while the color explains esti- mated property damages. Now it is more apparent that Kansas endured almost as many events as Alabama but suffered more damage.
CHOOSING THE RIGHT CHART
When you have options, it is important to go back to our three keys to effective data visualization before you choose your chart or graph.
These three rules will help you narrow your options and choose the right path.
What are you trying to say?
Who are you talking to?
What is the most efficient way
to convey the information?
Conclusion
We live in a world inundated with data, and organizations need better ways to communicate it in order to drive good de- cisions. Data visualization improves this communication, which aids organization- al harmony and efficiency. If a business leader can demonstrate why a decision is correct and support that decision with easily consumed information, the whole company can move united behind him or her from the top down.
When you learn to create truly effective data visualizations, you can lead your organization in the right direction.
To learn more about data visualization techniques and how your organization can distill data into decisions, read a white paper from a Zencos consultant.
“How We Visualize Data and How to Apply Those Findings in SAS® Visual Analytics.”
Ryan Kumpfmiller
“How to Become the MacGyver of Data Visualizations.”
Tricia Aanderud
Resources
1. Mayer, Richard and Valerie K. Sims.
“For Whom Is a Picture Worth a Thou- sand Words? Extensions of Dual-Cod- ing Theory of Multimedia Learning.”
Journal of Educational Psychology, Vol.
86, No. 3, 389-401. 1994. Retrieved from http://visuallearningresearch.wiki.
educ.msu.edu/file/view/Mayer+%26+- Sims+%281994%29.pdf/50533673/
Mayer+%26+Sims+%281994%29.pdf, 11/10/2015.
2. Medina, John. Brain Rules: 12 Princi- ples for Surviving and Thriving at Work, Home, and School. Seattle, WA: Pear, 2008. Print.
3. Kumpfmiller, Ryan. “How We Visualize Data and How to Apply Those Findings in SAS® Visual Analytics.” Zencos. 2015.
4. Aanderud, Tricia. “How to Become the MacGyver of Data Visualizations.” Zen- cos. 2015.
