Get to the Point HOW GOOD DATA VISUALIZATION IMPROVES BUSINESS DECISIONS

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 efficient, 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 practices, 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 business decisions the livelihoods of employees 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 visualization techniques pay off well into the future. Why does data visualization work so well? The answer lies deep in your brain. How much more quickly does the brain take in images? A plane figure with three straight sides and three angles. WHICH TRIANGLE DID YOU UNDERSTAND FIRST? GET TO THE POINT 5

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 John J. Medina, a molecular biologist who researches learning, makes similar 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 HEAR IT 3 days later you ll remember 10% SEE IT 3 days later you ll remember 65% John Medina, Brain Rules, 2008 Data visualization takes advantage of our predisposition toward visual learning. Effective data visualization does so in a way that maximizes its potential. GET TO THE POINT 6

THE VISUAL PERCEPTUAL PROCESS Maximizing visual learning is about understanding how we perceive images. Ryan Kumpfmiller from Zencos Consulting 3 explains that the mind visualizes in three phases: First, it picks up general attributes, like form or whether an image is divided into sections. Next, it examines each section individually, scanning for patterns and noticing inconsistencies. Only then does the brain begin to analyze a picture in detail, committing elements of it to long-term memory. 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- 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 learning in your communication, it s time to clarify why you re communicating in the first place. As you create your data visualization, ask yourself: what story are you trying to tell? GET TO THE POINT 7

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 relationships 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 presentation method. GET TO THE POINT 8

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 reason 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 different types of data visualizations and how to use them most effectively. GET TO THE POINT 9

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 minute. The following line chart is the perfect way to show the arrival rate for consumer 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 displays information in a linear fashion and connects each data point. CONSUMER COMPLAINTS ARRIVAL RATE BY PRODUCT FREQUENCY 5,000 PRODUCT: BANK ACCOUNT OR SERVICE CREDIT REPORTING MORTGAGE 4,000 3,000 2,000 1,000 01/13 03/13 05/13 07/13 09/13 11/13 01/14 03/14 05/14 07/14 09/14 11/14 02/13 04/13 06/13 08/13 10/13 12/13 02/14 04/14 06/14 08/14 10/14 12/14 GET TO THE POINT 10

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. CONSUMER COMPLAINTS ARRIVAL RATE FOR CREDIT REPORTING 2,600 2,400 2,200 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 2,500 2,000 1,500 1,000 500 0 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 GET TO THE POINT 11

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 information than line charts. This datavis type makes it easier to compare exact quantitative categories. There are two types of bar charts: vertical and horizontal. Vertical charts compare categories while horizontal charts work especially well for ranking. In the following figure, you can more easily see how the line chart allows the eye to see the trend while the bar chart shows a specific value. HOW MANY CONSUMER LOAN COMPLAINTS WERE RECEIVED? 300 250 200 150 100 50 0 Mar2012 Apr2012 May2012 Jun2012 Jul2012 Aug2012 Sep2012 Oct2012 Nov2012 Dec2012 Jan2013 Feb2013 Mar2013 Apr2013 May2013 Jun2013 Jul2013 Aug2013 300 250 200 150 100 50 0 Mar2012 Apr2012 May2012 Jun2012 Jul2012 Aug2012 Sep2012 Oct2012 Nov2012 Dec2012 Jan2013 Feb2013 Mar2013 Apr2013 May2013 Jun2013 Jul2013 Aug2013 GET TO THE POINT 12

HOW TO CREATE AN EFFECTIVE BAR CHART Keep white space between bars Use like colors for like data sets Avoid patterns on the bars 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. Which Channel do Customers Prefer? WHICH CHANNEL D Referrals Web Postal Mail Phone Fax Email Referrals Postal Mail Phone Other Other 0% 10% 20% 30% 40% 50% 60% 0% 10% 20% tomers Prefer? WHICH CHANNEL DO CUSTOMERS PREFER? Web Referrals Postal Mail Phone Other 40% 50% 60% 0% 10% 20% 30% 40% 50% 60% GET TO THE POINT 13

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 are sorted, which ranks the values. Even with values not shown as percentages, you get a sense of how many more complaints are about mortgages than about other categories. STACKED VERTICAL BAR CHART (Part to the Whole) CHANNEL PHONE POSTAL MAIL REFFERAL WEB 100,000 MORTGAGE 80,000 CREDIT REPORTING 60,000 40,000 BANK ACCOUNT OR SERVICE 20,000 0 0 20,000 40,000 60,000 80,000 100,000 L rt to the Whole) WEB STACKED VERTICAL BAR CHART (Part to the Whole) CHANNEL PHONE POSTAL MAIL REFFERAL WEB 100,000 80,000 60,000 40,000 20,000 0 80,000 100,000 MORTGAGE CREDIT REPORTING BANK ACCOUNT OR SERVICE GET TO THE POINT 14

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. STACKED VERTICAL BAR CHART (Part to the Whole) CHANNEL PHONE POSTAL MAIL REFFERAL WEB STAC MORTGAGE 50,000 40,000 CREDIT REPORTING 30,000 20,000 BANK ACCOUNT OR SERVICE 10,000 0 10,000 20,000 30,000 40,000 50,000 0 M ART (Part to the Whole) REFFERAL WEB STACKED VERTICAL BAR CHART (Part to the Whole) CHANNEL PHONE POSTAL MAIL REFFERAL WEB 50,000 40,000 30,000 20,000 10,000 00 40,000 50,000 0 MORTGAGE CREDIT REPORTING BANK ACCOUNT OR SERVICE GET TO THE POINT 15

ents or representation t WHEN TO USE HORIZONTAL BAR CHARTS Horizontal bar charts assist with making comparisons, but are also useful to simplify 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. COMPLAINTS ABOUT DEBT COLLECTORS COMPLAINT 5,000 4,000 3,000 2,000 1,000 0 Con t attempts collect debt owed Communications tactics Disclosure verification of debt False statements or representation Communications tactics Disclosure verification of debt Con t attempts collect debt owned Taking/threatening an illegal action Improper contact or sharing of info False statements or representation Improper contact or sharing of info Taking/threatening an illegal action OLLECTORS COMPLAINTS ABOUT DEBT COLLECTORS Con t attempts collect debt owed Communications tactics Disclosure verification of debt False statements or representation Taking/threatening an illegal action Improper contact or sharing of info Improper contact or sharing of info Taking/threatening an illegal action 0 1000 2000 3000 4000 5000 GET TO THE POINT 16

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 effective? 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. WHICH PRODUCTS GENERATE THE MOST CONSUMER COMPLAINTS? W THE Product Bank Account or Service Consumer Loan Credit Card Credit Reporting Debt Collection Money Transfers Mortgagae Other Financial Services Payday Loan Prepaid Card Student Loan Credit Reporting Credit Card Bank Account or Service Debt Collection Student Loan All Other 0 WHICH PRODUCTS GENERATE THE MOST CONSUMER COMPLAINTS? uct Account or Service mer Loan Card Reporting ollection y Transfers agae Financial Services y Loan id Card nt Loan Credit Reporting Credit Card Bank Account or Service Debt Collection Student Loan All Other 0 20,000 40,000 60,000 80,000 100,000 GET TO THE POINT 17

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 occurred, 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. GET TO THE POINT 18

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 intense in the southern states, but surprisingly 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 estimated property damages. Now it is more apparent that Kansas endured almost as many events as Alabama but suffered more damage. GET TO THE POINT 19

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. What are you trying to say? Who are you talking to? What is the most efficient way to convey the information? These three rules will help you narrow your options and choose the right path. GET TO THE POINT 20

Conclusion We live in a world inundated with data, and organizations need better ways to communicate it in order to drive good decisions. Data visualization improves this communication, which aids organizational 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 GET TO THE POINT 21

Resources 1. Mayer, Richard and Valerie K. Sims. For Whom Is a Picture Worth a Thousand Words? Extensions of Dual-Coding 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 Principles 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. Zencos. 2015. GET TO THE POINT 22