Build data visualizations into your thought leadership book
As a financial advisor, you’re writing a thought leadership book on topics you’re intimately familiar with. No so much for everyone else — much of what you’re writing about is confusing, if not downright frightening for most of your readers.
That’s why it’s important to use data visualization techniques to connect more closely with your readers. Data visualizations — or graphic elements — serve to enhance the written page. They provide entry points into complex concepts for the reader and offer a fresh presentation of facts and points. Data visualization techniques that you might want to use include lists, callouts, drop quotes, sidebars, tables and charts
Graphics are a fantastic addition to your book, enhancing your examples, appealing to readers with different learning styles and, of course, breaking up large blocks of text. Data visualization through graphic elements helps your readers connect with your content in a different way than the written word. That’s the good news. The bad news is that it costs more to format and publish a book that includes graphic elements. You will also likely incur additional charges for a graphic artist to actually format charts and tables so that they fit within the book’s format.
A middle ground with graphics
Remember that you aren’t choosing from two extremes — lots of graphics or none. There is a middle ground. It might make sense to talk to a few of the book publishing and design companies I mention in Publish Your Book to get a sense of how much graphic elements might cost. Perhaps you could include two or three graphic elements per chapter at a more reasonable cost than graphic elements on every page.
Once you’ve decided how big of a part graphic elements will play in your book, it’s time to take a look at your completed manuscript and decide what types of graphic elements you want and where you want to place them. This chapter is designed to help you make all those decisions.
Value-add of graphics
As I’ve mentioned, graphics are a type of data visualization. Data visualization work because “data analysis and visualization isn’t only about reporting change; data can actually bring about change, according to Eva Murray in a Forbes.com article. “Data can change opinions. It can instill values and translate experiences. It can influence society and inform human behavior .”
Data visualizations are powerful precisely because human minds are wired to interpret the world through stories. In the book, Story Genius: How to Use Brian Science to Go Beyond Outlining and Write a Riveting Novel, Lisa Cron writes, “Humans are wired for story. We hunt for and respond to certain specific things in every story we hear, watch, or read—and they’re the exact same specific things, regardless of genre. Why is this so? Because story is the language of the Brian. We think in story. The brain evolved to use story as its go-to ‘decoder ring’ for reality, and so we’re really expert at probing stories for specific meaning and specific info—and I mean all of us, beginning at birth “.
It happens that graphic elements using data visualizations offer a powerful approach for telling stories in a way that humans can easily digest. Graphics provide an alternative entry point into your material and can often communicate a difficult to understand point in a way that words can’t. When you put words and graphic elements together, that union packs a powerful punch and shortcuts the time that it takes readers to understand what you’re trying to communicate.
Example: Graphics in Sequence of Returns Risk
When I write about sequence of returns risk, I unpack the concept incrementally, in a step-by-step way. I include analogies, client stories and examples. I don’t use the same presentation every time because the advisors that I work with have different approaches to the concept. Because it is such a complex topic, there are numerous ways to approach that it involve some kind of graphic element.
Explaining sequence of returns risk appropriately should take at least several paragraphs of copy because you need to break down each concept within the larger concept and bring the reader along a logical progression of ideas. I usually include some type of client story. Just about every financial advisor I’ve worked with has a sad story of someone who retired right before the market tanked in 2008, so use that one. Or you can talk about the client who decided not to retire then, and ended up in a much better position a year or two later and why that happened.
One approach is to complement a written example with a chart — or two charts — that show the impact of market returns on a portfolio of the same size. For simplicity’s sake, I would use a simple number such as a $500,000 or $1 million retirement portfolio allocated 60 percent to stocks and 40 percent to bonds. The I would start the portfolio at two different dates — one with a retirement date of Jan. 1, 1998 and the other with a retirement date 10 years later of Jan. 1, 2008. Then I would graph the ups and downs of how that portfolio performed during the next 10 years. You can certainly other dates and other time frames — this is just a suggestion.
If that’s too complicated, a more simple presentation that shows the beginning and ending values can work to make your point nearly as well. You could even use a callout that reports the unhappy outcome of someone who retired at the wrong time or the difference between an unhappy and happy outcome.
Data visualizations don’t have to be complicated to work. In fact, it can be easy sometimes to go overboard and make your visualizations more complicated than they need to be. There’s an art to data visualizations, which is why you might want to hire a graphic artist experienced with financial data to help create graphics for your book.
Types of data visualizations
There are many different types of graphic treatments and many ways to visualize data. You’ve probably noticed that I use several different types of graphic treatments in this ebook series: callouts, drop quotes, sidebars and lists. In addition to these graphic elements, many thought leadership books use word clouds, timelines, pie charts, bar chart, line chart and scatter plots.
There are many other types of data visualizations you can use, but I want to focus on these because they are the most common types that readers tend to be familiar with. Just like you don’t want to run wild with long, dense paragraphs, you don’t want to run wild with too many complex types of data visualization. Here’s a breakdown of what these types of data visualization are and what they are designed to accomplish:
Callouts: A short phrase or sentence highlighted a larger type size to bring attention to a specific point
Drop quote: A quote from someone well known in your field that supports your specific point
Sidebars: A longer block of copy designed to provide an example or emphasize a specific point
Lists: Bulleted or numbered lists create an easy way to break up what could be a large block of listed text
Word clouds: Presentation of a group of related words that shows how they are related to each other in terms of frequency of use. Shows which terms are used more frequently than others
Timelines: Shows the historical changes over a specific period of time
Pie chart: Illustrates parts of a whole relationships in a way that is easily scannable
Bar chart: Organizes data into rectangular bars that allow readers to compare lanes in the same category or parts to a whole
Line chart: Connects points on a line to show trends, patterns and volatility in data
Scatterplot: Organizes multiple points of data so that viewers can understand the distribution of and relationship between data points
In a recent financial planning book that I collaborated on, there were at least 50 charts and graphs in the 65,000 word manuscript.
That may not seem like a lot given the length of the book or just the sheer number — 50 — may seem large. I will say that while these graphics are definitely going to compliment the book and make it a better read, adding graphics creates even more complexity in a book project, which is already complex by nature. That’s because relevant data must be sourced before the data visualization can be created. The best format must selected and then the graphic must be numbered and appropriately integrated into the copy.
You can’t just throw a chart up in the middle of text and expect people to understand it’s relevance. You also can’t leave it floating in space. You have to organize all your charts and graphs by number and by chapter. So if you have four data visualization elements in Chapter 5, you would label those Exhibit 5.1, Exhibit 5.3, Exhibit 5.3 and Exhibit 5.5. Each would need it’s own title and then a source with an endnote at the bottom.
For example, if you wanted to show the rate of inflation during the past 10 years, you would use Consumer Price Index information from the U.S. Bureau of Labor Statistics. Then you would convert that into a chart using excel or some other data visualization tool. You would label it with the appropriate number and create a note directly underneath the graphic that says: Source: U.S. Bureau of Labor Statistics with an endnote containing the URL, date of the data, name of the federal department and bureau and date you accessed that information.
A final word
Like I said, it’s complicated. However it does add more credibility to your book. How? Because you’re employing credible evidence to support your points and showcasing it with a data visualization. Readers respond well to credible evidence and to data visualizations, giving you a one-two punch and advantage in explaining complicated material. Also, readers are used to graphs and charts and having information broken up. They are accustomed to easily consuming material, so you don’t want to make it too difficult for them, which can happen when you have long blocks of text without breaks for drop quotes, lists, sidebars, callouts, graphs and charts.