Storytelling with Data: A Data Visualization Guide for Business Professionals Paperback – November 2, 2015

People wanting a basic introduction to presentation graphics would be
well served by this book by Cole Nussbaumer Knaflic. Prerequisites are
minimal: there is almost no mathematical content and no use of any but
the most elementary statistical methods. Knaflic's encouraging message
is that MS Excel and PowerPoint can be quite enough software for good
graphics, but you will need to go beyond the defaults and work at the
details.

Almost all the examples are of very small datasets already to hand with
two-way structure. 2 variables for 12 months and 5 products for 7 years
are typical sizes. In practice when analysing data it can be hard work
deciding what methods to use and reducing a mass of raw data to a
concise summary. These steps, sometimes most of a project, are here
assumed already done.

The subtitle flags a focus on "business professionals"; the content
tactfully implies junior people presenting with PowerPoint to
time-challenged bosses at brief meetings. Seemingly few write reports to
be read any more, or use any other presentation software.

Knaflic is excellent on the need to keep things simple. She has a good
eye and sound logic on what looks and works well and what does not.
Examples show how mediocre graphs can be improved by reducing clutter,
killing the key, better use of color, and similar standard tricks.
Horizontal bar charts are usually more readable than vertical, and pie
charts and a false third dimension are best avoided: these points have
been well made many times, yet do deserve forceful repetition. Various
kinds of bar and line charts are her main work-horses.

Sometimes the discussion seems a little contrived, as poor graphs are
set up to be shot down, but that's often what convinces. Readers should
be on the author's side as she encourages us towards effective and
tasteful graphics. Her combinations of blue for data deserving emphasis
and grey for data providing context -- or of blue and orange for groups
to contrast -- are good design patterns for experienced analysts as well
as outright beginners.

The closing chapters are more long-winded and repetitive, but do include
small gems. A splendid case study on avoiding spaghetti graphics (lots
of tangled lines) stands out, and the problem and the ideas deserved
more.

I always find it disappointing when datasets are fabricated or
sufficiently anonymous that they might as well be. People care most
about their own data which an author cannot provide, and confidentiality
constraints often bite, but real data examples are still generally
preferable to fake. Too many examples here are variants on Products A to
E or Features A to O. Unfortunately an outrageous example of a bar
chart from a well-known U.S. television news network (p.50) seems all
too real.

What's not here includes Cleveland dot charts, histograms and box plots
even among the staples of good introductory statistics courses, let
alone (say) use of logarithmic scale, always one of the first graphical
devices for many sciences. So if you want something with more
statistical bite or depth, you need to look elsewhere. Naomi Robbins'
excellent, no nonsense Creating more effective graphs
http://www.amazon.com/Creating-Effective-Graphs-Naomi-Robbins/dp/0985911123
would enable you to go further.

As in any first edition there are some small slips and exaggerated
claims. 40% is not a majority (p.5). There is confusion between number
and percentage on p.39. Any rule that "bar charts must have a zero
baseline" (p.52) is simplistic. It is quite correct that bar charts
should encode departures from some sensible reference level. (The
television network responsible should have paid attention.) But that
reference level could easily be some value not zero, such as parity
between men and women, or the mean of a variable, or 32 degrees
Fahrenheit to separate freezing and non-freezing temperatures. I
disagree that every dollar amount or percent should be labeled as such
(p.90); that is repetitive clutter such as Knaflic rightly deplores. Nor
is it an absolute principle that every axis needs a title. If the axis
labels are 2008 to 2015, no one should need "Year" to explain what is
happening. Far from being "extremely rare" (p.141), several exceptions
to that principle are included in this book!

A note on style: Inside a very useful book is an even more useful
shorter book struggling to get out. For my taste, the motivational
warm-ups and little anecdotes are often too spun-out or too trite. Good
graphics should be presented as illustrations within a good story: a key
point, but not one that required a long chapter with digressions on Red
Riding Hood or on Aristotle on drama, or advice from a junior high
school teacher. A tighter copy-editor would have signalled that
"leverage" (used as a verb about 70 times) was too much of a personal
favorite, while "de-emphasize" for "tone down", "utilize" for "use" and
"incredible" for things all too credible are among several other
repeated tics.

An easy solution is to skip and skim: if a book is on graphics, you can
always just look at the graphics. In this case, Knaflic has written a
worthwhile book that, small details aside, does well what it tries to
do.

If I could go back in time to one point in history I would go back to the start of my career to give myself this book. I stumbled across this just by happenstance after leaving my boss’ office completely frustrated. I had spent a good amount of time on a report for him that showed number of sales leads, conversions, locations, etc. just to have him proceed to rip apart everything I had worked so hard on. I kept telling him that the data was all there and that he just wasn’t looking at it right. I went to the internet to find something to help me build better dashboards. I found “storytelling with data”. I read the entire book as fast as I could. I then spent the next few days fixing my entire report. Turns out that it wasn’t my boss that was looking at the report wrong, he just had a very busy story to try and read to get the data he was looking for (complete with pie charts). After reading Cole’s book I completely changed the way I approach reports and dashboards. Now, I can send them out to our team and not get a hundred email responses to clarify everything. The story is getting told. I would recommend this book to anyone and everyone. I currently have 52 books (I’m somewhat of a book nerd) on my desk and shelf at work… this one is my favorite of them all.

Cole takes a difficult subject and makes it understandable. By itself that would be good and worthy of praise. Clarity is always appreciated. But she does this by employing the skills, traits, and tricks that she so clearly explains. Cole implores the reader to eliminate clutter, visually demonstrates why it is important and its potential impact, then strips away at difficult concepts with clear and concise prose again and again. We readily grasp all this because of her use of context, visual display, simplicity, focus, design, and in so doing she tells a story about dealing with data and information, so that we can inform and not confuse. Perfect. But she achieves even more because through the use of these concepts she makes them useful for everyone and not only those dealing with large data sets; she demonstrates that which she illustrates. I'm a trial lawyer. I found her chapters on thinking like a designer and lessons in storytelling to be more than helpful. From the importance of aesthetics, audience, controlling narrative flow, to repetition she provides lessons in telling stories that can benefit anyone. Recommended for everyone!

Very rarely do I find a business book that so fully meets my needs and expectations...and then surpasses them.

As a full-time business analyst who was hoping for some practical guidance to improve his visualisations, I was delighted by how clearly the author delivered it with her easily understood concepts and step-by-step demonstrations.

Whether you are already acquainted with data analytics tools like Tableau but think your presentations look boring or you're an artistic designer who can't figure out how to use software to express your point, you need this book!

This is far and away the BEST data vis book because it goes beyond the techniques for making visualizations to the ways in which you can connect with clients, co-researchers, and stakeholders. This is an essential book for effective reporting and dissemination of information. Truly exceptional.

As a graphic designer working in finance, this book has become my bible. I have dozens of books on data visualization, but unlike the others, this book is the most applicable to my every day work, and I keep it close to my desk and reference it regularly.

It is both easy to read and easy to skim if looking for a specific topic (the glossary at the back is also quite helpful).

I can't recommend this book enough for those who work in marketing, graphic design, or are knee-deep in data all day. Put an end to ineffective graphs and buy this book.