Tag Archives: analysis

3 Very Simple Rules for Displaying Data Effectively

Visualizing data has two separate and distinct purposes, each with a different audience. The first is for exploring the data—examining distributions, identifying trends, observing correlations, and the like—which gives the analyst information that is used to direct the analysis project. In this case, functionality is much more important than style.

The second purpose is for conveying the results, so that any conclusions or significant findings from the analysis can be clearly communicated to another person. Unlike data exploration, however, in this case style is often considered to be more important than functionality—and therein lies the problem.

I work in the music industry, which for the most part is comprised of very creative individuals who tend to place significant emphasis on style and design. As basic data visualization techniques are typically not considered to be very sexy, charts and graphs intended for this audience are often modified to make them as “hip” and stylish as possible. Consider the following graph, which recently appeared in a major music industry magazine. This publication frequently presents data visualizations, and most of them are quite effective (while also being quite stylish), but this one left me scratching my head a little.

[NOTE: The data descriptions have been removed to prevent revealing any specific information, but the two colors represent two points in time for each of the six items.]


At first glance, it appears to be somewhat of a bar chart, but instead of the bars being vertical, they have been conformed into a circular shape, with the circumference of the “circle” equal to 100 (it took me a while to figure that out, and likely never would have if the actual figures had not been there!). This transformation makes the graph quite difficult to interpret because it is now being measured in circular units (where one unit is equal to 360/100 = 3.6 degrees or 2π/100 = 0.0628 radians), and thus the actual lengths of the bars are not the same for any of the six items (in other words, because of its proximity to the radius of the circle, a bar of length 100 for item #6 would be much shorter than a bar of length 100 for item #1). What’s more, the value of zero has been placed on the vertical (y) axis instead of the usual horizontal (x) axis. Other than the fact that item #1 is much greater in value than the other five, it is very difficult to determine much from this chart. This is clearly an example of placing style over functionality—and unfortunately that’s really all that’s clear about it.

There are several sources for learning how to create meaningful visual descriptions of data (I recommend Edward Tufte’s classic text The Visual Display of Quantitative Information as well as Stephen Few’s book Now You See It), but I believe these three simple rules will help guide you in most situations:

1.  Your #1 priority should be clarity of information.  If your audience has to take more than a few seconds to understand what your visualization is trying to convey, it needs to be simplified.

2.  ALWAYS value function over style.  There’s nothing wrong with trying to make your visualizations attractive, but if doing so compromises their functionality, see Rule #1.

3.  Keep your intended audience in mind with regard to functionality.  Early in my career, I submitted a report to management that included a series of boxplots, which resulted in some very puzzled looks. It’s not that these managers weren’t smart, it’s just that they were not accustomed to seeing these kinds of diagrams and thus didn’t know how to properly interpret them. The circular graph described above does appear to have been created with the intended audience’s sense of style in mind, but not necessarily their ability to understand such a cool-looking chart. Always keep visualizations as simple as possible so that your readers can easily understand your message (again, see Rule #1).

Bottom line: the objective of any data visualization is to support the story you’re telling in your analysis. By always focusing on clarity and simplicity, and using elements of style sparingly, your visualizations—and, as a result, your overall analysis—will be much more effective.

5 Questions to Ask Before Responding to an Analysis Request

In any organization, time is at a premium—especially for managers. As an analyst, it is likely that you have received at least one brief and hurried call from a member of management asking for information of some kind, but without taking the time to give you much background because of their busy schedule. When this happens, don’t simply say “OK” and hang up! Instead, take a breath, kindly ask if you could have just a couple of minutes of their time to gain some additional insight, then ask the following questions:

1. Can you give me a brief overview of the situation?

When I was beginning my career as a young analyst, I didn’t feel it was my place to ask this question out of fear that management would think I was overstepping my bounds and venturing into higher-level issues that were none of my business. However, I soon realized that gaining an understanding of the “big picture” helped put what I was being asked to do into context so that I could approach the request from the proper perspective.

2. What’s the objective of this particular analysis?   

Once you know what the situation is, determine specifically what the person hopes to accomplish based on your findings. Not only will this help you focus your efforts, but may also lead you to recommend alternative methods that you believe may address their request more appropriately.

3. How should the results be summarized or presented?

Monthly or quarterly? For the last two years or last five years? By customer group or by region? For all products, or just for a certain line? Clarifying upfront how the person needs the information to be summarized will save you from having to repeat all or part of your analysis if you are unable to segregate the final results in that manner.

4. Do you know if anyone else working on this project or something similar?   

In some cases, another person is asked to work on the same analysis from a different perspective, or to address a separate (but related) part of it. If possible, find out who that person is and coordinate with him or her to prevent duplication of efforts, as well as to avoid providing different results to the same question (which can occur if multiple people each approach the same request using a different dataset or by specifying different parameters).

5. What’s your time table?

This is by far the most significant question of all, because in most cases the overall project (or a significant part of it) cannot proceed until you’ve completed your analysis. But make sure you get a specific (and realistic) answer! Many managers like to say “yesterday” or “ASAP”, but the first response is impossible and the second is vague. Evaluate how long the analysis will take, find out exactly when the results are needed, and mutually agree upon a specific date and time. Keep in touch with the person as the project proceeds, being sure to notify him or her if any issues arise that might delay delivery of the results.

In practice, most managers will eagerly comply with your request for additional information, but there’s always a chance that the person might initially be annoyed with your request. If this is the case, assure the person that you will be as expeditious as possible, but that their responses to your questions will help you deliver the results they need as efficiently and accurately as possible. What’s more (as has been my experience), practicing this technique shows the manager not only that you are capable of thinking at a higher level, but that you are interested in helping that person achieve his or her ultimate objective—and isn’t this what every manager wants?