Organizing and Interpreting Complex Sets of Survey Data

Large surveys make the task of data analysis much more complex. In order to uncover meaningful information from your large survey efforts, you will need to define a logical process for organizing and interpreting survey data at the start. While there are numerous techniques you could employ, the following offers a series of reliable techniques for working with complex sets of survey data. Continue reading

The Rise of Infographics in Presenting Data Analysis

In an earlier post we talked about the difference between graphics used for visualization of data points and graphics used for presentation.  We concluded that the point of an analyst’s effort when analyzing survey data was to communicate the results to busy decision makers in a format they could understand.

Enter The Infographic

Using information graphics to convey an idea or meaning has been around since the earliest cave paintings. Today, infographics are an essential part of the survey analysts tool box because they convey complex data in an easy to follow and visually appealing format.

From blog posts and web articles to glossy brochures and of course, data analysis presentation, infographics are a ubiquitous part of the information landscape. But why have they become so prevalent?

Infographics Are Easier Than Ever To Create

Modern computers and sophisticated software can easily render thousands, even millions, of data points into a visual representation, often with nothing more than a mouse click.  What used to take hours to create by hand (and yes, most graphics used to be done by hand, I’m talking 1980s and 90s, not the 1800s!) can now be done as a matter of course.

Decision Makers Have Faster Access To More Data than Ever Before

The trend toward greater use of infographics results in part from the speed at which information is available to decision makers. The Internet and the World Wide Web have transformed not only how we receive our information but how fast we have access to it.  Also, our expectations regarding how much information we are willing to absorb has changed.  When was the last time anyone picked up a 2000 page reference book and actually read it?

It’s Easier To Look At An Infographic Than It Is To Read About The Same Thing

Today data and information comes at us in packets.  This blog post is an excellent example.  It’s short, concise, and to the point.  The title and sub headings tell you most of what you want to know regarding the topic and they provide key information you might need to justify a decision to use more infographics in your next data analysis presentation.  The rest of these words are written to support the headings but the important information might’ve been rendered visually rather than in prose.  If it were, you might have spent half the time absorbing the information.

Now, if I could present this post using only an infographic…

Presenting Analytics to the C-Level Executive

For many analysts, presenting your data analysis and reporting to C-Level executives is challenging and often frustrating. The company invests a lot of time, money and effort in the process. The data is clean, the proper conclusions are drawn and the information is communicated and visually supported by charts, graphs and tables in a bang up presentation.  So why is it often ignored or given little weight in the decision making process?

The answer is found in the disparity between the mind set of the analyst and that of the executive.  The analyst looks at data, cleans it, looks at it again, thinks about the data, thinks about the problem, looks at the data again and comes to a conclusion.  The decision is driven by the data, not by the analyst. It is very logical.  Not so with C-level executives.

To say that C-level execs make decisions based solely on their gut feeling or past experience is to do them a disservice.  Although this often appears to be the case, most execs make decisions, whether they realize it or not, based on the axiom, what’s good for the company is good for me provided (this is important) the decision is one I can personally benefit from (increase in power, acknowledged success, etc.) or one I can deflect if the decision proves detrimental. Data analysis and logic have little to do with it.

As an analyst you have a greater chance of C-level execs accepting your data analysis and reporting if you understand these 5 rules.

  1. Less is more.  State your conclusion first but don’t say how you came to that conclusion.
  2. Stay on point. Don’t provide information that doesn’t directly support your conclusion.
  3. Numbers are boring. Execs will only “hear” a number that has a dollar sign in front of it.  So don’t use them.
  4. Speak in plain English.  No jargon. If you must use a technical term explain it briefly and succinctly (without using other terms to describe that one!)
  5. Give’em what they want, leave’em wanting more. Present charts and graphs only if the exec asks for them (have them in a packet if presenting to a group).

Although the data is clear, let the exec ask questions that leads them to the conclusion you already know. It empowers them, allowing them to decide what’s best for the company rather than having the data force their hand. Being heard will empower you.