Lately I have spent a lot of time going to conferences and seminars within the realm of visualizing statistics. I missed out on the OECD conference in Washington July 2009 about “Turning statistics into knowledge”, but Robert Kosara  attended and was nice enough to write a blog post with his impressions of the seminar.See the post here!

His post bring on some interesting points which touches the problem statistical offices/organizations have when trying to get a grip on the development happening in the field of communicating statistics. As an interaction designer I can relate to a lot of what is pointed out in his post.

Before commenting on Robert Kosara’s post, it is important to emphasize some big issues.

1. Fast moving development
   The area of statistical visualization is  moving forward with the same speed as the technological development. New technologies enables new ways of communicating statistics. Statistical offices/organizations are not ahead of this development, but tries hard to be (which is very understandable).
2. Credibility
   This is a very important issue and can’t be emphasized strong enough. A statistical office has to have credibility. A statistical organization must be politically independent. It has to be trustworthy. Not many outside this world (of statistics) knows what important role an independent statistical office plays. It is often THE base for important decisions made by governments and/or political decision-makers. The question of credibility or independency should never be put at risk.
   For a statistical office to achieve these high standards of credibility and independency, it has to be on guard in many ways. One issue is not to simplify too much, or be too tabloid. Another aspect is that it has to communicate statistics (and/or statistical research findings) in a neutral way. And not to favor any particular audience (this is one very important issue for Statistics Norway, where I work, everybody should have the same access to the same statistics, at the same time). [Ref Norwegian article about this principal].
   This is only a few aspects, but as a communicator I have an inkling of how difficult it is to communicate without simplify too much and to communicate in a neutral way to an undefined audience (same access for everybody at the same time). To meet these requirements can be hard. This last point is discussed in more detail later in this post and is an important one for the author of this post.
3. The understanding of communication as a professional field
   The world of statistics has a history of visual communication, a time when it was at the forefront.
   But in the last fifteen or twenty years the technological development has played an important part and done a devastated job in ruining the understanding of visual communication as a profession. Everybody can make a diagram in excel, everybody can make graphics. Everyone has the power to visualize but not necessarily the knowledge to communicate well.  “Everyone’s a critic graphic designer“.
   Making things pretty,  it doesn’t make it more right, or more understandable.
   “Graphic design is about making things more beautiful” is a preconception of my field of profession I know I have to live with for a long time ahead. Though making things beautiful is a part of what I do… it’s far from the most important one. A professional information designer is trained at grapple with what the world of statistics struggles with today, namely how to make things more understandable.

Turning statistics into knowledge

This is a quote from Roberto’s post from the OECD’s conference on Turning Statistics into Knowledge, which I think is worth mentioning.

Nobody really talked about the seminar topic of Turning Statistics into Knowledge. Some of the talks I mention above came close, but there was no explicit discussion of how it might be done. No overarching approach that said: this is our idea of how it might work, what we’re going to demo is the first step, motivated by our overall design. Perhaps that also explains the lack of evaluation: to evaluate, you have to know what you’re evaluating.

These visualization tools do not magically create knowledge, they only produce colored pixels. In several presentations, I got the distinct feeling that they really mostly wanted to make something pretty and colorful, and didn’t really care about how useful it would be.

I can relate to this statement,  after attending quite a few statistical conferences and seminars.  It has  very often been overly focused on what technical platform too choose and on how to make good-looking diagrams. And I think there is a common misunderstanding that technical platform and aesthetics will solve the communication problem, which it alone never will.

Design thinking

“…a process of creative and critical thinking that allows information and ideas to be organized, decisions to be made, situations to be improved, and knowledge to be gained.”
Charles Burnette in his IDeSiGN curriculum

Design thinking is very much about how you approach a problem. It is a very common way to think for designers, often embedded deep in their back spine.

In the world of statistics this is not a very commonly used  method.

The most common way to solve problem without using design thinking, is to start with the product, in this case statistical numbers, then you consider technology and in the end (if you got time) you consider how to present it to the user. In all parts of this process, usually very highly qualified people are at work gathering data, mining the data, researching the data and building technological solutions. In the end somebody get called to color it up and make it presentable (pretty).

Design thinking doesn’t replace the ordinary thinking or process, but  adds to it, in an early stage, and is then capable of testing and adjusting the message into something knowledgeable for the user through design.

The design thinking starts with the user and ask questions like “for whom is this gonna be made for?”, “what is the best way to present this?”,  “is this the best way, or that way?”. Doing tests and adjustments, so it aligns with the user, the technology and the context in which it is to be presented.

To better communicate statistics one has to turn around the whole mindset. The common mindset looks something like this:

1. we have statistics
2. lets get them on the net looking good
3. lets educate the user in the way we think is the right way

Using visual thinking as an approach, it’s sort of the other way around.

1. who is the user?
2. how can we make the specific statistics understandable (for that user)?
3. how is it possible to match the specific statistics criteria with the users need to understand?

To exemplify this, lets make it into a more simpler process by comparing it to the making of a slide show presentation.
When you are making a presentation for a group, you have to think about what you want to get across(content), and to whom you speak. If you first make your presentation without thinking about the audience you may not get your message across, or be understood.
So what is more important? Your message or your audience? This is always a tricky question. If your audience doesn’t understand what you are saying, you might as well skip the whole presentation. Or you can try to understand your audience and present your message in a way they understand.
If you’re trying to communicate well, you have to understand/acknowledge your user/audience.

Kinky problem

And now you probably see the one kinky problem rising on the horizon. Previously I talked about how important it is to be independent and maintain credibility by not favoring any particular audience, by not to oversimplify, but maintain a neutral state. How is it then possible to communicate well?

By pointing out this problem, I’m not saying it is impossible to communicate well. It just mean we have to work harder, work with the right knowledge and evaluate our solutions.

It doesn’t mean a statistical office has to oversimplify or be tabloid. But it means it has to take its users (and potential users) seriously and acknowledge them for whom they are. Then it is possible to communicate efficiently and well.

I like Matthew Ericson(deputy graphics director at The New York Times) approach, when he says that he’s trying to build work for “both Bart and Lisa Simpson,” meaning that it can be surface and simple (like Bart) or deeper and thoughtful (like Lisa). It’s a good way to think about making work that appeals to two very different kinds of readers. [ref: The Update Blog]

Epilog

This post may sound a bit frustrated, but I’m not. I know this is the time of possibilities, it is exiting times. The technology is moving fast forward  and the time will come when the fascination for technology trade places for good solutions.

‘Good visual design is serious in purpose. Its aim is not to attain popular success by going back to the nostalgia of the past, or by sinking to the infantile level of mythical public taste. It aspires to uplift the public to an expert design level. To inspire improvement and progress demands that the designer perform to the fullest limits of his ability. The designer must think first, work later.’ …For Sutnar, the practice of information design, a subset of graphic design, ‘should be understood as the integration of meaning [content] and visualisation [format] into an entity that produces a desired action.’ Conveying information was the designer’s most crucial responsibility.
[Ref: Eyemagazine article on Ladislav Sutnar]

All views expressed in this post is private views.

Last Modified : August 2nd, 2009
Filed under : Statistics Norway, Visualization
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