Meld Consulting » techniques

New article for Johnny Holland: Deconstruction

Steve Baty — Tue, 14 Apr 2009 10:00:32 +0000

Deconstruction is one of the most frequently used and fundamental analysis techniques in our toolkit. It is used as both a preparatory technique to get research data ready for use in other ways; and a powerful technique in its own right as a method of isolating, exposing, and testing assumptions deeply embedded in our mental models.

One example of deconstruction is turning an interview transcript into a series of separate comments or answers to questions. Deconstruction is often used simply to prepare data for other analytic processes such as manipulation or summarization, or even abstraction.

Read the full article: Deconstructing Analysis Techniques: Deconstruction

Deconstructing Analysis Techniques – johnnyholland.org

Steve Baty — Wed, 18 Feb 2009 02:20:59 +0000

I’m extremely happy to announce the publication of my first article to the interaction design magazine Johnny Holland. The article, titled “Deconstructing Analysis Techniques” looks at the major techniques we use in design research to move from observation to design insights and solutions. Here’s the introduction:

Analysis is that oft-glossed over, but extremely important step in the research process that sits between observation (data gathering) and our design insights or recommendations. In many respects, analysis is crucial to realizing the value of our research since good analysis can salvage something from bad research, but the converse is not so true. This is where the literature tends to fall a little silent, jumping over the analysis techniques straight to a discussion of how best to document and communicate the findings from analysis. This article seeks to begin to redress that imbalance by breaking down the analysis black box into its major sub-techniques.

Please take a read and let me know what you think.

Visualisation is an analytic technique

Steve Baty — Tue, 27 Jan 2009 07:00:53 +0000

I’m working on an article at the moment, as part of a broader series of work on the topic of analysis. That article – which will be published soon, and I’ll post a link to it when its available – is about the different techniques we use during our analysis work.

I won’t pre-empt the main article, but as I’ve thought about these techniques I’ve come to the recognition that data visualisation is an analysis technique. It’s a tool that helps us not only make sense of the data, but offers us a way of analysing it as well.

How does that work? We’re not really doing anything to the data, just making a diagram or illustration, right?

Well, what we’re doing is providing an alternative representation of the data. Let me give you an example: let’s say our data is a list of words and the frequency with which they appear in an interview transcript. It looks like a table of word-value pairs, a little like this:

Analysis: 12
technique: 8
well: 6
etc

Now compare that to this:

Suddenly, the data takes on a new dimension. Literally. The significance of those numbers is made more real, more tangible through the visualization. The same is true of graphs, charts, histograms, radial graphs and pie charts: the visualization of the data adds to the narrative and helps expose patterns, grouping and holes that are otherwise ambiguous or completely obscured as a list of numbers.

Visualizations have the added advantage of being a much better tool for communication than a spreadsheet or lists. You can bring them out at a meeting and elicit interest instead of the glazed expression that only a large spreadsheet seems to bring about. And they can be re-used down the track as an illustration for any reports that may be required.

Lastly, they give you something to look at. A good visual is one of those things that brings your data to life, making it stand out (as we saw above) and really start to speak to you. So during those periods when you’re soaking in the research data and the progress you’ve made on the analysis, those visualizations can provide an anchor for your thinking and help you move on to the next stages of the analysis.

So, don’t discount the power of a good visualization to do more than just communicate. Remember that it can also be a powerful tool for gaining insights from your data, which is, after all, what analysis is all about.