Content Analysis
At the very bottom of each site sits the content that users spend time trying to find. We must immerse ourselves in this messy reality before we can craft workable solutions. A bottom-up approach will help us do that.
Begin content analysis by gathering a representative sample of your site's content. There's no need to get overly scientific with the sample definition. Rather, adopt a Noah's Ark approach: Try to capture a couple of each type of animal. "Gathering Content" should help you distinguish one beast from another and create a diverse, useful sample.
When you examine each content object, ask basic questions such as: What is this content object? How can I describe it? What distinguishes it from other content objects? How can I make it findable?
Once you've reviewed a few dozen content objects, patterns and relationships will emerge that inform your definition of structural, descriptive, and administrative metadata.
We'll return to metadata in a moment, but first let's acknowledge what we haven't done. We haven't allowed the overwhelming volume of documents and applications to scare us from looking at any content. While we may not be able to see the whole picture, our designs will at least be informed by parts of the whole.
Information Ecologies
Now let's survey the broader research terrain. Our goal is to learn enough about the existing system to make real improvements during the redesign. An important step toward success is the recognition that we really can make things worse if we're not careful.
Ecologies offer a useful analogy. In the natural world, researchers have opened our eyes to the interdependence of systems. While we might love to rid ourselves of pestilential mosquitoes, we now understand the critical role they play as a source of food for ants, bats, birds, and so on.
This type of hidden interdependence is also present in our information ecologies. Changes to a single interface or subsystem may have a ripple effect with harmful consequences. To avoid inadvertently damaging something, we need a well-rounded research program designed to study the information ecology from top to bottom. Core elements should include: stakeholder interviews, user interviews, usability testing, search log analysis, and content analysis.
Blind Taxonomies
Once you've done content analysis and researched the heck out of your information ecology, you can finally put on blinders and build the taxonomy, right? Yes, absolutely, as long as you're not bothered by creating something that's unusable and unsustainable. The first rule in resisting reductionism is that you never really get to put blinders on. Focus and discipline are good. Willful ignorance and obliviousness are not.
I have been flabbergasted in recent months by taxonomy construction projects in Fortune 500 companies. Some completely lack user research, and there is often a fierce resistance to discussing how the taxonomy will be used. Let's just focus on the taxonomy, they say. We don't want to get distracted by implementation details.
It appears that reductionists have co-opted the taxonomy. While they may have the best intentions, they know just enough to be dangerous. By ignoring the broader context, they are crafting taxonomies in the dark. There will certainly be a backlash when these costly taxonomies shrivel up in the light of day.
