Probably the one question I find myself asking when making IA decisions is “Is this content important to a user?” – and for much of our content the answer is no. Unfortunately, that unused content may contribute to a larger picture in some way (such as demonstrating program goals). The problem I find I’m often wrestling with is finding a balance between content “completeness” and content “simplicity”.

Any suggestions?

For a standard commercial enterprise, information architecture is fairly simple. You have products and/or services. You divide them up into categories, add an “About” page and a “Contact” page and you’ve got a well-organized, sensible site.

However, for higher education, we have to consider our audiences more than we consider our “products” and “services” and have to come up with six or seven different architectures for basically the same information. That makes for a lot of necessary duplication, and can cause the architecture of the site to become extremely confusing.

You can say that they don’t comprehend the IA, but test after test seems to confirm that they do indeed infer an IA regardless of how explicit it is.

I guess the point I’m making is that the IA for a large site is VERY important in the usability/accessibility and ultimately search engine optimization of a site.

Funny, a coworker and I were discussing this exact thing today at lunch. I just finished a draft wireframe for our new home page and we were going over the contextual clues that the wireframe provided users and the flexibility that the layout would provide subsites with different contexts.

Specifically, we were talking about how people instinctively wayfind on sites using clues that they are not even consciously aware of and how the wireframe leveraged those, particularly in cases where users teleported to a page deep within the site.

Your post will go a long way in helping us explain/defend our decisions.

Thanks!

Alternatively, for a large site, you have multiple people involved in the operation of the site. Any change or decision affects more than one person and any miscommunication or difference of opinion can create friction and, perhaps, hard to remove consequences like politics, power struggles and/or poor teamwork. IA, in that sense, comes to the rescue.

A well crafted IA phase where key people collaborate and are empowered to contribute their best efforts serves as an agreed upon platform for everyone to work upon. If a usability problem crops up, then the team as a whole is responsible. There is less chance of finger pointing or other negative consequences because the team was involved as a group in laying out the roadmap. A problem is therefore shared, worked on and solved as a cohesive group. I could go on, but that’s the power of IA and why it’s important.

The benefits that site visitors get from it can be regarded as icing on the cake if you care to look at things from a different perspective.

But, where I think things differ is in execution. In higher ed, we are always defending decisions, sometimes to the savvy, more often to the not. These “nots” don’t know what a bounce is, they don’t get siloing, and they rarely care. It just comes down to whether or not you can spin it in a way they will care about. Maybe that means falling back on the research, or maybe it just means telling them what they want to hear to get the green light to do things your way (i.e. the right way).

Absolutely I could take an afternoon to review them on usability testing, lexicon, flow charts, etc, but in the long run, it’s usually easier (and cheaper) to just convince them in a simple way and move on.

That said, this:

“Information architecture is not science, it is art. Like conducting a symphony. It’s one part knowledge, two parts skill, and three parts just saying stuff like you know what you’re talking about and hoping others will go along with you”

I have to disagree with.

The best design decisions you can make are the ones you can defend with evidence: quantitative evidence, from usability studies, task analysis, eye tracking studies, or analytics; or qualitative evidence from user research interviews, contextual inquiry, surveys, or other ethnographic research techniques. At my agency we sell and defend work based on the “guess – think – know” spectrum. When you design based on guessing (informed by standards & conventions, best practices, expert opinion), you have no way to defend yourself other than through persuasion. If you design based on what you think you know, from user research, you’re much better off. If you run a usability test and validate your design decisions, then you know your choices were right.

The goal of any good information architect, user experience architect, ui designer, or what have you, is whittling down the number of assumptions and guesses you have to make.

In that sense, there has to be a central brain running things, but you have to have a certain amount of trust in how people do things. It’s like that adage: You can have it fast, cheap, and good – pick two. We can’t have it all. But if we acknowledge that there is a problem with old IA gameplans, we can start changes to improve it.