I was in a meeting recently to talk through a new website project – discussing the stages of the project. I was suggesting my normal approach – understand the project goals, do some user research, analyse content, draft the IA etc etc.
As we were talking through the process, I noticed one of the senior managers was clearly unsettled. After we talked a bit about the early steps, he finally said “Why do we need to do this? Why can’t we just come up with the IA. After all, it’s not rocket science”.
He, as a senior manager, had a fairly good idea of the domain. So he had a fairly clear idea of how it would best be represented on the website. His ideas weren’t bad at all, but I didn’t know if they were ‘right’. After a bit of discussion we agreed to make some quick changes based on his ideas, but reserved the right to change it when we had collected some information.
But it did make me think. Why do I think there is some complexity to creating a good IA for a website, when to others it appears simple? (I’ve noticed that people generally think their own field or expertise is complex, and assume that other fields are straightforward – I think that is just human.)
I don’t really think IA is as hard as rocket science. But I do think there are some hard parts:
- We usually deal with messy problems
- Our projects are all about language and concepts, which vary from person to person
- A lot of what we do is pulling together different (often competing) inputs to try our best to create a balance
- We have to work with opinionated people. And everyone has an opinion on how things should be grouped, labelled and what is most important!
- There is no one right answer
- Our individual experiences contribute to solutions – so the ‘answer’ depends on who creates it
But it is achievable. I think part of the trick to helping people understand that there is complexity is to better explain the pathway and rationale for decisions – show how inputs contributed to outputs, how we’ve balanced priorities. Not just show the end result…