This is not really a new blog post. It's a relatively recent post that didn't manage to make it over from my independent blog. I wanted to be sure it made it to my Forrester blog because I will have lots of publications and posts on information architecture coming up and this was a post on my first piece in this series. So here's the original post:
In January, the lead-off piece that introduces my research thread on information architecture hit our web site. It’s called Topic Overview: Information Architecture. Information architecture (IA) is a huge topic and a hugely important one, but IA is really the worst-performing domain of enterprise architecture. Sure, even fewer EA teams have a mature — or even active — business architecture practice, but somehow I’m inclined to give that domain a break. Many, if not most, organizations have just started with business architecture, and I have a feeling business architecture efforts will hit practical paydirt fairly quickly. I’m expecting to soon hear more and more stories of architects relating business strategy, goals, capabilities, and processes to application and technology strategies, tightly focusing their planning and implementation on areas of critical business value, and ultimately finding their EA programs being recognized for having new relevance, all as a result of smart initial forays into business architecture in some form.
Gene briefly explores the misunderstanding between “Enterprise IA” and “User Experience IA.” This tension was well characterized by Peter Morville almost 10 years ago (See “Big Architect, Little Architect.” Personally I think it’s clear that content is always in motion, and unsupported efforts to dominate and control it are doomed. People are a critical element of a successful IA project, since those who create and use information are in the best position to judge and improve its quality. Many hands make light work, as the saying goes.
For example, if you want a rich interactive search results page, you need to add some structure to your content. This can happen anytime from before the content is created (using pre-defined templates) to when it is presented to a user on the search results page. Content is different than data, a theme Rob Karel and I explored in our research on Data and Content Classification. For this reason, IA is both a “Back end” and a “Front end” initiative.