Analytics apps don't tell you much about usage behavior. You might be able to see how many users performed an event, or how many times they did it. But none of the analytics packages out there are good at showing you how often people do things. Are they using to-dos once a week? Every day? Only signing into the app once a month but happily paying for years?
Time matters. You can't understand usage without time.
Here I describe an approach for defining new information architectures for large organizational websites managed by many stakeholder groups.
Broadly speaking, there are four general phases to the approach:
Auditing. Begin by immersing yourself in existing content and encourage stakeholders to adopt a critical, audience-minded perspective of their content.
Diagramming. Work with stakeholders to develop new conceptual categories that better serve audiences and organizational direction.
Elaborating. Think through content in detail and test new categories against specific instances and edge cases.
Producing. Prepare content teams for production using a shared database of new sitemap pages and editorial considerations that you’ve developed incrementally.
Whilst Feature Parity often sounds like a reasonable proposition, we have learnt the hard way that people greatly underestimate the effort required, and thus misjudge the choice between this and the other alternatives. For example even just defining the 'as is' scope can be a huge effort, especially for legacy systems that have become core to the business.
Most legacy systems have 'bloated' over time, with many features unused by users (50% according to a 2014 Standish Group report) as new features have been added without the old ones being removed. Workarounds for past bugs and limitations have become 'must have' requirements for current business processes, with the way users work defined as much by the limitations of legacy as anything else. Rebuilding these features is not only waste it also represents a missed opportunity to build what is actually needed today. These systems were often defined 10 or 20 years ago within the constraints of previous generations of technology, it very rarely makes sense to replicate them 'as is'.