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Nov 03, 2010: Contending with a second set of silos

Like a lot of information architects, I make a living trying to break down content silos that grow around organizational boundaries, and reorganize it in ways that respond to users' needs. In fact, if you look at the banner of my old workshop on enterprise information architecture, you'll see Kevin Cheng's drawing of me literally blowing up organizational silos.

So I'm finding it ironic that in the last couple years of my career, I'm contending with a entirely new set of silos. Like content silos, these also grow organically around political divisions within an organization, and to the detriment of the organization. What's different about these silos is that they each contain a different (and incomplete) collection of user research, data, and reports. These silos are arranged by:

  • Discipline: web analytics data here, user research data there...
  • Application: Omniture jockeys here, SalesForce.com experts over there...
  • Department: Marketing stuff here, Business Analysis there...

There are other organizational silos like these, and none make sense, really. They're legacies of political intrigue, technology-driven purchasing, and worst of all, a piecemeal approach to how organizations should set themselves up to make design and other major decisions.

If you could start a large organization from scratch, is this the sort of apparatus you'd set in place to make major decisions? Unlikely. (In fact, if you find yourself in a position to design your organization's decision-making platform, I suggest banning all those baggage-laden terms from the discussion.

I think you'd probably take something of a more balanced approach to assembling the your research, along the lines of Christian Rohrer's Landscape of User Research Methods. I love his use of the two axes: attitudinal/behavioral, and quantitative/qualitative. Including his two axes, I'd add these other dimensions:

  • things that tell you about attitudes vs. things that tell you about behaviors
  • things that are quantitative vs. things that are qualitative
  • things that tell you what vs. things that tell you why
  • things that help you measure the world that you know vs. things that teach you about the world you don't know

Working on this stuff a lot lately, for keynotes, in consulting... Are you?

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Comment: Mark Thristan (Nov 16, 2010)

Lou, this is the bane of my life!
Large organisations typically collect data for one, very single-minded purpose, and keep such data (user research or otherwise) very ring-fenced.
Even when companies move toward master data sources, the issues are 1) they only think about structured data 2) it is still focused on these single-minded purpose (the word "teleological" comes to mind). User research data is bottom of the list, and - as it is often received in unstuctured format - rarely receives the additional effort to join it to other data insights where it can really add value.
This is where online/offline value analysis, and so-called 360 degree marketing initiatives find their wheels falling off. Having been involved in a few of these, I can add that the human element is also critical - typically speaking, much user research data is under the governance of non-data-driven parts of the organisation who are unwilling or unable to take steps to develop the technical skills (or to hand over control to those who have these) to gather the most benefit from these.
As usual it is a people, process, technology issue rather than just a question of "the data is out there, let's use it". I think the best way to attack these are via skunkworks projects (if you can get away with it) with small pieces of data loosely joined rather than via larger enterprise rearchitecting (and I think I include full-blown IA efforts under this also): this delivers advocacy through results, delivers the message that it will always be "work in progress", and gets some early-stage return on effort (the enterprise stuff comes later).
I am actually doubtful that organisational changes would make any difference in the long term: what is required is the org. equivalent of the API - a hook that enables communication between disciplines, applications, departments and their data, and again this needs to be initiated at the people, process and technology level. Decent, well-supported knowledge management initiatives can bear fruit in these areas, but are usually curtailed by under-estimation of effort, under-resourcing and misdirection (they are just seen as "information-sharing" rather than "problem-solving"). Hmm - big problem: do you have any more information to share about the direction of your thinking? That way could perhaps provide some more focused thoughts.

Comment: Lou (Nov 18, 2010)

Hi Mark, I think we're sharing much of the same pain. Here's what I'm wondering: are we the only ones? I just don't hear this discussed much, and I'm both surprised and concerned. Or maybe we're just ahead of the curve? ;-)

I'm trying to carry the ball a bit on this at places like UX Lisbon (maybe see you there?). But I'm afraid I'll give an impassioned presentation to the sound of crickets...

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