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Information Governance: Three Pivot Points to Consider

ChrisSurdak on ‎11-11-2013 11:38 AM

I started working on the problem of managing corporate digital data in the early 1990s.  Information Technology (IT) was just hitting end-user desktops and with the advent of office productivity software companies suddenly found that they had thousands and thousands of electronic documents which needed to be placed under some sort of control.


This quickly led to a new class of software called Enterprise Content Management (ECM). These technologies were created to allow organizations to maintain the same sort of control over digital content as they had previously maintained over paper-based content.


From that point in time, through today, the standard process for building out an ECM system went something like this:


  1. Get together five, ten or fifty “experts” to define a structure within which the electronic data would be contained. 
  2. Spend 6-18 months trying to define every possible type of data the organization would create, every possible user of that data, and every possible need for that data.
  3. Reduce this whole analysis into something called a taxonomy, ontology or metadata catalog.
  4. Build the resulting system.
  5. Move all of your content into the system.
  6. Manage your data.


When I describe this process as such, it sounds patently absurd.  How in the world could a small group of data managers predict every possible use of every possible piece of data for every possible user in the organization?  Any yet, this is still pretty much the standard practice across the industry.


In this three-part series on new best practices for Information Governance, I’d like to address the shortcomings inherent in how many of us have been managing digital content and for each provide a conceptual pivot around which we might find a better way of doing things.


Pivot Point One:  Content Organization: Think Colloquial, Instead of Prescriptive

The approach to ECM described above is prescriptive, as with prescriptive linguistics, where a small group of “authorities” determine the proper way for everyone to speak a certain language.  This leads to things like “Proper English”, “Political Correctness” and crap like that. Likewise, the prescriptive approach to ECM development attempts to force a large group of end users to follow the design definitions of a chosen few.


Inevitably, the moment these systems were turned on someone, somewhere had a document that didn’t fit the defined structure. What were they to do?  Fortunately, around the year 2000 Microsoft polished up the interface of Windows Explorer, named the result SharePoint, and started giving it away for free.


Suddenly, users who hated ECM and needed to get their work done simply put their content into SharePoint.  Over a few years, ECM systems rapidly became content crash-pads; places where documents went to sleep off the collaboration hangovers the got while partying in SharePoint.  More and more of a business’ critical data was living in SharePoint and ECM systems controlled less and less.


Et Tu, SharePoint?

This situation worried records managers.  SharePoint was soon holding millions and millions of documents critical to the business, and they needed to be managed.  As a result, by 2007 SharePoint was being released with tools like taxonomy management, metadata catalogs, etc., so that content could be better controlled. 


Hey, wait a minute, where have I heard this before?


This process has been so insidious that today SharePoint is actually marketed as a governance platform!  Indeed, for the last 6 years SharePoint has become more and more structured and controlled, and less and less useable by end-users trying to be productive.


The Content Cloud Catastrophe

Users being users, they started looking for an alternative to SharePoint for collaboration and the market was happy to oblige.  Around 2008 cloud-based collaboration platforms began popping up, where users could dump their content into someone’s cloud, collaborate like mad, and not have to worry about structure or oversight.  These cloud providers (e.g. Doug’ tout their ability to allow users to collaborate seamlessly and extremely cheaply.


We are now in the midst of the mass migration of user content into these 3rd party cloud platforms and records managers are having palpitations.  Billions of business-critical documents are finding their way into these clouds, and they need to be managed.  Records managers are demanding, and cloud providers are releasing, new tools such as taxonomy management, metadata catalogs, workflow engines… hold on. 


Enough is enough.


Over the next three years (note the shrinking cycle times) collaborative clouds will deploy all of the same old control mechanisms that end users have worked-around for the last twenty years.  In turn, those users will continue to figure out any way possible to get around their inherent limitations. Is there something that we should learn from all of this? I’m glad you asked. 


Colloquial Organization

Prescriptive organization of content doesn’t work.  Period.  It hasn’t worked before, it won’t work now.  Users hate it, it’s ineffective, and it adds layers of complexity that destroy value and trap information in artificial cages.  There must be a better way of managing data.  And these days, thankfully, there is.


Colloquial organization is the antithesis of prescriptive organization.  Colloquialisms are how humans actually communicate ideas with one another.  Earlier, I wrote the phrase “crap like that.” Prescriptively, this phrase makes no sense at all, and might even be faintly offensive.  But colloquially, you likely understood exactly what I meant.  So too, colloquial organization is sensitive to context, of both the data itself and the questions being asked of it.


Take the word “apple”, for example.  If I said I was looking for documents about “apple” I’d get some documents about fruit, some about computer companies, some about neck anatomy and some about New York City.  That’s the problem with keyword searches. They give us exactly what we ask for and little of what we want.


Now let’s say instead I was looking for documents about “apple stock.” Adding one word made it much easier for you to know that I was thinking of the company, rather than your neck.  Context matters, and in fact if I manage data according to its context and meaning, rather than mere keywords, metadata, taxonomy and other such half-measures, I get much better results.


Colloquial organization of data means that I determine what is relevant at the time the question is asked, not before, and I return results based upon the context of the data, rather than by which artificial bucket I forced it into.


Such organization of data is possible with contemporary technologies such as HP’s Records Manager and Control Point.  Given the historical failures of prescriptive organization, and the increasing volume of digital stuff that we need to manage, can you afford to keep managing content in the same old fashion?

Stay tuned for Pivot Point Two….

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About the Author


Chris Surdak is a Subject Matter Expert on Information Governance, analytics and eDiscovery for HP Autonomy. He has over 20 years of consulting and technology experience, and holds a Juris Doctor from Taft University, an MS from the Wharton School at the University of Pennsylvania, a CISSP Master's Certificate from Villanova and a BS in Mechanical Engineering from Penn State. Chris is author of the Big Data strategy book, "Data Crush," which was recently nominated as International Book of the Year for 2014, by GetAbstract. Chris is also contributing editor and columnist for European Business Review magazine.

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