September 24, 2009
1:00-2:30 p.m. EDT

John Greene, Managing Director, Guy Carpenter & Company, LLC
Seth Earley, President & CEO , Earley & Associates
Mike Axelrod, Senior Consultant , Earley & Associates

What is the role of Web 2.0 and Social Media in the insurance industry? How do these new technologies and approaches for creating content fit in with more structured content processes?

In this first session we’ll survey the core processes of insurance operations, show what types of content typically supports such processes, and talk about how some of the newer approaches to collaboration and user generated content fit in to the big picture. Learn how Guy Carpenter & Company, LLC, the world’s leading risk and reinsurance specialist, utilizes social media from John Green, Managing Director in Global Marketing & Communications.

We’ll provide tangible examples of how improvements can provide bottom line benefits and how services can be better performed, products can be more accurately priced, and customer experiences can be improved by well designed content management approaches. We’ll discuss types of challenges in each of these areas and approaches for remediation.

Topics include:

• Overview of content intensive processes
• The use of social media in insurance
• How well architected content can improve knowledge flow
• Classes of content technology in support of insurance processes

Visit earley.com for more information or to register

You can add your own favorite blogs to the list on GoogleDocs.

Date: Wednesday, July 15, 2009
Time: 1:00 – 2:00 Eastern Time
Cost: $50 (Survey respondents need not register and will receive an invitation to this call at no cost)

Register here.

Four years ago, a benchmark survey was conducted to understand how organizations understood and applied metadata to content assets and what business benefits they were realizing. Earley & Associates along with Taxonomy Strategies, launched a project to update this research. The goal of the study was to measure industry progress on a Metadata Maturity Model scale, a road map designed to help practitioners get started – and continuously improve – content tagging within organizations.

Preliminary results have shown that organizations that are more mature in metadata and taxonomy best practices outperform less mature organizations, with more mature organizations reporting findability and content management problems 10-15% less often. In addition to presenting results around maturity levels, this call will benchmark current search, taxonomy, and metadata practices against the 2005 survey and report on some surprising key findings around information access and best practices adoption.

Register here.

Take the Survey

Depending upon context, “tagging” can mean one of three different things: tagging a document, tagging within a document, or tagging a content object.

Tagging documents.  These days most of us think of tagging as the keywords we put on our documents – like our photos and websites – so that others can find them when they search.  User tags are fine for finding photos in flickr, but for tagging to be effective in business we need to make it systematic, so that we avoid ambiguity and improve search recall and relevance.  So we’re increasingly “mature” in our approaches to tagging: We use taxonomy to organize our terms into classes and to manage the relationships between terms.  We develop thesauri and foreign language equivalents.  We integrate taxonomies and thesauri into search indexes for ECM and site search and SEO.

Tagging within a document.  I got interested in tagging in the early days of XML (back when we spelled it “S-G-M-L”), when we were tagging within documents.  By tagging unstructured content inside documents we could do really sophisticated things – not just multi-channel output.  For example, knowing that a paragraph in a document was a step in a service procedure or that a string of gibberish was a part number let us bring life to that content when we transformed it from markup into an interactive electronic technical manual.  Tagging let us turn books into diagnostic software.

Tagging reusable content objects. As content reuse matured with standards like DITA, organizations had more reusable components, with more people creating them in more departments.  Tagging reusable content objects became essential to actually reusing them – if you couldn’t find it, you’d never reuse it.  If you had a single service manual with 100 procedures, now you have at least 100 reusable content objects, so the search scope increased by two orders of magnitude.  At IBM, colleagues report having over a million DITA topics in more than six repositories, with over a dozen departments sharing content across thousands of publications.  Searching for content objects is like trying to find a needle in a haystack, except you’re trying to find the right needle, and you have more and smaller needles to search amongst, in more and increasingly bigger haystacks.

Measuring Metadata Maturity.  Each type of tagging can have measurable benefits on your business.  Five years ago, Earley & Associates and Taxonomy Strategies developed a survey to understand metadata maturity for various types of businesses.  Earley is conducting an updated survey to see how organizations have moved up the learning curve.  Since we have a baseline of responses from five years ago, we’ll be able to describe how metadata and taxonomy practices have matured over time.  Also, the original survey was focused on the impact of metadata best practices on knowledge management and e-commerce search.  We now recognize that metadata is also used by technical communicators – especially those that use XML and other technologies to create, manage, and multichannel publish reusable content.  We want to hear from you all for the first time.

The survey is pretty detailed, so you might want to grab your favorite caffeinated beverage before you dig in.  As compensation for your time (about 15 minutes) Earley & Associates is offering these nifty incentives:

• A free pass to any future Earley & Associates Community of Practice conference call (a $50 value).  These are monthly, and the next one is Wednesday June 2^nd on Taxonomy for Portals featuring Giovanni Piazza, Chief Knowledge Officer of Ernst & Young, and Ralph Poole of Earley & Associates.
• A $200 discount on registration to the Henry Stewart conference on digital asset management, June 1-2 in NYC.  Seth Earley will be there presenting preliminary results.
• Free participation in a webcast reviewing the results of the survey (date TBA).

Take the Survey

Check-in, metadata, and taxonomies.

Many organizations have a formal system for classifying content called a taxonomy. Think of it like the naming of the sections in the yellow pages directory – it provides consistent category names. This avoids the problem I call “the Yellow Pages Problem,” where some people call those guys who represent you in court “lawyers” while other people call them “attorneys at law” (or worse things). When an organization uses a taxonomy, everyone uses consistent category names – that is, if they actually use it.

Compliance blues. Taxonomies can be configured into the CMS, so that category names are able to be selected on the check-in dialog box. While that saves the author guesswork of remembering category names and avoids mistyping, it still requires an author to take action – and to get it right. This is a point of failure of many ECM initiatives: authors either fail to classify content at check-in time, or they accept the default settings, or the author applies the wrong category (or even too few categories when the content really crosses genres).

The problem is worse when the author isn’t a fulltime writer, but instead a business contributor who’s creating content as they serve their role in some business process. In these cases the author lacks the time, talent, or motivation to tag the content with the appropriate metadata. They may not see it as part of their job.

Cure for the blues? So can this process be automated? Absolutely. Technologies have existed for some years now to analyze unstructured content. Algorithms involve some combination of statistical, linguistic, and structural analysis.

• Statistical methods look at the document as a “bag of words” – words or phrases that occur more frequently, or that are “improbable” statistically are more important. Amazon uses SIPs – Statistically Improbable Phrases – to pull keywords out of books. This is purely statistical – the system doesn’t know what the words mean, just that they are “odd” so probably meaningful.
• Linguistic methods actually analyze the natural language in the document. If you know what the subject, verb, and object are in a sentence, then you know what it is about. Linguistic methods have gotten better with improvements in algorithms and increases in computing power.
• Structural methods leverage underlying markup in documents, like XML structural tags or even styling or text flow (e.g. recognizing terms in headers).

These methods not only provide automated metadata tagging (document categorization), they can also determine what type of document is being analyzed (document classification). They can also be used to identify Named Entities – named people, places, things, and events. It’s one thing to say this document is a Legal Brief (document type or class). It’s another to say that Legal Brief is about Patent Infringement (a category). It’s another thing still to say that it’s a case between Palm and Xerox (named companies) about handwriting recognition (a named technology). Named entities can be extracted and listed in metadata. They can also be tagged in-line in an XML document (this is often called “auto-tagging” – a post for another day).

Named entities are not addressed by taxomonies, rather by lists or directories of named entities.  A number of these named entity directories are available as web services. Several are kept evergreen by using Wikipedia to drive the ever growing list of named entities.

Making it real. So given this technology, how do you implement such a system?  My preferred method is to customize the authoring environment so that the “Save” dialog box in the editor of choice presents the ECM system’s check-in dialog.  This way the author does not take extra steps to check content in.

Also at check-in time, in the background, the customized editor performs a temporary save to the local file system, and automatically sends a copy of the document to a categorizer web service. This is a content categorizer application running on a server.  That categorizer service would apply the organization’s standard taxonomy to the document, using some classification algorithm to define one or more categories for the document. The results can be applied in either of two ways:

• Classify the document automatically with no user intervention. This can be done completely in the background with no user interface, even as part of an automated check-in workflow.
• Classify the document automatically and have the user verify the results. This requires exposing the proposed metadata tags in the check-in dialog.

Categorizers often provide some scoring of the certainty of a given tag; this score can be used to make the call about whether the automatic tag is applied, or whether it needs (or allows) end user verification or editing. Business requirements determine what the best approach or best combination is.

What are the barriers? The reason this technique isn’t used more often is the integration required between the authoring tools, the ECM solution, and the categorization technology. In today’s market these technologies are typically provided by independent software vendors, who have few incentives for bundling tightly integrated solutions (and wish to remain “vendor neutral” with their own technology). As the ECM marketplace continues to consolidate vertically we may see some content lifecycle vendors with more complete solutions (watch IBM and EMC). Services firms specializing in unstructured content and ECM can be one source for prepackaged solutions that combine these ECM, authoring tools, and content classification into a seamless user experience – which is the key to success in deploying an automated solution.

At the end of the day, consideration of the needs and behavior of content authors and contributors (who are very often change-averse) is the most important step in adoption of a content lifecycle solution. Making content classification and categorization a “no brainer” through automation and a seamless user experience improves the likelihood of success.