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Tagging Beyond Content: Applications & People

Historically, developers have provided a variety of interfaces that enabled users to flag applications or add unstructured information to them (e.g., for exception processing, or handling comments and ad-hoc notes). Other alternatives have also existed for some time. Users have used e-mail or other collaboration tools (e.g., workspaces) or task management and workflow products to direct actions on certain work items. Tags (and related tools like social bookmarks) offer another option that has some interesting possibilities.  Tag buttons added to browsers could be used to tag application-related data in the same manner that they are used to tag content. Similar tag functions could be added as client-side plug-ins to traditional desktop applications. Tagging applications would likely have to capture key metadata about the record being processed and store the resulting tag data in a manner similar to content-centric tags.

There would have to be some subtle differences however since record-level tagging would also need to extract business data (e.g., account number, product information) to aid in locating and recalling what was tagged or bookmarked. Tag Clouds could be integrated with applications as well, functioning as an alternative navigational technique. Information could be dynamically collected based on tag actions of peers working within related applications to surface interesting topics or keywords to co-workers. Or the tag cloud could just act as a peripheral vision mechanism that users could glance at while processing work items. Back-end systems could filter information and feed tag clouds with a variety of topical information as well (e.g., a tag cloud could categorize call types in a call center so operators could get a sense of “customer service hot topics” or whether inbound calls were related to a marketing campaign.

Tags As Intelligence Gathering & Routing Technique

Consumer sites encourage use of tags and tagging in a variety of ways. Users tag information objects (e.g., photos, web pages) with some assumption that tags will be clicked on by other users as a navigational method to discover that same information object or similar objects. There are similarities in this model for how users could also tag applications (through a controlled vocabulary or entry of ad-hoc labels). A claim interaction could be tagged as “fraud”. A sales transaction could be tagged as “HugeWinOverCompetion”. A product defect report in a customer service transaction could be tagged as “Recall_Issue”. Tags could also be interpreted by applications (given consistent formats and structure), to aid in routing and escalation of transactions tagged in certain manners (e.g., a “fraud” tag could route a transaction to an investigative unit). They key point here is that capture of opinion (via tagging) by line workers as they enter transactional data (given the proper vocabulary and bookmark system), can provide invaluable insight over a collective set of business activities and provide very dynamic routing capabilities based on metadata applied by users in a relatively unrestricted manner.  Of course this is easy to say. Not all work scenarios would allow time for tagging due to cycle-time, volumes, velocity of incoming tractions, etc. And there are certainly behavioral issues to overcome. But it does open some interesting insight to collective work activities.

Tagging People

Not only are there application possibilities with tagging but also interesting opportunities to exploit tags by applying them to people. Putting aside issues of appropriateness, security, privacy concerns (which obviously would have to be handled properly through policy, monitoring and enforcement procedures), tags can be used to dynamically and informally describe people around a particular context. In this approach, tagging people becomes a form of social annotation. For instance, as part of pre-sales activities, prospects and leads could be tagged to suggest characteristics about individuals that others on the account team might find helpful. Tags might include “tough_minded”, “difficult-negotiator”, “KeyDecisionMaker”, or “Prefers_Competition”. Tagging as a type of speech and conversation is an emerging area of social software research with some examples within consumer-oriented services. Tags applied to people provide anecdotal information that might not be captured in formal applications. Such opinionated insight however could provide situational awareness to an account team, even if the data was transitory to a particular time-period while a proposal or other engagement was underway. Such tags also acts as an indicators that such support should be included as part of the application itself through a more structured vocabulary.

Tags might also be used by users to describe themselves in terms of user profiles. Such tags could reflect professional interests, current activities and areas of expertise. There are well-known concerns with self-profiling (people tend to over-profile themselves, under-report competencies, or fail to maintain such profiles over time). The key point here is that tagging people will raise a variety of issues that include appropriate use (e.g., a user tags someone as “idiot”), but the model could become more applicable to upcoming demographics if consumer behavior around tagging continues to expand beyond bookmark services and social networking sites and becomes a behavioral norm in terms of work and lifestyle. Tags and tagging are already evolving within consumer contexts as an ad-hoc language based on social annotation of objects that could be described as a type of conversational discourse with its own grammar and colloquialisms (e.g., idioms and jargon).

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