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Content analytics becomes an enterprise must-have

As companies generate increasingly more content, they are coming to recognize that content analytics is a nonnegotiable.

Gleaning business insight from content analytics is still in the early-adopter and well-hyped phase, but companies are beginning to see results emerge in terms of smoother workflows, improved search and better compliance practices.

Content analytics is a business practice that analyzes and derives insight from data about the amount of content being created, the nature of that content and how it is used. Content analytics can help companies manage their information lifecycle management chains by creating relevant cost and consumption metrics. With business metrics in place, companies can identify which digital content is most valuable and adjust investments in storage and future analytics as needed.

According to the AIIM survey "Content Analytics: automating processes and extracting knowledge," content analytics is fast becoming a pivotal business tool: In the survey, 60% of enterprises said it will be essential within five years' time. Three-quarters of enterprises said content analytics provides real business insight, further highlighting its position as a technology that adds true value to an organization.

AIIM survey respondents also identified content analytics as increasingly essential to addressing risks associated with incorrectly identified content. Survey respondents also said auto-classification of content helps protect against security breaches, sensitive or offensive content, and exposure to compliance regulations. More than half of enterprises (54%) said their organization is at risk from such threats.

When companies rely on manual processes, staying on top of high-volume, multichannel content (e.g., content that comes from multiple communication channels) is increasingly difficult if relying on manual processes, and users are coming to accept that automated handling is as accurate but more consistent than humans. Email archiving in particular presents a dilemma, and content analytics offers a way to carry out defensible deletion in line with information governance polices. Dealing with dark data -- that is, information that organizations collect, process and store in the course of their regular business activity, but generally fail to use for other purposes -- elsewhere in the business, and adding value to content rather than deleting it is a common objective.

When companies rely on manual processes, staying on top of high-volume content is increasingly difficult.

Despite the potential benefits, 80% of survey respondents have yet to allocate a senior role to initiate and coordinate analytics applications. This lack of designated leadership and shortfall of analytics skills is restricting the potential and holding back the deployment of content analytics tools, according to almost two-thirds (63%) of respondents.

So how can you get your content analytics initiatives moving? Here are seven suggestions:

  1. Reinvigorate your records management efforts. If your content or records management deployment has stalled due to poor decisions early on regarding classification, metadata and taxonomies, or if you are migrating content from multiple repositories to a single system, consider  metadata correction agents that can sort ROT (redundant, outdated and trivial) from valuable content and align content types and metadata.
  2. Tune search. If you have access to contextual search, ensure that it is properly tuned and that staff know how to use it. If you are reliant on more basic search, consider improving the searchability, and, therefore, the value of your content, by correcting and enhancing the metadata with analytic agents.
  3. Enlist help with auto-classification. Unless your staff is diligent and consistent at declaring, classifying and tagging records, consider providing auto-classification assistance or full auto-classification. Information governance policies need to be updated and consistent to provide the rules for automated agents.
  4. Take control of email. If you have no archive or the archive is "file and forget," you are losing corporate knowledge, exposing the business to risk and creating a potential e-discovery nightmare.
  5. Review retention policies. Consider your retention policies as a way to control increasing storage requirements. Accurate metadata and enforced retention policies are the only way to limit storage, but will also improve your compliance and risk exposure.
  6. Automate content handling. Inbound content handling can rapidly overload process staff, and reduce speed of response to customers. Implement a digital mailroom philosophy, and use automated recognition, routing and data extraction.
  7. Use content analytics for business insight. Look across the range of your business activities to see where content analytics could provide business insight to understand customer needs, improve competitive advantage, help to solve cases and investigations, or prevent noncompliance and fraud.

We have seen increasing interest and adoption in recognition and routing of inbound content, automated classification of records and email, metadata addition and correction, and all of the improvements in access, security, deduplication and retention that flow from this. But content analytics can offer so much more than this, with many applications and uses yet to come, and by 2020 will be one of the primary tools used by any enterprise.

Now is the time to get serious about content analytics.

About the author:
John Mancini is an author, speaker and respected leader of the AIIM global community of information professionals. He believes in the next five years, a wave of digital transformation will sweep through businesses and organizations, causing them to make a fundamental choice between information opportunity and information chaos.

The information in this article is based on the new AIIM survey "Content Analytics: automating processes and extracting knowledge." Survey downloads are free.

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