Where did that document go?
If you’re like me, one of the most frustrating things in your workday is searching for some piece of information that you’re sure you have, but is just out of your grasp. Is it in my email? Did I put that in the team folder? Which folder? Is it archived?
A report by Hyperion Group confirms that a major barrier to adopting Enterprise Content Management (ECM) systems is that users find it too difficult to locate documents (Source: Hyperion Research, MarketView Report 2016).
Content needs to be findable
Organizations continue to create a massive amount of content – from contracts to engineering drawings, email messages, images, and much more. For the most part, ECM systems have brought good rigor to collecting and storing content – and applying basic metadata to aid in classification and retrieval.
So why can’t I find that document – even using the search function? Well, it could be a couple of things.
- The metadata captured from the user when submitting the document to the repository was limited.
- Over time, terminology has changed – and the metadata associated with the document has become less meaningful (e.g. you’re searching for “terminations” but the content was originally classified as “layoffs”)
New approach required
For searches to be effective, an investment into organizing your content must be made. And this can’t just be forcing your staff to fill out more metadata fields when they submit a document to the system.
Fortunately, there have been many advancements in software that can automate the capture of metadata in order to augment the findability of information. I really believe that this promises to be the next leap forward that will drive user adoption of ECM systems and make ECM an indispensable tool rather than an obligation that is mandated from management.
Beyond structured metadata
Take for example OpenText™ eDOCS which can be paired with OpenText™ Content Analytics to dramatically improve the content search experience. It’s all about using technology to automate the remediation of metadata. It can be as simple as using metadata to coalesce all kinds of content (e.g. “find all contracts for vendor ACME”). But it’s also about going beyond structural metadata (e.g. title, date) and leveraging semantic metadata. By this, I mean things like:
- Similarity analysis that enables you to find similar documents for any document
- Sentiment analysis that addresses what one might think of as subjective things like the tonality of an item (e.g. negative opinions).
Companies are investing in these sorts of technologies in order to unlock business value from stockpiled content by applying automation to the capture of inferred metadata. These companies are at the forefront of driving adoption of ECM systems by appealing to that most basic need – i.e. making your content more findable.
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