Tuesday, January 7, 2014

Information Workers are Sick of Looking for Documents

Just as we were mentioning to you a couple of months ago, in one of our infographics about  searches in document managers, searching for documents continues to be a worry and a factor contributing to the working inefficiency of information workers.

Today, we’d like to share an infographic from SearchYourCloud which follows the same lines and which brings us interesting data taken from a studio of more than 300 workers in the US and the UK:
  • In their daily work routines, information workers conduct up to eight searches to find the documents they’re looking for.
  • Only one out of five searches gets the right results on the first try. 
  • 57.56% can’t conduct searches from their mobile devices.

One more reason why ECM applications should be smart 

The problem with locating and recovering information has a lot to do with the capacity that ECM and document management applications have to be smart. As they are, these applications offer us a powerful search mechanism: metadata.

However, the reality is that even though these applications offer the possibility to associate metadata with documents, those same metadata, in most cases, have to be filled in manually. As a result, the metadata end up not being completed, and the power that these systems offer ends up being lost. 

One of the solutions to this problem (goes by) the smart capture of data which makes it so that applications, and not people, are the ones that fill in the metadata, which is the case of Athento.

However, there are various smart functionalities that are able to make life easier for information workers when they’re looking for documents. Here, we’ll leave with you some of the functionalities available in Athento’s case:
  • Semantic Auto-tagging: The system extracts key terms from documents (tags) so that when users are moving around documents, they can access those documents which contain those tags. You can see this Athento functionality in this video, which shows Athento integrated with Box.net.
  • Relations between documents: Automatic relations are built every time that document share the same piece of metadata and the same value. For example, if we upload two documents (a university degree and a national identity number), and the two documents share the “national identity number” metadata whose value matches, the systems will automatically create a relationship between them so that if we access one document, we can get to the other one, too (and vice-versa).
  • Full-text indexing of document content: Here, the OCR functionality plays a fundamental role since it allows the searches to include not just metadata (like the title of the document), but also the content itself.  

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