Requests for credit or allowances, opening of an account or entitlement, declaration of loss, change of circumstances, complaints, etc., every day private and public organizations process large volumes of documents submitted by their customers and users.
Coming from multiple channels (letters, emails, web portals, etc.), these documents contain key information for completing different types of requests and the business processes related to them. Identifying them becomes complex when the vast majority of this data is presented in an unstructured format (see graphic).
Often, “the volume, speed and variety of the information that they have to manage far exceeds their capacity to keep up the pace”, says the Association for Intelligent Information Management (1). And leads the AIIM to emphasize the clear link between “this informational chaos” and the failure of certain digital transformation initiatives.
Manual processing of incoming documents is no longer viable
Because processing these incoming documents manually in order to extract the information from them is no longer viable – neither from an economic point of view (productivity), nor from the point of view of the quality of the data obtained, compliance with response times, the fight against fraud and customer-user satisfaction.
For the AIIM, a fervent defender of automation and digitization, this processing must be “standardized and automated” with support from omnichannel capture, OCR and ADR-ADS technologies (2). And this has to become “a strategic priority” for organizations.
When they aim to offer the best possible customer or user experience, to improve their productivity and limit their risks, find out from this graphic why it is urgent to automate processing of incoming streams.
(1) AIIM, State of the IIM Industry 2020: Are You a Digital Transformation Leader or Follower? (2) OCR: Optical Character Recognition); ADR: Automatic Document Recognition; ADS: Automatic Document Scanning
Digitization of incoming documents can increase customer user satisfaction and guarantee improved quality of data.