4 Challenges to Realistic Records Management

records management

Extract from article by Kon Leong published by GCN

Data analysis has become a twisting Mobius strip, looping back not only to influence not only how we look at data but also how we manage data itself. That makes deriving value from content anything but an easy process.

Despite the rapidly advancing processing and algorithmic tools available today, organizations are having a difficult time reaping the insights that these technologies are supposed to generate. This is largely because of to the mismanagement of data; data that hasn’t been managed and cleaned is of little use for analytics, no matter how slick the user interface is. Unstructured data, in particular, is resistant to uniform management. Its multiformat nature and ongoing, rapid generation spawn a wildly diverse and rapidly evolving ecosystem of content. Nevertheless, structured data is critical to daily business productivity and is needed for meeting legal and regulatory requirements. It also has immense potential for business insight.

At the heart of this struggle are the records and information management (RIM) professionals, who experienced a rapid metamorphosis of their roles as data volumes expanded and paper dwindled. Legal changes a decade ago prompted a whack-a-mole approach to information management, segregating data into separate systems, depending on need. The paradoxical result of these data management silos is an environment that is even more expensive and difficult to manage. With guidelines and objectives now cemented via the Managing Government Records Directive (M-12-18), agencies are faced with the daunting task of implementing seemingly “simple” requirements that are actually quite complicated, given how disparate data has become.