For processes that depend on documents – like loans, mortgages, claim processing, insurance applications and numerous other financial services products – as well as regulated industries like manufacturing, health care and life sciences – turning documents into data is the only way to measure, manage and ultimately optimize.
According to the “Digital Transformation Index”, most industries are embracing various types of digital transformation, such as the streamlining of business processes through innovative technology. In document-intensive workplaces, for example, the automation of document classification has enabled businesses to greatly drive workflow efficiency. Document-driven workplaces have also discovered a secondary benefit from implementing optimal technology: the ability to minimize employee turnover.
The mortgage loan servicing industry faces unique pressures to optimize document management and streamline workflows. Unlike most industries, loan servicers are formally evaluated by rating agencies (such as S&P and Fitch) on the efficiency and strength of their operations and internal controls. When a rating is published for a mortgage loan servicer (particularly when it involves an upgrade or downgrade), it’s a major business-impacting event.
We’ve all seen statistics and charts showing how fast corporate data is growing. There seems to be no limit to not just this idea of big data, but the growth rate of it. Most charts show accelerating growth, typically in an exponential fashion. And these massive collections contain huge amounts of dark, structured and unstructured data.
In Part 1 of this blog, we explored what metadata is, using an analogy to digital music stored on your phone or computer. Now let’s extend that analogy into the enterprise data management space, where we would like to use metadata to tag important files. Maybe invoices can be tagged with the Company Name, Billing Date, and Invoice Amount. Or a sales presentation would be tagged with Author, Subject, Client, and Presentation Date.
With the explosion of data in the world, and your company, finding and making sense of it is becoming increasingly harder. It is said that the average employee spends 400 hours per year just searching for documents. There are a variety of tools to help you manage and understand this data, but one key to unlocking that puzzle revolves around the quality and quantity of your metadata. Let’s look at what metadata is and why you need more of it in some detail.
Moving data, applications, and processes to the Cloud is rapidly occurring across a wide variety of enterprises. The benefits (and costs) of doing so have been well discussed, but moving the applications and processes can take a long time. One strategy to ease this transition is to move your data to the cloud first, and follow on with applications later. This allows you to transition your legacy applications and IT infrastructure gradually.
Enterprise Content Management (ECM) has been around for a long time, and has evolved significantly to include many features and functions to help organizations and departments manage documents.
The Actionable Intelligence Lifecycle is a process that scales beyond a single document or ECM system, to an enterprise-wide way to deal with a large variety of different repositories and systems that manage individual documents. By being able to apply the lifecycle to these varying systems, the enterprise has a common methodology to deal with their documents, and to ultimately migrate to a single system and process.