The Concise Framework for Discovery Automation takes the overall process of discovery, breaks it down into a data discovery component and a legal discovery component, aligns these components with insight and intelligence, and then highlights four key processes and eight key tasks that appear to be important in the discovery process across the lifecycle of information and litigation.
Epiq, a global leader in the legal services industry, today [July 9, 2018] announced that it acquired a majority interest in Controle, LLC, a leader in information governance services and solutions.
The characteristics of a fifth generation eDiscovery offering would be the adaptation of current data discovery offerings for use with offerings that were designed for eDiscovery, designed for eDiscovery task integration, and designed for eDiscovery task automation.
We have an effective model for converting information governance requirements into a digital framework. It is called the DIRKS methodology and you’ll find it in ISO 15489 Standard for Records Management.
The right level of detail at which to analyze the potential impact of automation is that of individual activities rather than entire occupations.
“It’s really the first complete offering of what we call data discovery from the point of creation.”
Multidisciplinary teams are essential to success in complex societies and economies. The most important member of any multidisciplinary team is the customer.
One of the biggest challenges facing information, business, and legal professionals is the ability to cohesively consider the elements of data discovery and legal discovery within a technology framework that is comprehensive enough to address critical discovery tasks throughout information and legal lifecycles yet concise enough to be realistically approached from an automation perspective.
In-Place Records Management is when the Records Management Solution does not physically move the content to manage it; the content remains it its original location, but the solution is managing the retention policies and overall File Plan for the content.
Automation of data management can be transformational in the enterprise. Eliminating low-level manual processes frees up people resources, amplifying human potential to deliver more value and creativity further up the value chain.