Superior Documents Services is proud to announce that two members of our team, Daniel Attaway and Bryant Overgard, have recently become Relativity Certified Administrators! The Relativity Certified Administrator (RCA) program ensures that case administrators fully understand Relativity's capabilities, allowing you to maximize the software's flexibility and provide an intuitive interface for end users. To obtain certification, you must earn a score of 80% or higher on the RCA exam, which contains both written and practical elements
By completing the Relativity Certified Administrator (RCA) program, these individuals have shown a thorough understanding of Relativity and how to best leverage the platform to our clients’ advantage. This is just part of our ongoing goal to provide truly Superior service to all of our clients.
In the case of predictive coding, its advocates have touted the efficacy of their approaches in white papers, blogs, and social media postings, and have practically created a separate industry to host conferences promoting the wonders of predictive coding. Few people want to ruin the moment or buck the trend by pointing out what is obvious when one considers the technology underlying predictive coding - it is completely dependent on having text to analyze. It will absolutely fail to analyze documents for which there is no text, and will do a miserable job where the text is of poor quality.
In practically all industries it is common practice to develop documents in one application like Word and then, once finalized, distribute them as image-only PDF so they can be viewed on a variety of devices and so recipients can't easily change the content. In one collection we analyzed, only 20% of the PDFs had associated text. Even if predictive coding were 100% effective, the most it could classify would be 20% because it literally cannot "see" the 80% without text. If in fact predictive coding has a recall rate of 70-80% of what it can see, that would mean that predictive coding would have identified 14 to 16% of the total PDFs (70% x 20% = 14% or 80% of 20% = 16%). By contrast, BR's visual classification technology classified 100% of them.
Most of us have heard about the parable of the six blind men and the elephant - it may actually be the first recorded instance of faceted classification. Six blind men touched different parts of an elephant and each described a completely different thing based on their own perspective or “view” of the elephant: The one who felt a tusk reported it as a pipe, the one who felt an ear reported a fan, the belly was reported as a wall, the trunk as a branch, a leg was reported as a pillar and the tail was described as being a rope.
Different Stakeholders Have Different Views & Needs. People’s views of and information needs from any given corpus of documents will vary according to where they are in an organization and the functions they perform. People with different roles in a company will naturally be interested in different attributes of the documents in the corpus and may well use different descriptors when describing or trying to find some of them. While some document attributes are common to all stakeholders, others, namely those which enable an individual or group to perform their job function within an organization, are probably not.
Just preserving documents without having a systematic, dynamically updatable and holistic view created by assimilating other interrelated data points will result in an incomplete picture of a project or process. Without a holistic way of assembling and viewing all the extracted document attributes of interest to the various stakeholders, the overarching information governance needs of the organization will never be met. There will be incomplete, ambiguous, erroneous and superfluous data points.
Duplicated data sets. Without a holistic enterprise content plan, each stakeholder starts keeping their own copies of documents so they can extract the attributes they are interested in. The result is multiple copies of the same documents, multiple expenditures to extract the same attributes, and inconsistencies in ways that the same data is extracted and stored.
The highly experienced CA team chose to align with BR as it is the only technology in the world that automatically classifies electronic files or scanned paper documents based on their visual characteristics – and without having to waste time writing rules to identify each type of document or designating exemplars for each document type. This is tremendously important because accurate, consistent classification is the bedrock upon which all IG initiatives are built. BR solves this long-standing, previously intractable problem.
