Close
Enter your
text here

EDRM

More Updates from the EDRM Annual Meeting – eDiscovery Trends

Yesterday, we discussed some general observations from the Annual Meeting for the Electronic Discovery Reference Model (EDRM) group and discussed some significant efforts and accomplishments by the (suddenly heavily talked about) EDRM Data Set project.  Here are some updates from other projects within EDRM.

It should be noted these are summary updates and that most of the focus on these updates is on accomplishments for the past year and deliverables that are imminent.  Over the next few weeks, eDiscovery Daily will cover each project in more depth with more details regarding planned activities for the coming year.

Model Code of Conduct (MCoC)

The MCoC was introduced in 2011 and became available for organizations to subscribe last year.  To learn more about the MCoC, you can read the code online here, or download it as a 22 page PDF file here.  Subscribing is easy!  To voluntarily subscribe to the MCoC, you can register on the EDRM website here.  Identify your organization, provide information for an authorized representative and answer four verification questions (truthfully, of course) to affirm your organization’s commitment to the spirit of the MCoC, and your organization is in!  You can also provide a logo for EDRM to include when adding you to the list of subscribing organizations.  Pending a survey of EDRM members to determine if any changes are needed, this project has been completed.  Team leaders include Eric Mandel of Zelle Hofmann, Kevin Esposito of Rivulex and Nancy Wallrich.

Information Governance Reference Model (IGRM)

The IGRM team has continued to make strides and improvements on an already terrific model.  Last October, they unveiled the release of version 3.0 of the IGRM.  As their press release noted, “The updated model now includes privacy and security as primary functions and stakeholders in the effective governance of information.”  IGRM continues to be one of the most active and well participated EDRM projects.  This year, the early focus – as quoted from Judge Andrew Peck’s keynote speech at Legal Tech this past year – is “getting rid of the junk”.  Project leaders are Aliye Ergulen from IBM, Reed Irvin from Viewpointe and Marcus Ledergerber from Morgan Lewis.

Search

One of the best examples of the new, more agile process for creating deliverables within EDRM comes from the Search team, which released its new draft Computer Assisted Review Reference Model (CARRM), which depicts the flow for a successful Computer Assisted Review project. The entire model was created in only a matter of weeks.  Early focus for the Search project for the coming year includes adjustments to CARRM (based on feedback at the annual meeting).  You can also still send your comments regarding the model to mail@edrm.net or post them on the EDRM site here.  A webinar regarding CARRM is also planned for late July.  Kudos to the Search team, including project leaders Dominic Brown of Autonomy and also Jay Lieb of kCura, who got unmerciful ribbing for insisting (jokingly, I think) that TIFF files, unlike Generalissimo Francisco Franco, are still alive.  🙂

Jobs

In late January, the Jobs Project announced the release of the EDRM Talent Task Matrix diagram and spreadsheet, which is available in XLSX or PDF format. As noted in their press release, the Matrix is a tool designed to help hiring managers better understand the responsibilities associated with common eDiscovery roles. The Matrix maps responsibilities to the EDRM framework, so eDiscovery duties associated can be assigned to the appropriate parties.  Project leader Keith Tom noted that next steps include surveying EDRM members regarding the Matrix, requesting and co-authoring case-studies and white papers, and creating a short video on how to use the Matrix.

Metrics

In today’s session, the Metrics project team unveiled the first draft of the new Metrics model to EDRM participants!  Feedback was provided during the session and the team will make the model available for additional comments from EDRM members over the next week or so, with a goal of publishing for public comments in the next two to three weeks.  The team is also working to create a page to collect Metrics measurement tools from eDiscovery professionals that can benefit the eDiscovery community as a whole.  Project leaders Dera Nevin of TD Bank and Kevin Clark noted that June is “budget calculator month”.

Other Initiatives

As noted yesterday, there is a new project to address standards for working with native files in the different EDRM phases led by Eric Mandel from Zelle Hofmann and also a new initiative to establish collection guidelines, spearheaded by Julie Brown from Vorys.  There is also an effort underway to refocus the XML project, as it works to complete the 2.0 version of the EDRM XML model.  In addition, there was quite a spirited discussion as to where EDRM is heading as it approaches ten years of existence and it will be interesting to see how the EDRM group continues to evolve over the next year or so.  As you can see, a lot is happening within the EDRM group – there’s a lot more to it than just the base Electronic Discovery Reference Model.

So, what do you think?  Are you a member of EDRM?  If not, why not?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Reporting from the EDRM Annual Meeting and a Data Set Update – eDiscovery Trends

The Electronic Discovery Reference Model (EDRM) Project was created in May 2005 by George Socha of Socha Consulting LLC and Tom Gelbmann of Gelbmann & Associates to address the lack of standards and guidelines in the electronic discovery market.  Now, beginning its ninth year of operation with its annual meeting in St. Paul, MN, EDRM is accomplishing more than ever to address those needs.  Here are some highlights from the meeting, and an update regarding the (suddenly heavily talked about) EDRM Data Set project.

Annual Meeting

Twice a year, in May and October, eDiscovery professionals who are EDRM members meet to continue the process of working together on various standards projects.  This will be my eighth year participating in EDRM at some level and, oddly enough, I’m assisting with PR and promotion (how am I doing so far?).  eDiscovery Daily has referenced EDRM and its phases many times in the 2 1/2 years plus history of the blog – this is our 144th post that relates to EDRM!

Some notable observations about today’s meeting:

  • New Participants: More than half the attendees at this year’s annual meeting are attending for the first time.  EDRM is not just a core group of “die-hards”, it continues to find appeal with eDiscovery professionals throughout the industry.
  • Agile Approach: EDRM has adopted an Agile approach to shorten the time to complete and publish deliverables, a change in philosophy that facilitated several notable accomplishments from working groups over the past year including the Model Code of Conduct (MCoC), Information Governance Reference Model (IGRM), Search and Jobs (among others).  More on that tomorrow.
  • Educational Alliances: For the first time, EDRM has formed some interesting and unique educational alliances.  In April, EDRM teamed with the University of Florida Levin College of Law to present a day and a half conference entitled E-Discovery for the Small and Medium Case.  And, this June, EDRM will team with Bryan University to provide an in-depth, four-week E-Discovery Software & Applied Skills Summer Immersion Program for Law School Students.
  • New Working Group: A new working group to be lead by Eric Mandel of Zelle Hoffman was formed to address standards for working with native files in the different EDRM phases.

Tomorrow, we’ll discuss the highlights for most of the individual working groups.  Given the recent amount of discussion about the EDRM Data Set group, we’ll start with that one today!

Data Set

The EDRM Enron Data Set has been around for several years and has been a valuable resource for eDiscovery software demonstration and testing (we covered it here back in January 2011).  The data in the EDRM Enron PST Data Set files is sourced from the FERC Enron Investigation release made available by Lockheed Martin Corporation.  It was reconstituted as PST files with attachments for the EDRM Data Set Project.  So, in essence EDRM took already public domain available data and made the data much more usable.  Initially, the data was made available for download on the EDRM site, then subsequently moved to Amazon Web Services (AWS).

In the past several days, there has been much discussion about the personally-identifiable information (“PII”) available within the FERC (and consequently the EDRM Data Set), including social security numbers, credit card numbers, dates of birth, home addresses and phone numbers.  Consequently, the EDRM Data Set has been taken down from the AWS site.

The Data Set team led by Michael Lappin of Nuix and Eric Robi of Elluma Discovery has been working on a process (using predictive coding technology) to identify and remove the PII data from the EDRM Data Set.  Discussions about this process began months ago, prior to the recent discussions about the PII data contained within the set.  The team has completed this iterative process for V1 of the data set (which contains 1,317,158 items), identifying and removing 10,568 items with PII, HIPAA and other sensitive information.  This version of the data set will be made available within the EDRM community shortly for peer review testing.  The data set team will then repeat the process for the larger V2 version of the data set (2,287,984 items).  A timetable for republishing both sets should be available soon and the efforts of the Data Set team on this project should pay dividends in developing and standardizing processes for identifying and eliminating sensitive data that eDiscovery professionals can use in their own data sets.

The team has also implemented a Forensic Files Testing Project site where users can upload their own “modern”, non-copyrighted file samples that are typically encountered during electronic discovery processing to provide a more diverse set of data than is currently available within the Enron data set.

So, what do you think?  How has EDRM impacted how you manage eDiscovery?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Daily Is Thirty! (Months Old, That Is)

Thirty months ago yesterday, eDiscovery Daily was launched.  It’s hard to believe that it has been 2 1/2 years since our first three posts that debuted on our first day.  635 posts later, a lot has happened in the industry that we’ve covered.  And, yes we’re still crazy after all these years for committing to a daily post each business day, but we still haven’t missed a business day yet.  Twice a year, we like to take a look back at some of the important stories and topics during that time.  So, here are just a few of the posts over the last six months you may have missed.  Enjoy!

In addition, Jane Gennarelli has been publishing an excellent series to introduce new eDiscovery professionals to the litigation process and litigation terminology.  Here is the latest post, which includes links to the previous twenty one posts.

Thanks for noticing us!  We’ve nearly quadrupled our readership since the first six month period and almost septupled (that’s grown 7 times in size!) our subscriber base since those first six months!  We appreciate the interest you’ve shown in the topics and will do our best to continue to provide interesting and useful eDiscovery news and analysis.  And, as always, please share any comments you might have or if you’d like to know more about a particular topic!

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Five Common Myths About Predictive Coding – eDiscovery Best Practices

During my interviews with various thought leaders (a list of which can be found here, with links to each interview), we discussed various aspects of predictive coding and some of the perceived myths that exist regarding predictive coding and what it means to the review process.  I thought it would be a good idea to recap some of those myths and how they compare to the “reality” (at least as some of us see it).  Or maybe just me.  🙂

1.     Predictive Coding is New Technology

Actually, with all due respect to each of the various vendors that have their own custom algorithm for predictive coding, the technology for predictive coding as a whole is not new technology.  Ever heard of artificial intelligence?  Predictive coding, in fact, applies artificial intelligence to the review process.  With all of the acronyms we use to describe predictive coding, here’s one more for consideration: “Artificial Intelligence for Review” or “AIR”.  May not catch on, but I like it.

Maybe attorneys would be more receptive to it if they understood as artificial intelligence?  As Laura Zubulake pointed out in my interview with her, “For years, algorithms have been used in government, law enforcement, and Wall Street.  It is not a new concept.”  With that in mind, Ralph Losey predicts that “The future is artificial intelligence leveraging your human intelligence and teaching a computer what you know about a particular case and then letting the computer do what it does best – which is read at 1 million miles per hour and be totally consistent.”

2.     Predictive Coding is Just Technology

Treating predictive coding as just the algorithm that “reviews” the documents is shortsighted.  Predictive coding is a process that includes the algorithm.  Without a sound approach for identifying appropriate example documents for the collection, ensuring educated and knowledgeable reviewers to appropriately code those documents and testing and evaluating the results to confirm success, the algorithm alone would simply be another case of “garbage in, garbage out” and doomed to fail.

As discussed by both George Socha and Tom Gelbmann during their interviews with this blog, EDRM’s Search project has published the Computer Assisted Review Reference Model (CARRM), which has taken steps to define that sound approach.  Nigel Murray also noted that “The people who really understand computer assisted review understand that it requires a process.”  So, it’s more than just the technology.

3.     Predictive Coding and Keyword Searching are Mutually Exclusive

I’ve talked to some people that think that predictive coding and key word searching are mutually exclusive, i.e., that you wouldn’t perform key word searching on a case where you plan to use predictive coding.  Not necessarily.  Ralph Losey advocates a “multimodal” approach, noting it as: “more than one kind of search – using predictive coding, but also using keyword search, concept search, similarity search, all kinds of other methods that we have developed over the years to help train the machine.  The main goal is to train the machine.”

4.     Predictive Coding Eliminates Manual Review

Many people think of predictive coding as the death of manual review, with all attorney reviewers being replaced by machines.  Actually, manual review is a part of the predictive coding process in several aspects, including: 1) Subject matter knowledgeable reviewers are necessary to perform review to create a training set of documents for the technology, 2) After the process is performed, both sets (the included and excluded documents) are sampled and the samples are reviewed to determine the effectiveness of the process, and 3) The resulting responsive set is generally reviewed to confirm responsiveness and also to determine whether the documents are privileged.  Without manual review to train the technology and verify the results, the process would fail.

5.     Predictive Coding Has to Be Perfect to Be Useful

Detractors of predictive coding note that predictive coding can miss plenty of responsive documents and is nowhere near 100% accurate.  In one recent case, the producing party estimated as many as 31,000 relevant documents may have been missed by the predictive coding process.  However, they also estimated that a much more costly manual review would have missed as many as 62,000 relevant documents.

Craig Ball’s analogy about the two hikers that encounter the angry grizzly bear is appropriate – the one hiker doesn’t have to outrun the bear, just the other hiker.  Craig notes: “That is how I look at technology assisted review.  It does not have to be vastly superior to human review; it only has to outrun human review.  It just has to be as good or better while being faster and cheaper.”

So, what do you think?  Do you agree that these are myths?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

George Socha of Socha Consulting LLC – eDiscovery Trends

This is the seventh of the 2013 LegalTech New York (LTNY) Thought Leader Interview series.  eDiscoveryDaily interviewed several thought leaders at LTNY this year and generally asked each of them the following questions:

  1. What are your general observations about LTNY this year and how it fits into emerging trends?
  2. If last year’s “next big thing” was the emergence of predictive coding, what do you feel is this year’s “next big thing”?
  3. What are you working on that you’d like our readers to know about?

Today’s thought leader is George Socha.  A litigator for 16 years, George is President of Socha Consulting LLC, offering services as an electronic discovery expert witness, special master and advisor to corporations, law firms and their clients, and legal vertical market software and service providers in the areas of electronic discovery and automated litigation support. George has also been co-author of the leading survey on the electronic discovery market, The Socha-Gelbmann Electronic Discovery Survey; in 2011, he and Tom Gelbmann converted the Survey into Apersee, an online system for selecting eDiscovery providers and their offerings.  In 2005, he and Tom Gelbmann launched the Electronic Discovery Reference Model project to establish standards within the eDiscovery industry – today, the EDRM model has become a standard in the industry for the eDiscovery life cycle and there are nine active projects with over 300 members from 81 participating organizations.  George has a J.D. for Cornell Law School and a B.A. from the University of Wisconsin – Madison.

What are your general observations about LTNY this year and how it fits into emerging trends?

First of all, this year’s show has a livelier feel to it after a few years where it was feeling a bit flat, no doubt probably due to the economy.  The show has more “spark” to it, which is good not just for this conference but also for the industry and where it’s at and where it’s going.

As for the curriculum, if last year was the year of TAR/CAR/Predictive Coding, so was this year.  It’s also the year of “big data” – whatever “big data” means – and it may or may not be the year of information governance – whatever that means. I think a lot of what we see continues to focus on the same underlining set of issues, that providers are being ever more creative with the packages of the services, software and the capabilities they are offering.  They are trying to figure out how to get those offerings in front of the consuming audience with a compelling story addressing the question of why should you go the extra step and use what they have to offer instead of doing things as you always have done them.  Predictive coding is still more discussion than action, but it is interesting to hear the different opinions.  I moderated a panel with two trial lawyers who are head of their eDiscovery practice groups, who talked about the processes they now go through with clients where discussing predictive coding, to determine whether it’s appropriate for a given case.  The two attorneys were discussing the benefits of CAR, the drawbacks, how much extra it is likely to cost, how much it is likely to save and whether it is likely to even save anything.  This is a discussion that didn’t happen much a year ago and hardly at all two years ago.  To place this in context, however, I have worked with one corporation that has been doing what we now call Computer Assisted Review since 2003 to my direct knowledge and, I am told, since 2000.  CAR is not new in terms of techniques, rather it is new in terms of its packaging and presentation and “productization”.

If last year’s “next big thing” was the emergence of predictive coding, what do you feel is this year’s “next big thing”?

If you look at the eDiscovery industry, what the software providers have been developing and the skills and expertise that the service providers and law firms have been building up over the years, they are amassing a powerful set of capabilities that until now has been focused on one pretty narrow set of issues – eDiscovery. I see people starting to take those tools, techniques and experience and beginning to point them in new directions far beyond just eDiscovery, because most of what we deal with in eDiscovery applies in other areas as well.  For example, I see a turn toward broader information governance issues, such as how you get your electronic house in order so that things like eDiscovery become less of a pain point, and how do you do a better job or figuring out what is and what isn’t a record, and how can you get rid of content you been holding onto for years.  These issues extend beyond eDiscovery.  They include what you do to identify compliance challenges, and monitoring whether you are meeting those challenges in an effective fashion.  You could use the same technologies and approaches to improve how you manage your intellectual property assets, essentially pointing the EDRM framework in a new direction.  I think we are on the brink of what could be an enormous of expansion of uses of these capabilities that have been developed in a niche area for some time now.

What are you working on that you’d like our readers to know about?

With regard to EDRM, we are approaching our tenth year.  We are looking to that milestone and asking ourselves what EDRM should be today, what it should be tomorrow, and what can we do to improve what we do and how we do it.  We are going to shift to smaller working groups focused on more targeted projects with a shorter delivery cycle.  You can see the beginnings of that in some of our recently published deliverables.

The Computer Assisted Review Reference Model (CARRM) (our blog post about CARRM here) was our first outcome using this process and the second was the EDRM Talent Task Matrix (our blog post about it here) that we published on Monday.  For now, the Talent Task Matrix consists of a diagram that helps explain the concept as well as an accompanying spreadsheet which is available in Excel format (XLSX) or Adobe Acrobat (PDF) format that anyone can download.  We are looking for comments and feedback on the matrix and anticipate that it will fill a need and a gap that are not otherwise being addressed.

With regard to Apersee, providers continue to add information about themselves and we continue to add features.  In the past year, we replaced the search engine with a faceted search mechanism that is simpler to use.  We added an Event Calendar with links to Apersee providers. We added in a Press Release section which works in much the same way.  We’re looking to develop two additional sections which take specific types of content associated with providers and make that available within the application.  The underlining notion is to better help consumers evaluate providers on many dimensions, with an easily followed structure to the content available through the site.

Finally, we added the ability for consumers to submit Special Requests, so that if in looking for a provider and searching through the website they do not find the result they need, they always can submit a special request to us through the click of a button.  We reformulate the message and send it out to about 2,700 people in the provider community.  Unless you choose otherwise, the request is totally anonymous.  Typically, we get back 20 to 40 relevant responses within the first few hours, which usually is more information than the requestor can handle.  The responses from the request system have been very positive.

Thanks, George, for participating in the interview!

And to the readers, as always, please share any comments you might have or if you’d like to know more about a particular topic!

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Tom Gelbmann of Gelbmann & Associates, LLC – eDiscovery Trends

This is the third of the 2013 LegalTech New York (LTNY) Thought Leader Interview series.  eDiscoveryDaily interviewed several thought leaders at LTNY this year and generally asked each of them the following questions:

  1. What are your general observations about LTNY this year and how it fits into emerging trends?
  2. If last year’s “next big thing” was the emergence of predictive coding, what do you feel is this year’s “next big thing”?
  3. What are you working on that you’d like our readers to know about?

Today’s thought leader is Tom Gelbmann. Tom is Principal of Gelbmann & Associates, LLC.  Since 1993, Gelbmann & Associates, LLC has advised law firms and Corporate Law Departments to realize the full benefit of their investments in Information Technology.  Tom has also been co-author of the leading survey on the electronic discovery market, The Socha-Gelbmann Electronic Discovery Survey; in 2011 he and George Socha converted the Survey into Apersee, an online system for selecting eDiscovery providers and their offerings.  In 2005, he and George Socha launched the Electronic Discovery Reference Model project to establish standards within the eDiscovery industry – today, the EDRM model has become a standard in the industry for the eDiscovery life cycle.

What are your general observations about LTNY this year and how it fits into emerging trends?

{Interviewed the first morning of LegalTech}  The most notable trend I have seen to lead up to LegalTech is the rush to jump on the computer assisted review bandwagon.  There are several sessions here at the show related to computer assisted review.  In addition, many in the industry seem to have a tool now some are promoting it as an “easy” button.  There is no “easy” button and, if I can mention a plug for EDRM, that’s one of the things the Search group was concerned with, so the group published the Computer Assisted Review Reference Model (CARRM) (our blog post about CARRM here).

To help people understand what computer assisted review is all about: it’s great technology and, if well used, it can really deliver great results, save time and save money, but it has to be understood it’s a tool.  It’s not a substitute for a process.  The good news is the technology is helping and, as I have been seeing for years, the more technology is intelligently used, the more you can start to bend the cost curve down for electronic discovery.  So, what I think it has started to do and will continue to do is level off those costs on the right hand side of the model.

If last year’s “next big thing” was the emergence of predictive coding, what do you feel is this year’s “next big thing”?

I think one of the “next big things” which has already started is the whole left side of the model which I would characterize as information governance.  Information governance is on the rise and a lot of people in the industry believe that information governance today might be where electronic discovery was in about 2005 or 2006.  We need a lot of understanding, standards and education on effective approaches to information governance because that’s really where the problems are.  There are significant expenditures by organizations trying to work with too much data and not being able to find their data.  Associated with that, will be technology that will help and I also anticipate a significant increase in consulting services to help organizations develop effective policies and procedures.  The consulting organizations that can get it right and communicate it effectively will be able to capitalize on this aspect of the market.  Related to that, from a preservation standpoint, we have been seeing more software tools to help with litigation hold as more organizations get serious about preservation.

Another big trend is education.  EDRM is involved with the programs at Bryan University and the University of Florida (Bill Hamilton deserves a lot of credit for what is happening there).  I think you are going to see that continue to expand as more universities and educational facilities will be providing quality programs in the area of electronic discovery and perhaps information governance along the way.

The last trend I want to mention is a greater focus on marketing.  From a provider’s standpoint, it seems that there has been a flood of announcements about organizations that have hired a new marketing director, either overall for a specific region (west coast, east coast, South America, etc.).  Marketing is really expanding in the community, so it seems that providers are realizing they really have to intelligently go after business.  I don’t believe we saw that level of activity even two or three years ago.

What are you working on that you’d like our readers to know about?

With regard to EDRM, we had a very productive mid-year meeting where we asked our participants to help us plan for the future of EDRM.  As a result, we came up with several changes we are immediately implementing. One change is that projects are going to be much smaller and shorter duration with as few as one to five people working on a particular item to get it done and get it out to the community more quickly for feedback.  One example of that which we discussed above is CARRM.  We just announced another project yesterday which was the Talent Task Matrix (our blog post about it here).  We already have 91 downloads of the diagram and 87 downloads of the spreadsheet in less than a day. The matrix was very good work done by a very small group of EDRM folks.  We also dropped the prices for EDRM participation and there are also going to be additional changes in terms of sponsorships and advertising, so we are changing as we are gearing up for our 10th year.

Also, we’re very excited about the additions we have made to Apersee in the last six months.  One addition is the calendar which we believe is the most comprehensive calendar around for eDiscovery events.  If it is happening in the eDiscovery world globally, it’s probably on the Apersee calendar.  For conferences and webinars, the participating organizations will be listed, with a link back to their profile within Apersee.  We are also tracking press releases related to eDiscovery, enabling users to view press releases chronologically and also see the press releases associated within organization to see what they have said about themselves through their press releases.  These are examples of what Apersee is doing to build the comprehensive view of eDiscovery organizations to show what is happening, what they are doing and what services and products they offer.

Thanks, Tom, for participating in the interview!

And to the readers, as always, please share any comments you might have or if you’d like to know more about a particular topic!

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Pro Football Players Aren’t the Only Ones with Talent – eDiscovery Trends

In football, each team member has responsibilities.  For example, the quarterback throws the football (and sometimes changes the plays at the line of scrimmage), the receivers catch the football, the offensive line blocks and the defense tackles the guy with the ball.  Each player has responsibilities that align with their talents.  Likewise, the members of a litigation team have responsibilities that align with their talents.  Now, the Electronic Discovery Reference Model (EDRM) has created a new tool to align talents with their associated tasks.

Last week, EDRM announced the release of the EDRM Talent Task Matrix diagram and spreadsheet. As noted in their press release, the Matrix, collaboratively developed by EDRM’s Jobs Project Team, is a tool designed to help hiring managers better understand the responsibilities associated with common eDiscovery roles. The Matrix maps responsibilities to the EDRM framework, so eDiscovery duties associated can be assigned to the appropriate parties.

The EDRM Talent Task Matrix Spreadsheet is available in XLSX or PDF format.  It shows the EDRM Stage and Stage Area, the Responsibility within each stage, followed by the various positions that have responsibilities within the eDiscovery life cycle, as follows:

  • CXO
  • Senior Attorney
  • Attorney
  • Paralegal
  • Litigation Support
  • Discovery Analyst
  • Document / Data Analysis
  • Forensic
  • Records Management
  • Information Technology
  • Review Lead
  • Review Quality Control

The Matrix shows a “Yes” for each responsibility that each position participates in the responsibility.  There are 130 responsibilities listed in the Matrix, covering the entire EDRM life cycle.

EDRM’s Talent Task Matrix represents the joint efforts of the entire EDRM Jobs Project Team, spearheaded by co-leaders Maria Montoya of Bryan University and Keith Tom. Wade Peterson of Bowman & Brooke LLP led the development of the Talent Task Matrix diagram.

Comments on the EDRM Talent Task Matrix Diagram and the EDRM Talent Task Matrix are now being accepted and can be posted at the bottom of the page here. The comment period continues until February 28.  It’s quite in-depth, so they might have to consider extending it.

Of course, when it comes to football, only one team can apply their talent best to accomplish their task – winning the game!  Congrats to the Baltimore Ravens – winners of Super Bowl XLVII!  Not even a power outage could keep them from accomplishing their goal.

So, what do you think?  Could this Matrix be useful to managing the resources in your litigation project?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Baby, You Can Drive My CARRM – eDiscovery Trends

Full disclosure: this post is NOT about the Beatles’ song, but I liked the title.

There have been a number of terms applied to using technology to aid in eDiscovery review, including technology assisted review (often referred to by its acronym “TAR”) and predictive coding.  Another term is Computer Assisted Review (which lends itself to the obvious acronym of “CAR”).

Now, the Electronic Discovery Reference Model (EDRM) is looking to provide an “owner’s manual” to that CAR with its new draft Computer Assisted Review Reference Model (CARRM), which depicts the flow for a successful CAR project.  The CAR process depends on, among other things, a sound approach for identifying appropriate example documents for the collection, ensuring educated and knowledgeable reviewers to appropriately code those documents and testing and evaluating the results to confirm success.  That’s why the “A” in CAR stands for “assisted” – regardless of how good the tool is, a flawed approach will yield flawed results.

As noted on the EDRM site, the major steps in the CARRM process are:

Set Goals

The process of deciding the outcome of the Computer Assisted Review process for a specific case. Some of the outcomes may be:

  • reduction and culling of not-relevant documents;
  • prioritization of the most substantive documents; and
  • quality control of the human reviewers.

Set Protocol

The process of building the human coding rules that take into account the use of CAR technology. CAR technology must be taught about the document collection by having the human reviewers submit documents to be used as examples of a particular category, e.g. Relevant documents. Creating a coding protocol that can properly incorporate the fact pattern of the case and the training requirements of the CAR system takes place at this stage. An example of a protocol determination is to decide how to treat the coding of family documents during the CAR training process.

Educate Reviewer

The process of transferring the review protocol information to the human reviewers prior to the start of the CAR Review.

Code Documents

The process of human reviewers applying subjective coding decisions to documents in an effort to adequately train the CAR system to “understand” the boundaries of a category, e.g. Relevancy.

Predict Results

The process of the CAR system applying the information “learned” from the human reviewers and classifying a selected document corpus with pre-determined labels.

Test Results

The process of human reviewers using a validation process, typically statistical sampling, in an effort to create a meaningful metric of CAR performance. The metrics can take many forms, they may include estimates in defect counts in the classified population, or use information retrieval metrics like Precision, Recall and F1.

Evaluate Results

The process of the review team deciding if the CAR system has achieved the goals of anticipated by the review team.

Achieve Goals

The process of ending the CAR workflow and moving to the next phase in the review lifecycle, e.g. Privilege Review.

The diagram does a good job of reflecting the linear steps (Set Goals, Set Protocol, Educate Reviewer and, at the end, Achieve Goals) and a circle to represent the iterative steps (Code Documents, Predict Results, Test Results and Evaluate Results) that may need to be performed more than once to achieve the desired results.  It’s a very straightforward model to represent the process.  Nicely done!

Nonetheless, it’s a draft version of the model and EDRM wants your feedback.  You can send your comments to mail@edrm.net or post them on the EDRM site here.

So, what do you think?  Does the CARRM model make computer assisted review more straightforward?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

ARMA/Forrester Survey: Only One in Eight Records Managers Trusts Their ESI – eDiscovery Trends

According to the Forrester Research and ARMA International Records Management Online Survey, Q3 2012, only 12 percent of records managers are “very confident” that, if challenged, their organization could demonstrate that their electronically stored information (ESI) is “accurate, accessible, complete and trustworthy”.  That’s less than one in eight.

The report, co-authored by ARMA and Forrester Research, contains the results of a survey of 354 records managers.

Some of the less than optimistic comments from the report include: “Records managers report abysmally low e-discovery confidence…This bleak data point represents an even lower e-discovery confidence rate than captured in past surveys…[S]urvey data show that integrated legal hold – a critical component needed for successful defensible disposition – is simply missing in organizations.”

And this: “Organizations aren’t sure of the business value or legal obligations to preserve content so they simply continue to accumulate digital debris, slowing down overtaxed systems, adding to storage costs, and posing potential additional litigation and investigation burdens over time.”

Some of the reasons cited as obstacles to improved records management include:

  • Poor systems integration – 74 percent of respondents;
  • Inadequate budget – 73 percent;
  • Lack of experienced staff – 64 percent;
  • Outdated policies or procedures – 55 percent; and
  • Lack of clear leadership – 54 percent.

So, what are organizations doing to address the obstacles?  Here are some indications:

  • 40 percent of survey respondents expect that their organization’s overall records management spending will increase at least 5% from 2012 to 2013;
  • 71 percent currently have implementation plans underway, or plans to implement records management technology within the next year;
  • 81 percent consider an improvement in records management policy consistency an important objective for their organization.

A copy of the report is available here from Forrester Research for $499.

Since, according to the Compliance, Governance and Oversight Council (CGOC), information volume doubles every 18-24 months, you would think organizations would be making greater strides in implementing information governance programs.  Of course, many information governance industry initiatives are still in relative infancy, including the Information Governance Reference Model (IGRM) Project of the Electronic Discovery Reference Model (EDRM), which was started a mere two years ago (click here for information on their newest version).  It appears that organizations still have a long way to go to get their data under control.

So, what do you think?  What, if any, records management obstacles are your organization facing?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

EDRM Announces Several Updates at Mid-Year Meeting – eDiscovery Trends

Last week, the Electronic Discovery Reference Model (EDRM) conducted its mid-year meeting to enable the working groups to meet and further accomplishments in each of the teams for the year.  Having attended several of these meetings in the past, I’ve always found them to usually yield significant progress within the working groups, as well as providing a great opportunity for eDiscovery professionals to get together and talk shop.  Based on the results of the meeting, EDRM issued an announcement with updates from several of their more active projects.

Here are the updates:

  • Data Set: The Data Set project announced the launch of its new file upload utility. “The upload utility will allow us to develop a modern data set that more accurately represents the type of files that are commonly encountered in data processing,” said Eric Robi of Elluma Discovery, co-chair of the project with Michael Lappin of NUIX. The Data Set project also announced a soon-to-be-published “million file dataset” and an upcoming redacted version of the Enron data set, previously described on this blog here.
  • Information Governance Reference Model (IGRM): The IGRM team announced that its updated model (IGRM v3) was recently published and presented at ARMA International’s 57th Annual Conference & Expo and the IAPP Privacy Academy 2012. As discussed on this blog just a couple of weeks ago, the updated version adds privacy and security as key stakeholders in the model.
  • Jobs: The Jobs project continued development of the EDRM RACI (responsible, accountable, consulted, informed) Matrix, a tool designed to help hiring managers better understand the responsibilities associated with common e-discovery roles. RACI maps responsibilities to the EDRM framework so e-discovery duties associated can be assigned to the appropriate parties.
  • Metrics: The Metrics project team refined the EDRM Metrics database, an anonymous set of e-discovery processing metrics derived from actual matters, which will include a CSV upload function to make it easier for vendors and law firms to anonymously submit data to the system.  Having worked on the early stages of this project, my “hats off” to the team for the additional accomplishments.
  • Search: The Search group announced that its EDRM Computer Assisted Review Reference Model (CARRM) soon will be available for public comment. The goal of CARRM is to demystify the predictive coding process and to allow for a common communication platform between vendors and end-users at each phase of the CAR process and it will be interesting to see the document that emerges from these efforts.

EDRM meets in person twice a year, in May for the annual meeting and October for the mid-year meeting, with regular working group phone calls scheduled throughout the year to keep the projects progressing.  The next in person meeting is next year’s annual meeting, currently scheduled for May 7 thru 9, 2013.  For more information about EDRM, click here.  For information on joining EDRM, including fee information for participation, click here.

So, what do you think?  Have you been following the activity of EDRM?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.