Identification

Reporting from the EDRM Mid-Year Meeting

 

Launched in May 2005, the Electronic Discovery Reference Model (EDRM) Project was created to address the lack of standards and guidelines in the electronic discovery market.  Now, in its sixth year of operation, EDRM has become the gold standard for…well…standards in eDiscovery.  Most references to the eDiscovery industry these days refer to the EDRM model as a representation of the eDiscovery life cycle.

At the first meeting in May 2005, there were 35 attendees, according to Tom Gelbmann of Gelbmann & Associates, co-founder of EDRM along with George Socha of Socha Consulting LLC.  Check out the preliminary first draft of the EDRM diagram – it has evolved a bit!  Most participants were eDiscovery providers and, according to Gelbmann, they asked “Do you really expect us all to work together?”  The answer was “yes”, and the question hasn’t been asked again.  Today, there are over 300 members from 81 participating organizations including eDiscovery providers, law firms and corporations (as well as some individual participants).

This week, the EDRM Mid-Year meeting is taking place in St. Paul, MN.  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.  EDRM has eight currently active projects, as follows:

  • Data Set: provides industry-standard, reference data sets of electronically stored information (ESI) and software files that can be used to test various aspects of eDiscovery software and services,
  • Evergreen: ensures that EDRM remains current, practical and relevant and educates about how to make effective use of the Model,
  • Information Management Reference Model (IMRM): provides a common, practical, flexible framework to help organizations develop and implement effective and actionable information management programs,
  • Jobs: develops a framework for evaluating pre-discovery and discovery personnel needs or issues,
  • Metrics: provides an effective means of measuring the time, money and volumes associated with eDiscovery activities,
  • Model Code of Conduct: evaluates and defines acceptable boundaries of ethical business practices within the eDiscovery service industry,
  • Search: provides a framework for defining and managing various aspects of Search as applied to eDiscovery workflow,
  • XML: provides a standard format for e-discovery data exchange between parties and systems, reducing the time and risk involved with data exchange.

This is my fourth year participating in the EDRM Metrics project and it has been exciting to see several accomplishments made by the group, including creation of a code schema for measuring activities across the EDRM phases, glossary definitions of those codes and tools to track early data assessment, collection and review activities.  Today, we made significant progress in developing survey questions designed to gather and provide typical metrics experienced by eDiscovery legal teams in today’s environment.

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

Thought Leader Q&A: Jim McGann of Index Engines

 

Tell me about your company and the products you represent.  Businesses today face a significant challenge organizing their files and email to ensure timely and cost efficient access, while also maintaining compliance to regulations governing electronic data. Founded in 2003, Index Engines’ mission is to organize enterprise data assets, and make them immediately accessible, searchable and easy to manage. 

Index Engines’ discovery platform is the only solution on the market to offer a complete view of electronic data assets. Online data is indexed in-stream at wire speed in native enterprise storage protocols, enabling high-speed, efficient indexing of proprietary backup and transfer formats. Our unique approach to offline records scans backup tapes, indexes the contents and extracts relevant data, eliminating the time-consuming restoration process. Index Engines provides the only comprehensive discovery platform across both online and offline data, saving time and money when managing enterprise information.

What has caused backup tapes to become so relevant in eDiscovery?  Tape discovery actually appeared on the map after the renowned Zubulake case in 2003, and was reinforced by the FRCP amendments in 2006 and then again last year with the adoption of California’s eDiscovery act AB-5. Each of these milestones propelled tape discovery further into the eDiscovery market. These days, tapes are as common as any other container to discover relevant electronically stored information (ESI).

What can companies proactively do to address tape storage?  Needlessly storing old backup tapes is both a potential liability and a wasted expense. The liability comes from not knowing what information the tapes contain. The cost of offsite tape storage –  even if it is only a few dollars a month per tape –  quickly adds up. Tape remediation is the process of proactively discovering data contained on legacy backup tapes, and then applying a corporate retention policy to this tape data. Once the relevant data has been identified and archived accordingly, the tapes can be destroyed or recycled. 

How can a legal or litigation support professional substantiate claims of processing speed made by eDiscovery vendors?  Without an industry standard vendor-neutral benchmarking process, this is a difficult challenge. I would recommend performing a proof of concept to actually see the performance in action. Another idea would be to question the components of the technology. Is the technology simply off-the-shelf freeware that has been repackaged, or is it something more powerful?

You have recently had patents approved for your technology. Can you explain this in greater detail?  Index Engines has engineered a platform that performs sequential processing of data. We received both US and European patents for this unique approach towards the processing of enterprise data, which makes the data searchable and discoverable across both primary and secondary (backup) storage. Our patented approach enables the indexing of electronic data as it flows to backup, as well as documented high speed indexing of network data at 1TB per hour per node.

About Jim McGann
Jim is Vice President of Information Discovery for Index Engines. Jim has extensive experience with the eDiscovery and Information Management. He is currently contributing to the Sedona working group addressing electronic document retention and production. Jim is also a frequent speaker for industry organizations such as ARMA and ILTA, and has authored multiple articles for legal technology and information management publications.  In recent years, Jim has worked for technology based start-ups that provided financial services and information management solutions. Prior to Index Engines, he worked for leading software firms, including Information Builders and the French based engineering software provider Dassault Systemes. Jim was responsible for the Business Development of Scopeware at Mirror Worlds Technologies, the knowledge management software firm founded by Dr. David Gelernter of Yale University. Jim graduated from Villanova University with a degree in Mechanical Engineering.

Announcing eDiscovery Thought Leader Q&A Series!

 

eDiscovery Daily is excited to announce a new blog series of Q&A interviews with various eDiscovery thought leaders.  Over the next three weeks, we will publish interviews conducted with six individuals with unique and informative perspectives on various eDiscovery topics.  Mark your calendars for these industry experts!

Christine Musil is Director of Marketing for Informative Graphics Corporation, a viewing, annotation and content management software company based in Arizona.  Christine will be discussing issues associated with native redaction and redaction of Adobe PDF files.  Her interview will be published this Thursday, October 14.

Jim McGann is Vice President of Information Discovery for Index Engines. Jim has extensive experience with the eDiscovery and Information Management.  Jim will be discussing issues associated with tape backup and retrieval.  His interview will be published this Friday, October 15.

Alon Israely is a Senior Advisor in BIA’s Advisory Services group and currently oversees BIA’s product development for its core technology products.  Alon will be discussing best practices associated with “left side of the EDRM model” processes such as preservation and collection.  His interview will be published next Thursday, October 21.

Chris Jurkiewicz is Co-Founder of Venio Systems, which provides Venio FPR™ allowing legal teams to analyze data, provide an early case assessment and a first pass review of any size data set.  Chris will be discussing current trends associated with early case assessment and first pass review tools.  His interview will be published next Friday, October 22.

Kirke Snyder is Owner of Legal Information Consultants, a consulting firm specializing in eDiscovery Process Audits to help organizations lower the risk and cost of e-discovery.  Kirke will be discussing best practices associated with records and information management.  His interview will be published on Monday, October 25.

Brad Jenkins is President and CEO for Trial Solutions, which is an electronic discovery software and services company that assists litigators in the collection, processing and review of electronic information.  Brad will be discussing trends associated with SaaS eDiscovery solutions.  His interview will be published on Tuesday, October 26.

We thank all of our guests for participating!

So, what do you think?  Is there someone you would like to see interviewed for the blog?  Are you an industry expert with some information to share from your “soapbox”?  If so, please share any comments or contact me at daustin@trialsolutions.net.  We’re looking to assemble our next group of interviews now!

eDiscovery Best Practices: Cost of Data Storage is Declining – Or Is It?

Recently, I was gathering information on the cost of data storage and ran across this ad from the early 1980s for a 10 MB disk drive – for $3,398! That’s MB (megabytes), not GB (gigabytes) or TB (terabytes). What a deal!

Even in 2000, storage costs were around $20 per GB, so an 8 GB drive would cost about $160.

Today, 1 TB is available for $100 or less. HP has a 2 TB external drive available at Best Buy for $140 (prices subject to change of course). That’s 7 cents per GB. Network storage drives are more expensive, but still available for around $100 per TB.

At these prices, it’s natural for online, accessible data in corporations to rise exponentially. It’s great to have more and more data readily available to you, until you are hit with litigation or regulatory requests. Then, you potentially have to go through all that data for discovery to determine what to preserve, collect, process, analyze, review and produce.

Here is what each additional GB can cost to review (based on typical industry averages):

  • 1 GB = 20,000 documents (can vary widely, depending on file formats)
  • Review attorneys typically average 60 documents reviewed per hour (for simple relevancy determinations)
  • That equals an average of 333 review hours per GB (20,000 / 60)
  • If you’re using contract reviewers at $50 per hour – each extra GB just cost you $16,650 to review (333×50)

That’s expensive storage! And, that doesn’t even take into consideration the costs to identify, preserve, collect, and process each additional GB.

Managing Storage Costs Effectively

One way to manage those costs is to limit the data retained in the first place through an effective records management program that calls for regular destruction of data not subject to a litigation hold. If you’re eliminating expired data on a regular basis, there is less data to go through the EDRM discovery “funnel” to production.

Sophisticated collection tools or first pass review tools (like FirstPass™, powered by Venio FPR™) can also help cull data for attorney review to reduce those costs, which is the most expensive component of eDiscovery.

So, what do you think? Do you track GB metrics for your eDiscovery cases? Please share any comments you might have or if you’d like to know more about a particular topic.