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Analysis

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.

First Pass Review: Domain Categorization of Your Opponent’s Data

Yesterday, we talked about the use of First Pass Review (FPR) applications (such as FirstPass™, powered by Venio FPR™) to not only conduct first pass review of your own collection, but also to analyze your opponent’s ESI production. One way to analyze that data is through “fuzzy” searching to find misspellings or OCR errors in an opponent’s produced ESI.

Domain Categorization

Another type of analysis is the use of domain categorization. Email is generally the biggest component of most ESI collections and each participant in an email communication belongs to a domain associated with the email server that manages their email.

FirstPass supports domain categorization by providing a list of domains associated with the ESI collection being reviewed, with a count for each domain that appears in emails in the collection. Domain categorization provides several benefits when reviewing your opponent’s ESI:

  • Non-Responsive Produced ESI: Domains in the list that are obviously non-responsive to the case can be quickly identified and all messages associated with those domains can be “group-tagged” as non-responsive. If a significant percentage of files are identified as non-responsive, that may be a sign that your opponent is trying to “bury you with paper” (albeit electronic).
  • Inadvertent Disclosures: If there are any emails associated with outside counsel’s domain, they could be inadvertent disclosures of attorney work product or attorney-client privileged communications. If so, you can then address those according to the agreed-upon process for handling inadvertent disclosures and clawback of same.
  • Issue Identification: Messages associated with certain parties might be related to specific issues (e.g., an alleged design flaw of a specific subcontractor’s product), so domain categorization can isolate those messages more quickly.

In summary, there are several ways to use first pass review tools, like FirstPass, for reviewing your opponent’s ESI production, including: email analytics, synonym searching, fuzzy searching and domain categorization. First pass review isn’t just for your own production; it’s also an effective process to quickly evaluate your opponent’s production.

So, what do you think? Have you used first pass review tools to assess an opponent’s produced ESI? Please share any comments you might have or if you’d like to know more about a particular topic.

First Pass Review: Fuzzy Searching Your Opponent’s Data

Yesterday, we talked about the use of First Pass Review (FPR) applications (such as FirstPass™, powered by Venio FPR™) to not only conduct first pass review of your own collection, but also to analyze your opponent’s ESI production. One way to analyze that data is through synonym searching to find variations of your search terms to increase the possibility of finding the terminology used by your opponents.

Fuzzy Searching

Another type of analysis is the use of fuzzy searching. Attorneys know what terms they’re looking for, but those terms may not often be spelled correctly. Also, opposing counsel may produce a number of image only files that require Optical Character Recognition (OCR), which is usually not 100% accurate.

FirstPass supports “fuzzy” searching, which is a mechanism by finding alternate words that are close in spelling to the word you’re looking for (usually one or two characters off). FirstPass will display all of the words – in the collection – close to the word you’re looking for, so if you’re looking for the term “petroleum”, you can find variations such as “peroleum”, “petoleum” or even “petroleom” – misspellings or OCR errors that could be relevant. Then, simply select the variations you wish to include in the search. Fuzzy searching is the best way to broaden your search to include potential misspellings and OCR errors and FirstPass provides a terrific capability to select those variations to review additional potential “hits” in your collection.

Tomorrow, I’ll talk about the use of domain categorization to quickly identify potential inadvertent disclosures and weed out non-responsive files produced by your opponent, based on the domain of the communicators. Hasta la vista, baby!  🙂

In the meantime, what do you think? Have you used fuzzy searching to find misspellings or OCR errors in an opponent’s produced ESI? Please share any comments you might have or if you’d like to know more about a particular topic.

First Pass Review: Synonym Searching Your Opponent’s Data

Yesterday, we talked about the use of First Pass Review (FPR) applications (such as FirstPass™, powered by Venio FPR™) to not only conduct first pass review of your own collection, but also to analyze your opponent’s ESI production. One way to analyze that data is through email analytics to see the communication patterns graphically to identify key parties for deposition purposes and look for potential production omissions.

Synonym Searching

Another type of analysis is the use of synonym searching. Attorneys understand the key terminology their client uses, but they often don’t know the terminology their client’s opposition uses because they haven’t interviewed the opposition’s custodians. In a product defect case, the opposition may refer to admitted design or construction “mistakes” in their product or process as “flaws”, “errors”, “goofs” or even “flubs”. With FirstPass, you can enter your search term into the synonym searching section of the application and it will provide a list of synonyms (with hit counts of each, if selected). Then, you can simply select the synonyms you wish to include in the search. As a result, FirstPass identifies synonyms of your search terms to broaden the scope and catch key “hits” that could be the “smoking gun” in the case.

Tomorrow, I’ll talk about the use of fuzzy searching to find misspellings that may be commonly used by your opponent or errors resulting from Optical Character Recognition (OCR) of any image-only files that they produce. Stay tuned! 🙂

In the meantime, what do you think? Have you used synonym searching to identify variations on terms in an opponent’s produced ESI? Please share any comments you might have or if you’d like to know more about a particular topic.

First Pass Review: Of Your Opponent’s Data

In the past few years, applications that support Early Case Assessment (ECA) (or Early Data Assessment, as I prefer to call it) and First Pass Review (FPR) of ESI have become widely popular in eDiscovery as the analytical and culling benefits of conducting FPR have become obvious. The benefit of these FPR tools to analyze and cull their ESI before conducting attorney review and producing relevant files has become increasingly clear. But, nobody seems to talk about what these tools can do with opponent’s produced ESI.

Less Resources to Understand Data Produced to You

In eDiscovery, attorneys typically develop a reasonably in-depth understanding of their collection. They know who the custodians are, have a chance to interview those custodians and develop a good knowledge of standard operating procedures and terminology of their client to effectively retrieve responsive ESI. However, that same knowledge isn’t present when reviewing opponent’s data. Unless they are deposed, the opposition’s custodians aren’t interviewed and where the data originated is often unclear. The only source of information is the data itself, which requires in-depth analysis. An FPR application like FirstPass™, powered by Venio FPR™, can make a significant difference in conducting that analysis – provided that you request a native production from your opponent, which is vital to being able to perform an in-depth analysis.

Email Analytics

The ability to see the communication patterns graphically – to identify the parties involved, with whom they communicated and how frequently – is a significant benefit to understanding the data received. FirstPass provides email analytics to understand the parties involved and potentially identify other key opponent individuals to depose in the case. Dedupe capabilities enable quick comparison against your production to confirm if the opposition has possibly withheld key emails between opposing parties. FirstPass also provides an email timeline to enable you to determine whether any gaps exist in the opponent’s production.

Tomorrow, I’ll talk about the use of synonym searching to find variations of your search terms that may be common terminology of your opponent. Same bat time, same bat channel! 🙂

In the meantime, what do you think? Have you used email analytics to analyze an opponent’s produced ESI? Please share any comments you might have or if you’d like to know more about a particular topic.