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Experts in the emerging field of data analytics now provide attorneys with powerful new tools to transform and evaluate 'data dumps' exchanged during legal discovery. While many national-scope firms have developed in-house data analytics skills, regional and local firms now also have full access to third party state-of-the-art processing algorithms and optical scanning software that convert paper images to analyzable data. Over the past five years, refinements in data analytics techniques and document review software have moved to the forefront of litigation support to dramatically change the landscape of discovery. To improve case outcomes, outside experts in data analytics look to: 1) get more out of the available case data, 2) reduce human error and risk, and 3) save 30-70% (or more) in costs and time. Several examples below illustrate the case for advanced analytics.

Case Example #1. In a real estate case that included the production of 29,000 partial names and addresses, a custom data analytics application was designed to: 1) fill in the blanks for partial addresses with missing zip codes and other data, and 2) match the enhanced address list with multiple public websites and databases to retrieve unique assessor parcel numbers (APN) and thus to track sales price histories for the properties in the dispute. The automated analytics process was completed in three days and generated significant additional background data, including enough data to generate meaningful business revenue opportunities for the client.

Case Example #2. In a toxic contaminant class action case where the insurance policyholder client required counsel to allocate defense costs at the claimant level, the law firm was faced with processing 23,000 invoices containing 17,000 non-standardized claimant formats/names that covered $25,500,000 in costs. In two weeks of work, two paralegals assigned by the firm were able to match only $1,500,000 in costs with 1,500 invoices. A custom data analytics application was crafted and run in only two days that quickly matched 20,500 invoices covering $22,000,000 in related costs, with more than a 70% savings in time and case costs.

Experts in the emerging field of data analytics now provide attorneys with powerful new tools.

Case Example #3. In a prototypical breach of contract and fraud case involving two private equity firms, a completed technology acquisition and before-and-after management teams, the plaintiff's new substitute law firm received a 68,000-page data dump including a mix of both electronic and hard copies, plus exhibits and schedules under two ongoing parallel lawsuits extending back over four years. Within three business days, a data analytics program was designed and implemented to:

  • Source, scan, date and prioritize all correspondence, emails/email chains and texts among 84 individuals,
  • Identify 'incidentally copied' email/text recipients as added prospective witnesses and/or co-defendants,
  • Complete a stage one auto-translation of emails from three foreign entities into English, and
  • Recover and collate historical Board and Sub-Committee Minutes from three affiliated entities.

The supervising attorney was also able to correlate and compare data over selected timeframes from each of the parties. Additionally, by using algorithmic sentiment analysis and concept clustering techniques, the attorney was able quickly to identify emails and other communications which focused on common areas of interest, dispute and/or disagreement. Finally, the application was enhanced to highlight and cross-reference key abbreviations, nicknames, acronyms, industry-specific terms and selected insider phrases which had developed during the parallel case review among two attorneys and two paralegals.

Case Example #4. In a parallel criminal investigation, the receiving firm was faced with a supplemental late-stage discovery production that included the delivery of archaic floppy disks as well as zip drives, thumb drives and dozens of boxes of highly-disorganized financial data. For various tactical reasons the supervising attorney was reluctant to request any case delays. Within 48 hours a custom data analytics application was implemented to:
  • Separate and sequence eight years of bank statements (seventeen accounts at four different banks),
  • Scan over 31,000 paper checks - segregating them by account, date, check number, amount, and payee.
  • Sequence and compare raw paper invoices with full and partial claims data.

The combined data analytics response for these two related case examples was under 7 days (all in accordance with required confidentiality restrictions, chain of custody requirements, and relevant court protocols) and the results were available in time for deposition to impeach one key witness, and to limit the testimony of a second witness. In addition to the powerful tactical value of the data analytics-assisted discovery review, the attorney estimated a minimum of at least a 50% cost savings in the case over manual review techniques.

Case Example #5. In a Hart-Scott-Rodino 'second request' filing involving a key healthcare industry acquisition involving several law firms, counsel for the acquiring company was tasked with organizing the review of almost 5 Terabytes (approximately 200 million pages) of potentially responsive data, plus a summary assessment, within 60 days. Using data analytics-driven methodologies, the full project was completed ahead of deadline, with the ultimate cost at just over 30% of the initial budget, and at a review cost of less than 30 cents per document. The expansive project involved cross-validated search terms filters, two levels of predictive text classification, and the coordination of five separate teams totaling over 100 contract attorneys. To maximize cooperation, a three-pronged bonus incentive matrix was developed that encouraged the attorneys to work both collaboratively, competitively, and accurately, and also to be able to compare their personal contributions through adopted individual code names. At completion, the client estimated a 70% overall savings, in addition to the valuable insights gained on the relative strengths among the firms.

Case Example #6. In a class action case relating to unsupervised sales calls targeting a database of over 120 million cell phone numbers, the law firm used data analytics experts to match call records with the mailing addresses of potential claimants in only three days. A court-ordered follow-up action required the law firm to scan and compare claimants' postcard responses and online data against the original database. The administrator estimated a savings of 60% over the prior firm which had been ineffective in organizing the multi-step project over two months. Advanced data analytics techniques and state-of-the-art document review software have revolutionized discovery and changed case outcomes. When used at the very start of litigation to identify key elements and timelines, they can streamline forensic accounting and litigation support activities and thus reduce overall case risks and costs.

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Douglas E. Johnston, Jr., is a C-Level executive with national experience in the core development of five 'best in class' companies in five different industries including Mergers & Acquisitions, Commercial Banking, Nationwide Commercial Real Estate, Consumer Products Manufacturing, and Media / Entertainment.

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