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Brad Jenkins

Brad Jenkins, President and CEO of CloudNine Discovery, has over 20 years of experience leading customer focused companies in the litigation support arena. Brad has authored many articles on litigation support issues, and has spoken before national audiences on document management practices and solutions.

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Doug Austin, Professional Services Manager for CloudNine Discovery, has over 20 years experience providing legal technology consulting and technical project management services to numerous commercial and government clients. Doug has also authored several articles on eDiscovery best practices.

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Don Philbin of Picture It Settled – eDiscovery Trends

February 18, 2013

By Doug Austin

 

This is the fourth 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 Don Philbin.  Don is a nationally recognized attorney-mediator and is President and founder of Picture It Settled®, a predictive analytics tool for negotiation.  Holding both a law degree and an MBA, Don mediates individual and class matters, and he teaches courses at Pepperdine Law’s Straus Institute for Dispute Resolution.  He was one of three Texas mediators listed in the 2011 inaugural edition of The International Who’s Who of Commercial Mediation, and he was named the 2011 Outstanding Lawyer in Mediation by the San Antonio Business Journal.   He is an elected fellow of the International Academy of Mediators and the American Academy of Civil Trial Mediators.

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

This is my first LegalTech and I was kind of “bug eyed” about it.  It’s a big show.  Everyone that I’ve talked to tells me this year’s show is bigger than it has been in four years and I rode in the elevator with some of the ALM execs this morning and they were happy to see the increased attendance.  As for some of the highlights of the show so far, I went to yesterday’s keynote and enjoyed hearing Ted Olsen’s speech – he is always interesting.  I also went to a couple of eDiscovery forums that were mainly focused on housing the data and security concerns for the data.  I did walk through the exhibit hall to check out the variety of vendors and clearly most of them appear to be eDiscovery related, though there were some telecom and conferencing vendors.

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 may not the best one to ask about that since I am not a vendor, but it looks to me like the “next big thing” would be adoption of the predictive coding technology at this point.  It seems as though the court opinions that have come through have validated the technology as acceptable.  A survey on Twitter at one of the sessions found that 48% of respondents have been involved in predictive coding or technology assisted review in the last year and one of the commentators at the session said “this is the bubble”.  So, it seems as though the development for the next year is how far it gets outside “the bubble” in terms of adoption.

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

We’re here to let people know about Picture It Settled, which is a predictive analytics tool in its own right – for the settlement negotiation process.  To support this process, we have collected data for about ten thousand cases – not just the outcomes, but also the incremental moves that people make in negotiation.  Some cases have as few as two or three rounds while others have many more – one case has at least fifty four pain staking rounds of negotiation.  We measure two dimensions of data: the dollar concession for each offer (i.e., the dollar amount each negotiating party moves from one offer to the next) and the elapsed time between the offers.  We know the right number at the wrong time is the wrong number.  People have to get used to the deal and need ample time to ensure that they are getting everything they possibly can from the other side.  Also, negotiations always expand to fit the space available.  Whether it’s deal making in Washington regarding the fiscal cliff, or settlement negotiations for a case, negotiating parties tend to go “right up to the buzzer” to make the deal.

We find that an all-day negotiation will typically take all day, so the question is “how do you pace yourself so that you can get the best deal?”  We have reverse engineered “splines” that separate the settled cases from the cases that ended in impasse. From that, we studied how successful negotiators “let out the string” in a way that kept their opponent engaged and cooperative instead of going competitive and “slamming their briefcase.” So we have developed a planning curve from the successful negotiations that can be applied to the current round.

Also, cases vary in value depending on the venue where they are filed and also by claim type.  For example, people negotiate personal injury cases differently than construction cases.  We collect the demographic data, ask whether there is insurance and the financial size of the negotiating parties.  Each of us have different risk preferences and tolerances. The scenario planning piece enables the lawyers to do a “high/medium/low/zero” assessment of the case, estimating their best case, worst case and in-between scenario. By attaching probabilities to those assessments, scenarios start to develop.  They use that tool to frame a valuation for the case.

Assuming you are going to negotiate the case and, for example, that the weighted average of the scenarios are $1.6 million, the software will plot the curve and suggest to you what you might consider in terms of offers to get from the best case scenario of perhaps $4 million if you are the plaintiff down to $1.9 million or whatever you assess to be your best alternative to a negotiated deal.  The inputs are lawyer driven, requiring their expertise.  So, this is certainly not removing the lawyers from the negotiation process; instead, it is just giving them a “scope on their gun” to “improve their aim” in negotiations.

The third component of the application is the most powerful. Based on early offers, the Settlement Prophet™ will make forecasts resembling “hurricane” projections, which take the data points on each side and project those out as many as fifth rounds to get a sense of where the opposing party might be headed. The darkest intersect point of the hurricane-type cones is the best estimate of where negotiations are headed. Armed with such data, a user can make mid-course corrections.  It is truly a data driven approach to improving your shot in negotiations.

{Editor’s Note: Don provided a demo for me of the software at the show so the comments above reflect that.  For more information about Picture It Settled and to request your own demo, click here.}

Thanks, Don, 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.
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