Big Data Yields Big Results: Marshal the facts, tell a compelling story, and build a winning case

Wednesday, May 4, 2016 - 15:31
Businesses are required to analyze and preserve more and more data as litigation unfolds. Longtime legal technology specialists Charles Platt and Donald W. Myers are in the trenches with hundreds of millions of data points across multiple systems and networks. Here they explain how big data is reshaping the litigation landscape. Their remarks have been edited for length and style.


MCC: Please give our readers a brief overview of your careers in the legal technology space.


Myers: I started out as a commercial litigator, where I found myself handling a fair amount of trade-secret work. Around 2004, I realized that the bulk of what we were dealing with in our cases was related to electronic discovery issues, forensic imaging, email, databases and those sorts of things. My practice continued to include a fair amount of time focused on e-discovery, and about four years ago it became my exclusive focus.


Platt: I started out in IT, consulting on database development for large corporations and on government contracts. I had been working with a gentleman who eventually went to work doing litigation support, forensics and investigations. He called me up and said, “This is exactly what you would love to do. You need to come join us.” So about 14 years ago, I switched over and started working in forensics, litigation support, investigations and expert support. Since then, I have worked on all sorts of different matters, including structured data, cybersecurity incident response and large litigation, all using data forensics and analytics to help understand and explain the facts of the case.


MCC: There’s a lot of discussion about big data and data analytics in litigation and other areas. Can you tell us briefly what those topics mean to you?


Platt: Big data to me is pretty much what it sounds like. It’s a lot of information being collected from many sources – Fitbits, iPhones, desktop and laptop computers, tablets and all sorts of devices that we use to stay connected – for huge numbers of individuals. Even our lightbulbs now have Wi-Fi connections and transmit data. Storage is so cheap that we’re storing exabytes of information. The trick isn’t storing the data, it’s the data analytics side. How do we make sense of the information that’s relevant to what we want? I’ve got 100,000,000 records about an individual’s transactions, locations, etc. How do I take that data and present it in a way that someone – not a computer, but a person – can review and actually understand it and make decisions based on it?


Myers: The amount of information out there is alarming, and it’s about things and being kept in ways you would never imagine in your wildest dreams. I’m thinking: How will we get it? How will we analyze it? What can we do with it to help our clients and case teams? Charlie hit the nail on the head. There is just so much information out there in so many devices and networks, and touching on so many other things – computer systems, wireless networks – what can we do to marshal that information and use it in a way that’s going to help our case and our clients?


MCC: How do you identify what data is available and also relevant to the case at hand?


Myers: The first thing we need to do is understand our client’s technology. That’s true even if it’s a case that doesn’t involve big data. If we have a case where big data is involved, it’s even more important. We’ve got to get in there to talk with the IT folks. We’ve got to gain an understanding of where they keep the data, what they use it for, what’s involved in accessing it. How long do they hold it? How frequently do they purge, and at what points in time? Once we get our arms around it, we can start to make decisions and determine what potentially could be relevant to the case.


Platt: Communication with the IT staff is critical. It’s a human approach. We’re talking to people and trying to understand their data. Ideally, we’re having an open conversation. The difficulty is that a lot of the time, we can end up talking past each other. For example, we’ve asked specifically for “email from your email archive” and then had IT come back wondering why nobody ever asked for the backup archive. “Why didn’t you tell us there was a backup archive?” “Well, no one asked.”

The quality of the conversation is crucial. We’re not giving orders or making uninformed demands, we’re just having a talk. “What type of email do you have? Where do you keep it? Do you have archives? What kind of archives? Over the past X years, have those archives changed? Has that information been moved? Have you switched service providers?” Asking questions like those is critical.


Myers: When we’re having these conversations, it’s important to remember that they’re using those systems for one thing – to track financial information or the hours that employees work – and we probably need the information for something different. We’ve got to make sure that we’re speaking the same language, because we’re probably asking IT for something that has nothing to do with their typical use of that information.


Platt: Little things can make a big difference. “Oh, you wanted all the data. I thought you just wanted the data we were preserving specifically for this. We’ve got other data that goes back another three years.” Being clear as to what you’re looking for and why goes a long way in getting you where you need to go.


MCC: How do you and your teams determine what data needs to be analyzed and what does not? What are the risks associated with these determinations, and how do you mitigate them?


Myers: Sometimes it’s very easy to figure out what type of data and what types of systems may be relevant to a given case. The challenge – and Charlie and I have dealt with this a lot recently – is when you start learning about systems that, on their face, don’t appear to be relevant to your matter. Then you start to learn a little bit more about the systems and you realize they’re tracking information that could be highly relevant to the matter at hand. Walking in, you’re going to know there are certain systems you definitely need to learn about and that are going to be relevant. But you’ve got to poke around a bit to understand other systems that may have information that nobody knows about, because it’s being used for something completely different and yet could be very helpful.


Platt: One other thing that can help is open conversations with opposing counsel. Ask them, “What are we looking for? What are we really trying to get to?” Meet and confer in a spirit of cooperation regarding what data is relevant and what’s not. That type of communication is being encouraged more and more, especially when we’re talking about risk associated with data. As long as we’re being open about what data we have, that can go a long way toward closing some of the risks. The other side is getting a good handle on what data is out there, and if you think it is going to be relevant, you put some type of preservation around it. We can always go back later and analyze it.


MCC: How are the courts viewing big data and data analytics? Have you seen changes since the amendments to the federal rules took effect late last year?


Myers: I think that the courts’ views on big data are very new and untested in a lot of respects. What we’ve seen in terms of the most recent amendments, even the amendments going back to 2006, is the emphasis in the rules surrounding technology – understanding it, working with your opponents to understand it and cooperate so we’re all on the same page and talking about it. If you’re not trying to cooperate about big data, nobody wins. I think that’s how the rules fit into this. There’s too much information and too much time and money that will be wasted if we don’t work together.


Platt: One trend we’ve been seeing in matters with big data is that they often never get to the court. We’ve had a few product liability cases where we’ve basically come back with data analytics that show a fairly clear picture of no case. From opposing counsel’s viewpoint, it’s going to cost a lot of time, effort and money, and they’re not going to get anywhere because of what the data can show. It’s less and less a question of the facts of the matter – we can tell you what the facts are – and more a matter of the merits. We’re willing to go to court, but what do they think now that we’ve shown you what the data says?


MCC: That leads to our next question. Big data is profoundly changing our lives generally. How do you think this will change litigation specifically?


Myers: Charlie keeps saying this, and I’m believing him more and more: As there is more and more data out there, there are going to be fewer and fewer questions of fact, such as whether a car was in a certain place at a certain time. Though I think there will always be some, if there’s data around it, you may be able to remove many of those questions completely.


Platt: Things we’re not even considering today are going to have an impact and increase our ability to put together a compelling story. Even as a technologist, I wonder why I would want my tea kettle to connect to the Internet. Somebody had a reason, and now the world knows when I’m boiling water. These data points start to compound. Maybe my tea kettle alone says it was on at 10 a.m. on the 5th. I could argue that somebody else was in my office at that time. Guess what: All the lights in my office were turned on at the same time. My iPhone says I was in that office. My Fitbit says I just walked up three flights of stairs – and my office is on the third floor. Once you begin compounding all of this data, it starts to tell a very compelling story.


MCC: Do you have any specific examples of using big data successfully in litigation?


Platt: I had mentioned a product liability case where a plaintiff had brought a suit against one of our clients. Their argument was that they were harmed by a product that they purchased at our client’s store. They didn’t have a receipt, but they did have photographs of the product and several eyewitness affidavits stating that this product was purchased at this store sometime within a specific two- to three-week period. After getting the product and model number from the photos, we went through all of the historical sales records, shipping records and manufacturing purchase orders for products that fit the model number and the product’s description. We were able to show fairly clearly that they did not purchase that product from our client’s store at the time they said they did. In fact, our client had stopped selling it about a year and a half previously. They did sell a product in the store that month that was similar, and may have appeared to these people to have been the product in question, but it wasn’t the product they brought the liability claim on. That data clearly showed that the product in question must have been purchased somewhere else.


Myers: One area that gets me is the amount of GPS data that’s out there – the ability to tell not where the person was, per se, but where their car was. Then you can take the GPS data and bring in cell-phone information. You can start lining up what tower somebody was at when they were making calls and sending text messages. You can start to tell a pretty good story about what somebody did all day, including where they were.


MCC: Are there any specific rules or concerns about big data and attorney responsibilities? Changes to the ethics rules? Anything we should be aware of?


Myers: Attorneys have always had a duty to provide competent representation. One of the changes we’ve seen in the ethics rules over the past few years is that some state bar associations have said that in order to be competent, you need to understand technology and how it affects the practice of law. Now that so much litigation is moving into big data, I think to be competent when you represent your client, you have to understand technology, and not just the technology of how our clients are using big data, but how big data can impact a case in our representation of our clients.


Platt: As an expert, I think my ethical compass tells me I have a duty to tell you what the data says, and we go from there. I don’t hide data. I don’t make data up. I present data. I analyze data. I create the ability to view the data in a way that makes sense. I present you with the information, and then it’s your decision as an attorney how to use that. I’m not here to manufacture information or do anything other than present to you what the data tells us.


MCC: What are the risks of not being aware of big data and data analytics?


Platt: The biggest risk of not being aware is that opposing counsel is aware. You will either be aware of it ahead of time, or become aware of it too late and find yourself trying to catch up.


Myers: The scary part is you might be missing out on an entire aspect of the case. You might be missing out on the answer in the case. Charlie mentioned a product liability matter in which big data made that matter go away very quickly because they could prove that they didn’t sell that product at that time. You may be passing up an opportunity to help your client and the case.


Platt: You can also learn up front that you have a problem – that opposing counsel has a pretty good case. Maybe it’s time, before they realize how good a case they have, to start talking.