A few weeks ago, I was lucky enough to meet with some senior in-house counsel from a Fortune 10 company. We were discussing data and the powerful ways analytics can be used in litigation. One of the attorneys appeared somewhat dismayed, saying that while analytics are amazing and she really wanted to make use of the technology, rarely did any of her cases contain anything other than emails and documents. One of her colleagues asked, “Aren’t you working on the matter?” She was. Her colleague replied, “I used to work in that division; have you considered the following?” and then proceeded to list about a dozen different data sources that were present – many of which were good candidates for analytics.
This is a common scenario. There is no doubt that good data can shed factual light on litigation or investigations. And clear facts allow attorneys to focus on arguing the law. However, attorneys usually aren’t aware of all of the types of data available, or they may be hesitant to embrace them. Data looks complex, time consuming and, more importantly, expensive. It doesn’t have to be that way. When looking at data sets independently, it’s easy to overestimate the complexity and underestimate the power of combining them. With the right tools, skills and people, the data’s inherent value can be had for relatively little cost and effort.
Let’s look at an example from a wage and labor litigation that iDS recently worked on. Time-reporting data was of interest, with the plaintiff alleging a lack of compensation for off-the-clock work performed in the mornings while in the office. The data indicated the hours the employee had been compensated for but gave little insight into the legitimicy of the allegations. Incorporating network login data into the analysis revealed interesting, and relevant, patterns of behavior. The majority of the time in question, he had already been on the clock and he had started being paid when he began working – i.e. when he logged into the network.
The story became more compelling when building access-card data was added and the truth started to unfold. The data sets taken together clearly showed that the employee usually entered the building at a certain time, clocked in a few minutes later, and then finally logged onto the network. The combined data verified the order of, and time lapse between, each action, which proved critical to defense arguments. This narrative could easily be related to a judge, a jury or, as in this instance, to plaintiff’s counsel, who has little desire to pursue, and fund, a lawsuit that won’t stand on the facts.
While not used in the previous case, GPS data is another often overlooked, yet exceptionally valuable, source of information. Add this data in relevant cases and the story becomes richer and deeper. But where does it come from and how do we get it?
In some instances, it comes from company-owned equipment, like company-issued vehicles or cell phones. In others, it may be in response to discovery requests for personal devices or subpoenas of ISPs and cell-phone carriers. The devices we carry, wear or use track and record our location constantly, reporting that data to multiple companies like Google, Waze, Uber, Apple, etc. In a recent case, we convinced the court that personal cell phone data was of paramount importance. Despite opposing counsel’s arguments about privacy and overly burdensome discovery, the court agreed that the data could be informative and relevant, and it ordered the class members to produce it.
Data is everywhere. From corporate IT systems to smartphones to fitness trackers and other mobile devices, we are capturing, storing and reporting on all aspects of our lives and behavior. Companies like Google, Apple, Amazon and Microsoft use this data to predict behavior and target advertising, but in the world of litigation that same data accurately retells the past. Presenting the results of good data analysis in court effectively removes questions of fact. Join me throughout 2017 as we explore the rapidly expanding data universe and learn more about how data can help you with litigation and investigations.
Published January 31, 2017.