I miss House, MD. Yes, it was formulaic and highly sensationalized (med mal and employment lawyers in the Princeton, NJ area could make a nice living off the weekly goings-on at PPTH), but watching House and his dysfunctionally brilliant team investigate puzzling medical cases was great, literate fun.
If Gregory House were a litigator conducting a fact investigation, though, he’d be smart to use data analytics for eDiscovery (in addition to his beloved whiteboard). Analytics would help him reach critical insights faster, allowing him more time to focus on other priorities (like abusing his staff).
For example, let’s consider five classic House-isms:
1. “Everybody lies.”
Data tells a more complete story than people usually do. Short of breaking into their homes (a regular occurrence on House), examining custodians’ email communications with visualized analytics may be the best source for information. By cross-referencing keyword and phrase searches with email connections, times, volumes, and domains, you can see the true patterns emerge: Who spoke to whom, about what, how often, and from where? As House says, “The eyes can mislead, the smile can lie, but the shoes always tell the truth.”
2. “Anomalies bug me.”
When patterns change, something may be amiss. Why did certain emails get sent to a Hotmail address instead of the usual work domain? Why was this particular individual excluded from so many communications that month? Analytics help you spot anomalies that, upon further investigation, may lead you to the facts that make or break your case theory. To quote the good doctor, “There’s nothing in this universe that can’t be explained. Eventually.”
3. “We’re missing something.”
Visualized timelines let you see the ebbs and flows of activity over adjustable periods of time. When levels drop suddenly, you may be looking at a gap in collection or production — whether inadvertent or intentional. If the gap is in your own collection, rectifying it now can save big problems later. If you discover a gap in a received production set, even in the absence of malfeasance, you may be able to leverage the human error for negotiations. As House says, “Occam’s Razor: the simplest explanation is almost always somebody screwed up.”
4. “There’s no I in ‘team.’ There is a me, though, if you jumble it up.”
Sometimes you have to look at words differently to find what you seek. Traditional keyword search yields only specific instances of words (Tip: when analyzing employee emails for FCPA liability, don’t expect to find the word ‘bribery’). Phrase extraction goes a significant step further, showing useful word combinations you may not have thought to try. Advanced analytics go further still by looking at the statistical interrelationships among the words across an entire data set. This is why concept browsing and Predictive Coding can bring valuable documents to your attention even if they contain none of the words you’d thought to search for. As House would put it, “Cool.”
5. “I was wrong.” See also: “It’s never Lupus.” (Eventually, it was.)
Every House episode involves a series of diagnostic errors until (four commercial breaks later) House has an epiphany that saves the day – and the patient. Of course, it would be boring if House got it right in the first few minutes and we never got to see a treatment go horribly wrong, but real life lawyers don’t like being surprised late in a review by a document that undermines their case theory. Prioritizing your review with analytics helps ensure the important documents surface earlier, so you can correct a misstep while there’s still time and use the insight to re-frame the rest of your review. To quote our anti-hero: “Mistakes are as serious as the results they cause.”
Analytics help attorneys have their epiphanies sooner, so they can move on from the document review stage of eDiscovery to their ultimate goal: solving their clients’ problems. As House would say, “Welcome to the end of the thought process.”
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