Data Use in Complex Civil Litigation

Data is the next frontier in just about everything. Every tech company claims to be a data company (or an AI company, which is basically the same thing these days), and for good reason. Data has become extremely powerful thanks to artificial intelligence’s ability to comb through huge amounts of information. That information contains our spending habits, our driving behavior, our responses to brands, and so much more.

It’s no surprise that data aggregation and interpretation has come to the legal market. The truth is that it has been here for years. Insurance companies have been sharing lawsuit data for at least a decade. Now that same data is being mined for more useful information. We don’t only consider how much cases are worth but also information on individual lawyers and judges. There is no doubt that this information will be used by all law firms in the near future.

Data Available to Law Firms Today

There are three areas where data is being used today: case results, attorney profiles, and judge profiles.

The compilation of case results has been happening for decades, but with help from artificial intelligence more cases can be collected and nuanced data can be teased out of the information. No longer are we only concerned with the final amount paid to a plaintiff, now we can identify specifics about the case such as location, medical damages, and the nature of the injury. We can separate a soft tissue case in Kane County from a broken ankle in Cook County.

Some companies claim to be able to rate attorneys based on past performance. Premonition claims to be able to compare attorneys based on win rates, hourly cost, and the average length of time a case is open. Based on those metrics, Premonition ranks lawyers from best to worst. This is primarily offered to insurance companies and in-house counsel, both of which are in the business of hiring defense attorneys.

Premonition also claims to have profiles for judges. This is not unique to Premonition; many companies claim to have data on judges. The theory is that with enough data you can predict what a judge will do on a specific motion. This data is largely limited to federal judges, where the case details are more available. I have yet to see a company offer similar information on state court judges.

How Useful is this Data?

Information on the valuation of cases is very useful, and my guess is that virtually every insurance company uses that form of data on a regular basis. The data is limited somewhat, however, by the availability of information. For example, much more data is available in large urban areas than in rural areas, and the data doesn’t always apply across geographical regions. Chicago juries award more money than suburban juries, and there are perhaps 100 times more cases in Chicago than Aurora (Aurora is the second biggest city in Illinois but has 1/10th the population of Chicago). The information gained by analyzing Chicago juries will not be applicable to a case in Aurora.

The information supposedly gathered on attorneys is even less useful, in my opinion. They claim to rank lawyers based on win rate, hourly fees, and length of time a case is open. The lawyer has virtually no control over any of those factors. I’m not even sure how a win rate is calculated. Civil cases are never won or lost. Usually, a win is any verdict higher than you were expecting (or lower if you are defense counsel). There are very few cases that return a $0 verdict. Frankly, I think there are plenty of cases where both lawyers win.

Lawyers also have little control over the facts of the case, which are hugely determinative of the end result. Did the defendant rear-end the plaintiff? Pretty hard for the defense attorney to win that case. Maybe he or she can reduce the award, but a complete win is out of the question.

Also, difficult clients frequently dictate whether a case even goes to trial. I will give an example from my career. I handled a divorce case many years ago that had maybe 10 issues for trial. Our client was slated to lose on virtually all of them. The guardian ad litem was completely against her, and the odds of success (however you define it) looked grim. The trial went extremely well. We actually won on 9 of the 10 issues. To the judge and every lawyer in the room, it was a resounding victory. However, my client considered it a loss because we did not win on the one issue (btw, that issue was ranked at “not important” by our client prior to trial). So was that a win or a loss?

Similarly, an attorney has little control over hourly fees. Our market generally defines fees. If you charged drastically less than the competition, clients would be suspect of your abilities. And fees tend to follow experience. A brand-new attorney will have a lower rate than a seasoned litigator (and perhaps a better win rate, too, given the small number of cases). If you rank attorneys by the rate they charge, you will likely hire attorneys from smaller towns with less experience. Those are odd criteria with which to make a decision.

Lastly, lawyers have very little control over the length of time a case is open. There can be delays for all sorts of reasons: difficult clients, service issues, troublesome witnesses, complicated issues, etc. Some lawyers are slow, don’t get me wrong, and they are a headache to deal with, but to rank attorneys by the length of case misses the nuances of handling complex litigation. The lawyer is merely one factor in the length of time a case requires.

Judge profiles are potentially more useful but probably not for specific motions. Does this judge grant a lot of motions for summary judgment? A foundational question must be how many motions for summary judgment does he or she hear in a year. The higher the number of cases, the more useful the data for sure. This data will be more useful for judges in large counties, who handle many cases. A judge in a rural county might only hear 10 motions for summary judgment a year. With a data set that small, outliers are more likely to impact the data, making the information less useful.

The Data Will Become More Useful

We are just at the beginning of this trend in data use. As AI gets more sophisticated and courts store more data online, the information gains will be great. It’s not hard to imagine a world where every decision of a judge is recorded somewhere – in fact, that is already happening. The question is when will our data mining be effective enough to catalog everything. Advances in optical character recognition and natural language processing will usher in a new era of data gathering because machines will be able to understand the handwritten orders found in most courts. More importantly, the data will be organized in a way that is more useful to law firms and insurance companies.

What are the Implications of Better Data Sets?

I had a negotiations professor in law school that had an interesting experiment. He sent half of the class outside and then asked the remaining students two questions:

  1. Is the population of Pakistan greater or less than 90 million?
  2. What is the population of Pakistan?

Then he asked the second set of students, whom he had sent into the hall, two different questions:

  1. Is the population of Pakistan greater or less than 170 million?
  2. What is the population of Pakistan?

The first group of students predictably guessed that the population of Pakistan was around 90 million, and the second group put the number around 170 million. The population of Pakistan is 212 million according to the World Bank, but that was not the point of the exercise. The professor’s point was that the first mover in a negotiation frequently dictates the general area of the negotiation.

But this applies to big data sets, as well. If two attorneys have access to that same data which puts the value of their case between $30,000 and $50,000, the case will invariably settle around those numbers. This is especially true if the data set is large and trustworthy. There is nothing wrong with this, but isn’t the data influencing the settlement rather than the settlement influencing the data? Won’t the data become even more standardized? Isn’t this the tail wagging the dog?

Believe it or not, this already happens in workers’ compensation law. Every settlement or decision is recorded and the attorneys spend their time arguing whether the current case is worse or better than comparative injuries from other cases. This will start to become the norm in civil cases, as well.

In fact, the only arguments made by counsel might be to move the case from one data set to another. For example, I might argue that the case should be considered a broken leg rather than a broken ankle because a broken leg is worth more according to the data.

These issues will occur. The only question is when they will become mainstream. The other natural issue will become: what is the role of attorneys in this data-driven process? That’s the question that should make every civil litigation attorney sit bolt upright in the middle of the night.

Video Game Streaming Bans

I don’t frequently write about video games (in fact, this may be my first or maybe second time), but I am known to dabble in games from time-to-time. In any case, I recently heard the story of DrDisRespect and his recent ban from Twitch.

DrDisRespect refers to himself as the “most ruthless competitor in game history” and is known for streaming games like Fortnite, PUBG, and Call of Duty. He earned a reported $1.8 million from his 32,000 subscribers in 2019 per

Yeah, $1.8 million. By playing video games.

He was banned by Twitch recently for no discernible reason. I’m not going to go into the details of the ban, but theScore esports had a nice video summing it up, here.

These bans happen all the time. Many fans complain that the bans are not always consistent, and Twitch’s policies aren’t very well defined. Ill-defined policies would not normally be a problem for your average gamer who plays for fun, but these streamers play for serious money. Given the money at stake, clear policies and fair application are a must for Twitch, but you’ll find that both are lacking.

Twitch Guidelines

Twitch publishes its guidelines here. They outlaw pretty straightforward stuff like breaking the law, violence, hateful conduct (including hate speech), and nudity. However, the application of these guidelines lacks clear guidance to their users.

Nudity seems obvious, but it’s anything but clear. For example, a Brazilian streamer named Gabriel “Gabepeixe” Baptista was banned in September 2019, because a Pink Floyd poster was displayed on one of his streams. The poster was from Pink Floyd’s “Back Catalogue” album cover, which depicted nude women (though, in a reasonably tasteful way, showing only their backs, hence “Back Catalogue”). He was banned for three days.

Compare that to a popular streamer named Kaitlyn “Amouranth” Siragusa, who on September 8, 2019, had a “wardrobe malfunction” which revealed actual nudity. She was banned for three days. She has been known to skate the line of sexual conduct in the past and has been banned two more times in 2020.

Identical bans for clearly non-identical behavior. I’m not explicitly taking sides here. Frankly, I don’t care what people choose to do online (within some reason, I guess), but I think it’s interesting that the punishment appears to be the same regardless of the actual offense.

Further, Twitch appears to have a “three-strike rule” in that if you get three bans, your ban becomes permanent. But many big-name streamers bypass this rule. For example, Amouranth was banned three times, the last time was on May 10, 2020. But her stream was reinstated in less than 24 hours.

Other streamers, like DrDisRespect, don’t seem as lucky since his latest ban appears to be permanent.

Why Does This Matter

These bans involve streamers who make thousands, and sometimes millions, of dollars. It seems to me that clarity is very important when you’re dealing with people’s livelihoods. I don’t know the exact cost of these bans, and, in fact, some streamers may net subscribers from their bans. It seems like bans have a big effect on the economic ecosystem that exists on a platform like Twitch. That ecosystem is complicated and there are winners and losers, but you would think some clarity is necessary for long term health. How will a platform like Twitch continue to attract top-tier talent when that talent can be punished unfairly?

This also highlights the perils of making money on someone else’s platform. Twitch owns the court, and it can take its ball and go home whenever it pleases. Twitch and other social media outlets are private companies, they can police them any way they please. The trouble is that these streamers don’t really have any other choice. It’s not like they can drive as much traffic to their own site. But then they have to play by Twitch’s rules, regardless of how unclear they may be.

The streamers do have one advantage, though. Once they are popular, they can leave and take a ton of viewers (and money) with them.

The last thought I had was that Twitch (and other social media giants) are responsible for policing their own users, the same users that make them money. Ninja, the Fortnite streamer, made a reported $5.4 million from streaming in 2019. Imagine how much Twitch made on him. Now let’s assume he did something to get banned. I imagine that Twitch has a lot of incentive to reinstate him regardless of his actions. I’d say they have millions of reasons to keep him around.

It’s almost like the system maintains room for Twitch to make subjective, final decisions. By publishing guidelines that are not explicit, Twitch can basically do what it wants. That means it can protect the streamers it wants to protect and punish those it doesn’t value.

The Effect of COVID on Small Business

With case numbers rising across numerous states in the US, many have started to question what the long-term effects of COVID will be on small businesses. Here in Illinois, small businesses have just now started to partially open. If we have a second spike, as many experts are predicting and the data is suggesting, how will that affect these businesses that have already been hit?

Small Business Data

Reliable data on small business is hard to come by. I don’t know of any groups collecting and analyzing data in real-time. The data that is available is frequently not as useful as it appears. For example, some sources list small businesses as any business with less than 500 employees. That’s obviously far from small.

There is plenty of anecdotal evidence about what businesses are going through. As a manager of a firm that primarily works with small businesses, I have many stories from clients about their operational health. But that data is very specific to the company’s location and area of work. Data that covers broad swaths of American small business is tricky to find.

However, the US Chamber of Commerce recently published a poll of small businesses that appears to have good data backing it up. I have no idea what the US Chamber of Commerce is. ‘Chamber of Commerce’ is usually a title for a local community of businesses, it’s not a common title for a national organization. Given that, I believe the US Chamber of Commerce is a private company or an association of companies. In any case, you can see their original report here.

Their data was interesting. They reported that 41% of small businesses are fully open and 38% are partially open. About 19% of small businesses are temporarily closed, and 1% are permanently closed. Who is the 1% that took the survey despite their business being closed? I suspect that number may be underrepresented.

The report stated that 43% of business owners are ‘very concerned’ about the impact of COVID, which was down from 53% in May. Also, 53% of small businesses reported good overall health. In fact, 24% of business owners went so far as to say that the US economy was ‘good.’

This is touted by the article as a good sign, but I suggest that the reverse of that stat is that 76% of small businesses reported that the US economy was not good. And, by the way, economists would agree. The stock market may be doing well, but the market is not the only indication of a stable, healthy economy.

Another fascinating stat, 50% of business owners expect next year’s revenues to increase and 19% expect them to decrease. These numbers are slightly more positive than in May, but consider what is being said. Fifty percent think revenue in 2021 will increase. Notice, we aren’t talking about 2020. Given how bad 2020 has been for small business, how is it that 100% don’t think next year will be better? I find that stat concerning.

The fact is that these stats are not positive. Most business owners are legitimately concerned about this year and next, and that is without a second spike of cases occurring this fall (or right now).

Businesses Were Struggling Before COVID

NBC recently reported that a study involving 1.4 million small urban businesses done by JPMorgan Chase Institute found that nearly 29% of businesses were not profitable. That was as of September 2019. That study also found that nearly half of those businesses surveyed had no more than two weeks of cash on hand (article).

The fact is that many small businesses were failing before COVID hit, the pandemic simply sped up the process.

Now, even in the wake of the stay-at-home orders being lifted, many businesses don’t believe they can afford to carry on with normal operations. According to a LendingTree survey of 1,260 small businesses, approximately half of small businesses fear that they can’t reopen.

I have been saying this for weeks. The economy is not a light switch. Flipping it on does not guarantee demand for services. Businesses cannot operate at 50% or 25%, they don’t have the margins to survive such a downturn. Even if the stay-at-home orders are lifted, these businesses may not make it.

Business May Shift from Small Businesses to Larger Businesses

An article by The Washington Post considered what they called ‘micro-firms,’ or businesses with fewer than 10 employees (article). They interviewed Mark Zandi, chief economist for Moody’s Analytics, and he said that he wouldn’t be surprised if over 1 million micro-firms ultimately fail due to COVID. Given that there are approximately 30 million small businesses in the US, that would be about 3% of all small businesses. That’s about 30,000 businesses here in Illinois.

But something else to consider, those small businesses frequently transact with other small businesses. That means that when some go under there may be ripples in the small business community.

Large businesses will have a better chance at survival because they are more likely to have cash reserves and be able to borrow money. In fact, the Federal Reserve has made borrowing money easier than ever. Therefore, we may see a shift in our economy away from small businesses and towards larger businesses. I don’t know what that means for customers, but as a small business owner, I believe the movement away from small, local business would be a tremendous loss.

What Happens When We See a Second Spike in COVID?

I don’t see how the numbers could get better if we see a second spike. Businesses that are close to shuttering would almost certainly close. Continued unemployment would mean less demand for products and services offered by these small businesses, which could lead to even more closures.

Business will come back, that’s the beauty of the market, but this current crop of small businesses may see extremely high attrition rates. Time will tell how these closures will ripple out. Will we see impacts on commercial landlords? What about tax revenues?

I expect that this gets much worse before it gets better.