Moneyball for law: picking the best fantasy league legal team

Improving the likelihood of success

Our guest for this blog post, Mark Verhagen, is a PhD candidate at Nuffield College at Oxford (https://www.sociology.ox.ac.uk/people/mark-verhagen). In addition to his PhD, Mark also operates a machine learning consultancy focusing on optimizing people and talent.

We met in late 2020 on an Oxford University Law Facility Zoom presentations, and struck up a conversation about combining the use of computer vision and natural language processing to analyze legal documents. We decided we had to find a project to tackle together. While we waited for the right project, we decided to toy with the questions – how do we optimize the likely performance of legal teams, and therefore how do we improve the likelihood of success of legal work?

Much of legal technology seems to be focused on solutions that seem to “robotize the lawyer”, but Mark and I want to use this blog post to explore what could happen if we apply technology and data science to the layers above the expert services, and “robotized” those layers?

In other words, what if we optimized:

  • team selection

  • information preparation

 

What if we “robotize” everything up to the point when the lawyer goes into a room with a client?


Picking the fantasy league legal team

There is no single “best legal team” for all matters. Each matter will require different expertise, personalities and tendencies.

Mark notes during our conversations that there is an emerging practice in the management consulting world where data is used to improve hiring and assembling a team in order to ensure “case success” (assuming we know what “case success” means).

Unlike management consulting, when lawyers are picking their team for transactions or litigation, partners at law firms typically pick their team based on:

  • who they know in their firm

  • who they have worked with in the past

  • who they know might have relevant industry experience

In other words, the process is based almost wholly on intuition or “gut feelings” of senior lawyers. While it is possible that some firms have adopted a data-driven approach to pick the best team for each piece of work, the majority of lawyers seem to select their team using subjective metrics, or, at least, based on imperfect information.

… I wonder, can we explore the question of “what if the whole management team of your law firm is replaced by robots?”

This is an optimization problem – how do we pick the best team for any piece of legal work?

If the management team is replaced by robots, what decisions would be made a robot management team? How would we design a “training problem” to ensure the robot management team makes the best decisions?


What stops us from immediate experimentation?

If we had data about lawyers, such as their skills, their strengths and weaknesses, and their experiences, then perhaps we can immediately conduct experiments… but unlike sports, vital statistics and information about lawyers are not widely available. Even where data is privately available, the data tend to be either self-reported or trapped in the minds of those people who are within two degrees of separation from a lawyer.

How do we optimize everything up to the point the lawyer picks up the work?

 

Since we do not have data, Mark and I discussed how we can theoretically address this optimization problem, assuming that we could access relevant data, such as:

  • education and training history for each lawyer

  • documents opened by each lawyer

  • hours billed by each lawyer

  • narration of work done by each lawyer

  • anonymized annual performance review scores for each lawyer


This is how we would pull together our heist crew

Watch Mark and I discuss how we might solve this optimization problem in our unscripted conversation here:

Transcript of conversation


(Note: transcript is automatically generated, and may contain misspellings and typographical errors)

00:00

welcome to another not so casual

00:02

conversation this time

00:03

um we're talking to mark verhagen from

00:06

oxford university

00:07

he is an expert in machine learning and

00:09

we're going to talk about this idea of

00:11

money ball for law mark we've been

00:14

talking for the last couple of months

00:15

and i'd love your synopsis of this

00:17

problem we're trying to solve

00:19

i would have to give a synopsis of the

00:20

problem we're trying to solve i think

00:22

it's

00:22

easiest to make it as concrete as

00:24

possible so

00:26

many people have been talking about

00:27

robotizing all kinds of

00:30

manual tasks usually relatively low cost

00:33

tests which are done at scale

00:36

but there are other places

00:39

where we can use artificial intelligence

00:40

or analytics to actually improve our

00:42

decision making or or

00:44

efficiency and so so let's let's picture

00:46

the following

00:47

scenario where instead of optimizing

00:50

a lawyer which is basically the high

00:52

frequency worker

00:53

but let's automate that which happens

00:56

above the lawyers or the management

00:57

layer the part

00:59

so let's let's imagine the following

01:00

situation which is

01:02

we have a case a concrete case which we

01:04

have to

01:05

echo with our firm and we need a team of

01:07

five people

01:08

and we have four already and we need to

01:10

pick the last one

01:12

so how do we do that how do we pick this

01:14

fifth person

01:16

what would be the optimal way to do this

01:18

what is the actual way we're doing it

01:19

right now and how can we move from the

01:21

actual way

01:22

if it's up ideal to the optimal way

01:25

so i think that's the that's the

01:26

question which is most feels most

01:28

intuitive to me

01:29

to try to answer so how do you do this

01:33

and in particular let's say we have

01:37

a sort of sphinx who you can ask a

01:40

question

01:41

right so let's say we have a 100 lawyers

01:45

and you can ask the sphinx a question to

01:47

which the swings gives an answer

01:49

and so what would it be if you would ask

01:51

these things

01:53

what will be the most precise question

01:55

we can ask

01:56

based on which we can pick up the phone

01:58

call that person or

02:00

whatever way we want to do it pick the

02:02

fifth person

02:03

and and what are what is the current way

02:06

we're doing it and how can we

02:08

incrementally improve this process

02:12

so i think that's the that's the that's

02:14

the question in a nutshell

02:15

i suppose and that's that's where all

02:18

the complexity starts of course

02:21

and for me i mean how are you how do you

02:23

think people do this right now

02:25

in law firms right now these sorts of

02:28

decisions about

02:29

what you or who you put on a team is

02:32

very

02:32

personality driven it's very experience

02:35

driven

02:36

a senior person in the team would say i

02:38

have worked with person a before

02:40

therefore i like person a and he or she

02:43

is going to join my team

02:46

rarely is there any statistical or

02:49

deeper data analysis that's done in this

02:52

selection

02:53

now more and more these days law firms

02:55

are thinking about capacity

02:57

this purely quantitative factor of who

03:00

has time to help out and therefore who

03:02

can we bring on

03:04

but it doesn't bring into account well

03:06

what's that person

03:07

good at what's that person's experience

03:10

what is

03:11

the relationship that person might have

03:13

had to the client on that matter

03:15

and all of these other variables which i

03:17

think play a greater role than simply

03:19

how many hours do you have free this

03:21

week

03:22

i mean if you care about uh the

03:25

performance

03:26

right if you only care about billing

03:27

hours then possibly not

03:29

well that's a strong assumption yeah

03:31

yeah

03:32

i mean it's one of the many reasons why

03:34

applications of ai in practice that they

03:36

feel because you don't take into account

03:38

the actual capacity constraints which

03:40

are there

03:40

so it's great that they are already

03:42

accounted for so there are only a

03:43

limited number of hours in here so i

03:46

think that's a very

03:47

important component but unfortunately

03:50

the way you describe it there's very

03:52

little optimization going on

03:54

within the self-constraint so law firms

03:57

suffer from the problem of they don't

03:59

really know where to

04:00

start and and you know you've you've got

04:03

this experience from the management

04:04

consulting space having

04:06

essentially not maybe not solved this

04:08

problem but um

04:09

having worked on solving this problem in

04:12

management consulting

04:13

so maybe i'll ask you how how is it done

04:15

in management consulting

04:17

the situation the status quo that you

04:18

described for law

04:20

is very applicable to management

04:22

consulting so capacity

04:25

and personal preferences and biases so

04:28

in that sense they're very similar

04:32

so let me describe

04:35

one of the added value or advantages of

04:38

working in management consulting from

04:39

the perspective of selecting teams and

04:41

composing teams

04:42

which is the fact that they are quite

04:44

rigid

04:45

in the way they collect information

04:47

about their individual consultants

04:50

how they perform along a variety of axes

04:53

basically

04:54

so you'll have a performance report

04:56

after every project it'll be filled up

04:58

by using the project manager

05:00

um you can relate this over time so

05:02

every three months you get a new one

05:03

and you obviously have a lot of data on

05:05

promotions which are very formalized etc

05:08

so in a way it's in the management

05:10

consulting it it

05:11

it almost fundamentally

05:14

boils down to a question of bias in

05:17

evaluation and i think in the legal

05:20

industry

05:21

what we suffer from is that there's a

05:23

lack of data

05:24

now i i know a very very few firms and

05:27

in fact i can't think of any

05:29

that does a post-mortem after every deal

05:32

at best you might have a quarterly

05:35

review of an employee's performance

05:37

generally speaking it's once a year and

05:40

so

05:42

those are the data points that people

05:44

have in terms

05:45

of assessment of the performance of

05:47

individuals

05:48

and that's a big span of time and

05:50

they're very infrequent little points

05:53

supposing that is true for all law firms

05:56

that there's only

05:57

annual reviews of lawyers what other

06:00

data points can we look at

06:02

to get that quality qualitative data on

06:04

performance

06:06

yeah now this is the this is the big the

06:09

big

06:09

big question um what to collect

06:12

and how to collect it in a consistent

06:15

and accurate way

06:16

let's assume there is a lawyer there is

06:19

a record

06:20

somewhere that um ranks lawyers out of

06:22

five stars

06:23

um and and that is in the database

06:26

somewhere so

06:30

i guess i would i would ask there would

06:32

be the naive naive way of doing this so

06:34

which

06:35

which person has the best rating uh but

06:37

i think

06:38

well an obvious qualification of this

06:41

approach would be well

06:43

a lot of things around this case are

06:44

already set in stone for example

06:46

the industry or the the general topic of

06:49

the case

06:50

so a more precise question would be

06:53

sphinx

06:55

from all individuals who have done maybe

06:57

at least 10 cases within this industry

07:00

who has the best performance who had the

07:02

most win rate it doesn't have to be the

07:04

same person as before right so you ask a

07:06

more specific question

07:08

which would lead should lead at least to

07:10

better performance because you would

07:11

have the person who's best in this

07:12

specific thing

07:13

right the question is then obviously

07:16

what are these cases which

07:17

levels do you specify because you can't

07:19

ask

07:20

two specific questions you just we won't

07:22

even even if we were perfect in

07:24

collecting everything you just won't

07:26

have

07:26

the volume the way you described it it

07:28

almost sounds like you're saying hey

07:30

pick the features that are most

07:31

meaningful first

07:33

um and and one of the things that i

07:36

think we're going to have trouble with

07:37

inside the legal industry is that those

07:39

features are not necessarily measured

07:42

and so what would work as proxies

07:45

for for those features and i can tell

07:48

you the data that is gathered by law

07:50

firms and it's gathered

07:51

with great stringency it's time um

07:55

everything is billable time and so you

07:58

have a lot of record

07:59

on what lawyers have done how they spent

08:01

their time and

08:03

generally they'll give a narrative

08:05

description of what they spent their

08:07

time doing

08:09

on the flip side of that is you can see

08:12

what documents

08:13

and what words were written during those

08:15

time periods or what words were read

08:17

during that time period and so without

08:21

this external qualitative

08:24

assessment by more senior partners you

08:27

do have

08:28

time record and documentary record

08:33

so then what would you do with those two

08:35

parcels of data

08:37

and what can we possibly what can we

08:39

possibly extrapolate

08:41

now i think i think this is a crucial

08:43

part this content content-based

08:45

predisposition so i think actually on

08:48

learning this it's

08:49

very interesting because management

08:51

consultants don't necessarily have this

08:54

finesse in the way that people actually

08:56

do their work so how many hours do they

08:58

spend on this part in that part and

08:59

what's the preference between it

09:01

so this is i think it's fascinating for

09:03

me new world that would open

09:05

so i've worked much more with for

09:07

example the traits and the personality

09:10

traits of individuals and how does a

09:11

team

09:12

of very dominant people together feel

09:16

even though every individual one seems

09:18

to be a high performer

09:20

but i think this is this is truly um

09:23

yeah i mean this is something which i

09:24

think the law scene might be

09:27

fairly unique in in a way that you can

09:28

actually go so precisely into the way a

09:31

person

09:31

does his or her job like yeah that's

09:34

fascinating yeah

09:36

yeah and i think it's not utilized at

09:38

the moment um

09:39

at least it's not utilized by anyone

09:41

i've spoken to

09:43

um so so i guess maybe i'll

09:46

turn the question around and go back to

09:48

this features id that we spoke about a

09:50

few minutes ago

09:51

which is if we were to have

09:54

the sphinx and the sphinx has all the

09:57

power in the universe

09:59

what do you think are the five up to

10:01

five

10:02

most meaningful features that you would

10:05

look for

10:05

in assembling a team in professional

10:08

services

10:11

you need a baseline familiarity with

10:14

what you're supposed to do

10:15

but i think most people would maybe

10:19

you need that one and after that in this

10:22

case

10:22

it's the other four team members hands

10:26

down i would say

10:26

it's the interaction which will be

10:28

generated

10:30

unless it's a type of business where you

10:32

can really

10:33

decompose the tasks at hand and everyone

10:35

works in a sort of

10:36

independent way but generally speaking

10:39

at least in the management consulting

10:40

sphere

10:41

i would say that the composition is most

10:44

leading so the energy that's created by

10:46

the interaction between individuals

10:49

which is not something which stands on

10:51

its own it's not the case that you can

10:53

always assemble the

10:54

five best people it's in the context of

10:57

the project which is going to be done so

10:58

the relationship to the client

11:00

etc um so it's just

11:03

it's more complicated than maybe maybe

11:06

this is first i would say that

11:08

the people plus the high level

11:11

context of the case so what is the

11:13

industry what is the type of work has to

11:15

be done

11:16

high pressure low pressure etc i think

11:19

that that will be the

11:21

key ones i would look at first from

11:24

[Music]

11:25

two aspects one the way that legal work

11:28

is compartmentalized and broken out

11:32

you do find in a lot of cases there are

11:35

very clear dividing lines

11:37

so i'll give you an example from a

11:39

transaction where

11:41

if you're doing a merger and acquisition

11:44

you would have a corporate lawyer or

11:46

corporate team leading this transaction

11:49

but then the specific issues that arise

11:51

like employees and tax

11:53

they go to specialists and they do

11:55

siloed work

11:57

and it doesn't really matter about

11:58

personalities in that case

12:01

but what does matter is your core

12:05

emanating your corporate associates and

12:07

partners

12:08

they have to work well together and they

12:11

have to work well

12:12

with the client which

12:15

is a really difficult to measure

12:19

thing and i think this is why

12:22

at the moment the current practices

12:24

partners will go i like

12:25

person a i like to work with them

12:27

therefore we're going to have them on

12:28

the team

12:30

even if they're not the most skilled

12:31

person now i can definitely see that and

12:34

i can see

12:34

it's also i mean we always deride the

12:37

strategy in a way

12:38

that just seems like the the most sort

12:41

of stupid thing to do but

12:42

i i actually personally think that it's

12:44

a pretty good heuristic

12:46

in a limited information setting so that

12:49

that's a lot of complexity

12:52

to take into account definitely it's a

12:54

web yeah yeah

12:56

indeed but i mean if if you if you're

12:58

able to define the axes

13:00

and make a matrix and you can actually

13:02

fit every client or every aspect of the

13:04

case into it

13:07

you at least go some way into

13:10

determining the context of the case so

13:11

with context i mean the things you

13:13

cannot change

13:14

it's the people you have to work with

13:16

the client that's the

13:18

case in content-wise duration even

13:22

whatever so i think these things have to

13:24

be set in stone

13:26

because it's so if the variation within

13:29

between cases is large and this is the

13:30

most important one to actually find

13:32

some way to get a grasp on it somewhere

13:34

to categorize it

13:36

so i think intuitively speaking that

13:38

will be one of the ways to

13:40

to make make progress to find

13:42

classification and it can be

13:44

i mean we don't have to be perfect from

13:47

the start we just have to be able to

13:48

start

13:50

looking at so let's say a table of the

13:53

following form so

13:55

every row is a type of case and we have

13:58

maybe five

13:59

which is way too few but let's say

14:02

we start somewhere right exactly exactly

14:05

yep and then we have four types of

14:07

so five like a rows and four types of

14:11

let's say four types of lawyers in this

14:14

case we don't we neglect the interaction

14:17

between the team

14:17

etc and we just want to see performance

14:20

you want to see how

14:22

type a lawyer does for every five of the

14:25

different

14:26

types of cases and we just want to look

14:28

at this this data and say like okay so

14:30

we see that the type a lawyers are best

14:32

in

14:34

case type d and case type e for b

14:37

they're all round doesn't really matter

14:39

they just perform well everywhere

14:41

c is maybe only good in a and b etc and

14:43

that's just a starting point something

14:45

to to look at

14:46

and the moment you look at it you know

14:48

it's wrong you just know that we have to

14:50

be more specific right since it's just

14:53

i mean it's just too high level and

14:55

that's the moment when we decide to

14:57

either

14:58

split up one of these columns to be more

15:00

specific

15:01

or fill up one of the rows be more

15:03

specific we just have to keep on doing

15:05

this iterative process until we're happy

15:06

with the way this matrix

15:08

and it can get very large obviously we

15:10

have to feel comfortable with

15:12

the granularity of the roads and the

15:14

colors

15:16

so i think we have to yeah we have to

15:18

have a high level categorization of

15:20

cases a high level generation of lawyers

15:23

then we even discard the whole

15:25

the whole team complexity i think that

15:26

that would be the starting point

15:28

um and and i mean i'm not sure because

15:31

i think it's it's not straightforward it

15:33

wasn't said for the management

15:35

consulting but

15:36

so every cell in this table is the

15:38

performance of this type of lawyer for

15:40

this type of case

15:41

but do we really are we able to generate

15:44

performance is it

15:45

is it straightforward i i think so i

15:48

mean you can have

15:49

client feedback that tells you dude are

15:52

they happy

15:53

um and sometimes you even have

15:57

actual measurements like if you go to

15:59

court did you win or did you lose

16:02

and so i think i think it is measurable

16:05

and i really like the idea that you

16:08

suggested which is

16:10

start somewhere create a matrix start

16:13

start putting it down and then you'll

16:15

know where the gaps are and then you'll

16:17

know

16:18

what to break apart be more nuanced

16:21

um i do have a an interesting question

16:24

which is

16:26

measurable improvement what what sort of

16:29

uplift can we expect looking at other

16:32

industries

16:33

if law firms were to start taking this

16:36

money ball approach to picking teams

16:39

so so yeah so the question is how much

16:41

can you actually

16:43

so how well does this matrix discern

16:46

differences in performance

16:47

but let's say i mean if it's reasonable

16:50

that a

16:51

type of lawyer has a performance of 30

16:53

percent where

16:55

30 of the cases this person does have a

16:58

reasonably

16:59

successful outcome and this person has

17:03

70 percent

17:04

in some other type of case and that 40

17:07

has this delta just this gap between the

17:08

two becomes larger that's where the

17:10

possible gain is

17:11

because right now this type lawyer a is

17:13

just randomly assigned to a and b

17:16

so basically if it's a 50 50 split this

17:19

person will have 50

17:20

success but if you would just assign

17:22

this person to

17:23

type d which this person has percent

17:25

success well

17:26

that 20 percent more case of success

17:28

that that's your gain there's a possible

17:30

efficiency

17:31

question is is it as straightforward as

17:33

that and are the gaps as large as this

17:35

right and what's the cost in producing

17:37

the data in order to have this

17:39

efficiency gain

17:40

exactly so it's complicated it's very

17:42

difficult to know

17:43

how much to be gained from this

17:47

um they're also completely different

17:49

performance metrics or outcome metrics

17:51

to think to account so let's say

17:52

you as a law firm assume that you always

17:55

get a reasonable

17:56

outcome let's just test it how much time

17:59

did it cost

18:00

person a or person b and we want to

18:02

minimize time

18:03

maybe be a reverse incentive because you

18:05

want to build more so so

18:06

this is definitely a question here well

18:09

it's changing the landscape is

18:11

morphing towards profit rather than

18:13

revenue right

18:14

i see i see so because in an efficiency

18:16

perspective it will be completely

18:18

reasonable to so let's say in a fixed

18:20

fee contract

18:21

maybe a management consulting setup

18:23

where you just you bill

18:24

a number of hours pre-determined and

18:27

then you just have to make

18:28

student work basically then it will be a

18:30

strong incentive to make sure you

18:32

assemble the team which does it in the

18:33

least amount of time

18:35

in the most efficient way so there you

18:37

would have a sort of

18:38

the cells wouldn't be successful or not

18:40

the cells would be number of hours

18:42

necessary for a success

18:44

there's something else and that would be

18:45

a different perspective how you look at

18:47

the possible gains to be had so if there

18:50

is a strong intuition amongst

18:52

law firm partners or stakeholder

18:54

shareholders in a way right now

18:56

that some people are just good at

18:58

something and i'm bad at

19:00

other things and it costs a lot more

19:02

time but that delta has your potential

19:04

efficiency gain

19:05

but i mean i agree it's extremely

19:07

difficult to know

19:08

a priori what these these differences

19:11

are because if it's just a percentage

19:12

point or something

19:14

it's really marginal the possible gain

19:16

you get into optimizing allocation of

19:18

people to cases

19:20

um so it really is a it's an intuition

19:22

question

19:23

at the heart but if it's as big as 20

19:26

from just allocating one person around

19:28

then that's an enormous gain

19:31

it almost i mean you can break it down

19:33

like any business problem

19:34

it almost feels like you have to

19:36

determine the objective first

19:38

then you just have to start taking

19:39

actions you have to you have to

19:41

experiment and go right

19:42

we have this amount of data we have this

19:44

available let's see what we can do and

19:46

then

19:47

iterate from that point onwards

19:51

i mean and you can do it in all kinds of

19:54

parts in the process if you look at

19:56

roboticizing or automating or at least

19:59

giving decision support to the

20:02

management level

20:03

it's even fair to say for example in

20:06

picking the cases you take up

20:08

as a as a as a law firm do

20:11

i want to do this or not and basically

20:13

using this type of approach what is my

20:15

availability

20:16

right now what do i know of these types

20:18

of lawyers doing this type of case

20:20

and actually having a sort of decision

20:22

support in terms of okay we only have a

20:24

30

20:24

probability of actually doing this

20:26

successfully right will be a different

20:28

part right it's the same data the same

20:30

so i think law firms have to be very

20:32

pragmatic here and i think

20:34

about where do we think this lack of

20:36

decision support

20:38

is the biggest where can we where can we

20:40

improve the most

20:41

and um pick those very different fruits

20:44

exactly

20:45

exactly because obviously you have to

20:46

think about how difficult it is but

20:47

which proxies matter

20:49

for this specific optimization problem

20:51

can we get them

20:52

yes there's a there's a really active

20:56

field in

20:57

legal tech at the moment and that's case

21:00

law analytics

21:01

looking at judges looking at the

21:02

circumstances and then measuring

21:04

what's the likelihood that this argument

21:06

would succeed in front of this judge

21:09

and i think this conversation is kind of

21:12

creating a much more broad

21:13

spectrum data analytics problem of

21:17

who do we pick as our team do we even

21:20

take on a case given this is a team that

21:22

we have

21:24

um and that's fascinating i think

21:28

your insights on that's just phenomenal

21:30

and the power levels to the

21:31

management industry is extremely

21:34

informative

21:35

the differences are also very very

21:37

interesting i must say

21:39

in the end of the day i mean it's just

21:40

this matrix thinking about

21:43

we we know this is this is external the

21:46

case

21:46

before us and this is what we choose and

21:49

finding a way to fill this first matrix

21:51

even if it's scuffed in all kinds of

21:54

ways just start looking at it

21:56

start trying to dig i think it's it's

21:58

it's very widely applicable

22:00

uh yeah marketing and magic resulting

22:03

it's just basic

22:04

data analytics of course so it's um

22:07

in a way it's the parallels are so

22:09

there's so many

22:10

but they're always very interesting

22:11

nuances where i think a lot tech or

22:13

legal

22:15

work is just such a fascinating

22:17

sub-specific

22:18

domain here yeah i would i would love

22:21

for a law firm to listen to this pick it

22:23

up and say hey let's experiment

22:25

because i think knowing what the

22:27

potential

22:28

impact would be from this type of work

22:31

would be

22:33

possibly possibly game changing

22:37

and you know uh if a firm says let's uh

22:41

let's experiment for six months

22:43

i think that would be personal you know

22:46

i mean this type of

22:47

problem is so rich i would definitely

22:49

love a good time

22:51

oh well look we will do what we can um

22:54

and mark i've had so much fun chatting i

22:57

think

22:57

what you've the insights you've given

22:59

the kind of pointers as to the actual

23:00

steps people can take

23:02

is hopefully gonna spark someone

23:05

inside of a law firm to take these steps

23:08

and if they do we'd love to hear from

23:11

them to see what the results are

23:13

of course and thank you again for your

23:16

time

Previous
Previous

Witness familiarization and how to combat the dark arts of cross examination

Next
Next

Pairing “hard technology” with “soft service” to deliver better outcomes