could’ve
been
done
on
Zoom,
but
I
have
to
be
here
just
like
you.’
BigHand,
a
legal
tech
software
provider,
recently
released
a
Survey
and
Report
entitled
Navigating
the
Million
Dollar
Problem,
Resource
management
for
Profitability,
Client
and
Talent
Retention.
The
report
is
based
on
responses
from
over
800
law
firm
leaders
and
professionals
across
firms
with
50
or
more
lawyers.
The
report
confirms
what
I
have
heard
over
and
over
again
from
lawyers,
particularly
at
smaller
and
midsize
law
firms:
they
simply
can’t
find
good
quality
associates,
and
when
they
do,
they
frequently
leave
for
perceived
greener
pastures.
BigHand
believes,
and
I
agree,
that
one
solution
is
to
better
utilize
the
associates
that
you
have.
And
that
comes
down,
in
part,
to
better
resource
allocation.
As
BigHand
puts
it,
it’s
a
$1
million
problem.
BigHand
is
selling
a
resource
management
tool
that
purportedly
solves
that
problem.
Some
Numbers
But
first,
some
numbers
from
the
report
that
reflect
the
resource
allocation
problem
and
paint
a
stark
picture:
-
43%
of
assignment
decisions
are
made
by
lawyers,
and
37%
are
based
on
personal
preference
over
merit. -
45%
of
the
firms
surveyed
report
they
only
have
partial
data
on
the
capacity
and
utilization
of
their
associates. -
Only
40%
have
partial
data
on
the
work
allocated
from
partners
to
associates.
Many
firms
are
essentially
resourcing
in
the
dark.
The
Clients
Eighty-six
percent
of
the
firms
surveyed
reported
that
client
demand
had
increased
over
the
last
year.
At
the
same
time,
despite
the
increased
demand,
40%
said
clients
are
reducing
their
spend,
38%
are
reducing
the
number
of
firms
that
they
use,
and
30%
of
the
firms
believed
clients
had
found
cheaper
alternatives.
Most
law
firms
surveyed
reported
client
attrition
in
the
last
12
months.
In
short,
there
are
tremendous
opportunities
for
firms
that
can
meet
client
demand.
And
one
way
to
help
do
that
is
to
retain
and
appropriately
utilize
associates.
The
Associates
So,
what
about
the
associates?
It’s
not
pretty.
The
number
of
associates
leaving
the
profession
has
almost
doubled
in
the
last
12
months
from
9%
in
2024
to
17%
in
2025.
The
main
reason
for
associates’
departure
is
the
desire
for
hybrid
working
and
better
work-life
balance.
Other
factors
include
a
lack
of
professional
development
as
well
as
concerns
over
salary.
According
to
the
report,
more
associates
are
moving
in-house
than
ever.
And
clearly,
when
an
associate
leaves,
it
disrupts
the
quality
of
service.
It
increases
the
workload
for
the
remaining
staff.
It
increases
recruiting
and
training
costs,
not
to
mention
the
loss
of
institutional
and
cultural
knowledge.
BigHand
estimates
that
the
cost
of
losing
a
third-year
associate
exceeds
$1,000,000,
even
before
considering
the
impact
on
other
lawyers
and
client
relationships.
Thus,
trying
to
reduce
attrition
is
crucial
for
these
reasons
alone.
And
33%
of
the
firms
surveyed
are
planning
to
reduce
equity
partners.
So,
not
surprisingly,
40%
of
the
firms
surveyed
want
to
increase
senior
associate
levels
in
the
next
year.
A
Perfect
Storm
It
sounds
like
a
perfect
storm:
more
work
available
from
clients,
increased
competition
with
emphasis
on
efficiency,
fewer
partners,
and
unhappy
associates
leaving
in
droves.
No
wonder
law
firm
leaders
keep
wailing
about
not
having
quality
associates
to
do
the
work.
So,
what
are
law
firms
doing?
Based
on
the
Survey,
not
much.
Instead,
they’re
relying
on
lawyers’
gut
instincts
about
associate
quality,
instincts
that
are
often
wrong.
Why
Use
Data
to
Allocate
Resources?
I
know
from
experience
that
many
resource
allocation
decisions
in
law
firms
are
made
based
on
a
partner’s
perceived
abilities
and
qualities
of
associates,
which
are
often
not
entirely
correct.
This
inevitably
results
in
underutilized
associates
on
one
hand
and
overutilized
associates
on
the
other.
The
overutilized
associates
quickly
become
burned
out
and
chafe
at
the
unfairness
of
the
system.
The
underutilized
associate,
on
the
other
hand,
worries
constantly
about
their
development
and
future
at
the
firm.
And
perhaps
they
should.
A
more
data-driven
allocation
method
might
result
in
utilization
on
a
more
accurate
and
fairer
basis
and
alleviate
the
stress
of
too
much
or
too
little
work,
stress
that
drives
associates
to
leave
and
costs
firms
dearly.
Dave
Cook,
BigHand’s
Global
Director
–
Resource
Management,
agrees:
“Partner-led
resourcing
with
no
data
visibility
leads
to
some
associates
being
overloaded
with
work
while
others
are
underutilized,
slowing
their
development
and
limiting
growth
opportunities.”
And
There’s
More
In
addition
to
relieving
associate
utilization
stress,
there
are
other
reasons
for
better
allocation.
For
example,
much
of
what
is
perceived
associate
quality
is
based
on
little
more
than
reputation.
I
remember
a
situation
when
I
was
a
partner
with
an
associate
who
had
the
reputation
of
being
underperforming.
The
firm
was
this
close
to
firing
the
associate
when
another
partner
took
the
associate
under
their
wing
and
moved
them
from
the
section
in
which
they
were
working
to
another
completely
different
section
where
that
partner
could
mentor
the
associate.
That
associate
later
became
an
equity
partner
and
had
some
of
the
highest
origination
of
any
lawyer
in
the
firm.
That,
of
course,
occurred
by
pure
happenstance.
But
if
there
were
data-driven
resources
that
could
help
determine
where
the
needs
were
and
match
those
needs
with
the
skill
set
of
associates,
keeping
in
mind
that,
as
the
associate
I
referred
to,
many
have
different
skill
sets
that
are
suited
to
different
types
of
practice.
A
closer
look
at
utilization
could
help
solve
both
problems
and
decrease
attrition.
It
might
also
detect
quality
issues
that
need
to
be
addressed
with
an
associate
before
it
becomes
such
a
significant
problem
as
in
the
example
that
I
provided.
And
let’s
face
facts.
Not
using
data
to
drive
work
assignments
and
instead
letting
the
lawyer
do
it
themselves
often
mean
lawyers
assigning
work
to
people
that
look
like
them
and
come
from
similar
backgrounds.
Since
most
assigning
lawyers
are
white
male
partners,
you
get
an
inevitably
unfair
result.
In
turn,
the
firm
loses
what
could
be
an
excellent
lawyer.
Cook
puts
it
this
way:
lawyer-based
assignment
“also
opens
the
door
to
all
kinds
of
bias.
Work
is
rarely
ever
equitably
allocated,
leading
to
frustration,
and
sometimes
departures,
from
talent
that
would
otherwise
help
the
firm
succeed.”
The
associate
in
my
example,
by
the
way?
A
black
female.
So,
Why
Not?
So,
why
aren’t
firms
using
a
data-driven
approach
to
allocating
work
to
associates?
As
the
report
points
out,
robust
resource
allocation
is
not
something
that
lawyers
without
data
are
good
at,
and
it
takes
away
from
billable
time.
Yet
they
keep
insisting
on
doing
it
themselves.
That’s
because
most
partners
want
the
freedom
to
utilize
their
favorite
associates.
They
perceive
themselves
as
special
snowflakes
with
the
unique
ability
to
spot
and
develop
talent.
They
believe
that,
instead
of
data,
their
“gut
instinct”
is
the
most
valid
determining
factor.
They
believe
that
their
work
is
so
important
that
only
the
best
associates
can
work
on
it.
And
they
aren’t
going
to
give
up
that
control.
Secondly,
too
many
partners
are
unwilling
to
delegate
the
allocation
of
their
work
to
a
data-driven
platform
and
personnel
who
are
not
lawyers.
The
idea
is
that
this
is
my
practice,
this
is
my
law
firm,
and
you
work
for
me
–
so
butt
out.
I’ve
seen
this
hubris
repeatedly,
especially
from
senior
partners
who’ve
never
had
or
wanted
to
justify
their
resource
decisions
with
data.
Moreover,
rather
than
looking
hard
at
career
development
and
addressing
problems
before
they
get
too
large,
too
many
partners
are
too
focused
on
billable
hours
and
client
origination
to
worry
about
the
development
of
associates,
the
lifeblood
for
the
future
of
the
law
firm.
Conclusion
So
even
though
data-driven
resource
allocation
reduces
associate
attrition
at
a
time
when
more
not
fewer
are
needed,
reduces
cost
and
disruption,
and
may
indirectly
lead
to
better
partners,
firms
are
slow
to
embrace
it.
But
BigHand
is
right;
to
compete
effectively
for
new
work
and
keep
the
clients
and
associates
you
have,
resources
need
to
be
appropriately
allocated
to
the
right
levels
based
upon
profitability,
hourly
rates,
and
efficiencies.
The
best
way
to
do
that
is
not
by
gut
instinct
but
by
data
and
analytics.
While
I
can’t
verify
all
of
BigHand’s
findings,
the
core
problems
they
identify
align
with
what
I’ve
observed
repeatedly.
Does
BigHand’s
resource
management
tool
better
allocate
work?
I
couldn’t
tell
you
that
either.
But
data-driven
resource
allocation
is
the
right
idea
at
the
right
time.
Stephen
Embry
is
a
lawyer,
speaker,
blogger,
and
writer.
He
publishes TechLaw
Crossroads,
a
blog
devoted
to
the
examination
of
the
tension
between
technology,
the
law,
and
the
practice
of
law.