Hello.
My
name
is
Thor
Osborn.
I
work
at
Sandia
National
Laboratories
as
a
systems
research
analyst.
That's
basically
a
combination
of
operations,
research,
and
investigative
reporting.
I'm
going
to
present
an
analysis
of
personnel
movements
pre-
and
post-COVID
for
a
large
organization.
In
this
case,
the
large
organization
is
the
State
employees
of
the
State
of
Florida,
the
State
of
Florida
government
employees.
I'll
say
that
that's
fortuitous
because
that's
part
of
their
transparency
policy.
So
we
can
look
at
that
data,
anyone
can,
and
I'll
give
you
the
link
for
that.
The
data
that
I'm
going
to
be
showing
analysis
of
is
from
August
of
2017
through
July
of
this
year.
Why
do
this?
C
OVID-19
pandemic
and
the
mitigations
that
have
been
instituted
to
address
that
have
been
cited
as
catalysts
for
substantive
changes
in
the
workplace.
For
example,
5 or 10
years
ago,
work
from
home
was
considered
an
unusual
opportunity
or
a
temporary
thing
to
address
some
kind
of
temporary
issue
like
a
[inaudible 00:01:20]
.
It
wasn't
considered
something
that
most
companies
would
do
a
lot
of
on
an
ongoing
basis.
Now,
it's
considered
a
thing
that
job
seekers
may
rate
companies
on,
if
you
take
a
look
at
the
web,
for
example.
Also,
a nursing
profession
was
especially
impacted
by
C
OVID-19
response,
extreme
hours,
burnt
out.
But
that
has,
in
a
lot
of
cases,
led
to
exodus
from
the
profession.
F
or
many
who'
ve
stayed
in
the
profession,
departure
from
typical
long-
term
employment
like
working
in
a
hospital
in
favor
of
traveling
nurse
or
concierge
contracts
where
they
get
paid
a
lot
more
and
they
have
more
flexible
hours
and
aren't
committed
to,
say,
12
hours
since
one
after
the
other
in
a
hospital.
I'll
say
that
the
hospital,
our
end
turnover
went
up to
8.4%
from
2020
to
2021
to
about
27%
per
year,
according
to
the
NSI
National
Health Care
Retention
Report.
RN
vacancies,
meaning
slots
that
hospitals
want
to
fill,
have
gone
up
from
about
8%
in
2018%
to
17%
this
year.
So
basically,
one
in
every
six
nurses
who's
supposed
to
be
there
to
help
give
care
isn't.
Now,
motivation
for
doing
it
the
way
I'm
doing
it.
Periodic
tabulation
of
movements
or
rates
is
a
typical
business
approach
to
business
reporting,
and
almost
every
company
does
this.
But
it
may
obscure
underlying
behavior
patterns
because
tallies
don't
tell
you
the
micro behavior,
and
time-
to-
event
analysis
will
enable
a
deeper
look.
I
like
to
use
parametric
time-
to-
event
analysis
for
this
because
the
parameters
can
be
informative.
But
to
do
that,
you
have
to
have
a
lot
of
events,
and
to
get
a
lot
of
events
unless
events
are
extremely
frequent
and
need
an
even
larger
population.
This
is
fortuitous
that
the
State
of
Florida
makes
weekly
employee
data
available
for
about
100,000
people.
Quick
synopsis
of
the
show
for
those
with
no
attention
span
or just
to
help
me
and
you,
the
COVID-19
pandemic
was
implicated
as
catalyst
for
many
changes.
I
went
over
that.
A
longitudinal
examination
of
behavior
based
on
the
evidence
from
a
large
organization
seems
timely.
We
need
to
look
at
these
things.
This
is
a
natural
experiment
of
magnificent
or
awful
proportions.
The
data
available
on
a
weekly
basis,
as
I
said,
straddle
the
beginning
of
the
COVID-19
pandemic.
This
is
a
fortuitous
collection.
I
started
it
on
Intuition
back
in
2017,
but
then
things
happened.
The
State
of
Florida's
decision
to
build
its
broadband
structure
around
a
categorization
system
that
mirrors
and
links
up
with
the
federal
SOC,
or
Standard
Occupation
Classification
code
structure,
also
provides
a
well
established
and
readily
available
frame
of
reference,
meaning
you
can
get
it
and
it's
free,
and
it's
reasonably
well
worked
out,
documented.
You
can
look
at
employee
populations,
you
can
look
at
hiring,
separations,
all
longitudinally
within
that
framework
at
varying
levels
of
specificity,
and
that's
pre-
framed
by
the
SOC structure.
The
fact
that
they've
melded
with
that
structure
provides
an
easy
window
into
that
level
of
analysis.
I
finish
off
with
an
analysis
of
the
nursing
profession
as
represented
by
registered
nurses.
That
demonstrates
what
I'm
calling
a
substantive
difference.
It's
definitely
visible
in
personnel
flows
between
the
pre-
and
post-COVID
timeframes.
This
is
an
example.
I
haven't
been
able
to
go
into
the
level
of
depth
that
I
would
like
to
with
this
analysis
and
this
data
set,
but
I
wanted
to
show
at
least
an
example
of
what
I
was
talking
about
[inaudible 00:05:36]
.
Again,
just
to
really
beat
this
one
down,
an
unusual
opportunity.
Typical
practice
in
HR
is
to
frame
salary
structures
in
context
with
other
similar
organizations.
Salary
information
is
generally
compiled
by
a
consulting
firm
in
HR
from
a
collection
of
organizations
that
chose
to
participate
in
a
defined
pool
for
survey
and
referencing
purposes.
They
don't
do
that
for
free.
It
costs
a
substantial
amount
of
money.
Now,
the
BLS
also
compiles
salary
surveys
of
its
own
on
a
national
and
state
basis
with
jobs
categorized
by
a
standard
structure,
which
they
call
the
SOC.
That
data
can
be
downloaded
for
free,
and
the
State
of
Florida
has
referenced
its
structure
to
that.
It's
fortuitous
in
a
way
for
them,
because
they
don't
have
to
pay
for
seller
surveys
if
they
don't
want
to,
because
it's
all
referenced
against
the
federally
established
free
data
set.
Now,
I'm
going
to
show
if
I
can.
Here's
just
a
table.
Apologies
if
it's
a
little
small.
A
table
showing
broadband
code
right
here,
10, that
means
Executive,
1011-03,
Chief
Executives.
The
point
is,
everything
in
the
Florida
set,
this
is
about
3,000
codes.
Except
for
a
few
recent
ones,
everything
in
the
Florida
set
is
referenced
against
this.
The
first
six
digits
are
the
six
digits
in
the
SOC
code.
The
first
two
are
the
major
code.
It's the job
family,
like
10
is
Executive
s,
11
is
Management,
13
is
Business
jobs,
and
then
a
four-
digit
code
for
more
specificity.
In
the
case
of
Florida,
they
have
an
extra
two
digits
which
denotes
a
job
level
within
their
salary
structure.
But
this
framing
allows
you
to
link
things
back
to
the
SOC.
What
did
they
give
you?
They
give
you
an
agency
name
of
which
there
are
33
state
agencies;
budget
entity,
an
office
within
the
agency;
a
position
number,
that's
a
position
within
the
agency;
employee
names.
I'm
not
showing
you
that
because
I
feel
uncomfortable
even
though
when
you
download
it,
you
can
obviously
see
who's
who,
whether
the
person
is
salaried
or
exempt
hourly,
or other
personal
services
they
call
them,
full-
or
part-
time.
A
class
code
which
is
a
code
that
indicates
both
the
profession
and
the
level.
A
class
title
which
is
essentially
the
same
thing
in
words.
State
hire
date,
which
is
the
first
date
that
the
individuals
hired
by
the
state.
They
could
have
had
many
terms
of
employment,
come and
left
,
but
the
state
hire date
is
a
fixed
point
in
time
for
each
person
salary
or
hourly
rate
if
the
person
is
doing
an
hourly
job.
Again,
this
is
freely
available
at
the
link
noted
on
the
screen.
Just
for
a
bit
more
framing,
long-
term
view
of
wages
in
the
State
of
Florida,
looking
at
BLS,
Bureau
of
Labor
Standards
data
for
SOC,
is 00-000,
just
a
weighted
all
occupations
number.
It
covers
everything.
These
are
a
lot
of
people,
so
I
don't
have
error
bars,
130 million
people
nationally
and
7
million
employees
in
Florida.
What
you
see
is
that
Florida's
salaries
,
the
blue
line,
are
typically
less
than
national,
but
they've
been
tracking
pretty
closely.
There's
not
been
much
relative
change
in
a
long
time
except
for
this
past
year.
Sometimes
there
are
revisions.
I'm
not
going
to
say
this
is
necessarily
meaningful.
If
it
is
a
real
difference
then
obviously
be
interesting
to
know
about
that.
I
haven't
seen
anything
reported
about
that
though,
so
I
can't
give
you
any
further
insight
on
that.
If
you
look
at
Florida
State
employees
versus
typical
Floridians,
I
don't
have
enough
data
in
the
set
to
really
say
very
much,
except
for
it
looks
like
being
a
state
employee
is
fairly
attractive,
at
least
if
the
jobs
are
typically
comparable.
There's
no
overriding
incentive
for
people
who
work
for
the
state
to
leave
to
go
into
the
private
sector
there
based
on
this.
These
are
for
median
salaries,
annual
salaries.
Looking
at
the
Florida
State
employee
population
totals
in
the
green
line
here
starting
at
around
100,000
for
exempt
staff,
doesn't
include
the
hourly
folks
in
either
case
here
or
here.
Looking
at
separation
rates
and
hiring
rates
as
nine-
week
moving
averages
to
be
about
two
months
as
a
centralized
moving
average,
with
JMP's
usual
capability
for
handling
the
endpoints.
What
you
see
is
that
for
a
fairly
long
time,
except
for
this
spike,
which
again,
I
haven't
found
anything
to
explain
in
the
literature,
nor
in
HR
reports
published
by
Florida.
Pretty
constant.
After
the
pandemic
hit,
there
was
a
long
time
period
where
the
hiring
rate
was
below
the
separation
rate.
So
people
were
slowly
leaving
Florida.
You
can
see
that
here
in
a
downward
slope
on
the
green
line.
And
then
just
this
year,
that
stopped
and
began
to
reverse.
Now,
to
be
clear,
the
population
is
only
salaried
workers,
only
those
holding
one
salaried
state
position
at
all
times.
Anybody
with
two
salaried
positions
was
removed
because
it
could
be
a flawed
data
or
it
could
be
a
very
ambitious
person.
But
I
can't
handle
that
with
the
time-
to-
event
data
because
it's
hard
to
understand
exactly
what
a
separation
means
when
you
still
have
a
job
at
the
same
place.
But
it's
only
less
than
half
a
percent
of
the
total
people,
so
it
shouldn't
be
a
huge
perturbation.
Now,
when
I
show
this
is
a
bit
of
a
demo
as
well.
Florida
State
personnel
flows
by
SOC major
code.
But
you
can
see
on
the
right
tableâ¦
Here's
the
population
by
SOC
major
code,
every
individual
grouping
over
time.
This
is
code
43.
That's
Office
Administrative
Assistants.
What
I've
done
is
I've
used
the
hide
and
exclude
capability
to
remove
everything
except
for
six
codes,
which
are
the
largest
codes.
You
see,
the
Administrative
Assistants
is
43.
And
also
down
here,
19
for
Life
and
Physical
Sciences
is
included,
Business
is
included,
Manager is included.
What
I'm
trying
to
say
here
is
simply
that
this
is
only
including
six
out
of
something
like
20
or
so
major
SOC codes.
But
these
are
the
largest.
Using
graph
builder,
it
only
shows
those.
That's
really
all
it
amounts
to.
Business
and
Finance,
Community
and
Social
Services,
that
we
code
21,
code
19,
code
11.
Now,
one
thing
you'll
see
with
Manager
is
that
the
hiring
rate
is
always
quite
a
bit
less
than
the
separation
rate,
and
yet
the
net
number
of
managers
is
roughly
the
same,
and
that's
because
only
about
half
of
the
managers
come
from
external
sources,
a
lot
of
them
come
from
internal
promotions.
You
see
this
population
over
time,
despite
the
vast
difference
in
separations
versus
hiring,
that's
simply
because
about
half
of
them
come
from
internal.
Now,
you
can
also,
again,
as
I
was
saying
earlier,
you
can
do
detailed
codes
and
the
same
principle
applies.
All
I've
done
here
is
I've
only
included
three
SOC detail
codes.
The
29
major
code,
which
is
Medical
Professionals,
the
31
which
is
Support
Folks
in
Medical
Work,
and
then
back
to
29
again
for
Registered
Nurses,
but
this
is
the
Nurses
and
Nursing
Assistants
taken
together.
This
code
is
no
longer
used
and
hasn't
been
for
a
while.
But
Florida
set
up
its
code
system
about
two
decades
ago
and
so
it's
been
kept
in
and
they
use
it
even
though
it
isn't
part
of
the
standard
SOC
now.
But
the
bottom
line
you'll
see
from
here
is
that
Florida
is
not
attracting
enough
nurses
to
compensate
for
attrition.
If
you
look
at
the
State
of
Florida
HR R
eports,
what
you'll
see
there
is
that
they
think
most
separations
are
voluntary,
about
92%.
The
number
of
authorized
positions
in
the
health
agency
has
only
been
reduced
by
about
5%
in
the
last
several
years,
and
yet
the
number
of
RNs
has
dropped
by
about
a
fourth.
You
can
see
that
the
number
of
nurses
is
falling
rapidly
compared
to
the
allocation
of
nursing
spots.
If
you
go
to
the
State
of
Florida
website
and
look
for
a
job
in
nursing,
you'll
see
that
there's
plenty
of
opportunity.
They've been trying to hire.
Now,
I
am
going
to
show
some
time-
to-e
vent
analysis.
I'm
not
going
to
show
the
script
work
that
generated
the
data
set
for
this,
because
although
I
find
it
fascinating,
I
know
that
a
lot
of
folks
don't
do
scripting.
It's
essentially
an
inference
between
who's
there
and
who
wasn't.
If
you
go
from
one
week
to
the
next
and
people
disappear
and
you've
allowed
for
the
fact
that
people
do
name
changes
sometimes,
which
requires
coming
up
with
a
different
way
of
IDing
people
to
straddle
the
difference.
Once
you've
accounted
for
that,
then
they
must
have
left.
Having
left,
that's
a
separation.
They
can
also
get
promoted,
and
you
can
see
that
because
one
week
they
have
a
job,
and
then
the
next
week
they
have
a
job
that
pays
better,
often
the
same
general
line,
but
with
a
different
title.
Capturing
those
movements
is
a
bit
of
work
but
it's
pretty
straightforward,
really.
What
you
see
here,
I
tried
to
capture
four
different
kinds
of
events:
demotions,
a lateral
to
another
SOC,
could
be
moving
out
of
the
nursing
profession,
but
nevertheless
haven't
changed
their
salary
much,
promotion,
or
separations.
Separations
is
obviously
the
dominant
factor
here
in
terms
of
total
counts.
I'm
using
the
Weibull
typically
because
I
find
it
more
informative
and
it's
not
a
bad
fit.
Post-COVID,
you
see
a
very
similar
curve,
more
promotions,
relatively
speaking.
That's
interesting.
Now,
here
is
the
detail
in
tabular
form
so
that
you
can
see
all
the
different
pre-
and
post-
cases
for
the
major
movements,
lateral
movement,
promotion,
and
separation.
What
I'm
talking
about
though,
let's
just
go
back
to
pre-COVID.
Here's
a
subset
of
Exit
Events,
essentially
exit
from
the
status
as
an
RN
to
whatever
they
moved
to.
Just
to
make
it
clear
what
was
done
here.
If
you
relaunch,
what
you
see
is
that
I
have
a
Censor
column,
just
ones
and
zeros.
The
Exit
Event
is
however
they
exit,
or
if
they
didn't
exit,
then
it's
just
an
active
person
in
the
field
and
they
are
not
marked
with
a
censor
code.
The
Employment
Segment
Span,
which
is
how
long
have
they
been
employed
in
that
particular
segment
of
employment.
Now,
see
that
the
number
of
laterals
is
really
small
compared
to
everything
else.
Promotions
is
definitely
visible.
Another
thing
you
can
see
if
you
go
down
and
look
at
separations
is
that
the
Weibull
beta,
which
you
can
think
of
as
the
acceleration
factor,
even
at
the
high
end
of
the
95%
limits,
it's
still
below
unity,
and
below
unity
means
that
people
are
less
likely
to
go
through
that
transition
as
time
goes
on,
less
likely
to
separate
the
longer
they've
done
there.
That's
straightforward.
You'll
see
it
here.
In
fact,
that's
also
through
post-COVID,
same
basic
beta
factor
or
parameter, rather.
Now,
I'm
going
to
show
the
post-COVID.
Again,
this
is
the
same
basic
analysis.
This
is
what
happens
when
you
do
live
demos.
Something
goofy
with
this
one.
Now
it's
giving
me
grief.
Here,
you
see
it's
basically
the
same
thing.
Lateral
is
distorting
because
the
lateral,
there's
only
two
counts.
If
you
just
get
rid
of
that
,
you
can
see
a
much
more
clear
picture.
What
you
see
is
that
the
Promotions
piece
is
moving
up
faster,
50
versus
744,
whereas
pre
over
a
longer
time
spent,
it
was
about
50
for
about
1,200
separations.
There's
a
predominance
is
shifting
there.
Going
back
to
the
more
convenient
layout
here.
Pre-COVID
promotions
were
in
this
range
where
beta
was
a
little
over
unity.
But
the
95%
limits
basically
tell
you
that
that's
ambiguous.
It
could
be
really
anywhere
between
a
bit
below
and
a
bit
above
unity.
Post-COVID,
it's
about
1.29,
and
within
these
95%
limits,
always
above
unity.
In
other
words,
it's
accelerating
with
time.
The
longer
you
go,
the
more
likely
you
are
to
go
through
a
promotion
if
you
stay
in
that
job.
Here
with
the
lateral
movement,
there
really
was
never
enough
counts
to
do
much
of
anything
with
that.
The
limits
are
very
broad.
I
wouldn't
put
too
much tal
k
in
that,
regardless.
Now,
if
you
put
these
on
a
common
scale
just
to
make
sure
that
this
isn't
too
confusing,
I
hope.
You
see
very
similar.
I've
shifted
the
color
for
the
post-COVID
case
a
little
bit.
On
a
similar
scale,
if
you
didn't
superimpose
these,
promotions
are
clearly
accelerated,
p
ost
-COVID.
Clearly
a
bigger
impact,
they're
more
opportunity.
We
do
know
from
many
news
reports
that
people
who
are
closest
to
retirement,
often
within
the
COVID
complications
and
changes,
simply
moved
forward
with
retirement
more
quickly
because
they
wanted
to
get
out
other
than
deal
with
things.
There
is
a
shift
here
with
the
separations,
and
it
does
look
real,
but
it's
also
small
enough
compared
to
the
overall
magnitude
that
it
isn't
quite
as
obviously
different.
In
either
case,
the
separation
rate
is
similar
and
not
changed
overly
much.
This
is
a
factor
of
two.
This
is
a
factor
of
a
few
percent.
To
conclude,
wages
in
Florida
have
run
lower
than
national
values
typically
over
the
last
decade,
but
haven't
proportionally
changed
much.
There
certainly
doesn't
seem
to
be
any
obvious
change
in
Florida
salaries
that
would
cause
people
to
suddenly
leave.
The
State
of
Florida's
registered
nurses
have
enjoyed
greater
and
earlier
promotion
opportunities
post-COVID.
But I
think
it's
also
worth
noting
here
that
they
work
in
a
health
organization
for
the
State.
This
is
not
a
State
hospital.
This
is
a
health
management,
health
support,
health
education
activity.
It's
not
24/7
in
a
hospital.
That
moderates
expectations.
But
you
might
expect
the
separation
behavior
among
their
RNs
would
change
because
opportunities
have
changed
in
the
private
sector.
There's
a
lot
of
demand.
On
the
other
hand,
state
employees,
they
might
be
thought
to
be
comfortable.
I
was
expecting
my
hypothesis
was
that
they
would
be
more
likely
to
separate,
but
that
didn't
happen.
There
really
is
no
apparent
difference.
Now,
this
is
not
a
complete
bibliography
of
everything
that
I
read
in
the
last
five
years,
before
and
after
COVID
that
may
have
influenced
things.
This
is
just
a
handful
of
things.
I
thought
they
were
fairly
telling.
The
National
Healthcare
Retention
& RN
Staffing
Report
is
a
fairly
thorough
assessment
of
what
people
expect
in
hospital
administration
and
what's
actually
been
happening
in
terms
of
the
employment
and
the
separations,
the
turnover
behavior
of
nurses.
Three
State
of
Florida
annual
reports.
They
do
an
annual
report
on
a
fiscal
year
that
straddles
two
calendar
years.
The
last
one
available
is
2020.
But
essentially,
they're
simply
reiterating
that,
yes,
they
have
a
number
of
open
slots,
they
don't
have
them
all
full.
Employment
and
nursing
is
dropping.
They
don't
have
any
explanations
for
these
things.
I
also
don't
have
any
explanation
for
the
spikes
and
activity
earlier,
pre-COVID.
I
have
a
question
into
someone
in
the
Governor's
office
there,
but
I
haven't
heard
back
yet.
That's
basically
all
I
have
for
this
presentation.
I
would
be
happy
to
entertain
questions.
The
slides
show
at
the
beginning,
there's
my
email.
You
can
contact
me
if
you
want.
Thanks.
