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Quantifying Your Organization's Analytical Maturity: Data-Driven Decision Making to Do Things Better - (2023-US-30MP-1380)

Data is everything. Every organization, big or small, collects data and knows the more insight they can gain from the data, the more competitive they will be. But what tools does the organization need? What skill sets are necessary for their most valuable asset, their employees? How do they quickly ascertain the level of competency their people have in order to achieve this end?

 

Enter the JMP Analytical Workflow Survey (JAWS). JAWS is an expeditious tool for organizations at all scales to rapidly and succinctly identify the competency of their people – their strengths and weaknesses and an estimate of time they spend to perform certain analytical tasks – to create a roadmap to achieve organizational goals. By deploying JAWS in your organization, you will gain insight into the current state of your analytical fitness, identify strengths within your organization, and develop targeted action items to address your weaknesses. Perhaps most importantly, it will identify areas in your analytical process that are overly time-consuming or ripe for automation, freeing up valuable brainpower to address more pressing issues.

 

In this presentation, we walk you through the steps of deploying the JAWS and highlight the incredibly valuable insights one can gain, which will allow your organization to make data-driven decisions efficiently to achieve the analytical ends you desire.

 

Learn More.

 

 

Hello.  My  name  is  Peter  Polito.

 

I'm  a  Senior  Systems  Engineer  at  JMP.

Today  I'm  going  to  be  talking  to  you

about  quantifying   your  organization's  analytical  maturity

in  order  to  make   data- driven  decision  making

so  you  can  do  things  better.

I've  been  using  JMP  for  some  time.

I  actually  learned  JMP  on  a  boot  leg  copy

of  version  six   when  I  was  in  graduate  school.

It's  been  a  part  of  my  life  for  a  long  time,

and  being  able  to  use  it  to  help  others find  success  is  one  of  my  great  joys.

Today,  I  have  a  lot  of  people   that  are  helping  support  this,

primarily  is  Brady  Brady.

He  is  a  Principal  Systems  Engineer   also  at  JMP.

He  helped  craft  the  background  tool

to  perform  all  the  analytics  that  I'll  be  presenting

and  that  you  may be  able  to  take  advantage  of.

Then,  of  course, I  want  to  thank  my  team.

We  work  with  high  tech  companies   here  in  the  United  States,

and  that  is  Ben  Ross, who  is  a  Strategic  Account  Manager,

and  Kyle  Bickford, a  Senior  Account  Executive.

The  goal  for  today  is  to  demonstrate

how  you  can  collaborate   with  your  JMP  support  team

to  quantify  your  organization's  analytical  maturity.

By  quantifying  that,

you'll  be  able  to  understand   where  people  are  spending  their  time

and  how  competent  they  are,

and  then  use  that  as a  benchmark  to  track  progress.

By  working  with  your   JMP  support  team  in  this  effort,

they  can  help  craft  the  support  necessary

to  bring  your  team  from  where  they  are to  where  you  would  like  them  to  be.

How  do  we  do  this?

We  use  the   JMP Analytical Workflow Survey.

I'll  refer  to  it  as  JAWS throughout  this  talk.

I  feel  that's  a  little  catchier.

The  tool,  it's  a  quantitative  tool

to  just  measure  the  analytical  maturity  for  your  entire  organization.

Despite  JMP being  in  the  name, it  is  not  just  for  JMP  users

and  so  the  idea  is  that  you assess  an  entire  organization.

You  can  break  it  down  by  department, by  job  title,  etc.,

and  then  use  this  by  annual  rerunning of  the  survey  to  understand

if  you're  moving  in  the  right  direction and  what  areas  you  need  help  in.

It  also  helps  you  identify  white  space where  maybe  analytics  is  heavily  used,

so  that  you  can  bring   that  up  to  your  management

or  whoever  it  might  be

in  order  to  help  get   your  entire  organization  moving  in  mass

in  the  direction   that's  going  to  drive  your  company

towards  discovery,  efficiency  and  growth.

How  does  it  work?

It's  simple. It's  a  five  minute  anonymous  survey.

It  measures  the  amount  of  time

person  spends  performing a  particular  analytical  task.

It's  not  just  one, but  all  of  their  analytical  tasks.

It  understands  their self-professed  competency.

By  doing  this  anonymously,  we  find that  people  tend  to  be  more  honest.

Not  only  do  they  get  to  say,

I  spend  two  hours  a  week  doing  data  visualization,

but  they  can  also  say,

I  don't  really  know  what  I'm  doing,   or  I  got  this.

I'm  definitely  an  advanced  user.

So  we  can  understand   how  much  time  they're  spending

and  what  level  of  competency  they  have.

Maybe  most  importantly,

it'll  give  the  person  opportunity  to  say, I  need  to  know  how  to  do  this,

and  I  need  help   because  I  don't  know  what  I'm  doing,

or  I  need  to  do  this  to  complete  my  job,

and  I'm  totally  competent  in  this.

It's  time  spent,

how  well  they  think   that  they're  able  to  do  it,

and  where  do  they  need  support   to  do  their  job  better.

If  you  think  about  it,

those  three  things  for  management  to  know  that,

I  mean,  that's  incredibly  valuable.

This  is  a  very  easy  way   to  identify  this  information,

and  we  present  it  in  a  way  that  has  great  visuals,

easy  to  comprehend  and  digest,

easy  to  share  with  upper  management to  help  build  that  roadmap

for  getting  your  organization  from  where  they  are

to  where  you  want  them  to  be.

What  exactly  are  we  looking  at?

Well,  if  you're  unfamiliar,

this  is  called  the  JMP  analytical  workflow.

It  works  left  to  right.

On  the  left  you  have  where  is  data  coming  from?

For  example,  in  the  survey, it's  going  to  ask  how  much  of  your  week

is  spent  interacting  with  files  or  documents  or  databases  or  web  APIs.

Your  data  comes  into  some  analytical  tool,

preferably  JMP,   but  it  might  be  something  else.

Then  people  spend  time  doing  tasks.

From  accessing  data

to   performing  basic  data  analysis  and  modeling.

Maybe  they're  doing  reliability, consumer  research.

Maybe  their  job  is  more  focused

on  building  automations for  the  organization.

They're  doing  something  or  a  series  of  some  things

that  take  some  time   and  requires  competency.

Then,  of  course, they  need  to  share  that.

It'd  be  a  shame  if  all  of  our  hard  work  just  lived  in  our  hard  drive,

we  presented  it  in  a  PowerPoint in  a  meeting,  and  then  it  just  goes  away.

We  want  data  to  come  in,

we  want  something  to  be  done  to  that  data,

and  then  we  want  data  to  be  shared

with  the  entire  organization so  that  people  can  learn.

The  longer  I  am  in  this  position,

the  longer  I  recognize  there's  no such  thing  as  a  one-off  problem.

Everything  comes  back  in  some  shade of  gray  relative  to  where  it  started.

If  we  have  an  area  or  a  way  to  query

all  of  the  problems   an  organization  has  solved,

it's  going  to  save  a  lot of  time  in  the  future

because  people  aren't  going  to  be starting  at  ground  zero.

W e  want  to  measure  all  of  these  things.

Where  are  they  spending  their  time?

How  capable  do  they  feel they're  at  doing  that?

And  where  do  they  need support  to  do  that  better?

The  first  step  is  collecting  the  data.

This  is,  as  I  mentioned, about  a  five  minute  survey.

The  first  three  questions

are c ompletely  customizable to  fit  your  organization.

This  is  anonymous,  but  we  want  to  know  some  things.

We  want  to  know   where  are  these  people  located?

For  some  of  you,  it  might  be  we're  all  in  one  place.

Maybe  they  work  in  the  office, they  work  from  home.

Who  knows?

Maybe  they  work  in  the  United  States.

Maybe  they  work  in  Europe. Maybe  they  work  in  Asia.

Maybe  they're  just  spread  out in  different  sites  across  the  US.

But  we  can  customize  that  to  fit your  o rganizational  design.

Then  we  want  to  know  what  department  they're  in

and  what  are  their  job  roles.

This  allows  us  to  slice  and  dice  that  data once  that  survey  data  is  collected

to  better  understand  where  are  things working  well  and  where  do  we  need  support?

You  may  have  an  R&D  department  that's in  one  location  that's  just  crushing  it.

They  are  very  competent. They're  very  capable.

They're  not  spending  too  much  time because  they  built  automation.

Then  their  peers  at  maybe a  newer  location  are  way  behind.

They're  the  ones  that  need  support   by  designing  it  in  such  a  way

that  we  can  slice  and  dice  it   by  department,  by  job  title,  by  region.

We  can  really  get to  the  heart  of  where  support  is  needed

or  really  pat  ourselves  in  the  back because  we're  doing  things  well.

We  are  where  we  thought  we  would  be.

But  I've  administered   the  survey  many  times,

and  every  single  time  I  hear, I  thought  we  were  better,

so this  is  a  great  way  to  measure  that.

From  there,  we're  going  to  look  at  how  much  time

do  people  spend  doing  particular  things.

You'll  see,  none  of  this  is  JMP  specific.

It's  really  designed  for  anyone.

Anyone  working  with  data needs  to  get  that  data.

Anyone  working  with  data  needs  to  clean  that  data,

put  it  into  a  position   where  they  can  analyze  it,

look  for  outliers, visualize  it,  whatever  the  case  may  be.

Additionally,  we'll  have  something  very  similar  to  this

to  collect  data  on  what  their  competency  is.

Then,  of  course,  as  I  mentioned,

we  have  the  opportunity  for  them  to  say, I  need  to  access  data.

It  is  critical  to  my  task, and  I  am  not  good  at  it.

I'm  inefficient, I  don't  know  how  to  query  our  database,

I  don't  know  how  to  bring  in  55  CSV  files  efficiently,

I  need  advanced  training.

Or  I'm  really  good  at  this,   or  I  don't  even  need  this,

someone  just  emails  me a  file  and  I  do  my  work.

It  allows  them  to  tell  you  what  do  I  need  to  be  better  at,

so  that  I  can  be  better  at  my  job.

At  the  end  of  the  day,

most  of  our  people   want  to  do  their  job  well.

They  want  to  be  successful. They  want  to  advance  in  the  company.

They  want  to  show  that  they have  value  and  worth.

This  is  an  opportunity  for  them

to  tell  you  where they  think  they  need  help.

There's  been  a  few  instances   where  I've  talked  to  a  management  team,

and  they're  like,  this  department doesn't  know  how  to  do  that.

Then  the  survey  results  come  back and  the  manager  is  like,  my  goodness,

they  all  feel  like  they  need to  know  how  to  do  this  better.

I  have  no  idea.

This  is  really  an  eye- opening  opportunity

for  a  lot  of  people   when  they  see  these  results

to  really  fully  understand  exactly  where  their  people  are

versus  where  they  think  they  should  be.

We  collect  this  data,

your  JMP  support  team   will  analyze  this  data,

and  then  they'll  be able  to  present  it  to  you.

Now  we're  going  to  walk  through   what  this  data  looks  like,

so  you  can  get  a  sense   of  what  will  I  learn.

We'll  go  at  a  couple of  different  views.

At  the  10,000  foot  view,

we  get  these  heat  maps  that  show  where  are  people  spending  their  time.

I've  broken  this  up by  organizational  wide  on  the  upper  left,

by  job  title  on  the  upper  right, and  by  department  at  the  bottom.

If  we  just  look  at  the  upper  left,

we  can  see  that  people  are  predominantly interacting  with  files,

probably  Excel  files  or  databases,

and  they're  doing  a  lot  of  data  exploration,

a  lot  of  basic  data  analysis  modeling,

very  little  reliability  analysis,

a  little  bit   of  quality  process  engineering,

and  they're  primarily  sharing  images.

If  we  look  at  job  title,

it's  a  similar  story, but  this  particular  job  title

is  maybe  doing  a  little  bit  more  time running  design  experiments.

Then  by  department, maybe  this  is  an  analytics  department

or  a  chemistry  department, but  they're  doing  a  lot  of  DOE,

a  lot  of  basic  data  analysis,

a  lot  of  data  base,   and  then  sharing  images.

As  a  leader  in  your  organization,

you  might  ask  yourself,  are  images the  best  way  to  share  this  data?

If  not,  this  shines  a  light  on  the  fact

that  your  company  is  spending a  lot  of  time  sharing  images.

Maybe  A,  this  could  be  automated,

or  B,  maybe  we  want  to  push  people in  a  different  direction

sharing  some  other  data  format,  writing  particular  reports  or  etc.

But  it  just  shines  a  light on  the  things  that  are  going  on.

Then  you  and  the  support  team  will  work  together  to  better  understand,

they'll  probably  have  lots  of  questions,

is  this  what  you  want?

Is  this  what  you  expected?

Should  you  have  people  doing  more  quality if  you're,  say,  a  manufacturing  firm?

Do  you  want  people  to  be  quality  minded or  do  you  have  a  quality  department?

Those  sorts  of  questions  will  start to  flesh  themselves  out

and  they'll  help  you  craft

how  they  might  be  able to  provide  that  support  to  you.

Or  you  might  just  take  these results  and  say,  thank  you  so  much.

Now  we're  going  to  go do  what  we  think  we  need  to  do.

Going  a  little  bit  deeper.

We'll  call  this  the  maybe  8,000  foot  view.

This  example  is  broken  up  by  department  and  location,

and  it's  showing  how  much  time  people

are  spending  doing data  exploration  and  visualization.

We  can  see  in  the  manufacturing  department

and  in  the  fermentation  PD  department,

a  few  people  are  spending  over  eight  hours  a  week.

Whereas  over  at  R&D,  they're  spending  considerably  less  time.

Maybe  that's  fine, maybe  that  isn't  fine.

But  again,  it  just  helps  you  see  exactly how  your  people  are  spending  their  time.

If  you  have  someone  located  in  the  east  in  the  firm  department

and  they're  spending  zero  time doing  data  exploration and  visualization,

that  might  be  a  problem.

I  would  think  they  would  need  to  share their  data  and  look  at  that  data.

So  you  might  have  some  questions and  you  go  ask  that  team

to  better  understand   exactly  how  they're  doing  things.

Then  we  get  to  go  a  little  bit  deeper, and  these  are  my  favorite  images.

What  we're  looking  at  is  proficiency  on  the  left

and  usage  on  the  bottom.

Y  versus  X.

Then  these  cells  are  colored

by  how  many  people  are  spending  time or  grafted  with  their  competency.

If  we  look  on  the  left, we  see  quality  process  and  engineering.

For  this  particular  organization,

by  and  large,  people  are  not doing  much  quality  work.

This  is  where  I  always  ask,

do  you  want  your  company   to  be  quality  minded,

or  is  quality  focused  on  a  single  department?

If  you  want  your  people  to  be quality  minded,  this  might  be  a  red  flag.

No  one  is  an  advanced  user.

People  are  spending  predominantly   less  than  an  hour  a  week,

and  the  majority of  the  people  aren't  doing  it  at  all.

This  would  be  a  situation   where  I  might  come  in  and  say,

can  I  teach  your  people  about  the  quality  tools  in  JMP

so they  can  better  understand

how  to  build   and  interpret  a  control  chart?

How  they  might  look at  metrics  like  CPK  and  PPK.

Are  we  hitting  spec  limits? Are  we  not  hitting  spec  limits?

How  do  we  understand  that  more  deeply

so  we  can  make  more  intelligent  decisions to  solve  problems  and  understand  things.

Contrasting  that  on  the  right

with  this  basic  data  analysis  and  modeling  image,

we  see,  I  would  call,  more  maturity.

There  are  very  few  people  that  aren't  performing  this  task  at  all.

The  majority  of  the  people   are  intermediate  too  with  some  advance,

and  there's  also  a  lot  of  beginners.

But  what  I  see  here  is  critical  mass.

I  see  that  this  organization  has  enough  competence

and  enough  people that  understand  it  well  enough

that  they  can  help  draw  those  novice  users down  to  the  intermediate  level

and we  have  some  advanced  users

that  can  bring  the  intermediate  down  to  their  level.

We  also  have  people  spending, predominantly  1-4  hours.

Not  that  many  people  are  spending   20 %  of  their  week  performing  this  task.

When  I  see  that,  I  ask, could  this  be  automated?

We'll  get  to  more of  that  in  just  a  moment.

This  really  helps  people understand  where  they  are.

Do  they  have  maturity  in  this  analytical  capability

or  do  they  need  support?

Are  they  where  they  thought  they  would  be

or  do  they  need  to  move  their  people  through  support

to  a  more  advanced understanding  and  competency?

This  is  probably  one of  my  favorite  images.

What  we're  looking  at  here  is on  the  left  on  the  Y  axis,

is  the  amount  of  time  people  are  using a  particular  capability  per  week.

On  the  X  are  those  different  capabilities

that  we  saw in  the  JMP  analytical  workflow.

For  now,  you  can  just  ignore  the  color.

Those  are  color  coded  by  the  amount of  time  they've  been  using  JMP.

That's  one  of  the  only   JMP  specific  questions

in  the  entire  survey.

But  what  we  see  here,

and  I  want  to  draw  your  attention  right  here,

is  there  are  six  people  spending  eight  plus  hours  a  week

performing  data  access.

If  you  have  1  person  spending 8   hours  a  week,

that's  20 %  of  the  week.

That  means  five  dots equate  to  one  annual  salary.

Is  one  annual  salary   how  you  want  to  be  spending…

Do  you  want  to  be  spending that  amount  of  time  on  data  access?

Probably  not.

I  mean,  it's  not  cheap  to  hire  someone.

It's  not  cheap  to  support  them, provide  benefits  and  training,

and  keep  them  motivated  and  keep  them growing  within  the  organization.

This  is  a  very  impactful  image  because it  shows  us  where  can  we  automate.

Clearly,  you  can  see   up  in  the  very  upper  left,

that  green  dot,  someone  has already  automated  data  access.

Whereas  we're  spending

1.2  annual  salaries  on  data  access,

and  many  of  them  are  new  users.

Half  of  them  are  only  1-3  years.

So  could  we  come  in   and  teach  people  about  automation?

Could  the  person   that  has  already  automated  this

sit  down  with  these  other  six  people

and  teach  them  how  they have  automated  their  process?

Because  if  you  can  free  up   an  entire  annual  salary,

think  of  what  you  can  do.

I've  worked  with  people that  are  in  hiring.

I've  worked  with  people  that  manage  teams.

The  common  thread  I  hear is  we  need  more  people.

Either  A,  we  don't  have  the  budget,

or  B,  and  right  now  in  this  environment, it's  just  sometimes  hard  to  hire  people.

If  you  can  liberate  an  entire  person

from  a  particular  task, just  think  of  what  more  you  could  do.

They  could  solve  more  problems,

they  could  help  bring automation  elsewhere.

They  can  automate  data  access for  everybody  potentially.

This  is  a  really  useful  thing.

On  the  flip  side, if  we  look  at,  say,

predictive  modeling  and  machine  learning, it's  right  here  in  the  center,

we  can  see  there  are  only  two  people spending  any  time  at  all:

one,  one to  four  hours  a  week   and  one  less  than  an  hour  a  week.

We're  spending  a  fraction  of  the  time,

particularly  compared  to  data  access,

on  predictive  modeling   and  machine  learning.

Perhaps  this  is  not  necessary in  your  organization.

Perhaps  it's  very  necessary

if  you  are  trying  to  understand

why  aren't  we  hitting  our  manufacturing  KPIs?

Why  are  we  having  these issues  in  our  process?

We're  not  able  to  understand  exactly  why, despite  having  everything  set  up

the  way  we  think  should  work, we're  not  hitting  our  metrics.

Well,  again,  this  is   a  ripe  opportunity  for  support.

Yet  on  the  other  flip  side,

so  I  think  we're  looking at  a  triangle  here,  a  prism  here,

basic  data  analysis  and  modeling, I  see  they're  doing  fantastic.

They  have  a  lot  of  people

that  are  performing   basic  data  analysis  and  modeling.

We  have,  as  we  saw  earlier, some  good  there.

We're  not  spending  a  lot  of  time.

These  are  one  of  the  tasks   where  automation  may  not  be  possible.

It  might  be,  but  it  might  be  people  are

dealing  with  problems  that  are  unique  every  single  time.

Again,  this  is  an  opportunity  where  I,

as  someone  trying  to  support  a  customer, might  be  starting  to  ask  some  questions

and  understand  if  automation is  even  possible.

But  by  and  large,  this  is  a  good  vertical  in  this  particular  graph,

as  well  as  over  on  the  far  right, sharing  and  communicating  results.

That's  another  one  that  is  very  easy  to  automate,

but  the  majority of  people  are  sharing  results.

I  might  have  some  questions

about  why  there's  maybe   about  40 %  that  aren't

and  is  that  important  to  you?

But  this  just  really  puts  the  entire  story

in  one  image  that  really  helps  you  understand

where  opportunity  is  to  A,  automate,  B,  train,

and  C,  say,  great,  we're  doing  well,

we  don't  need  to  spend  time  on  that.

Then  finally,  where  do  your  people   think  they  need  support?

On  the  left, we  have  those  capabilities.

On  the  bottom,  we  have  four  questions.

Is  this  critical  to  my  task and  training  is  needed?

This  is  critical  to  my  task and  basic  training  is  needed.

I  don't  need  this, or  maybe  I'm  just  interested.

I've  organized  these  based   on  the  majority  of  people

or  the  number  of  people  that  feel  that  advanced  training  is  needed.

This  is  from  a  different  organization.

But  I  imagine  if  you   are  a  tech-driven  company,

an  analytically- driven  company, you  would  probably  think

that  basic  data  analysis  and  modeling

is  not  something that  you  need  to  worry  about.

But  here,  the  majority  of  the  people

are  saying  this  is  critical  to  my  task and  I  need  advanced  training.

Again,  it's  just  shining  a  spotlight on  the  areas  where  you  might  need

to  support  your  organization,

where  you  might  need  to  support  your  people

because  they're  saying very  clearly,  I  need  help.

Whereas  mass  customization, automation  and  scripting,

reliability  analysis,  these  aren't  things that  people  need  as  much  support  on.

You  can  know  that  I  don't  need to  spend  time  in  this  area  or  that  area.

I  need  to  focus  up  here.

It  turns  out  a  lot  of  these  are  fairly  basic  tasks

that  I  think  a  lot  of  people  think

that  people  are  fully  capable  and  competent  of,

but  they're  clearly  saying,   no,  no,  I  need  some  help.

The  benefits  of  the  JAWS  is,

it  identifies  strengths  and  areas for  improvement  within  your  organization.

You're  able  to  work  with  your  JMP  support  team

and  provide  support  in  those  areas.

Your  support  team  has  the  training, has  the  tools,  has  the  backing  support

of  a  large  organization  that  is  focused solely  on  expanding  the  use  of  JMP

to  come  in  and  guide  your  people in  whatever  support  you  need.

We  are  here  to  help  you  out.

Then  the  beauty  of  this  is  if  you administer  this  survey  annually,

you're  going  to  start  to  be  able  to  track  progress.

You'll  be  able  to  see  we  needed a  lot  of  help  in  design  of  experiment.

A  year  later,  we  see  improvement.

The  support  has  worked,

and  we  just  need  to  go  a  little  bit  farther.

We  can  say  DOE  is  now  doing  great.

Let's  focus  our  attention  elsewhere.

Some  best  practices.

This  is  very  practical,   but  what  we  have  learned  is,

don't  allow  a  long  time for  the  survey  to  be  filled  out.

We  say  send  it  out  on  Monday,

send  a  reminder  email  on  Wednesday, and  close  the  survey  out  on  Friday.

How  this  would  work  is  you  would  work   with  your  JMP  support  team

to  craft  those  questions  about  region,

about  department,  about  job  title,

and  then  they'll  just   provide  you  the  survey.,

You  send  that  survey  out and  people  fill  it  out,

we  collect  the  data,  it's  all  anonymous, and  then  we  analyze  those  results

and  then  come  back  and  share  those  results  with  you.

But  keep  it  short.

Don't  allow  people  a  long  time  because people  get  busy  and  they  just  forget.

It's  really  important,  I  think, to  get  those  three  questions  right.

We  don't  want  to  be  too  much  of  a  grouper

because  then  you  don't  have

the  level  of  understanding that  you  might  want.

You  want  to  be  a  splitter.

Really  dig  down,   get  those  departments  right,

get  those  job  titles  right, get  those  regions  right,

because  you  can  always   group  things  together  later

to  understand  the  survey  results,

but  you  can't  split  them once  you've  collected  that  data.

This  one  is  probably  the  most  important,

is  it's  incredibly  valuable   to  get  management  buy-in

and  then  develop  a  team   to  help  administer  that  survey.

You  need  people  that  people are  going  to  listen  to.

If  you  have  someone  in  your  company

who  is,  for  lack  of  a  better  term, not  well  liked  and  they  send  out  a  survey,

people  probably  aren't  going  to  be  as  likely  to  participate

as  if  you  have  a  team  of   3-5  people

that  are  leaders  within  the  departments

or  leaders  within  their  organizations,

and  people  are  going   to  hear  that  and  listen  to  that.

It  helps  even  more  when  you  have management  saying,  you  need  to  do  this.

The  flip  side  of  this  is  when  you  get  the  data  back,

you  want  management  to  be  involved.

You  want  someone  that  has   some  decision- making  capabilities

to  see  the  results

and  understand  what's  going  on

so  that  they  can  help   craft  the  big  picture.

It's  great  when  JMP  usage  expands from  the  bottom  up,

but  when  you're  trying  to  drive  something at  an  organizational  level,

you  really  need  people  that  are  higher  up to  help  drive  the  usage  from  the  top  down.

We  strongly  encourage  that  you administer  this  organization  wide.

Ignore  JMP  usage.

A  lot  of  our  companies  have

email  list  group   of   strictly  their  JMP  users.

But  really,  that's  often  just a  snippet  of  the  company.

We  have  found  people  and  human  resources

that  when  they  see  what  JMP  can  do, like  I've  got  to  have  that.

We  don't  always  think  of  an  analytical software  tool  as  being  something

that  maybe  HR  would  want   or  would  gain  benefit  from,  but  they  do.

By  understanding   where  your  entire  organization  is,

you're  going  to  be  able  to  make  better  decisions,

you're  going  to  be  able  to  make better  support  calls,

and  you're  going  to  be  able  to  move  your  entire  organization

versus  just  moving single  department  or  a  single  job  title.

Lastly,  I'm  sorry,  second  to  last, lean  on  your  JMP  support  team.

They  administer  these  surveys  frequently.

They  know  how  to  interpret  the  results.

They  know  how  to  help  you.

Even  if  you  don't  want  to  use  them to  provide  that  support,

if  you  have  an  internal  education,

maybe  you  want  to  build   internal  education  up

as  a  result  of  the  survey,

but  lean  on  them  to  help  guide  you  because  this  is  what  we  do.

We  support  companies  like  yours to  help  them  build  analytical  excellence.

Lastly,  and  I've  said  this  a  few  times,

administer  the  survey  annually,

so  that  you  can  actually  track  your  progress.

It's  one  thing  to  have  an  analytical  snapshot.

It's  a  lot  better  to  have an  analytical  time  series.

Collecting  that  data  annually

is  going  to  really  help  you gage  is  this  successful?

Do  we  need  to  change  things?

Is  what  we're  doing  working.

Maybe  you  go  to  your  support  team

and  they  lead  the  training and  you  don't  see  growth.

So  you  turn  to  your  internal  education  team,

or  maybe  the  flip  side  is  true.

We  just  want  you  to  be  better, we  want  to  be  collaborators  with  you.

We  want  to  support  you

in  whatever  you  think  is  the  best  way to  execute  that  plan.

I  will  close  with  a  call  to  action   [inaudible 00:24:26]   survey.

It  can  really  help  an  organization.

I've  seen  it  help  an  organization.

I've  been  able  to  administer  close to  a  dozen  of  these,

and  all  of  them  have  resulted  in...

I'm  going  to  close with  a  call  to  action.

Connect  with  your  JMP  support  team

and  complete  the   JMP Analytical Workflow Survey.

Being  able  to  understand   where  you  are  as  an  organization

versus  where  you  want  to  be   is  incredibly  valuable.

At  the  end  of  the  day,

our  goal  is  to  help  you   democratize  analytics,

help  you  have  one  version  of  the  truth,

help  you  make   analytically- driven  decisions,

and  from  that,  gain  efficiency,

quicker  discovery, and  save  money,  save  time.

This  survey  is   an  incredibly  powerful  tool

to  help  you  achieve  those  ends.

We  have  the  expertise  to  help  you  not  only  administer  the  survey,

but  interpret  the  survey  and  create  a  plan

to  then  make  decisions   for  training  support,

and  help  drive  you  from  where  you  are  to  where  you  want  to  be.

Thank  you  very  much.