Pay scale presentation 7 questions to ask about salary data sources

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Pay scale presentation 7 questions to ask about salary data sources

  1. 1. 7  Ques/ons  to  Ask  When  Evalua/ng  Salary  Surveys   Presented  by:     Tim  Low,  VP  Marke0ng   0ml@payscale.com   With     Ka0e  Bardaro,  Director  of   Analy0cs  and  Lead  Economist    
  2. 2. AGENDA  o  The  7  Ques/ons  you  Must  Ask   o  Is  the  data  current?   o  Are  all  loca0ons  covered?   o  Does  the  data  match  your  unique  situa0on?   o  How  many  compensable  factors?   o  Where  does  the  data  come  from?   o  How  much  0me  do  I  need  to  give  to  get  the  data?   o  Is  the  data  complete?  o  Audience  Q  &  A  (Please  submit  ques/ons  through  chat)  
  3. 3. A  Brief  History  of  Salary  Data…  o  30  years  ago…   o  There  were  salary  surveys   o  Conducted  by  consultants.  Yearly.   o  You  paid  for  a  ‘slice’  of  data   o  You  paid  more  for  each  slice  o  10-­‐12  years  ago...   o  Online  data  emerged   o  Not  all  the  same  o  Today…   o  crowdsourcing,  big  data,  real-­‐/me  analy/cs,  etc.  
  4. 4. Ques/on  #1.  Is  the  Data  Current?   Old  data  might  not  reflect  current  trends  Tradi/onal   o  Annual   o  3-­‐6  months  to  complete   o  Must  be  aged  by  a  comp  professional   o  By  the  /me  you  use  it,  it  could  easily  be  one  year  old  PayScale   o  Collected  and  processed  con/nually   o  Always  at  market   o  No  need  to  age  
  5. 5. Ques/on  #2.  Are  all  Loca/ons  Covered?  You  need  compensa5on  data  that  covers  all  loca5ons,  major  and  rural,  to  get  the  right  fit  for  you.    Tradi/onal   o  Limited  geographies,  typically  major  ci/es   o  Data  must  be  adjusted  to  account  for  cost  of  living  differences  and   posi/on  demand  for  loca/ons  outside  of  that  scope  PayScale   o  Unlimited  geographies,  most  specific  loca/ons  covered   o  Matches  for  rural  loca/ons  are  more  precise   o  No  need  to  adjust  the  data  
  6. 6. Ques/on  #3.  Does  the  Data  Match  You?  Your  employees  may  have  a  unique  combina5on  of  knowledge,  skills  and  abili5es    Tradi/onal   o  It  may  include  pay  differen/als,  different  years  of  experience,   cer/fica/ons,  or  skills,  but  never  in  combina/on  with  each  other   o  If  the  posi/on  is  unique,  it  may  not  be  covered  PayScale   o  Combina/ons  of  skills  and  abili/es  are  covered   o  Broader  base  of  input  means  unique  posi/ons  can  likely  be  matched  
  7. 7. Ques/on  #4.  How  Many  Compensable  Factors?  The  more  factors  included,  the  more  accurate  the  salary  data  Tradi/onal   o  Must  find  slices  of  data  that  match  all  the  compensable  factors   o  Intensive  calcula/ons  needed  to  blend  the  data  PayScale   o  Matches  your  unique  job  to  a     market  salary   o  Your  employee’s  educa/on,  skills,     experience  level,  cer/fica/ons  and     more  are  matched   o  250  compensable  factors  with  more     than  2000  skills  and  3000  cer/fica/ons  
  8. 8. Ques/on  #5.  Where  do  they  get  the  data?  Data  transparency  lets  comp  pros  make  beCer  decisions  about  how  well  the  data  source  matches  their  employees  Tradi/onal   o  Data  collec/on  methods  are  well-­‐known  and  understood   o  However,  exact  sources  of  data  are  not  included  in  a  survey   o  Some  consultants  and  online  survey  providers  aggregate  informa/on   from  mul/ple  sources  and  don’t  provide  those  details  PayScale   o  Transparent   o  Our  methodology  is  public  and  data  sources  are  provided,  right  down  to   specific  user  profiles  (anonymous  of  course)  that  provided  the  info   o  PayScale  tells  you  why  it  used  the  source  as  a  match  and  gives  you   control  over  which  data  is  used  
  9. 9. The  PayScale  Way:  An  example…  
  10. 10. Using  the  45  closest  matching  profiles,  these  factors  drive  the  salary  #  for  your  par0cular  job  
  11. 11. PayScale  shows  you  actual  profiles  that  went  into  your  match  
  12. 12. Ques/on  #6.  How  much  /me  do  you  have  to  invest  to  get  the  data?  What  is  required  to  be  eligible  to  receive  the  data?  How  much  5me  to  do  you  have?  Tradi/onal   o  Paper,  spreadsheets   o  It  is  typically  required  or  requested  that  employers  par/cipate  in  their  surveys  before   receiving  results.  Comprehensive  data  about  the  company,  policies,  prac/ces  and  salaries     must  be  provided   o  The  employer  then  waits  typically  6  months  to  get  the  results   o  Time  must  then  be  spent  to  match  the  general  salary  data  to  the  specific  situa/on  PayScale   o  Cloud  sofware   o  Entering  a  job  /tle  unlocks  a  set  of  ques/ons  about  compensable  factors  affec/ng  pay  for   that  /tle   o  Adding  in  more  details  yields  greater  accuracy   o  PayScale  tells  you  instantly  what  that  job  should  be  paid,  including  recommended  ranges   o  No  aging  or  blending  required—data  is  real-­‐/me  and  at-­‐market  
  13. 13. Ques/on  #7.  How  complete  is  the  data?  OGen,  employers  compete  for  talent  in  more  than  one  labor  market    Tradi/onal   o  Charge  individually  for  each  ‘slice’  of  data  and  add  up  the  different   segments  you  need  to  create  a  final  price     o  It’s  some/mes  not  possible  to  access  the  en/re  database  of  salary   informa/on  PayScale   o  100%  of  data  is  available  to  each  PayScale  subscriber   o  36  million  salary  profiles   o  Accurate  salary  matches  for  all  your  posi/ons  are  very  likely   o  Providing  matches,  not  slices,  is  more  modern  and  more  customer-­‐friendly  
  14. 14. On   “Theyre  like  the  10  Tradi/onal   Oclock  news.  I  dont  wait  Salary   ‘/l  10  0clock  to  watch  the  Surveys…   news  anymore.  PayScale  is   informa/on  on  demand.  ”     Shad  Glass,   Director  of  HR,  Kimray,  Inc.  
  15. 15. Special  Access  for  You:   Get  the  Complete   Whitepaper   Presented  by:     Tim  Low,  VP  Marke0ng   0ml@payscale.com     Ka0e  Bardaro,  Director  of   Analy0cs  and  Lead  Economist  

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