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Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
Big data in HR: Why all the fuss?
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Big data in HR: Why all the fuss?

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Big Data is big buzz at the present. …

Big Data is big buzz at the present.

There's so much press, but so little clarity about what "big data" actually is (and what it can do for HR).

This presentation is an introduction to big data and data analytics. With no techno-babble, find out:
> What is big data?
> What do I really need to know?
> What can it do?
> How does it apply to Human Resources / HR?
> What are some examples of big data being used in the HR "space"?
> How will big data change HR in general?

Highly relevant for anyone involved in people management, human resources, organisational design and change management.

Published in: Business, Technology
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  • 1. DATA IN HR: WHY ALL THE FUSS?
  • 2. NOT BUSINESS AS USUAL Flickr  CC  lukepeterson  
  • 3. IN HOW HR WORKS WITH THE BUSINESS FUNDAMENTAL SHIFT Flickr  CC  mar2nluff  
  • 4. BUT
  • 5. “BIG DATA”
  • 6. IS
  • 7. BULLSHIT Flickr  CC  jmpznz  
  • 8. (IT’S ONLY A TECHNICAL DEFINITION ANYWAY) Flickr  CC  jmpznz  
  • 9. DON’T GET CAUGHT IN THE TECHNICALITIES
  • 10. WHAT MATTERS IS WHAT DATA LETS YOU DO
  • 11. 11 FINDING PATTERNS Flickr  CC  mister_tee  
  • 12. 12 FINDING PATTERNS EITHER INVISIBLE OR DIFFICULT TO SEE BY EYE Flickr  CC  mister_tee  
  • 13. WHEN YOU READ: ‘BIG DATA’ THINK: FINDING PATTERNS
  • 14. WHEN YOU READ: ‘DATA REVOLUTION’ THINK: FINDING PATTERNS
  • 15. WHEN YOU READ: ‘DATA ANALYTICS’ THINK: FINDING PATTERNS
  • 16. THINK MONEYBALL FOR THE WORKFORCE
  • 17. FOR HR, THIS MEANS…
  • 18. A NEW WAY OF LOOKING AT THE SAME PROBLEMS Flickr  CC  wvs  
  • 19. Less impact on day to day Transactional HR
  • 20. 20 Analytics is… Moving from data to understanding The difference between having data and gaining insight is often the difference between winning and losing. But HR adoption rates for analytics are discouraging. BUT Fundamental changes AT THE STRATEGIC LEVEL
  • 21. WHERE THIS DATA COMES FROM?
  • 22. HRIS
  • 23. HRIS TALENT MANAGEMENT
  • 24. HRIS TALENT MANAGEMENT EMAIL
  • 25. HRIS TALENT MANAGEMENT EMAIL FINANCIALS
  • 26. HRIS TALENT MANAGEMENT EMAIL FINANCIALS CRM
  • 27. HRIS TALENT MANAGEMENT EMAIL FINANCIALS CRM PHONE
  • 28. HRIS TALENT MANAGEMENT EMAIL FINANCIALS CRM PHONE SOCIAL
  • 29. HRIS TALENT MANAGEMENT EMAIL FINANCIALS CRM PHONE SOCIAL ETC.
  • 30. SOME PRACTICAL EXAMPLES…
  • 31. HIRING: WHO IS MOST LIKELY TO BE SUCCESSFUL? Flickr  CC  23912576@N05  
  • 32. TALENT MANAGEMENT: WHAT BEHAVIOURS REALLY DIFFERENTIATE YOUR TOP PERFORMERS? Flickr  CC  ironrodart  
  • 33. 33 Flickr  CC  :  s2gnygaard  Flickr  CC  jo_mur   DIVERSITY: WHERE DO THE BOYS CLUBS EXIST?
  • 34. MANY, MANY OTHERS…
  • 35. THE TIMELINE?
  • 36. “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don't let yourself be lulled into inaction.” - Bill gates Flickr  CC  thomashawk  
  • 37. From:  Bersin  &  Associates  “Big  Data  in  HR  Research  Study”   Stage 1: Reactive – Operational Reporting Operational reporting for measurement of efficiency and compliance, data exploration and integration, development of data dictionary THE FOUR STAGES OF DATA MATURITY
  • 38. From:  Bersin  &  Associates  “Big  Data  in  HR  Research  Study”   Stage 1: Reactive – Operational Reporting Operational reporting for measurement of efficiency and compliance, data exploration and integration, development of data dictionary Stage 2: Proactive – Advanced Reporting Operational reporting for benchmarking and decision-making, multi-dimensional analysis and dashboards THE FOUR STAGES OF DATA MATURITY
  • 39. From:  Bersin  &  Associates  “Big  Data  in  HR  Research  Study”   Stage 3: Strategic Analytics Segmentation, statistical analysis, development of “people models”, analysis of dimensions to understand cause and delivery of actionable solutions Stage 1: Reactive – Operational Reporting Operational reporting for measurement of efficiency and compliance, data exploration and integration, development of data dictionary Stage 2: Proactive – Advanced Reporting Operational reporting for benchmarking and decision-making, multi-dimensional analysis and dashboards THE FOUR STAGES OF DATA MATURITY
  • 40. From:  Bersin  &  Associates  “Big  Data  in  HR  Research  Study”   Stage 3: Strategic Analytics Segmentation, statistical analysis, development of “people models”, analysis of dimensions to understand cause and delivery of actionable solutions Stage 4: Predictive Analytics Development of predictive models, scenario planning, risk analysis and mitigation, integration with strategic planning Stage 1: Reactive – Operational Reporting Operational reporting for measurement of efficiency and compliance, data exploration and integration, development of data dictionary Stage 2: Proactive – Advanced Reporting Operational reporting for benchmarking and decision-making, multi-dimensional analysis and dashboards THE FOUR STAGES OF DATA MATURITY
  • 41. SOME THINGS TO REMEMBER:
  • 42. Start with the outcome in mind Flickr  CC  laffy4k  
  • 43. 43 Bigger Does not mean better Flickr  CC  bicycleimages  
  • 44. CEOs and CFOS Already speak DATA Flickr  CC  372527185@N05  
  • 45. QUESTIONS?
  • 46. INTERESTING COMPANIES TO LOOK AT: A  freestanding  analyst  firm  (un@l  recent   purchase  by  DeloiCe)  offering  selec@on   services,  research,  data  analysis,  industry   insights.       The  company  host  a  deep  collec@on  of   blogs  covering  data  driven  HR  and  talent   management.       hCp://www.bersin.com/Blog/     Evolv’s  workforce  performance  solu@ons   leverage  the  power  of  big  data  and   predic@ve  analy@cs  to  help  businesses   select,  retain  and  develop  a  more   produc@ve,  more  posi@ve  and  more   profitable  workforce.         The  blog  is  science  based,  focusing  on   prac@cal  applica@on.       hCp://www.evolvondemand.com/ thinking/blog    
  • 47. INTERESTING COMPANIES TO LOOK AT: Intrascope  builds  soPware  that  uses   email  and  phone  data  to  iden@fy  low   hanging  opportuni@es  to  improve  people   performance  -­‐  by  iden@fying  influencers,   boClenecks  and  micromanagement.       The  blog  features  prac@cal  ideas,  @ps  and   insights  designed  to  help  you  get  the   most  out  of  your  workforce.     www.intrascope.com.au   Kenexa  is  a  large  consul@ng,  content,  and   technology  company  which  plays  in  many   different  parts  of  the  talent  management   market.  The  company  was  recently   acquired  by  IBM.         The  blog  is  insighWul,  touches  on  a  broad   range  of  data/HR  topics,  and  is  generally   easy  to  read.     hCp://blog.kenexa.com/  
  • 48. INTERESTING COMPANIES TO LOOK AT: RoundPegg  provides  a  Culture   Intelligence  PlaWorm  upon  which   companies  can  ac@vely  manage  culture   shiPs,  iden@fy  sub-­‐cultures,  make  hires   who  scien@fically  fit  and  engage  their   employees  (think  eHarmony  For  Jobs).     Interes@ng  blog  that  covers  the  scien@fic   side  of  culture.     hCp://roundpegg.com/blog/     Visier  crunches  HR  data  for  enterprise   workers  into  a  consumer-­‐friendly   interface  designed  to  make  measuring,   repor@ng  on,  and  improving  the  ac@vi@es   of  a  given  workplace  easier,  faster,  and   more  accurate.       The  blog  can  tend  to  self-­‐promo@onal,   but  does  have  good  insights  for  geng   up  to  speed  with  workforce  analy@cs.     hCp://info.visier.com/blog/          
  • 49. Contact Details ©   2 0 1 3   I N T R A S C O P E .   A L L   R I G H T S   R E S E R V E D .     Intrascope  Analy@cs   Level  10/50  Market  Street   Melbourne  3000     +61  3  9111  5659     www.intrascope.com.au    

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