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© 2013, McBassi & Company
HR Analytics:
Why, What & How
Laurie Bassi
April 18, 2013
Why?
• Human capital management drives value creation
• Analytics drives better HCM
• Employee surveys have tremendous (but typically under-
utilized) potential to create actionable business intelligence
• Big data & predictive analytics are coming to the “people
side” of business
© 2013, McBassi & Company 2
© 2013, McBassi & Company3
1.10
2.29
0.00
0.50
1.00
1.50
2.00
2.50
1980 2012
Market to Book Ratio
9%
56%
0%
20%
40%
60%
80%
100%
1980 2012
Intangibles as % of Market Value
Role of intangibles has risen dramatically
Intangibles drive value
Human capital is the source of all intangibles
Human capital management is now an essential organizational competence
Analytics is now an essential HR competence
© 2013, McBassi & Company
We’ve invested on this insight for over 10 years
4
© 2013, McBassi & Company
Companies that use HC analytics
outperform
5
© 2013, McBassi & Company
Example: Common sense can lead to very wrong conclusions
6
© 2013, McBassi & Company
Why?
Opportunity Plus Necessity
Opportunity
Technological advances have greatly reduced the cost of doing
analytics
Necessity
As HCM has emerged as one of the few sustainable sources of
competitive advantage, decision-making by gut and intuition is
grossly inadequate
7
© 2013, McBassi & Company
What & How?
© 2013, McBassi & Company
What picture best describes analytics?
It’s not about
reporting, dashboards
or complex math.
It IS about data-derived
insights that drive better
decisions.
9
Fundamentally, analytics is about:
• Asking better questions
• Putting together disparate pieces of data to
produce actionable insight
© 2013, McBassi & Company 10
© 2013, McBassi & Company
Example:
Identify the human drivers of
business results
11
© 2013, McBassi & Company
Examples:
WHO USED
ANALYTICS TO
RESULT #1 RESULT #2
Payroll provider Improve leadership
development
Significantly
increased
leadership
effectiveness
4 percent more productive workforce
and a $20 million improvement to
the bottom line
Telecom
company
Improve customer
service
Over 10% increase
in service
productivity
More than $40 million in operating
profit improvement
US DoD
corporate
university
Reduce scrap
learning
50% reduction in
wasted
investments
Hundreds of millions of dollars in cost
savings for American taxpayers
12Examples provided by Knowledge Advisors
© 2013, McBassi & Company
4 Step Process
The Economic
Imperative
Statistical linkage
to results
Fact-based
prioritized
recommendations
Insightful, easy-to-
understand reports
Smarter
employee
surveys
13
Step #1 - Asking the right questions
McBassi People Index®
Typical employee engagement surveys are too narrow - not
up to the task of creating actionable business intelligence.
© 2013, McBassi & Company 14
A more innovative version of Step #1
McBassi Good Company Assessment
Good
Employer
Good
Seller
Good
Steward
Business
Results
Includes all elements of
MPI, plus additional
measures of “Good
Company”
- Diagnostics
- Outcomes
15
Step #2 - Statistical linkage analysis
Depending on specifics of data, there are three primary
statistical methods for linking people factors and business
outcomes:
1. Multivariate analysis
2. Correlations
3. Comparison of means/t-tests
Analytics is the “missing link” that enables you to identify the top
human drivers of your business results.
16
© 2013, McBassi & Company
Example of unified analysis database
Actionable
Insights
Customer
Satisfaction
Attainment
of Financial
Targets
Managers’
Profiles
Engagement
Onboarding
Exit & 360
Surveys
Learning &
Development
Profiles
Turnover
17
Two major types of business intelligence
analysis
1. Creating insightful reports from your employee survey
– Conduct statistical linkage analysis based on outcomes collected in the survey
itself
• Engagement (including intent to stay, willingness to refer a friend)
• Support for customer service
• Etc.
2. Ongoing (post-survey) analysis of the drivers of business
results
– Make decisions now that will ultimately make possible statistical linkage analysis
based on “hard” outcomes (collected outside the survey), even if that’s not part
of the first round
• Turnover
• Sales
• Cost containment
• Customer satisfaction
• Etc.
18
Step #3 - Identifying areas of opportunity
Top
Drivers
Areas of
Weakness
Top Areas of
Opportunity
This step systematically combines information about the
top drivers of business results with measures of relative weakness.
19
© 2013, McBassi & Company
Example: Common sense can lead to very wrong conclusions
20
Step #4 - Insightful reporting
Highly visual, easy-to-understand reports serve as a
catalyst for change
One of the most important lessons we’ve learned: less is more
when it comes to reporting and recommendations – tell
what’s important, not everything you know
• Avoid “data dumps”
• Focus on simple reporting that makes it easy for busy managers
and leaders to know what actions to take.
21
(Sample portions of) report elements
22
© 2013, McBassi & Company
So What?
• The “people side” of the business has become too
important to be left to guesswork and intuition
• Companies that use analytics wisely will continue to
outperform their competitors that don’t
• Analytics helps us speak the language of business – it
elevates our function
• It helps firms operate in the “sweet spot” – the
intersection of sustainably profitable & enlightened
management of people
© 2013, McBassi & Company 24
© 2013, McBassi & Company
Best Practices
&
Pitfalls to Avoid
Best Practices
• Learn to think of your organization as a “naturally occurring
experiment”
• Start small and build credibility
– In the early stages, focus on solving immediate problems
• Have the end in mind and build an infrastructure to support it
• Collaborate with other analytic groups within your company
• Build/buy analytics competence within HR
• Provide the right level of executive leadership support
• Engage a leader who has an analytics understanding, passion,
and interest
© 2013, McBassi & Company 26
Avoid
• Using analytics to “prove HR’s worth”
• Assigning this mission to a lower level technician
• Confusing:
– Data dumps with insight
– Benchmarking with analytics
• Allowing the perfect to become the enemy of the good
© 2013, McBassi & Company 27
© 2013, McBassi & Company
Resources
Useful resources
Good Company
Bassi, et al.
Analytics at Work
Davenport, et al.
Drive
Pink
Predictive Evaluation
Basarab
HR Analytics Handbook
Bassi, et al.
Investing in People
Cascio & Boudreau
The Business of Learning
Vance
© 2013, McBassi & Company 29
Free Resources
McBassi Articles
• How to Create More Value From Employee Surveys (Talent
Management, September 2012)
• Other briefs & white papers: mcbassi.com/free-resources/
Knowledge Advisor Resources
• Talent Analytics Module—June 2013
• What is Talent Analytics and Why Do We Measure?
Talent Development Reporting Principles
• centerfortalentreporting.org/
© 2013, McBassi & Company 30
Laurie Bassi
lbassi@mcbassi.com

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Hr analytics whywhathow

  • 1. © 2013, McBassi & Company HR Analytics: Why, What & How Laurie Bassi April 18, 2013
  • 2. Why? • Human capital management drives value creation • Analytics drives better HCM • Employee surveys have tremendous (but typically under- utilized) potential to create actionable business intelligence • Big data & predictive analytics are coming to the “people side” of business © 2013, McBassi & Company 2
  • 3. © 2013, McBassi & Company3 1.10 2.29 0.00 0.50 1.00 1.50 2.00 2.50 1980 2012 Market to Book Ratio 9% 56% 0% 20% 40% 60% 80% 100% 1980 2012 Intangibles as % of Market Value Role of intangibles has risen dramatically Intangibles drive value Human capital is the source of all intangibles Human capital management is now an essential organizational competence Analytics is now an essential HR competence
  • 4. © 2013, McBassi & Company We’ve invested on this insight for over 10 years 4
  • 5. © 2013, McBassi & Company Companies that use HC analytics outperform 5
  • 6. © 2013, McBassi & Company Example: Common sense can lead to very wrong conclusions 6
  • 7. © 2013, McBassi & Company Why? Opportunity Plus Necessity Opportunity Technological advances have greatly reduced the cost of doing analytics Necessity As HCM has emerged as one of the few sustainable sources of competitive advantage, decision-making by gut and intuition is grossly inadequate 7
  • 8. © 2013, McBassi & Company What & How?
  • 9. © 2013, McBassi & Company What picture best describes analytics? It’s not about reporting, dashboards or complex math. It IS about data-derived insights that drive better decisions. 9
  • 10. Fundamentally, analytics is about: • Asking better questions • Putting together disparate pieces of data to produce actionable insight © 2013, McBassi & Company 10
  • 11. © 2013, McBassi & Company Example: Identify the human drivers of business results 11
  • 12. © 2013, McBassi & Company Examples: WHO USED ANALYTICS TO RESULT #1 RESULT #2 Payroll provider Improve leadership development Significantly increased leadership effectiveness 4 percent more productive workforce and a $20 million improvement to the bottom line Telecom company Improve customer service Over 10% increase in service productivity More than $40 million in operating profit improvement US DoD corporate university Reduce scrap learning 50% reduction in wasted investments Hundreds of millions of dollars in cost savings for American taxpayers 12Examples provided by Knowledge Advisors
  • 13. © 2013, McBassi & Company 4 Step Process The Economic Imperative Statistical linkage to results Fact-based prioritized recommendations Insightful, easy-to- understand reports Smarter employee surveys 13
  • 14. Step #1 - Asking the right questions McBassi People Index® Typical employee engagement surveys are too narrow - not up to the task of creating actionable business intelligence. © 2013, McBassi & Company 14
  • 15. A more innovative version of Step #1 McBassi Good Company Assessment Good Employer Good Seller Good Steward Business Results Includes all elements of MPI, plus additional measures of “Good Company” - Diagnostics - Outcomes 15
  • 16. Step #2 - Statistical linkage analysis Depending on specifics of data, there are three primary statistical methods for linking people factors and business outcomes: 1. Multivariate analysis 2. Correlations 3. Comparison of means/t-tests Analytics is the “missing link” that enables you to identify the top human drivers of your business results. 16
  • 17. © 2013, McBassi & Company Example of unified analysis database Actionable Insights Customer Satisfaction Attainment of Financial Targets Managers’ Profiles Engagement Onboarding Exit & 360 Surveys Learning & Development Profiles Turnover 17
  • 18. Two major types of business intelligence analysis 1. Creating insightful reports from your employee survey – Conduct statistical linkage analysis based on outcomes collected in the survey itself • Engagement (including intent to stay, willingness to refer a friend) • Support for customer service • Etc. 2. Ongoing (post-survey) analysis of the drivers of business results – Make decisions now that will ultimately make possible statistical linkage analysis based on “hard” outcomes (collected outside the survey), even if that’s not part of the first round • Turnover • Sales • Cost containment • Customer satisfaction • Etc. 18
  • 19. Step #3 - Identifying areas of opportunity Top Drivers Areas of Weakness Top Areas of Opportunity This step systematically combines information about the top drivers of business results with measures of relative weakness. 19
  • 20. © 2013, McBassi & Company Example: Common sense can lead to very wrong conclusions 20
  • 21. Step #4 - Insightful reporting Highly visual, easy-to-understand reports serve as a catalyst for change One of the most important lessons we’ve learned: less is more when it comes to reporting and recommendations – tell what’s important, not everything you know • Avoid “data dumps” • Focus on simple reporting that makes it easy for busy managers and leaders to know what actions to take. 21
  • 22. (Sample portions of) report elements 22
  • 23. © 2013, McBassi & Company So What?
  • 24. • The “people side” of the business has become too important to be left to guesswork and intuition • Companies that use analytics wisely will continue to outperform their competitors that don’t • Analytics helps us speak the language of business – it elevates our function • It helps firms operate in the “sweet spot” – the intersection of sustainably profitable & enlightened management of people © 2013, McBassi & Company 24
  • 25. © 2013, McBassi & Company Best Practices & Pitfalls to Avoid
  • 26. Best Practices • Learn to think of your organization as a “naturally occurring experiment” • Start small and build credibility – In the early stages, focus on solving immediate problems • Have the end in mind and build an infrastructure to support it • Collaborate with other analytic groups within your company • Build/buy analytics competence within HR • Provide the right level of executive leadership support • Engage a leader who has an analytics understanding, passion, and interest © 2013, McBassi & Company 26
  • 27. Avoid • Using analytics to “prove HR’s worth” • Assigning this mission to a lower level technician • Confusing: – Data dumps with insight – Benchmarking with analytics • Allowing the perfect to become the enemy of the good © 2013, McBassi & Company 27
  • 28. © 2013, McBassi & Company Resources
  • 29. Useful resources Good Company Bassi, et al. Analytics at Work Davenport, et al. Drive Pink Predictive Evaluation Basarab HR Analytics Handbook Bassi, et al. Investing in People Cascio & Boudreau The Business of Learning Vance © 2013, McBassi & Company 29
  • 30. Free Resources McBassi Articles • How to Create More Value From Employee Surveys (Talent Management, September 2012) • Other briefs & white papers: mcbassi.com/free-resources/ Knowledge Advisor Resources • Talent Analytics Module—June 2013 • What is Talent Analytics and Why Do We Measure? Talent Development Reporting Principles • centerfortalentreporting.org/ © 2013, McBassi & Company 30