CFO VISION 2014 Navigate your world...•2 people •Focus: same as previous plus global HR...
Transcript of CFO VISION 2014 Navigate your world...•2 people •Focus: same as previous plus global HR...
November 19–21 | Washington, D.C.
CFO VISION 2014
Navigate your world
Vice President, Talent and HR Research
Bersin by Deloitte
Deloitte Consulting LLP
Stacia Sherman Garr
Talent analytics: Leveraging data
to develop critical staff, reduce costs,
and increase productivity
Tina Witney Finance Transformation Practice Leader
Human Capital
Deloitte Consulting LLP
Copyright © 2014 Deloitte Development LLC. All rights reserved.
• Welcome
• Setting the context
• Talent Analytics Maturity Model
• How organizations increase their maturity
• Partnering with HR for better analytics
• Key takeaways
Agenda
3 3
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Ninety-three percent of finance leaders agree that talent
is important to their finance strategy
It is my top concern 34% Somewhat
important 58%
Neutral 6%
Unimportant 2%
“How important is finance talent management to your finance strategy?”
Source: “Business Partners Needed: Results of Deloitte’s 2013
Global Finance Talent Survey,” Deloitte, 2013
4 4
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Yet, at least four out of 10 finance leaders don’t believe their
organization manages talent well
40%
42%
54%
54%
54%
55%
56%
59%
Deploys finance talent to key opportunities(outside the finance organization)
Plans in advance for talent needs
Recruits the right talent
Connects finance talent with otherprofessionals within the company
Develops future finance leaders
Retains the right finance talent
Deploys finance talent to key opportunities(in the finance organization)
Hires the right talent
“Indicate your agreement with the following statements about your finance organization's approach to talent management.”
Source: “Business Partners Needed: Results of Deloitte’s 2013 Global Finance Talent Survey,” Deloitte, 2013
Talent analytics can help the finance function, and all of the business,
address these critical talent challenges
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Copyright © 2014 Deloitte Development LLC. All rights reserved. 6 Talent Analytics
The hype
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Which functions have strong analytics capabilities?
The reality
15%
56%
58%
77%
81%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
HR
Marketing
Sales
Operations
Finance
Source: High-Impact Talent Analytics, Bersin by Deloitte, 2013
7
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Operational reporting Reactive reporting of operational and compliance measures •
Focus on data accuracy, consistency, timeliness
Advanced reporting Proactive reporting for decision making • Analysis of trends
and benchmarks • Customizable, self-service dashboards
Advanced analytics Statistical analysis to solve business problems • Identification of issues
and actionable solutions • Centralized staffing and integrated data
Predictive analytics Development of predictive models • Scenario planning • Integration
with business and workforce planning • Data governance model
Level 1
Level 2
Level 3
Level 4
Source: High-Impact Talent Analytics, Bersin by Deloitte, 2013
4%
10%
30%
56%
Bersin’s Talent Analytics Maturity Model
8
Where do you think your overall organization is currently
on the Talent Analytics Maturity Model?
What about your finance organization?
Questions for the room
Copyright © 2014 Deloitte Development LLC. All rights reserved.
The value of mature talent analytics
Today, just 4 percent of HR organizations have a mature talent analytics function,
and yet these organizations are…
2X more likely to
improve their
recruiting
efforts
2X more likely to
improve their
leadership
pipelines
3X more likely to
realize cost
savings and
efficiency
gains
generating
30% higher stock
returns than
the S&P 500
over the past
three years
Source: “High-Impact Talent Analytics,” Bersin by Deloitte, 2013
10
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Case in point: Reducing turnover in a large global pharmaceutical
company’s China operations using predictive analytics
Rank Variable Relationship with voluntary attrition Individuals
affected
1 Length of time in the
position
If an individual spends more than two years in a
position, the likelihood of voluntary attrition
increases considerably.
1,630
2 Marital status is single Individuals who have a marital status of “single”
have a higher likelihood of voluntary attrition.
2,363
3 Rehire status Individuals who were previously employed with
the company and were rehired have a higher
likelihood of voluntary attrition.
94
4 Low supervisor tenure Individuals with supervisors who have been with
the company for a shorter amount of time have a
higher likelihood of voluntary attrition.
1,058
5 Low performance/
bonus
Individuals who have lower performance ratings
and lower bonuses have a higher likelihood of
voluntary attrition.
907
Source: High-Impact Talent Analytics, Bersin by Deloitte, 2013
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Advancing maturity requires a long-term investment mindset
Level 2
Advanced reporting
Level 3
Advanced analytics
Level 4
Predictive analytics
Level 1
Operational reporting
Level of Effort
Level of Value
Choke point
Source: Bersin by Deloitte, 2014
12
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Capabilities and analytics staff size increase with higher
levels of maturity
Level 1:
Operational
reporting
Level 2:
Advanced
reporting
Level 3:
Advanced
analytics
Level 4:
Predictive
analytics
• Knowledge of data
sources and systems
• Understanding of
stakeholder requests
• Ability to create
reports and access
data for requests
• Deep knowledge of
data sources and
systems
• Ability to create
customizable
reports and
dashboards
• Ability to draw
insights from trends
and benchmarks
Background in:
• Statistics
• Database
• IT/systems
• Consulting
• Telling the story
• Business
• HR
Background in:
• Advanced modeling
• Data visualization
• Statistics
• Database
• IT/systems
• Consulting
• Telling the story
• Business
• HR
Source: “High-Impact Talent Analytics: Staffing & Organizing Your Talent Analytics Function,” Bersin by Deloitte, 2014
An
aly
tics T
eam
Siz
e
Cri
tical C
ap
ab
ilit
ies
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• 1 person
• Focus:
advanced HR
studies and
corporate HR
scorecard
• Goals from Chief
Human
Resources
Officer (CHRO)
• Audience:
CHRO
• 2 people
• Focus: same as
previous plus job
analysis,
competency
assessment, and
the organization
culture
• Goals from
CHRO
• Audience: CHRO
• 2 people
• Focus: same as
previous plus
global HR
scorecard,
workforce
forecasting, project
management, and
training
effectiveness
• Goals from CHRO
and HR staff
• Audience: mostly
HR, some
business and
functional leaders
• 1 person, plus 2
people in India
• Focus: same as
previous plus
talent acquisition
• Goals from CHRO,
business and
functional leaders
• Audience: mostly
HR, some
business and
functional leaders
• 8 people, including
its own vice
president
• Focus: same as
previous plus
predictions,
scenario planning,
succession
planning, root-
cause analysis
• Goals from same
• Audience: same,
but down to
plant/facility level
• 14 people
• Focus: same as
previous plus
predictions and
scenario planning
• Goals from same
• Audience: same,
but down to
plant/facility level
Case in point: A global manufacturer’s multiyear journey to
advanced analytics
14
Source: “Talent Analytics: A Multiyear Journey,” Bersin by Deloitte, 2014
Explore 10/
2006 Strategize 2007 Execute 2008 Operate 2009 Implement 2010 Impress 2011
Copyright © 2014 Deloitte Development LLC. All rights reserved.
• 1 person
• Focus:
advanced HR
studies and
corporate HR
scorecard
• Goals from Chief
Human
Resources
Officer (CHRO)
• Audience:
CHRO
• 2 people
• Focus: same as
previous plus job
analysis,
competency
assessment, and
the organization
culture
• Goals from
CHRO
• Audience: CHRO
• 2 people
• Focus: same as
previous plus
global HR
scorecard,
workforce
forecasting, project
management, and
training
effectiveness
• Goals from CHRO
and HR staff
• Audience: mostly
HR, some
business and
functional leaders
• 1 person, plus 2
people in India
• Focus: same as
previous plus
talent acquisition
• Goals from CHRO,
business and
functional leaders
• Audience: mostly
HR, some
business and
functional leaders
• 8 people, including
its own vice
president
• Focus: same as
previous plus
predictions,
scenario planning,
succession
planning, root-
cause analysis
• Goals from same
• Audience: same,
but down to
plant/facility level
• 14 people
• Focus: same as
previous plus
predictions and
scenario planning
• Goals from same
• Audience: same,
but down to
plant/facility level
Case in point: A global manufacturer’s multiyear journey to
advanced analytics
15
Source: “Talent Analytics: A Multiyear Journey,” Bersin by Deloitte, 2014
Explore 10/
2006 Strategize 2007 Execute 2008 Operate 2009 Implement 2010 Impress 2011
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Partnering for analytics:
Support investments in new technology
In 2013, approximately one-third of organizations made analytics technology
investments
Source: High-Impact Talent Analytics, Bersin by Deloitte, 2013
BUILT OR
IMPROVED
DATA
WAREHOUSES
31% PURCHASED
ANALYSIS
TOOLS OR
APPLICATIONS
33%
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Partnering for analytics:
Support investments in additional talent
In 2013, approximately one-third of organizations dedicated staff to analytics
33% 31% Hired or transferred
staff for analytics
161,000+ data analyst jobs posted on Indeed
91,000+ data analyst jobs posted on Glassdoor – July 2, 2014
Source: High-Impact Talent Analytics, Bersin by Deloitte, 2013
17
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Partnering for analytics:
Create a stronger partnership with HR
Three approaches finance can take to support analytics maturity
Share finance approaches and knowledge
with HR professionals
Partner with HR to provide finance information
that ties HR efforts to business outcomes $$
Volunteer to be a pilot for future analytics
initiatives or projects
Source: Bersin by Deloitte, 2014
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Q&A/Discussion
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Stacia Garr
Vice President, Talent Management and Human Resources Research
Bersin by Deloitte
Deloitte Consulting LLP
Tina Witney
Finance Transformation Practice Leader
Human Capital
Deloitte Consulting LLP
Contact info
20
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Copyright © 2014 Deloitte Development LLC. All rights reserved. Member of Deloitte Touche Tohmatsu Limited
Appendix
Copyright © 2014 Deloitte Development LLC. All rights reserved. 23 Talent Analytics
z
Quality Dashboards Team Data
Culture IT
Support
Driving to Mature Talent Analytics What you need for the road
Copyright © 2014 Deloitte Development LLC. All rights reserved.
Three factors to move from reporting to analytics
Implementing self-service reporting
Acquiring the right skills and
resources
Implementing a breakthrough
project