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Frequently Asked Ques6ons
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Ashley Collins Event Content Manager Workforce magazine
Human Capital Analy6cs Is a Journey: Wear Comfortable Shoes
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Jodi Crawford HR Quality & Analy>cs Leader Wes*ield Group
Human Capital Analy6cs Is a Journey: Wear Comfortable Shoes
Human Capital Analytics is a Journey: Wear Comfortable Shoes Jodi L. Crawford June 22, 2016 [email protected]
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Westfield Group � Privately held property & casualty insurance
and financial services company � Founded in 1848 � Approximately 2,500 employees � Provides commercial and personal insurance
in 21 states and surety services in 50 states, through a network of more than 1,000 independent insurance agencies
� $4.9 billion in consolidated assets and $1.8 billion in net written premium
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Poll Question
What is your company currently doing related to human capital analytics? A. Most human capital decisions are made
based on data analysis B. We do some analysis in addition to
providing standard and ad hoc reports C. We provide standard and ad hoc reports
only D. Nothing
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Workforce Intelligence Maturity This maturity curve is from PwcSaratoga. The Saratoga survey was founded by Dr. Jac Fitz-Enz, who is widely considered the “father” of human capital measurement and strategic analysis. NOTE: In reality the process is not this linear. Companies tend to achieve greater maturity in some analytics versus others at different times, driven by investment, resources, and timing related to business needs.
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Workforce Intelligence Elements
• What is likely to happen and how can we be better prepared?
• Why did it happen and how/where can we improve?
• What happened, and how do we compare to a defined set of metrics?
• What happened?
Ad hoc metrics and reports
Descriptive Dashboards/
Benchmarking
Predictive Analytics
Workforce Planning/ Survey
Analytics
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Why Did We Start?
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Where are we starting?
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Maintain Existing/Start Building New
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THE BUSINESS APPLICATION GAP Analytic Impact and Effectiveness at Business Application and Sophistication
There are two paths to improving Analytic Impact; however, first improving business application leads to more impact more quickly.
■ Improving business application alone can improve Analytic Impact by as much as 14%.
■ Improving sophistication alone can improve Analytic Impact by as much as 5%.
■ Organizations that are high on sophistication but low on business application are losing up to 17% of potential Analytic Impact.
Business Application is the ability to take specific actions from talent analytics.
Source: CEB, CEB Corporate Leadership Council Analytics Survey, 2013.
High
Low
Low High
Bus
ines
s A
pplic
atio
n 1
Sophistication2
High Application, Low Sophistication
Average Analytic Impact: 1.14x 3% of organizations
Leading Analytic Organizations
Average Analytic Impact: 1.22x 17% of organizations
Low Application, Low Sophistication
Average Analytic Impact: 1.00x 60% of organizations
Low Application, High Sophistication
Average Analytic Impact: 1.05x 20% of organizations
1
Business Application is measured by effectiveness at identifying the right business problems, applying business judgment to data, and engaging leaders to take action.
2
Sophistication is measured by effectiveness at complex analyses, (e.g., predictive and prescriptive modeling).
Only 17% of organizations match high sophistication with business application of insights.
Best Path to Impact
Analytic Sophistication is an organization’s effectiveness at using advanced methodology for talent analytics.
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Technology
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Scope
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Employee Insight for Performance Optimization
Employee Targeting Analysis reveals key target areas which drive strategic decisions
Employee Analysis Key elements are analyzed by segment
Employee Segmentation Meaningful segmentation is identified and used
Employee Profiling Basic data is accurate and complete
Employee Research Predictive models created/maintained; additional segmentation
The missing link in Westfield’s Business Intelligence . . . .
Soph
istica
tion
Leve
l
Depe
nden
cies
Prioritization of Work in Scope
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Employee Insight for Performance Optimization
Employee Profiling
Personal Data Role Data Hierarchy Data
Employee Segmentation Performance Segmentation
Network Segmentation
Functional Segmentation
Employee Analysis
Cost Analysis ROI Analysis Engagement
Analysis
Employee Targeting Selection Targeting Retention Targeting Development
Targeting
Employee Research Predictive Modeling Micro Segmentation
Priority Legend
High
Medium
Low Capability Data
Capability/ Experience
Segmentation
When We Started
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Now
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What Gets Most Praise?
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Where are we?
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Data Governance
25
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Likely Challenges
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1. Multiple systems that aren’t integrated 2. Data structures that were not designed for
easy output 3. People don’t think of human capital data as
“business data” 4. People don’t know what they want/need 5. People trust their opinion more than they
trust data 6. No money (or priority) to implement
technology
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Lessons Learned
1. Set clear, specific goals before you start
2. You need people who WANT to (and are capable of) doing data analysis
3. Commit the resources needed
4. Do not confuse measuring HR processes with human capital analysis
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Lessons Learned con’t
5. The people who do the analysis need to be in the conversation about the analysis
6. One size does not fit all
7. People need guidance in using the data or analysis
8. DO NOT underestimate the amount of change management needed
30
Remember . . .
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. . . And wear comfortable shoes!
Q&A
32
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