Human Capital Analytics Is a Journey: Wear Comfortable Shoes

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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


Low Application, Low Sophistication


Low Application, High Sophistication


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

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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

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

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Remember . . .

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. . . And wear comfortable shoes!

Q&A

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