1 © 2014 SHL, a part of CEB. All rights reserved Maximizing the Business Impact of Talent Analytics Jean Martin, CEB October 24, 2014

1© 2014 SHL, a part of CEB. All rights reserved

Maximizing the Business Impact of Talent Analytics

Jean Martin, CEB

October 24 , 2014


Pressure on HR to capitalize on data assets

Source: PwC, “15th Annual Global CEO Survey,” 2012, http:/ /www.pwc.com/en_GX/gx/ceo-survey/pdf/15th-global-ceo-survey.pdf.n = 1,258.

HR Plans to Increase Investments in HR Data and Analytics in the Next Two Years

Percentage of Senior HR Leaders

n = 108.

Source: CEB, CEB Corporate Leadership Council Analytics Survey 2013.

Information Is Important

Receives Sufficient Information

Percentage of CEOs

Costs of Employee Turnover

Return on Investment in

Human Capital

Assessments of Internal

Advancement

Labor Costs

Employees’ Views and

Needs

Staff Productivity

CEOs Want More Talent Data from HR

Percentage of CEOs Who Believe Information Is Important and Comprehensive

0% 50% 100%

95% Agree


Data is not leading to insights or impact

Lots of Data; Minimal Insight

“There’s a lot of data out there but not a lot of information.” VP, HR Mining Company

HR Analytics Has Led Me to Change a Business Decision in the Past Year

Percentage of Senior Business Leaders

15% Agree

Source: CEB, Business Barometer, 2013.n = 1,590.

I Believe I am Getting Significant Returns on Analytics Investments


8% Agree

Source: CEB, CEB Corporate Leadership Council Analytics Survey, 2013.n = 108.


From reporting to analytics

Defining Terms:

Talent Analytics: The discovery and communication of meaningful patterns in talent dataTalent Metrics: Units of measurement for talent dataTalent Dashboards and Reports: Tools to communicate talent data

From HR using:Data to provide talent reports

To HR using:Analytics to improve business decisions

Purpose of reports is to provide talent information

Purpose of analytics is to improve business decisions

Information provided is driven by leader requests and data availability

Analysis and insights link explicitly to evolving business challenges

Reports provide leaders with talent metrics

Insights provide implications for business outcomes


New Work Environment amplifies analytics need

Trend Implications for the HR Function

Degree of Change

Required in HR

Need forTalent

Analytics

Talent Shortage and Skills Scarcity

The New (Networked) Work Environment

Globalized and Multi-generational Workforce

Convergence of Talent Management and Business Management

Succession Planning Deeper into the Organization

Intelligent Sourcing and Attraction

Personalization of EVPs

Virtual Relationships and Fragmented Work Arrangements

Network Performance and Learning

Multi-Generational Management

Shift from Expat to Local Talent Investments

Knowledge Transfer from Retiring Workers

Heightened Talent Scrutiny by Board/CEO

Migration of HR Transaction Processing to Multifunction Shared Services

Trends Shaping the Future of HR and Their Implications


Recent analytics-related questions we are hearing

What actions can be taken to increase HIPO retention?

What types of training are most

effective in increasing

collaboration?

How can we better hire talent with critical skills in location “X”?

Which candidate should I hire?

How do I get more performance? What tools and practices

are effective?

Who are our most productive

employees, and how do we compare to other companies?

How does pay for similar jobs and

roles vary across our organization?

How are requirements of

critical jobs and roles changing in our

industry?

What are the barriers to staff mobility

across our organization?


Relying on gut instinct

Less Than One-Quarter of Business Leaders Use Data from HR for Key Talent Decisions

Percentage of Business Leaders Who Use HR Data for Key Talent Decisions

Fewer Analytic Tools Exist for Talent Decisions Than Other Critical Business Decisions

“When we make our finance decisions, we use data and spreadsheets. When we make decisions about our most important asset, our people, we don’t have the same tools.” SVP, Manufacturing Company

Source: CEB, Global Labor Market Survey, 2013.

n = 9,528.

0%

50%

100%

25% 24% 24% 24% 24% 23% 23% 23% 22% 22%

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Technology and analytic sophistication is heralded as path to success

Sample Talent Analytics Maturity Models Sample HR Technology Vendors

Source: http:/ /www.bersin.com/lexicon/Details.aspx?id=15302; http:/ /bitools.org/gartnerbi-emea-2013-part-1-analytics-moves-to-the-core/; http:/ /www.deloitte.com/view/en_US/us/Services/consulting/human-capital/hr-transformation/hrtimes/5b96651f98696310VgnVCM3000001c56f00aRCRD.htm.


Analytic sophistication alone is insufficient

Improvement in Talent Outcomes By Analytic Sophistication

Source: CEB, CEB Corporate Leadership Council Analytics Survey, 2013.

Low High

High

Low

Although a basic level of analytic sophistication is necessary for impact…

…further investments in sophistication alone yield low additional benefits.

Org

an

iza

tio

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l

Av

era

ge

Tale

nt

Ou

tco

me

s

Analytic Sophisticationn = 108.

Foundational Analytic Sophistication Requirements to Achieve Impact Maintaining consistent data governance and standards Protecting data from risks to security and confidentiality Maintaining accessible systems to store data

Talent Outcomes Include:

Employee performance

Quality of hire

Employee engagement

Employee retention

Leadership bench strength


A global study


Analytic impact leads to …

Analytic Impact:

The extent to which talent analytics improves decisions and provides actionable supportto key stakeholders

Decision Improvement:“Analytics Support from the HR Function Improves Talent Decisions”

Improvement of decisions made by:■CEO■Board of Directors■Business Leaders■Line Managers

Actionable Support:“HR Is Effective at Providing ActionableData-Based Guidance on Key Talent Areas”

Key talent areas include:■Sourcing■Performance Evaluation■HIPO Selection■Leadership Development■Employee Engagement■Succession Planning ■Compensation and Benefits

+


… talent and business outcomes

Analytic Impact Improves Key Talent Outcomes

Difference in Analytic Impact Between Leading Analytic Organizations and the Average Organization

n = 108. Source: CEB, CEB Corporate Leadership Council, Analytics Survey 2013.1. Financial information on participating organizations was collected through Compustat for organizations where it was available. The median organization has $9.21 billion in revenue and a 30.76% gross profit margin. Increasing from median to maximum Analytic Impact improves collected talent outcomes by 12 percentage points, which in turn leads to a 6% increase in gross profit margin. 2. Talent outcomes were identified by senior HR leaders and surveyed organizations and validated through other internal CEB surveys.

Bench Strength EmployeePerformance

Quality of Hire EmployeeEngagement

Average Organization

Leading Analytic Organizations(top quartile)

Average Improvement in Key Talent Outcomes by Leading Analytic Organizations = 12%

1.001.17

1.001.12

1.00 1.10 1.00 1.09

Analytic Impact = Decision Improvement +Actionable Support


The business application gap

Analytic Impact and Effectiveness at Business Application and 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., higher order data modeling, sophisticated systems).

High

LowLow High

Bu

sin

ess

Ap

pli

cati

on

1

Sophistication2

High Application, Low Sophistication

Average Analytic Impact: 1.14x

3% of organizations

Leading Analytic Organizations


17% of organizations

Low Application, Low Sophistication



Low Application, High Sophistication



Best Path to Impact

Only 17% of organizations match high sophistication with business application of insights.



CEB tested more than 200 metrics

The Long Tail of Metrics

Percentage of Organizations Reporting Usage by Metric

These metrics covered a wide variety of talent areas, including:

Employee engagement

Learning and development

Performance management

Recruiting

Succession planning

Workforce planningMetrics

Pe

rce

nta

ge

of

Org

an

iza

tio

ns

Re

po

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he

Me

tric

0%

50%

100%CEB asked members which metrics they track across their organization and report to the Board of Directors or the CEO.



No shortage of metrics

Wide Range of Metrics from “Mild” to “Wild”

Source: CEB, CEB Corporate Leadership Council Analytics Survey, 2013; Innovation Enterprise, “Innovation Enterprises HR & Workforce Analytics Innovation Summit,” 22 and 23 May 2013, https://theinnovationenterprise.com/summits/hr-chicago2013; Thomas H. Davenport, Jeanne Harris, and Jeremy Shapiro, “Competing on Talent Analytics,” Harvard Business Review, October 2010; http://hbr.org/2010/10/competing-on-talent-analytics.

Wild

Mild

Record the frequency with which customer-facing staff smile to determine customer satisfaction.

Benefits Cost Per Employee

Smiles Frequency (Harrah’s)

Employee Digital Footprint Size (Intel)

Forecast the future organizational structure based on current hiring and promotion practices.

Employee Loyalty Statistic (JetBlue)

Use employee behavior data to identify employees who are likely to leave. Departure Probability (Sprint)

Use a single question net promoter score to measure engagement.

Hire and Promotion Rate (Google)

Total Compensation Per Employee

Benefits Expense as Percentage of Total Operating Expense

Benefits Expense as Percentage of Revenue

Employee Retention Index

Employment Brand Strength

Employee Commitment Index

Average Employee Compensation

Compensation Expense Per FTE

Absentee Rate

Cost/FTEs

Employee Engagement Level

Cost Per Hire

# FTEs

Internal Pay Equity

Revenue per Employee


No magic metrics

Wide Range in the Number of Metrics Tracked and Reported by Leading Organizations

Range of Metrics Leading Analytic Organizations Report to CEO or Board

Range of Metrics Tracked by Leading Analytic Organizations

Overlapping MetricsSource: CEB, CEB Corporate Leadership Council Analytics Survey, 2013.n = 116.

0 110 220

35 81 140

Number of Metrics Reported0 110 220

1 49 118

Number of Metrics Reported

Bottom Quartile Organizations

1 Performance Appraisal Participation Rate

2 Gender Staffing Breakdown3 Performance Rating Distribution

4 Compensation Gap to Market5 Employee Engagement Level

6 Internal Hires/External Hires7 Transfers8 Ethnic Background

9 Average Merit Increase for Each Performance Rating10 Total Number of Hires

Leading Analytic Organizations

1 Performance Rating Distribution

2 Performance Appraisal Participation Rate3 Total Number of Hires4 Internal Hires/External Hires

5 Employee Engagement Level6 Average Performance Appraisal Rating7 Average Time to Fill

8 Average Merit Increase for Each Performance Rating9 Compensation Gap to Market

10 Average Employee Compensation


Progress in tracking and reporting talent metrics

Average Organizations: Leading Analytic Organizations:

Exclusively Tracking Operational Metrics Capture operational metrics recorded in information systems, such as number of employees, performance scores, etc.

1 Tracking Both Operational and Qualitative Metrics Capture critical talent information that is difficult to capture through traditional HRIS database fields (e.g. engagement and quality of hire) to expand the potential for metrics to impact business decisions.

Track Broad Metrics EpisodicallyA variety of metrics are tracked at specific times across the year as they align to HR initiatives and projects.

2 Tracking Key Metrics ContinuouslyHR identifies a set of key metrics that are measured more frequently.

Localized DefinitionsMetrics are measured differently across functions, BUs, and geographies making organization-wide comparisons difficult.

3 Standardized DefinitionsStandard definitions are enforced throughout the organization to ensure consistency and enable organization-wide comparisons.

Reporting Only to Senior LeadershipReport findings and insights to senior leaders, such as the CEO or board of directors, limiting the potential impact of metrics.

4 Reporting to Line ManagersReport findings and insights to line managers empowering them to make decisions.


Three challenges to improving analytic impact

n = 9,528.Source: CEB, CEB Global Labor Market Survey, 2013.

n = 108Source: CEB, CEB Corporate Leadership Council Analytic Survey, 2013.

n = 9,528.Source: CEB, CEB Global Labor Market Survey, 2013.

1

Few business leaders believe HR analytics focuses on the right business questions

Percentage of Business Leaders

Most HR leaders believe HR staff capabilities are a barrier to improving HR analytics


“Criticality”Where Should I Focus Talent Analytics?

“Capability”How Do I Upskill My HR Function?

“Credibility”How Can I Increase Credibility of HR Data?

17% Agree

80% Agree

18% Agree

2 3

Few business leaders findHR data credible



The Analytics Era: Transforming HR’s impact on the business

Criticality Capability Credibility

1Prioritize Critical

Business Questions

2Apply Business Judgment

to Data Science

3Drive End-User Ownership

of Talent Analytics

Prioritize the most scalable opportunities for business impact

rather than simply fulfilling on-demand data requests.

Reset goals for talent analytics to focus staff on

business judgment.

Provide implications of decisions; don’t prescribe

solutions.

Analytics Prioritization Principles Re-Goaled Talent Analytics Implication-Based Decision Support

Evaluate talent risks to business strategy to identify key metrics.

Revise HRBP competencies to emphasize application of business judgment to data.

Talent Analytics Map HRBP Analytics Competencies

Build capability by establishing accountability and facilitating

connection across the business.

Imperatives for CHROs to Improve Analytics Capability

1.Pseudonym.

Connect talent data to business

outcomes

Wishbone Inc.1

Talent P&L Dashboard


Most analytics efforts are misaligned withbusiness priorities

1,707%

Even Fewer Senior HR Leaders Believe Talent Analytics Are Effectively Aligned with the Right Business Issues


n = 108.Source: CEB, CEB Corporate Leadership Council Analytics Survey, 2013.

n = 9,528.Source: CEB, Global Labor Market Survey, 2013.

Less Than 20% of Business Leaders Believe Talent Analytics Are Focused on the Right Issues


17% Agree

14% Agree


Focus on business priorities, not metrics

Organizations That Effectively Align Analytics to Business Priorities Have a Greater Analytic Impact

Difference in Analytic Impact

“Our most successful analytics work is when we hit on a challenge aligned with the current business priorities.”

VP, Head of Talent Analytics, Manufacturing Organization

n = 108.


1.00x

Effectively aligning analytics to business problems has 9% greater Analytic Impact than effectively tracking metrics.

Ineffective at Tracking Metrics

Effective at Tracking Metrics

Effective at Aligning Analytics

to Business Priorities

1.16x 1.25x


Critical Talent Topics for Business Leaders

Sample Discussion Guide

Talent Attraction

Succession Risk

Business Strategy

EmployeePerformance

Business and Financial Performance

Talent Identification Engagement and

Development

What are the talent risks to executing our

business strategy?

How should we

scale talent with

business growth?

What are the highest- return interventions to

boost employee performance?

How can we compete more effectively for

top talent?

How can we accelerate

the development of our HIPO

staff?

How strong is our leadership

bench?

Design Prioritization Strategies to Maximize Business Alignment

Prioritize the Most Scalable Talent Questions Across the Business

Identify and pursue the most scalable opportunities for business impact; don’t just fulfill

on-demand data requests.

Provide implications of decisions

Facilitate leader-led diagnosis of talent challenges and identification of optimal solutions

Engage with the business to identify the most important business challenges

Wishbone Inc.1

Connect talent data to business outcomes

Create a talent P&L Dashboard

1.Pseudonym.


Example 1: Gap Inc.’s analytics prioritization principles

Principle 1

Conduct prioritization exercise based on key

questions

Question-Based Needs Assessment

Principle 2

Identify the most scalable opportunities for impact

Enterprise Opportunity Identification

Principle 3

Create a roadmap for action and investment

Analytics Input Evaluation

100 Human Capital Questions Illustrative

Please rank the top 15.

1.Are we losing critical talent?

2.Have we sufficiently minimized time to productivity for new hires?

3.Are we accurately predicting quality of hire?

4.…

Brand Operations Teams’ Responsibilities

Gap Inc. WorkforceAnalytics

Team Priorities

Turnover of Non-Critical

Talent Segments

Recruiting Efficiency

New Hire Quality

Training Participation

Productivity

Versus Competitors

Successor Pool Quality for Key Positions

Employee EngagementBenefits

Satisfaction

Staffing Ratios

Available? Location Other Barriers to Acquiring or Using Inputs

Required Investment

Today Scattered across the brands in disparate systems

We do not have a clear definition of “critical role.”

We need to invest to ensure a new definition is consistently applied across brands.

2013+ N/A Don’t capture reasons for turnover - use departure survey to fill the gaps.

Launch departure survey in all brands.

Availability Gaps Application Gaps

Criticality


Using analytics to advise business leaders on what actions to take to better address their talent management challenges based on use of proprietary models to produce tailored analysis of “specific” talent data used in “specific” ways.

(Predictive Models, Driver Analyses, Causal Models)

Two broad terms guiding approach to talent analytics

Using data and analytics to describe talent and to inform decision makers by analyzing the level of, change in, or basic relationships among (modeling) key talent metrics

(Benchmarking, Dashboards, Trend Analyses, Forecasts)

Descriptive Analytics

Prescriptive Analytics


Example 2: CEB TalentNeuron

WHERE to Build / Locate

Talent?

WHO to Target?

HOW to Win?

Increase Quality/Speed of Hire

Improve Business Partner Management

Optimize Talent Hub Costs

Minimize Business Execution Risk Management

Competitive Talent Advantage Business Questions & Outcomes Supported

Product Delivered From Data to Intelligence

Select List of Existing Clients

Capability


“New World” Analytics: CEB TalentNeuron

Richer Intelligence

Contextual Decision-SupportPlatform

Executive-ReadyAnalytical Support

CEB TalentNeuron

• Over 800 data sources spanning social media, research networks and primary research

• Multi-stage data validation including human curation to ensure quality and accuracy

• User experience aligned to business planning and resource allocation decisions

• Custom integration with internal customer data via TalentForecast module (add on)

• Predictive five-year talent supply/demand forecasting and wage inflation models

• On-call team of data scientists generate situation-specific insights and presentations

• Uniquely global coverage across 100+ countries and 900 cities

“Old World” Workforce Planning Analytics

• Data limited to just a few geographies

• Data sourced solely from job boards

• No human data quality management

• Web site oriented around job functions not business decisions

• Data describes current not future market conditions

• No option for integration of external with internal data from systems of record

• No on-call data scientist support

• Query workbench enables customers to establish internal talent analytics service model

• Inability to help HR manage internal business partner demand for data and analytics support


Seagate’s Analytics Delivery Strategy Addresses Three Common Delivery Pitfalls

Leader-Driven Decision Scenarios

Common Delivery Pitfalls

Seagate’s Delivery Strategy: Maximize End User Ownership

Too Much Data to Consume Quickly

Filtered DataVisualizations

Benchmark Visualization

Unclear DecisionImplications

Scenario Planning Tool

Limited Implementation

Proactive DecisionOutput

Staffing Plan for Recruiting Team

Workforce Distribution

Current State

Industry Benchmark

Internal Goal

Gra

duat

e

Inte

rmed

iate

Fel

low

Sen

ior

Sta

ff

Sen

ior

Sta

ff

Prin

cipa

l

40%

0%

20%

Staffing Plan

Job Level Estimated Hiring (2013)

Estimated Hiring (2014)

Graduate 35 30

Intermediate 40 35

Senior 45 40

Staff 20 15

Senior Staff 10 10

Principal 2 2

Fellow 0 0

1 2 3

Example 3: Seagate end user platform

Credibility


Example 4: Wishbone’s1 talent P&L dashboards

Continuous Checks for Business Relevance

Collect continuous line feedback on consumability of dashboards to ensure they include the most relevant data in the most easy-to-consume format.

Sample P&L Based Talent Dashboards

Leadership Dashboard: Corporate 2012

Talent Retention Dashboard: Manufacturing 2012

Talent Acquisition Dashboard:

Manufacturing Recruitment 2012

Highlights:

■Hired 82% of revised 2012 target

■ 2012 (goal): 6,542

■ 2012 (hired): 5,364

■Met 100% of the diversity recruitment target

■Reduced time to fill and cost per hire

■ Improved quality of hire

■ Implemented new applicant screening system—objective to reduce screening

time by 20%

Actual (2012) Goal (2012) Actual (2011)

1.Number of Hires 5,364 6,542 4,326

2. Number of Minority

Hires X X Y

3. Quality of Hire Index

(%)62% 60% 54%

4. Time to Fill (Months) 4.3 4 5.2

5. Cost per Hire

(Thousand $)23 24.5 25

Talent P&L

■Reduced cost per hire and time to fill lowered overall recruiting expense by $X over one year

■Improved quality of hire increased overall performance by Y%

■Increased head count led to reduced process times for key activities, lowering operational costs by Z%

Less Data, More Value

Highlight the few key numbers most relevant for senior executives to get a high-level overview of the function.

Wishbone Inc. 1

Wishbone Inc. 1

Wishbone Inc. 1

Talent P&L

Include a brief talent P&L statement in all talent dashboards, providing insight on how talent decisions impact business – productivity gains, financial gains, and operational gains resulting from the investments.

1.Pseudonym.

Credibility


The Analytics Era: Transforming HR’s impact on the business

1.Pseudonym.

Criticality Capability Credibility

1Prioritize Critical

Business Questions

2Apply Business Judgment

to Data Science

3Drive End-User Ownership

of Talent Analytics

Prioritize the most scalable opportunities for business impact

rather than simply fulfilling on-demand data requests.

Reset goals for talent analytics to focus staff on

business judgment.

Provide implications of decisions; don’t prescribe

solutions.

Analytics Prioritization Principles Re-Goaled Talent Analytics Implication-Based Decision Support

Evaluate talent risks to business strategy to identify key metrics.

Revise HRBP competencies to emphasize application of business judgment to data.

Talent Analytics Map HRBP Analytics Competencies

Build capability by establishing accountability and facilitating

connection across the business.

Connect talent data to business

outcomes

Wishbone Inc.1

Talent P&L Dashboard

Imperatives for CHROs to Improve Analytics Capability


Questions?

Maximizing the Business Impact of Talent Analytics

http://manage.eventmobi.com/en/ars/results/askaquestion/5760/395369/6c796e5bd8d90a1c87774716a7b09ceb/

Documents

1 © 2014 SHL, a part of CEB. All rights reserved Maximizing the Business Impact of Talent Analytics Jean Martin, CEB October 24, 2014