Talent Analytics Maturity Model® Level BigData in Human Resources - Making it Happen

About Us  Who We Are • Delivering the proven people strategies that leaders and their organizations need to deliver exceptional business results.  Practices Human • Enterprise Learning Resources • Human Resources • Talent Acquisition Leadership • Talent Management Development • Leadership & Succession Learning &  Services Development • WhatWorks® Membership • Research-based consulting services Talent Acquisition • IMPACT: The industry’s premiere conference on the Business of Talent, April 22-24, 2013 • BersinInsights® Talent • BersinBasics® Management Copyright © 2012 Bersin & Associates. All rights reserved. Page 2

Our Research  8 years of research into the measurement, operations of L&D, leadership, recruiting and HR  Education and best-practices on “how to build an analytics function”  Detailed information on tools and vendors  Assessment services and consulting to help you understand where you are and how to advance your program  Delivered through our WhatWorks® Membership http://www.bersin.com/hrbigdata2012 Copyright © 2012 Bersin & Associates. All rights reserved. Page 4

BigData in US Business 14 Exabytes of Data in US 6 billion photos uploaded to Corporations (1 Exabyte is Facebook every month 40,000X the library of congress) YouTube uploads more content each day than all networks combined We are at an inflexion point: Organizations US Businesses will be short 140,000-190,000 analytic positions whichyears to leverage big data will far in the next three learn 1.5 million more data-savvy outperform those who do needed to leverage managers not. big - McKinsey data in the United States Copyright © 2012 Bersin & Associates. All rights reserved. Page 6

2012 Business Environment Globalization, Innovation, Cost Containment What Are Your Organization’s Top Business Challenges for 2012? 35% of organizations see the need to +60% Increase accelerate growth and globalize – +10% Increase the highest level in four years…. yet… 51% struggle to hire the right talent, despite high unemployment… +70% Increase © Bersin & Associates, Corporate TalentWatch® Research, Senior HR and Business Executives, ■ Dec. 2011 ■ Aug. 2012 Copyright © 2012 Bersin & Associates. All rights reserved. Page 8

Increasing Specialization  Expertise drives competitive Top advantage Management  Specialization improves Senior quality and reduces cost Management The  Deep skills developed Experts Middle Management through “deliberate practice” and reinforcement Senior Specialists First Line Management  Deep skills come from a range Functional Specialists / Front-Line Employees of developmental experiences  We need career development Back Office, Operational, Contingent Employees in all critical job roles High Performing Organizations Understand This Copyright © 2012 Bersin & Associates. All rights reserved. Page 10

Young, Diverse Workforce …. Has Created Challenges in Engagement In 2012, 32% of employees are “planning on leaving” their employers, vs. 19% two years ago Only 55% of employees believe their employer is a sound “long term” place to work vs. 65% over last three years. People under the age of 35 are twice as likely to be looking for new work as older workers. - Mercer October 2011, Towers Watson July 2012 “By 2013, 47% of employees will be those born after 1977. -- US Census Bureau Copyright © 2012 Bersin & Associates. All rights reserved. Page 12

Analytics is Definitely Coming to HR The Evolution of Business Analytics in other Functions Finance & Logistics Customer & Marketing Talent & Leadership The Waves of Integrated ERP Predictive Predictive Business Analytics and Financial Customer Talent Models Analytics Behavior - CRM HR Analytics Integrated Web Behavior Business-driven Supply Chain Analytics Talent analytics 1980s Customer Integrated Financial and Segmentation Talent Management Budget Analytics Shopping Basket Workforce Planning Recruiting, Logistics and Customer Learning, Supply Chain Analytics – CRM Performance analytics (Data Warehouse) Measurement The Industrial The Financial The Customer The Talent Economy Economy Economy and Web Economy Conglomerates Customer Segmentation Globalization, Demographics Steel, Oil, Railroads Financial Engineering Personalized Products Skills and Leadership Shortages Early 1900s 1950s-60s 1970s-80s Today Copyright © 2012 Bersin & Associates. All rights reserved. Page 13

Typical People Decision-Making  How do baseball teams find great players?  They look for “traditional performance characteristics” • Speed and athleticism • Ability to hit, home runs • Appearance, confidence • Batting average (ie. GPA) Copyright © 2012 Bersin & Associates. All rights reserved. Page 16

Data Proves Different Factors Matter  What is the most important baseball statistic that drives a winning team? • Team batting average? • Runs batted in (RBI)? • Pitcher’s earn run average (ERA)?  On Base Percentage (OBP)  Not a Characteristic of the Player (candidate)  It is a characteristic of how they actually perform Copyright © 2012 Bersin & Associates. All rights reserved. Page 17

How do Companies Hire People? 2/3 of hiring done without any significant assessment % of Organizations Which Regularly Use Following Assessment Practices  Background checking: 79% 2/3 use no real  Managerial interviews: 64% assessment process  Interview training: 47% at all … leaving the process to  Behavioral assessments: 34% hiring managers or recruiters  Reference calls: 32%  Skills-based assessments: 25% Bersin & Associates High-Impact Talent Acquisition Study, Fall 2010, 158 organizations responded Copyright © 2012 Bersin & Associates. All rights reserved. Page 18

This Science is Coming to HR  Definition of “Science”: “Systematic knowledge of the world gained through observation and experimentation.”  What is Not Science Making talent decisions on the basis of “gut feel,” “beliefs,” or “philosophies.” Copyright © 2012 Bersin & Associates. All rights reserved. Page 19

Insurance Company Big Insurance  A $33 billion insurance company has developed a behavioral assessment based on a set of beliefs held by the top executives  Top sales people need college degrees from top rated schools, they should have good grades, and they should have experience selling high value products.  But the data proves otherwise. Copyright © 2012 Bersin & Associates. All rights reserved. Page 20

Insurance Company Data Showed Six Things Matter: Very Highly Correlated with Success 1. No typos, errors, grammatical mistakes on resume. The Belief 2. Did not quit school before obtaining some degree 3. Had experience selling real-estate or autos System 4. Demonstrated success in prior jobs 5. Ability to succeed with vague instruction Was Wrong 6. Experience planning time and managing lots of tasks Within six months of implementing a What Did NOT Matter new screening process • Where they went to school revenues went • What grades they had up by $4 million • The quality of their references Copyright © 2012 Bersin & Associates. All rights reserved. Page 22

Business Value Beliefs Gut Feel Reactive Checks Ad-Hoc and Ongoing Reports Dashboards and Reporting Benchmarks Correlations Simulations Analytics Predictions Causal Modeling Copyright © 2012 Bersin & Associates. All rights reserved. Journey into Data-Driven Decisions Page 24

Focus on Business Problem, not Data Business problem first, then focus on arranging and using the data Business Data Problem  Why is turnover high in some areas?  What drives sales productivity?  Why is their fraud in some branches?  What sales or service processes drive account renewal?  What is the impact of training on long term productivity?  How do we assess the “right” candidates for sales?  What will our talent gaps be next year based on retirement? Copyright © 2012 Bersin & Associates. All rights reserved. Page 26

Four Keys to Success 1. Reliable • Data must be “true” and validated over time • Seasonal changes, organization changes, must be handled 2. Actionable • Reports must be detailed enough to let managers take action • Drill, filter, group data so it is relevant and meaningful • Goal is a “business-driven” dashboard (red/yellow/green) 3. Scalable • The process of collecting and analyzing data must scale • Your outputs must be useful for people at all levels 4. Understandable • People must be able to visualize and understand what you find • Line managers, executives, and employees must use the data Copyright © 2012 Bersin & Associates. All rights reserved. Page 28

But What do you Measure? Supply, Talent Workforce Plan Open Internal Demand Demand Plan Scenarios Positions Mobility Recruiting Employer Time and Cost Onboarding Onboarding Turnover Brand, Alumni To Hire Effectiveness Performance Ratings Managerial Development 9-box Succession Rankings Grievances Plans Grids Skills Succession Promotional Seniority Readiness Certifications Depth Readiness Skills Depth Succession 360 and Other Successor Proficiency vs. Leadership Depth Assessments Readiness Leadership Comp. Budget by Comp by Perf-Pay Compa Compensation Group level/perf differentials Ratios Employee Employee Innovation Employee Engagement Opinion Engagement Programs Value Prop Retirement Tenure Age, geography, Span of Demographics Projections Education, etc. Skill level control HR/L&D HR/L&D Systems Satisfaction Spending Spending Staff Allocation Usage/$ With HR svc. Copyright © 2012 Bersin & Associates. All rights reserved. Page 29

Types of Measures you Need Why the analytics team must understand all areas of talent management… Workplace Leadership Individual Management Environment & Culture Characteristics Compensation Clarity of goals Leadership Education Benefits Coaching values Personality Safety Job fit Clarity of mission Skills Tools Team structure Type of leader Training Information Span of control Style of leader Experience Physical comfort Personal Values Location relationship Life situation Availability …. Org design …. Org “culture” …. Org “vision” “engagement” is often a surrogate …. for all this complexity Copyright © 2012 Bersin & Associates. All rights reserved. Page 30

Bersin & Associates HR Measurement Framework HR, Recruiting, and L&D Organizational Talent & Leadership Supply Scenario Manager and Effectiveness Readiness Workforce Planning & Future Planning Employee Dashboards Workforce Performance (How people impact the business) Financial results by person and unit I Net Promoter scores I Performance and Goal attainment I Innovation/Patents | Product measures Statistical and Data Analysis Skills, Collaboration with other Analytics Teams External Data and Benchmarks Measurement Process & Skills Talent Acquisition Workforce Measures I TM Measures I People Performance Data Cleansing | Data Dictionary | Analytic Measures (How well you are reaching candidate audiences) Internal HR Measures I HR Program Effectiveness I Employment Brand | Talent Pipeline | Time and Cost to Fill | Quality of Hire (External Benchmarking of all HR Measures) Integration of new sources and systems Data governance and stewardship Capabilities, Talent, & Leadership (Capabilities, leadership, progression, career, talent.) Leadership Pipeline | HiPOs I Stack Rankings I Pivotal Role Pools I Mobility | Compa Ratios I Rewards I Skill gaps I Certifications | Readiness I Turn- over I 360’s I Technical Skill Pools I Career Progression | Development Plans | Succession Depth and Pools Engagement & Culture (Employee engagement, wellness, and satisfaction – including external view) Engagement I Management Grievances I Turn-Over I Referral Rates I Exit Interviews I Development Plans | Diversity and Inclusion HR Programs & Processes (Status and maturity of HR Processes ) Learning Program Effectiveness I Total Rewards Effectiveness I Performance Management Effectiveness I On-Boarding Time to Productivity I Recruiting Effectiveness and Effieicney I Candidate Pipeline I Total Rewards Workforce Demographics (Facts and statistics about employees, alumni, and contractors) Payroll and Benefits | Demographics I Background I Experience I Tenure I Organization Structure I Spans of Control I Workforce Planning Performance & Talent Learning Management Compensation Third party Applicant Tracking | System System System System(s) data: Scenarios, talent supply, demand Recruiting System Performance, development planning, Learning, certification, skills delivery, Salary, benefits, budget, bonus and assessments, Applicant, source, recruiting data employee org charting succession, talent pool data content, learning organization data comp related data, payroll feeds engagement, external brand, HRMS’s – Payroll and Employee Demographic and System of Record Data social networks Copyright © 2012 Bersin & Associates. All rights reserved. Page 31

Traditional Data Architectures • Dynamic Aggregation • Drill up, down • Ad Hoc Filtering • Sorting and Subtotaling All this complexity is now moving to • Graphing “Cloud-Based” analytics systems. • • Subject Area Analytics Very fast response Operational Reports • Updated nightly Dashboards and (Crystal) These new solutions capture data Advanced Reports from your systems and deliver reporting and analysis tools to you without significant IT support. OLAP Operational Data Warehouse Multi HRMS or Or Analytics Dimensional LMS Application Database Turnkey ETL Process Cube Database Server (Extract/Transform/Load) Generation OLAP Database Server Copyright © 2012 Bersin & Associates. All rights reserved. Page 32

Integrated Systems Now a Top Priority BigData Projects Demand It Are you willing to sacrifice features for an integrated HR solution? 2011 2012 Not Not Sure, 19% Sure, 21% Yes, 33% Yes, 45% No, 36% No, 46% Bersin & Associates Talent and HR Systems Study, 2012 and 2011 Copyright © 2012 Bersin & Associates. All rights reserved. Page 33

Talent Analytics Maturity Model® Level 4: Predictive Analytics Development of predictive models, scenario planning <5% Risk analysis and mitigation, integration with strategic planning Level 3: Strategic Analytics Segmentation, statistical analysis, development of “people models”; <10% Analysis of dimensions to understand cause and delivery of actionable solutions Level 2: Proactive – Advanced Reporting Operational reporting for benchmarking and decision making >20% Multi-dimensional analysis and dashboards Level 1: Reactive – Operational Reporting Operational reporting for measurement of efficiency and compliance >60% Data exploration and integration, Development of data dictionary Copyright © 2012 Bersin & Associates. All rights reserved. Page 36

How HR Data is Likely Organized Recruiting and Performance Comp and Workforce Succession Benefits Planning Engagement HRMS HR Learning Employee Operations & Leadership Data Your goal is to integrate this information, over time, into a credible, actionable, scalable, understandable Talent Analytics function… one which delivers relevant Information, models, and tools to line leaders and executives Copyright © 2012 Bersin & Associates. All rights reserved. Page 37

Key to Success: WhatWorks®  Developing Credibility  Strong Relationship with IT  Sharing Experience across analytics teams  Patience to validate data before it is shared  Multi-year analysis to experience seasonal trends  Need to present findings in an understandable way  Skills in visual design and presentation  Focus on business solutions, not HR solutions Copyright © 2012 Bersin & Associates. All rights reserved. Page 38

Examples of Breakthrough Solutions  Major Retailer developed integrated “people model” to correlate relationship between engagement, rewards, leadership capabilities, tenure, skills and revenue.  Major Payroll Provider statistically validated 30+ factors in recruiting which led to 20%+ improvement in sales performance and completely revamped recruiting process  Major Food Service Company identified key drivers of account renewal and upgrade and developed statistically valid measures which have been used to create company-wide dashboard which measure risk on a weekly basis  Major Retail Bank correlated dozens of workforce measures against engagement and branch financials to develop risk management dashboard for small and large branches Copyright © 2012 Bersin & Associates. All rights reserved. Page 39

Data Analysis Skills Important to HR Top HR Skills | Capabilities Correlation Business Partner relationship management .52 Managing and leading people .51 Coaching and Mentoring .49 Change management and communications .48 Analyzing and interpreting data .47 Knowledge Sharing and expertise directories .47 Managing your Personal Development .45 Top Organizational | Managerial Capabilities Developing a high performance culture .77 Developing a strong learning culture .77 Developing strong talent segmentation .74 Developing high levels of career development and mobility .73 Attracting and selecting the right talent .64 Measuring business impact of HR .64 Developing high levels of engagement .54 Giving people honest feedback .49 Copyright © 2012 Bersin & Associates. All rights reserved. Page 41

HR Organizations are Not Ready What percentage of HR organizations do you believe feel have strong skills in data analysis and interpretation? 6% Rate themselves “High” 56% - “Poor” Bersin & Associates High-Impact HR Organization® 2011 and 2010, n=741 organizations Copyright © 2012 Bersin & Associates. All rights reserved. Page 42

Large Retailer The Evolution of Data Skills and Competencies 2007 - 2008 Solid Understanding of HR; I/O Psychology Degree; Strong Communication & Interpersonal Skills; Employee Research Background; Detail Oriented ; Project Management Qualitative Research Design & Analysis; HRIS; SPSS 2009 - 2010 Business Acumen; HR, Finance, Economics Degree; Consulting & Presentation Skills; Quantitative Research Design & Analysis Analytical Curiosity; Problem Solving; Passion for Data & Analytics; Strong Technical skills Collaborative; Teamwork; Networking Skills 2011 - 2012 Advanced Statistics & Social Research Acumen; Critical Thinking; Engineering Degree; Story Telling; Data Visualization; Customer Research Background; Statistics & Data Mining Ability to see data, and decipher insights Copyright © 2012 Bersin & Associates. All rights reserved. Page 43

Retailer An Evolved Organization VP Human Capital Analytics Director Director Workforce Manager HR Brand Org Diagnostics & Analytics & Content Design Research (2) Manager Manager Manager Business Sr. Consultant Workforce Employee Learning Operations ODD Analytics Research Analytics Specialist Program Manager Consultant (2) Analyst Employee Learning Sr. WFA Analyst Research Measurement Analyst Learning Analytics Copyright © 2012 Bersin & Associates. All rights reserved. Page 44

Retailer The Modeling Journey… Employee Employee 2008 Engagement Model Segmentation LVI Learning 2009 Diversity & Inclusion Leadership Learning & Employee 2010 Professional Development Lifecycle Research HR Scorecards Reactive Analytics Human Company Employee Proactive & 2011 Health Pentagram Research Cohorts Capital Executive Dashboard Exploratory Analytics Enterprise 2012 Measures of Success Talent Change Adoption Predictive Analytics Copyright © 2012 Bersin & Associates. All rights reserved. Page 45

Conclusion  BigData in HR is has become a business imperative  Tools are not the answer, but integrated data is needed  Analytics is a journey, it is a process not a project  Talent analytics will integrate all the functions within HR, and also across the business  Expertise and patience is key, but focus on key business problems first http://www.bersin.com/hrbigdata2012 Copyright © 2012 Bersin & Associates. All rights reserved. Page 46

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