Global Workforce Analytics: The Next Big Thing? Featuring: Linda E. Amuso Radford Dan Weber Radford

Global Workforce Analytics: The Next Big Thing? Featuring: Linda E. Amuso Radford Dan Weber Radford

Session Agenda Creating a Foundation for Analytics People & Spend Analytics Performance & Spend Analytics Closing Thoughts: What s Next? 1

Creating a Foundation for Analytics 2

What is Global Workforce Analytics (GWA)? Radford s GWA program allows clients to go beyond traditional benchmarking to unlock new insights that inform talent strategies The key driver behind GWA is the collection of full census data covering all employees in all global locations: Traditional, job specific matching captures the core of the population; with Non-benchmark jobs matched on a functional-basis This foundation, when merged with information like corporate performance, allows HR leaders to frame global talent and total compensation issues in an entirely new light Talent Model Total Compensation Company Performance = GWA 3

GWA Database Snapshot As of February 2014, the GWA database housed full census data for 124 technology clients, which employ 2.8 million people By the end of 2014, we anticipate participation in GWA to approach approximately 250 companies covering 3.5 million people 124 Participating Companies 2.8 Million Incumbents 120 Countries with Incumbents $223 Billion in Compensation Spend $1.4 Trillion in Annual Revenue $3.8 Trillion in Market Value 4

GWA s Global Footprint United States 1,050,000 FTEs $133B total spend Americas 210,000 FTEs $11.6B total spend EMEA 510,000 FTEs $43.5B total spend Asia Pacific 1,010,000 FTEs $34.7B total spend 5

GWA Financial Profile GWA companies range in size from Fortune 100 giants to small- and mid-sized emerging technology firms 64% of companies are over $1.0 billion in annual revenues Participant Revenue Distribution (Company Count) Median Financial Metrics (in $Billions) 60 $10.0 50 45 43 $8.0 $8.1 40 36 $6.0 $5.7 $5.9 $5.6 30 20 10 $4.0 $2.0 $2.2 $1.4 $3.2 $2.2 0 Under $1.0 Billion $1.0 to $5.0 Billion Over $5.0 Billion $- Full GWA Database Semiconductor Hardware Software Median Revenue Median Market Value 6

GWA Functional Profile GWA includes the ability to segment data by corporate function; across the entire database, 57% of incumbents are focused on product development and customer delivery, and 43% are in enabling functions GWA Function Demographics 2% 37% 2.8 Million 41% 20% Sales / Support Engineering Business Functions Human Resources 7

GWA Job Type Profile On average, a GWA company has 22,418 employees in 30 global locations; the typical staffing model is approximately 60% professional roles with 14% in management and executive roles Average Headcount Distribution by Job Level 13% 1% 27% 22.4 Thousand 59% Support Professional Management Executives 8

GWA Job Type Profile by Industry Across industries, we observe limited differentiation in overall job level distribution, with roughly 15% of people in management, 60% in professional roles and 25% in support 100% 90% Average Headcount Distribution by Job Level 1% 1% 0% < 1% 13% 13% 12% 14% 80% 70% 60% 50% 40% 30% 20% 10% 59% 56% 58% 27% 30% 29% 63% 22% 0% Full GWA Database Semiconductor Hardware Software Support (S1-S5) Professionals (P1-P6) Management (M1-M6) Executives (E7, E8 and E0) 9

GWA Performance Profile To assess corporate performance across the GWA database, we focused on 1-year TSR and 1-year revenue growth We then divided the database into top- and bottom-performers using the overall median TSR rate of 30% for analysis 70% 60% 1-Year Business Performance Metrics (Median) 59% 50% 40% 30% 20% 10% 0% 30% 4% Full GWA Database 24% 26% 2% 3% 37% Semiconductor Hardware Software Top-Performers TSR Over 30% Median TSR 6% Median Revenue Growth 8% 4% 4% Bottom-Performers TSR Under 30% 10

People & Spend Analytics 11

People & Spend The Business Case Behind Analytics The applications for workforce analytics are numerous and still growing To date, some of our clients have faced the following business questions, which in turn drives a need for analytics-based assessments Talent challenges: How does our distribution of talent, either by level, function or region, compare to the market? How should we expect this distribution to change as we scale or enter new regions? People & Spend challenges: Where does our compensation spend (across all forms of pay) go within the organization, either by level, function or region? Do these results align with our internal perceptions of where value is created in the business? How does our compensation spend, either by level, function or region, compare to the market? Do the results suggest we are paying too much in certain areas? 12

People & Spend Average Global Spend Total compensation spend in aggregate can be examined against the market and by element GWA companies on average spend $1.9 billion on compensation - getting it right matters Average Total Spend ($MM) 10% 13% $1.9 Billion 77% Base Salary Target Short-Term Incentives Target Long-Term Incentives 13

People & Spend Geographic Distribution of Resources On average, 38% of employees are typically in the US, and represent 59% of total compensation spend (a 1.57 to 1 cost to staffing ratio) Employees as a % of WW Headcount Asia Pacific 36% US 38% FTEs as % of WW FTEs TDC as a % of WW Payroll Cost to Staffing Ratio US 37.7% 59.3% 1.57x Japan 1.9% 2.6% 1.37x Canada 2.0% 2.7% 1.35x UK 3.1% 4.1% 1.32x Germany 2.6% 3.4% 1.17x Brazil 1.9% 1.2% 0.63x China 9.3% 3.0% 0.32x Malaysia 2.4% 0.6% 0.25x India 14.0% 3.5% 0.25x Philippines 3.2% 0.4% 0.13x EMEA 18% Americas Non-US 8% TDC as a % of WW TDC Payroll EMEA 20% Asia Pacific 16% Americas Non-US 5% US 59% 14

People & Spend Job Category Distribution Executives, while comprising a relatively small percentage of average global headcount, command a large share of total compensation spend Executives 9.5x cost to staffing ratio Support 0.25x cost to staffing ratio Average Global Headcount Distribution Average Distribution of Actual Spend 70.0% 60.0% 59.3% 70.0% 60.0% 62.3% 50.0% 50.0% 40.0% 40.0% 30.0% 27.1% 30.0% 25.1% 20.0% 10.0% 0.0% 13.0% 0.6% Executive Management Professional Support 20.0% 10.0% 0.0% 5.7% 6.9% Executive Management Professional Support 15

People & Spend Functional Distribution On a functional basis sales/service make up roughly 40% of the talent pool and cost 45% of TDC (a 1.07 to 1 cost to staffing ratio) Engineering 1.42x cost to staffing ratio Business Functions 0.70x cost to staffing ratio Percent of Total Global Headcount Percent of Total Global TDC Spend 50.0% 45.0% 40.0% 41.2% 38.9% 50.0% 45.0% 40.0% 44.5% 35.0% 30.0% 35.0% 30.0% 28.3% 27.2% 25.0% 20.0% 19.9% 25.0% 20.0% 15.0% 15.0% 10.0% 10.0% 5.0% 5.0% 0.0% Sales / Service Engineering Business Functions 0.0% Sales / Service Engineering Business Functions 16

People & Spend Pay Mix by Function Not surprisingly, sales/service roles account for nearly half of what companies spend on cash compensation; yet, these roles also receive a fairly equal share of equity awards 60.0% 54.1% Percent of Total Spend by Function 50.0% 44.6% 40.0% 30.0% 20.0% 35.2% 34.2% 28.0% 27.4% 24.7% 21.3% 30.6% 10.0% 0.0% Sales / Service Engineering Business Functions Base Salary Bonus LTI 17

Case Study Building Scale Applying People & Spend Challenge Approach Results A large, recently public technology firm was ready to scale its business, building an expanded US sales team, as well opening new operations in 10-15 countries Rather than simply benchmarking pay job-by-job, HR and the compensation team wanted to provide the C-suite with business targets for headcount growth, expected compensation costs and predictions on talent ROI by country Using GWA, Radford established a best-fit peer group to reflect the next stage of growth for the client; with the right peer group, functional, job level and compensation distributions analyses could be performed in all target countries Special attention was paid to identifying patterns in talent allocation to uncover optimal team structures that could achieve desired growth while examining aggregate compensation spend Radford developed prototype talent models for business- and product development-focused offices that could be replicated from country to country These models also included projections for expected compensation costs (as a percentage of revenue) as operations in each country scale; this also established a framework for what-if staffing models by level 18

Performance & Spend Analytics 19

Performance & Spend The Business Case Behind Analytics Again, the applications for workforce analytics are numerous, particularly when one starts considering total rewards in the context of business performance Merging absolute or relative measures of corporate performance into the mix of talent and compensation analytics creates tremendous potential to look at HR strategy in new ways How does our turnover compare to market and do we have a total compensation issue? How do our overall incentive costs compare against the market by value and performance? Is our equity expense appropriate based on our performance? Have we allocated our spend to drive long-term performance? How can we create new models for organizational growth or talent deployment that align with projected business performance? 20

Performance & Spend Voluntary Turnover Trends Voluntary turnover continues to be in the range of 6.5% to 9.0%, with top performs closer to 7.0% Turnover rates and performance in most engagement studies are directly related 12.0% Voluntary Turnover 10.0% 8.8% 8.5% 8.7% 9.7% 8.5% 9.0% 8.0% 6.8% 6.5% 7.1% 7.1% 6.0% 4.0% 2.0% 0.0% Semiconductor Hardware Software Top-Performers TSR Over 30% 2013 2014 Bottom-Performers TSR Under 30% 21

Performance & Spend TDC vs. Industry and TSR Performance Traditional benchmarking provides one-view, adding performance may also shed light on a pay gap Average Total Target Comp (TDC) and Mix Allocation $140.0 $120.0 $100.0 $80.0 $115 $15.2 $16.2 $107 $107 $13.4 $11.6 $11.6 $16.3 $129 $19.8 $19.6 $119 $17.0 $16.7 $111 $13.8 $15.5 $60.0 $40.0 $83.8 $81.6 $79.2 $89.2 $84.8 $81.8 $20.0 $0.0 Full GWA Database Semiconductor Hardware Software Top-Performers TSR Over 30% Base Salary Bonus LTI Bottom-Performers TSR Under 30% 22

Performance & Spend STI vs. Industry and TSR Performance Cash incentives typically fall between 1.6% and 3.8% of revenue, and account for approximately 9% of payroll Performance is also a factor which drives added funding Cash Incentive Spend Metrics 50.0% 42.0% 40.0% 34.9% 29.7% 30.0% 28.5% 20.0% 10.0% 0.0% 7.0% 1.6% 2.1% 19.9% 9.1% 9.9% 3.8% 8.6% 9.1% 2.6% 2.6% Semiconductor Hardware Software Top-Performers TSR Over 30% Bottom-Performers TSR Under 30% Percent of Revenue Percent of Net Income Percent of Payroll TSR Over 30% TSR Under 30% Average Spend per Employee $10,380 $10,278 23

Performance & Spend LTI vs. Industry and TSR Performance Long-term incentives fall between 2.3% and 4.7% of revenue, and only 1.5% of market cap 20.0% LTI Spend Metrics 15.0% 10.0% 11.9% 10.6% 12.9% 12.1% 11.8% 5.0% 0.0% 2.6% 2.3% 1.4% 1.6% 4.7% 3.4% 3.3% 1.0% 1.1% 1.5% Semiconductor Hardware Software Top-Performers TSR Over 30% Bottom-Performers TSR Under 30% Percent of Revenue Percent of Market Cap Percent of Payroll TSR Over 30% TSR Under 30% Average Spend per Employee $16,961 $13,776 24

Performance & Spend TDC vs. Revenue and Market Cap Total direct compensation must be examined given pay mix changes in the market Understanding TDC as a percent of revenue and market cap can raise the discussion 40.0% TDC as a % of Key Performance Measures 35.8% 30.0% 20.0% 10.0% 23.3% 13.6% 21.4% 17.5% 11.0% 27.2% 12.5% 28.3% 15.3% 0.0% Semiconductor Hardware Software Top-Performers TSR Over 30% Bottom-Performers TSR Under 30% Percent of Revenue Percent of Market Cap TSR Over 30% TSR Under 30% Average Spend per Employee $112,128 $105,808 25

Case Study Elevating Compensation to the C-Suite Challenge Radford was retained by a global technology leader with over $25 billion in annual revenues to assess the competitiveness of its incentive programs Rather than focus on target STI and LTI levels for each job type, the company wanted to know where it stood at a macro level in terms of actual spend and how that spend compared relative to the performance of its peers Approach Using GWA, Radford compared aggregate STI and LTI spend at the company against a select group of 12 peers Aggregate incentive compensation, STI spend and LTI spend were each calculated as percentage of revenue, operating income, net income, cash flow from operations and payroll to assess relative pay for performance outcomes Results While the client targeted 50 th percentile pay on a job-by-job basis, it discovered that actual LTI spend and aggregate incentive spend was positioned closer to the 25 th percentile, explaining retention challenges The client discovered that while its incentive pay as a percent of revenue was lowest in the peer group, its pay as a percent of net income was highest 26

Case Study Organizational Structure Unmasked Challenge Radford was retained by a global technology company with over $500 million in annual revenues to assess the structure of its global operations in relation to the market In particular, the company believed its organization was not optimized vs. the market in key functional areas and countries due to over-leveling Approach Using full census data from GWA, Radford compared functional and job level distributions at the company against a select group of 10 peer companies An analysis across 11 functional areas and 20 job levels was conducted in the United States, China and India; in each case, actual employee distributions and pay vs. employee distributions were considered Results The client discovered that the percentage of its workforce devoted to product development was significantly above market in the United States, China and India, resulting in a higher cost structure Additionally, the client realized its distribution of executive and management talent was not optimized vs. the market, due to heavy concentrations in the US 27

Case Study Organizational Modeling Example The CEO is evaluating moving your headquarters to Singapore? GWA can assist with what if? modeling and talent scoping Current State Future State US Americas EMEA APAC US Americas EMEA APAC Executive 102 2 18 9 79 6 26 19 Staffing by Location Management 1,385 168 579 789 1,108 184 633 827 Professional 5,204 944 2,722 4,423 4,163 1,038 2,994 5,087 Support 1,769 565 791 2,945 1,415 622 870 3,387 Total 8,460 1,680 4,110 8,166 6,766 1,850 4,524 9.319 Executive $85.3 $1.7 $10.5 $5.2 $60.3 $3.6 $16.0 $12.0 Management $268.2 $21.3 $89.3 $72.7 $214.6 $23.2 $97.0 $76.0 Spend by Location Professional $652.6 $62.2 $228.8 $178.1 $522.1 $68.4 $251.6 $204.8 Support $69.5 $8.6 $22.6 $23.6 $55.6 $9.4 $24.8 $27.1 Total $1,075.6 $93.8 $351.2 $279.6 $852.5 $104.7 $389.5 $319.9 Overall Cost $1.8B $1.6B 28

Closing Thoughts: What s Next? 29

Closing Thoughts HR data is big data in volume for most companies but may not be effective at predicting human behavior HR data is closed system data HR trends for hiring and turnover are not just about pay but many other factors (e.g., company performance, brand, benefits, work life policies and the manager) Moving past traditional compensation benchmarking (job by job analysis) to spend benchmarking can raise the nature of the business conversation for HR Examining data against a the right peer group is important Understanding pay in the context of performance matters Compensation rule changes may also impact the benefit of GWA 30

CEO Pay Ratios Once SEC requirements for CEO-to-worker pay ratios hit, GWA-like analyses will help companies put their ratios into context CEO TDC to Average Employee Pay Ratio 120.0x 100.0x 102.0x 109.0x 95.0x 80.0x 60.0x 57.0x 64.0x 52.0x 40.0x 20.0x 0.0x Full GWA Database Top-Performers TSR Over 30% Bottom-Performers TSR Under 30% Median Average 31

Thank You! Questions?