WORKFORCE METRICS SOLUTION2014 EMEA OVERVIEW12 November 2014

Tom Jacob, Senior PartnerDavid Elkjaer, Senior Associate

MERCER

Tom JacobSenior Partner

David ElkjaerSenior Associate

Global LeaderResearch & Insights ProductsPhiladelphia, United States

tom.jacob@mercer.com

+1 215 982 4254

david.elkjaer@mercer.com

+ 45 45959624

Global LeaderWorkforce MetricsCopenhagen, Denmark

TODAY’S PRESENTERS

MERCER

AGENDA

SOLUTIONOVERVIEW

02EMEATRENDS

03

CASE STORY

04

INTRODUCTION

01

Q&A

05

SECTION 01

INTRODUCTIONWHAT ARE METRICS

MERCER

WHAT ARE WORKFORCE METRICS?

Track the workforce

WORKFORCEMETRICS

Strategically aligned to thebusiness

Business planning and problemidentification/solving

External comparison puts themetric in context

MERCER

WHAT ARE WORKFORCE METRICS?

AnecdotesReactiveChecks

OngoingReports

Benchmarks

Correlations

Simulationsand

Forecasting

Predictiveand CausalModelling

WorkforceMetricsSolution

SECTION 02

SOLUTION OVERVIEW

MERCER

SOLUTION OVERVIEWMETRICS COVERED

Span of Control Financial Metrics Workforce Structure

Workforce RetentionWorkforce Cost(New in 2014)

Functional Outsourcing(New in 2014)

MERCER

20125,088 organizations57 markets

20136,323 organizations64 markets

201412,600*organizations78*markets

*NOTE: Based on 2014 participation projection

SOLUTION OVERVIEWPARTICIPATION OVERVIEW

MERCER

78 COUNTRIES COVERED IN THE 2014 METRICS SURVEY

SOLUTION OVERVIEWPARTICIPATION IN SELECECTED COUNTRIES

326

1,145

392

227

270

177

126

231204

174

200168

1631,605* 243*

534*150

392*

211*

*NOTE: Based on 2014 participation projection

MERCER

EMEA PARTICIPANT DISTRIBUTION BY INDUSTRY AND HEADCOUNT GROUPING

SOLUTION OVERVIEWPARTICIPATION OVERVIEW – EMEA – 3,700

0 100 200 300 400 500 600 700 800 900

Consumer Goods

Other Durable Goods Manufacturing

Life Sciences

Other Non-Manufacturing

High-Tech

Other Non-Durable Goods Manufacturing

Transportation Equipment

Services (Non-Financial)

Energy

Retail & Wholesale

Financial Services

Insurance

Mining & Metals 20,000 <10,001 - 20,000

5,001 - 10,0001,001 - 5,000

501 - 1,000101 - 500< 100

MERCER 11

ONLINE DATA DELIVERY TOOLSAMPLE DASHBOARD

Includes 2012, 2013and 2014 data,enabling time seriesanalysis.

Detailed informationand formula on eachmetric.

Easily switch betweengraphs and tables.

MERCER 12

ONLINE DATA DELIVERY TOOLSAMPLE DASHBOARD

View the structure oforganizations usingMercer Internal LaborMarket Map

Detailed data on eachcareer level

Filter by industry, sizeand geography

SECTION 03

EMEA TRENDS

MERCER

FOR A SAME SAMPLE OF COMPANIES IN OUR DATABASE THE GRAPH BELOW SHOWS THE 2013 &2014 PRODUCTIVITY AND THE LINE REPRESENTS THE PERCENTAGE CHANGE.

14

EMEA TRENDSSAME SAMPLE – PRODUCTIVITY 2013 – 2014 TREND

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

0

100

200

300

400

500

600

700

800

2013 2014 Percent Change(Secondary Axis)

USD

(000

’s)

MERCER 15

EMEA TRENDSSAME SAMPLE – DRIVERS OF PRODUCTIVITY CHANGE

Productivity Headcount Revenue

Western Europe

Northern Europe

Southern Europe

Northern Africa

Middle East

Eastern Europe

10% -8% 1%

2% 3% 5%

-3% -1% -4%

--4% 13% 9%

--15% 19% 1%

--35% 9% -29%

MERCER

THE BUSINESS MODELS WITHIN SPECIFIC SUB-SECTORS, HERE IN CONSUMER GOODS, IMPACTSTHE PRODUCTIVITY, IN SOME CASES, TO A LARGER DEGREE THAN THE GEOGRAPHY.

16

EMEA TRENDSSAME SAMPLE – PRODUCTIVITY INDUSTRY TREND

-

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Consumer Goods - Other orCombination

Beverage & Tobacco Food

Northern Europe

Western Europe

Southern Europe

Eastern Europe

USD

(000

’s)

MERCER 17

Blue Collar

White Collar

Professional (Non-Sales)

Professional (Sales)

Management

Executive

Northern Europe Eastern Europe

19%

8%

17%

3%

24%

29%

9%

25%

23%

1%

11%

31%

EMEA TRENDSSAME SAMPLE – CONSUMER GOODS COMPARISON

• In Northern Europethe top two layersare significantlylarger than inEastern Europe.

• This Indicates thatthere is a largerpresence ofinternationalmanagement inNorthern Europe.

MERCER 18

Northern Europe Eastern Europe

EMEA TRENDSSAME SAMPLE – CONSUMER GOODS COMPARISON

Marketing and Sales

Operations

Logistics and Distribution

Finance

Human Resources

Product or Service Development 10%

5%

8%

35%

19%

3%

5%

20%

30%

31%

1%

1%31%

78%

94%

67%

42%

100%

41%

96%

100%

91%

80%

98%

StructureHas

Function StructureHas

Function

• The size of theoperations functionis not significantlydifferent.

• The proportion ofcompanies havingoperations is twiceas large in EasternEurope.

MERCER 19

EMEA TRENDSCORRELATION – PRODUCTIVITY AND COMPENSATION REVENUEPERCENT

Percent of Revenue Allocated to Compensation

Prod

uctiv

ityU

SD(‘0

00)

• Overall across the EMEAregion we see a significantcorrelation between thepercent allocated to totalcompensation andproductivity.

• This trend is evidentacross most industriesexcept, as an example,Retail & Wholesale wherethere is no correlation.

MERCER 20

EMEA TRENDSCORRELATION – VOLUNTARY TURNOVER AND SALARYINCREASE

• Analyzing the averagesalary increase rate andthe voluntary turnover perlevel gave no significantcorrelation, at the countrylevel, except for theProfessional Sales level.

• A question in thisconnection could be if theProfessional Sales level istypically more extrinsicallymotivated compared toother level.

Average Salary Increase

Volu

ntar

yTu

rnov

er

Professional – Sales

MERCER 21

EMEA TRENDSCORRELATION – VOLUNTARY TURNOVER AND REAL SALARYINCREASE

• Analyzing the average realsalary increase rate andthe voluntary turnover perlevel gave no significantcorrelation, at the countrylevel, except for theProfessional Sales level.

• A question in thisconnection could be if theProfessional Sales level istypically more extrinsicallymotivated compared toother level.

Average Salary Increase Minus Inflation

Volu

ntar

yTu

rnov

er

Professional – Sales

MERCER 22

EMEA TRENDSCORRELATION – VOLUNTARY TURNOVER AND SPAN OFCONTROL

• The organizational span ofcontrol, especiallymanagement, is a proxyfor how much individualsupervision eachprofessional receives.

• In this analysis weexamined how themanagement span ofcontrol correlated withvoluntary turnover for thesales professionals.

• Taking the average,across all industries, wefound a positivecorrelation.

Management Span of Control

Volu

ntar

yTu

rnov

er

Professional – Sales

SECTION 4

CASE STORY

MERCER

USING FACTS AND DATA TO UNDERSTAND YOUR ORGANIZATION

RetentionAn organization’sworkforce is theoutcome of threeinterrelated laborflows and theeffectiveness withwhich they aremanaged.

Attraction

WHO COMES INTOTHEORGANIZATION?

Development

HOW DO PEOPLEMOVE THROUGH THEORGANIZATION,THROUGH DIFFERENTASSIGNMENTS, JOBSAND LEVELS OFRESPONSIBILITY?

WHO IS STAYINGAND WHO ISLEAVING?

MERCER 25

CASE STORYBACKGROUND

A North American Pharmaceutical company is experiencing ahigh level of turnover within specific levels of theirorganization; they believe this is partially due to theirorganizational structure being misaligned to the typicalmarket structure and is too top heavy.

Analysis of how organizational turnover levelscompare to external market.

Based on structural information contained in metricsdatabase, analyze if overall structure is different thanmarket.

To see impact of structure and turnover levels, examinehow productivity levels and total compensation structurecompare to external market.

MERCER 26

CASE STORYTURNOVER & STRUCTURAL BENCHMARK

Blue Collar

White Collar

Professional (Non-Sales)

Professional (Sales)

Management

Executive

Total / Voluntary

Turnover

16% / 12%

10% / 5%

15% / 10%

20% / 15%

10% / 5%

4% / 2%

0% / 0%

Overall

Structure

12% / 8%

7% / 4%

12% / 7%

11% / 7%

13% / 9%

10% / 6%

8% / 4%

Total / Voluntary

TurnoverStructure

Company Benchmark

20%

8%

26%

16%

16%

33%

3%

10%

27%

5%

11%

30%

MERCER 27

CASE STORYCOMPENSATION DISTRIBUTION BENCHMARK

Blue Collar

White Collar

Professional (Non-Sales)

Professional (Sales)

Management

Executive

% of revenue spent ontotal compensation

Compensation Distribution Compensation Distribution

Company Benchmark

33%

6%

20%

28%

11%

33%

10%

6%

16%

24% 23%

15%

7%

19%

MERCER 28

CASE STORYPRODUCTIVITY BENCHMARK

The below shows the productivity in North America for the company in question, thePharmaceutical industry and the All Industries benchmark as a reference point.

The low productivity is a result of the bottle neck found in the organization and the highturnover on the professional (non-sales level).

590791 713

480697 616

Company Pharma All Industries Company Pharma All Industries

United States Canada

MERCER

Organizational structure is a driver of overall workforce cost andorganizational effectiveness.

Overall turnover figures can mask the differences between levels andfunctions where issues may exist.

Do not base your decision purely on external data but use it as an inputto make informed decisions.

Knowing the drivers of productivity change is key to understandingproductivity in your industry.

KEY MESSAGES

29

SECTION 5

Q&A

MERCER

Q&A

To ask a question, click on the Q&A button on the bottom right-hand side of your screen.

MERCER

ADDITIONAL RESOURCES

You can request the complimentary executive summary, requestaccess to the demo site, view a robo demo of the system, andmore! visit us at www.imercer.com/workforcemetrics

SECTION 6

APPENDIXMERCER TEAM BIOGRAPHIES

MERCER

TOM JACOBGLOBAL LEADER | RESEARCH & INSIGHTS PRODUCTS

Tom is a Senior Partner in the Information Solutions (IS) group of Mercer’s TalentDivision. He joined Mercer in 2003 and is based in Philadelphia.

Tom has served in a number of roles at Mercer all having in common the innovationand launch of new products and services. He presently serves as the global leader ofResearch & Insights products which includes Mercer’s industries and metricsinformation products.

Prior to joining Mercer, Tom was Vice President/Global Managing Director of HayInformation Services, Inc. at HayGroup Inc. He served at DRI/McGraw Hill as GroupVice President/General Manager of the DRI Energy Forecasting and Consulting Group,and GPU Service Corporation in the Corporate Planning Division.

Tom earned a bachelor’s degree in economics from LaSalle University, a masters ineconomics / econometrics from Temple ,and has completed doctoral studies inEconomics at Temple University. He presently serves as a Member of the EnterpriseManagement Consulting Practice Advisory Board for the Temple University Fox Schoolof Business. He has been a speaker throughout the world on various topics includingthe return on investment in Human Capital Programs, the Global Economic Outlook,and the factors which distinguish quality compensation and benefits surveys.

Tom JacobSenior PartnerPhiladelphia

MERCER

DAVID ELKJAERGLOBAL LEADER | WORKFORCE METRICS

David is the global workforce metrics product manager. He is responsible fordeveloping Mercer’s capabilities in providing relevant Human Capital (HC) metrics inorder to provide clients with an external perspective within the areas of workforcecomposition, C&B, HR functional metrics, recruitment and retention.

From a technology standpoint David is an expert in Mercer’s Workforce analytics tool,Mercer Analytics, which enables organizations to gain critical insight into theirworkforce and utilize Mercer’s expertise within the field. One of David’s key strengths isto look past the complexity of data and numbers to reach business critical insight.

His work at Mercer within workforce analytics and HC metrics also involves theoperational part of gathering workforce data from Mercer’s different surveys,performing analysis and placing the data within an organizational context to make itactionable for clients.

David studied Sociology at Copenhagen University. He specialized in quantitative andqualitative data analysis and design of surveys. He also focused on organizational andeconomic analysis.

David ElkjaerSenior AssociateCopenhagen