Comptryx U.S. Virtual Conference - Mercer

welcome to brighter

Mercer | Comptryx

U.S. Virtual Conference

December 2nd, 2020

2

Colleen Resca

3

Agenda

1. Introduction/Welcome (Roger Sturtevant / Colleen Resca)

2. Mercer SSO: Login changes & client federation

3. Mercer | Comptryx: Hot Jobs & Market Trends

Europe (Patrick Gutmann), U.S. (Roger Sturtevant)

4. Pay for Distributed Work (Tauseef Rahman)

How the pandemic has altered pay practices for remote work

5. Product Roadmap with Your Input: Interactive (Michael Anderson)

6. Trend Analysis Feature in Comptryx: Tips & Trends (Nivasen Govender)

7. D&I Reporting: Gender, Age & U.S. Ethnicity Benchmarking (Ashley Blackman)

8. Q&A and Wrap-Up

Copyright © 2020 Mercer (UK) Inc. All rights reserved. 4

Mercer SSO (Single Sign On)

Mercer | Comptryx

• SSO represents a secure way of accessing Mercer Products

• Comptryx was added to Mercer SSO in late October

• It is important to use the direct Comptryx URL … https://comptryx.mercer.com

• With your Mercer SSO account you can log into Comptryx and other subscribed products

• If you would like to have your company “Federated” with Mercer SSO (log directly to

Mercer with your company’s credentials), please contact us at [email protected]

5

6

Patrick Gutmann


89%

71%

50%

45%

41%

38%

38%

37%

36%

34%

Cloud Services -Operations

User Interface Design

Scrum ProjectManagement

Release Engineering

DocumentationManagement

Software Engineering -Apps

Data Scientist

Information SystemsSecurity

Cloud Engineering

Human FactorsEngineering

New Hire Rate / EngineeringProfessionals

47%

41%

34%

34%

33%

31%

30%

28%

28%

27%

Lisbon

Madrid

Cambridge

Stockholm

London

Dublin

Prague

Budapest

Warsaw

Milan

New Hire Rate / R&D Professionals


2.6

%

2.8

%

3.1

%

3.1

%

3.0

%

3.1

%

3.4

%

3.2

%

3.2

%

3.4

%

3.8

%

7.6

%

2.2

%

2.4

%

2.5

%

2.4

%

2.5

%

2.5

%

2.8

%

2.7

%

2.8

%

2.9

%

3.4

%

5.4

%

2.6

%

2.7

%

2.7

%

2.8

%

2.8

%

2.8

%

3.0

%

3.0

%

3.1

%

3.1

%

3.7

%

7.9

%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

Port

ug

al

Denm

ark

Ita

ly

Fra

nce

Spain

Sw

ed

en

Germ

any

Ne

therl

and

s

Irela

nd

Unite

d K

ing

do

m

Pola

nd

Ukra

ine


2.6

%

2.7

%

2.7

%

2.8

%

2.8

%

2.8

%

3.0

%

3.0

%

3.1

%

3.1

% 3.7

%

3.3%

3.7%

3.2%

3.8% 3.9%3.7%

4.0%

3.4%

3.7%3.9%

4.4%

0%

1%

1%

2%

2%

3%

3%

4%

4%

5%

5%

Port

ug

al

Denm

ark

Ita

ly

Fra

nce

Spain

Sw

ed

en

Germ

any

Neth

erl

and

s

Irela

nd

Unite

d K

ing

do

m

Pola

nd

General Tech market Hardware Internet /Ecommerce Software


Industries have a different approach on compensationDublin, Non Sales Roles P3, EUR

Mercer | Comptryx 2019


69,70061,900

77,60085,300

67,200

103,600

Software/SaaS Overall Internet/E-Commerce

Non Sales Jobs Software Function

Segmentation of pay by industryDublin, Non Sales Roles vs Software Function, P3, EUR, Total Direct Pay

Mercer | Comptryx 2019

∆ 9%∆ 22% ∆ 34%

25%

54%

Segmentation of pay

by function within

Industry

Differences in levels of

pay between Industries


35,400

36,00037,900

76,10078,600 77,800

66,90070,100 68,800

32,600

38,200 39,600

42,500

47,600

58,700

62,90065,300

68,60072,500

75,300

20,000

40,000

60,000

80,000

2018

2019

2020

Germany: 2%

Increase from 2018 to 2020

UK: 10%

Netherlands: 3%

Sweden: 11%

Portugal: 12%

Poland: 21%

Czech: 7%

*Total Direct Compensation, Comp weighted

average, EUR

13

Roger Sturtevant


*Pay Premium of New Hire

Total Direct Comp /

Tenured EE TDC

Professional Level

Employee Hiring


*Pay Premium of New Hire

Base Salary / Tenured EE Base

Professional Level

Employee Hiring


Hiring Rates by Core Function by U.S. Location


Voluntary Turnover Rates by Core Function by U.S. Location


Hot Jobs– Software Engineering vs. AI / Machine Learning18

AI/ML pays higher (TDC)

than generic SW

Engineering and at the

90th percentile even the

P2-AI level pays more

than the P5-SW!

Definitely a hot job!

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

50th 60th 75th 90th

Software Engineering vs. AI / Machine Learning Engr (by Level)

Total Direct Comp 50th to 90th P'cile

P5-SW

P4-SW

P3-SW

P2-SW

P5-AI

P4-AI

P3-AI

P2-AI

19

Tauseef Rahman


The evolution of flexibility

pre-COVID future

Treated as a benefit

• ‘We work better together” culture or

locations where ‘face time’ is a cultural

norm

• Office is a space for both individual and

collaborative work

• Companies may allow work from home

with no support

• Work environment is catered to an on-site

• Culture where employees expect to flex

where they work

• Office is a space for collaboration (rather

than individual work)

• Company provides resources and benefits to

support remote work

• Work environment is adapted for a

blended model

No policy / manage

by exception

Part of company

culture and employee

mindset

Deter Accommodate Promote


The future of flexible working

Amir, engineer“I collaborate with my

team a few days a week

at the office, but otherwise

work from home!”

James, technician“I work 40 hours a week,

but vary the days and

times I work to meet the

needs of my family.”

Liz, accountant“I work 60 hours per week

during busy seasons, but

scale back to 30 hours per

week the rest of the year.”

Darnell, nurse

manager“I share my case load with

another manager, and work

a reduced schedule to meet

my personal needs.”

Hannah, designer“I work on demand on

projects that fit my interests

across multiple employers.

I’m my own boss!”

wherelocation & infrastructure

whenhours and scheduling

howscaling, technology

whatjob content and sharing

whoalt. workforce, automation


Three critical questions to drive flexibility at scale


Driving sustainable execution

em

plo

yee e

xp

eri

en

ce

foundational enablers: establish the building blocks

people programs: evolve for a new way of working

Infrastructure: resources to drive successful execution

policy and

governancecommunication

and change

analytics and

measurement

culture

and trust

performance

and careerstalent

acquisition

health and

well-beingdiversity and

inclusion

EVP and total

rewards

leadership /

training

onboarding

real estate

and space

remote

workplace

setup

virtual

collaboration

technology

Social

connectedness

compensation and

reimbursements

24

Will pay cuts persist related to flexible working?

VM Ware Cuts Pay for Remote

Workers Fleeing Silicon Valley

Bloomberg

Facebook employees could receive

pay cuts as they continue to work

from home USA Today

Silicon Valley Pay Cuts Ignite

Tech-Industry Covid-19

Tensions Wall Street Journal

Stripe Workers Who Relocate

Get $20,000 Bonus and a Pay Cut

Bloomberg

Will organizations make pay cuts for

workers who relocate?

3%

8%

54%

35%

Yes, employees will

receive a pay cut

Maybe, if pay is well

above market

No pay cuts for remote

workers

Yet to be determined

6%

23%

29%

42%

General

IndustryHigh

Tech

Source: Mercer US COVID Pulse Survey, General

Industry (n= 305), High Tech (n=31)



What will happen to compensation with more flexible working?Statistical analysis of Comptryx shows tech tends to pay different to all industries even when it comes to geographic differentials

-13%

-4%

-11%-10%

-16%

-21% -21%

-10%

-18%

-21%

-6%-7%

-9%

-11% -11% -11%

-14% -15%

-18%

-23%-25%

-20%

-15%

-10%

-5%

0%

Seattle New York Los Angeles Washington Chicago Portland Atlanta Boston Dallas Austin

Geographic Pay Differentials Relative to Silicon Valley

All Industry Geo Diff (ERI) Tech Geo Diff (Comptryx Analysis)


Determining a path forward

33%

12%

5%

11%

38%

23%

19%

6%

6%

45%

All Industries High Tech

Pay at the market rate

of the office location

Pay at the market rate

of the home location

Pay at a national rate

Pay at the defined labor

market for the role

Yet to be determined

What are you paying for today, and

how should that evolve?Cost of labor, Cost of living, skills

What is the labor market for your roles,

and how is it shifting with flex

working? Local, regional, national

How will you transition to align with

the new labor market?Will pay cuts happen – and if so, when,

how and what is adjusted?

How are companies handling localization of

pay for employees who work remotely?

Source: Mercer US COVID Pulse Survey, General Industry (n= 305), High Tech (n=31)


29


Comptryx Roadmap Feedback

Simplify Data Input

Mercer Data Connector

Show my Organization

ILM (Internal Labor Map) with external benchmarks

Surface Diversity Insights

DEI Dashboard to highlight key

diversity insights about my

organization vs peers

Custom Exec Reports

Enable me to build customized

reporting & dashboards that I can use

for executive reporting

Integrate Comptryx to our

Systems (HRIS, etc)

Give me fresh and automated insights

into my organizational metrics (with

benchmarks)

Total Rewards

Benchmarks

Add detail for benefits costs

(Health, Wealth) so that I can

better optimize my total rewards


Mercer Data Connector


Mercer Internal Labor MapGender Focused View


Gender Equity – External Labor Marketmale vs. female (hiring, promo, term)

33

Source: Mercer | Comptryx

• Females exceed males on these 3 metrics for the U.S. and each location

• NY Tri-State metro has the highest female hiring (32.6%), but also the highest turnover (12.9%)


35

Nivasen Govender


Outline

What is the Trend Analysis Functionality

Value of Trend Analysis

Demo of Trend Analysis Feature

Insights Derived from the System

Mercer | Comptryx


What is the Trend Analysis Functionality

Mercer | Comptryx

• A tool within the Mercer | Comptryx system that allows users to view year over year

trends

• Trends in Pay (base salary, total cash etc.) & Workforce Metrics (turnover, hiring,

promotion rates etc.)

• Analysis of trends in pay/metrics for the Market & Your Own Data – if data submitted

consistently for at least 2 years

• Ability to trend historical data over a 2 to 5 year time span & drill down into specific

categories (location, function, level, gender, age etc.)


Value of Trend Analysis

A C T U A L PAY

G R O W T H O V E R T I M E

Pay Trends

H I R I N G / T U R N O V E R

C H A N G E S B Y J O B /

L O C AT I O N

Workforce Churn

A R E I N I T I AT I V E S

T U R N I N G I N T O

R E A L I T Y ?

Diversity

P O P U L AT I O N A N D

PAY R O L L S H I F T S

Transformation

Mercer | Comptryx


Demo of Trend Analysis Feature

METRICS IN TREND% Population

% Payroll

Pay (Base, Tot Cash,

Bonus, LTI, Total Direct)

Hiring Rates

Turnover

% Female

Gender Wage Gap

Age/Age Groups

Tenure/Tenure Categories

Promotion Rates/Amounts

% Top Performer

Pay Leverage Calcs

TRENDING OF PAY AND WORKFORCE ANALYTICS

Mercer | Comptryx


METHODOLOGY

• Your data* and market data

• Market Views include all

Comptryx, standard market

views, and peers

• Can choose “same company” or

“all companies” for each trend

increment

• Trending from two to five years

• Choose the metric to analyze

• Market data is updated

quarterly, your data with each

annual submission

* Your data dependent on frequency and timing of input

Mercer | Comptryx


METRICS TO TREND

Mercer | Comptryx


PAY ELEMENTS TO TREND

Mercer | Comptryx

Companies in pay trending are a subset

of the global pay module and will not

align with those values


Mercer | Comptryx

ADDING CATEGORIES FOR COMPARISON


Mercer | Comptryx

UP TO 11 VALUES WITHIN A CATEGORY CAN BE ADDED


Mercer | Comptryx


CHARTING

• Your Data

• Market Data

• Your Data & Market

• Vertical or Horizontal

Mercer | Comptryx

CHARTING OPTIONS

FOR “YOU” &

“MARKET”


Mercer | Comptryx

Insights- Population Growth by Function, in the US, Across Levels

Growth within R&D

Decline and levelling out across ServicesIncreases in roles related to Software and Hardware

Engineering


Mercer | Comptryx

Insights- % Female & Wage Gap by Location

Tri State Metro only one to show growth when compared to

5 years ago.

At this typically most populated level, all locations have closed

the wage gap, with the most noticeable impact occurring in the

Tri State Metro


Mercer | Comptryx

Insights- Promotions as a % of Base by Gender (US, All Prof)

The data shows that women's promotion amounts as a % of base

have been slightly exceeding that of their male counterparts,

which could also be contributing to decreased wage gaps that we

saw in the previous slide.


Mercer | Comptryx

Insights- LTI Total by Level & Location (US, within R&D)

Sharp spike in Seattle, but beginning to trend down

Increases in Silicon Valley and the Tri State

Vast difference in total LTI between the two levels

Strong continuing upward trends – Seattle, Silicon Valley, Tri State

51

Ashley Blackman


But how do you identify

wider trends?Mercer | Comptryx

Platform

Gain insights into

workforce patterns

You know your

workforce

Get to know your workforce

D&I

Are you meeting your

diversity initiatives?

Compensation Metrics

Are you promoting

talent equitably?

Equity

Are you compensating equally

across genders?

Benchmark to

your competitors

Copyright 2020 Mercer LLC. All rights reserved. 52


Set achievablediversity targets

See where there is

work to do

Scan workforce Scan industry

Use benchmarks to

set targets

Meet pay equity requirements &

create realistic diversity goals

Legislation calls

for transparency

You need to see

the full picture

53

Gender ● U.S. Ethnicity


Use market industry benchmarks to establish diversity targetsGender

Analyze by: Standard Data Table Dynamic Data Visuals


% Female by Level Gender Metric Analysis

Use market industry benchmarks to establish diversity targetsGender

% Female

For each displayed category within the selected

population the percentage indicates the percentage of

female employees in the population.

Wage Gap (Base, STI, Total Cash, LTI, Total Direct Comp)

Calculated as the employee average pay of women

divided by the average of men. The wage gap will vary

with the "Pay Element" selected in the "Global

Parameters" in the upper left of the web tool.


Gender

56

Use market industry benchmarks to establish diversity targets

Boston, USA - P3 Level by Function

% Female - Software Engineers by Country


U.S. Ethnicity

57


Hiring RateBlack turnover 39% greater than white.

Second only to Two/+ Races, at 54%Black hiring rate 72% greater than white.

Second only to Two/+ Races, at 88%Turnover Rate (Vol)


U.S. Ethnicity

58


% Top Performer % Promoted Black/African American has the lowest

promotion rates of any ethnicity category

Black ee's receive top performer rating

at half the rate of White, Asian


Age Benchmarks

59


Documents

Comptryx U.S. Virtual Conference - Mercer