7. fri 840 930 houston - workforce analytics for hr decisions

Deloitte’s Analytics
Symposium 2010
Using advanced workforce
analytics to make business-
driven Human Resource
decisions
Russell Clarke
John Houston
Howard Hamilton, ESPN

October 2010

Agenda

• What we are seeing in the marketplace
• Workforce analytics approaches
• Deploying point solutions: Solving
specific problems
• Workforce planning and optimization
• Recruiting and predicting performance

1 Using advanced workforce analytics to make business-driven Human Resource decisions Copyright © 2010 Deloitte Development LLC. All rights reserved.

What we are seeing in the
marketplace

A great book about workforce analytics, not baseball


The Moneyball story

• In 1999, the Oakland A’s ranked 12th out of 14 in National League
payroll
– How could the A’s compete with richer teams to attract top players?
• The A’s manager (Billy Beane) decided to take an analytic approach
– He hired an analyst (Paul DePodesta) out of Harvard to try to predict player’s
future performance
– Example of DePodesta’s calculations

Runs Created = (Hits + Walks)*(Total Bases)/(At Bats + Walks)

• Beane used this model to hire excellent baseball players who had been
undervalued by the market
• The result?
– ―In 2006, the A's ranked 24th of 30 major league teams in player salaries, but
had the 5th-best regular-season record. This reflects a typical pattern
throughout Beane's stewardship.‖ — Wikipedia entry on Billy Beane.

The importance of business analytics

Visibility into analytics can help business leaders make decisions more
accurately, objectively, and economically — a rapidly developing
consensus in business, education, law, medicine, and even professional
sports.


The importance of business analytics (cont.)

Analytics Description
Descriptive reporting Summarize and compare operational and/or financial data
on key workforce variables within defined time frames.
These are used primarily to create lagging indicators.
Retrospective analytics Analyze one or more internal data sources to discover
useful information. Used to create both lagging indicators,
performance benchmarks, and insights.
Predictive analytics Mathematical models are applied to multiple internal and
external data sources to predict future workforce events.
Used to create leading indicators and focus limited
resources on critical employee populations.


What’s driving interest/demand for analytics in HR?

• Continued investment in technology infrastructure
– Enterprise Resource Planning (ERP) systems/data marts aggregate data
– HR process move to automated point solutions
• New type of HR leaders
– Come from finance and operations
– Common practice to use data and analytics for more effective business
decision making
• Challenging economy is forcing organizations to embrace change
– Visibility into business issues reduces risk for senior management teams
– Managing talent spend critical (one of the top three P&L line items)
• Dashboard overload


Positive financial impacts from workforce analytics

Company Impact
Top-ten national bank Increased redeployment activities from 12% to 18%
saving the corporation $18M
Global services company Improved their recruiting yield (hiring ratio) without
adding additional headcount, driving a $5.6M savings
Major airline Reduced their Full Time Employee (FTE) headcount
within their Reduction In Force (RIF) services group by
50%, saving the company $600,000 annually
National financial services Projected a cost savings of over $7M by reducing
company voluntary turnover of key employees by 1%
Leading wireless company Accelerated their decision/selection process during a
large M&A, saving $5.7M for every 1,000 employees
separated


Workforce analytics
approaches

Clients are following two paths

1. Building an HR business analytics capability

2. Deploying point solutions: Solving specific problems
– Workforce planning and optimization
– Recruiting and predicting performance


Where they are and where they want to be

We utilize the Deloitte HR business analytics maturity model when we
work with our clients in implementing reporting and workforce analytics
solutions. These steps are demonstrated to help companies reduce their
risk, optimize their spend, and facilitate executing an integrated
approach:

• There needs to be a single source of the truth
• Tools and data need to be created across all work streams
• Help to ensure that data is consistent, timely, well defined, and careful
• Tools need to be tailored to the business needs and the knowledge and
capabilities of the user; not one size fits all
• Evolve adoption over time, as capabilities, skills, tools, and data improve

As used in this document, ―Deloitte‖ means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see
www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries.


Keys to implementing an effective analytics strategy

1. Tie reporting and analytics to business-driven issues.

2. One technology is not the answer. Rather, a component strategy is
the key to success.

3. Implement in phases.


Building workforce analytics capabilities and delivering
benefits
Objective: Build a highly-effective human capital business analytics
capability and organization that is scalable and sustainable.
Phase I Phase II Phase III Phase IV Phase V
Nonexistent Developing Defined Advanced Leading
In addition to
Business Analytics

periodical reports,
management utilizes
data to test
hypotheses and
The organization improve the quality Sophisticated
produces periodical predictive modeling
of business
reports which is used in scenario-
operations
Analytics are used management uses based analysis; data
on an ad-hoc basis in decision making points management
to improve business to opportunities for
Analytics are not
operations improving operations
used in business
operations and mitigating risks

Business Analytics Capability

Key business analytics enablers

Enabler Key Questions
People What kind of organization do we need? How will we
design our organization to leverage current analytical
capabilities and understand what gaps we have?
Process What is the impact of analytics on how we do business?
Can we improve our decision-support process to more
effectively manage our ―People‖ supply chain?
Technology What solutions do I need, and when? How do I stitch
together the required technology components to enable
data-driven decision making?
Data How do I get the most out of my internal and external
data?
Security/ How are analytical decisions made? Who should be
Governance accountable for facilitating the analysis and leveraging its
insights?


Example: Workforce business analytics maturity model:
People

“People” maturity dimensions: Definitions
Leadership and Sponsorship leaders provide for championing workforce business
strategy analytics capability and the approach an organization takes towards
this goal
Talent attraction Ability to attract and recruit the talent that the service organization
needs
Competency Skills and capabilities that should be demonstrated by the people to
development meet the objectives of the organization
Organization Structure of the organization designed to deliver maximum value and
structure capability
Cross-functional Level of cross-functional interaction required to make informed and
integration business driven workforce decisions
Job design Identification and definition roles and jobs to achieve the service
organization’s objective
Culture Extent to which analytics driven business decision making is
embedded in day-to-day operations, customs, and behaviors


Example: Workforce business analytics maturity model:
People (cont.)
We have limited focus on developing Our leadership is educated on the Our workforce business analytics Our workforce analytics Our business strategy is informed and
Leadership workforce business analytics
capability.
importance of workforce business
analytics.
capability is an essential component
of our business strategy and
strategy and our business
strategy are seamlessly
influenced by our workforce insights and
predictions.
and strategy leadership focus. integrated and directionally
consistent.
We rarely seek analytical skills in We seek ―soft skills‖ in analytics and We seek candidates with strong For hiring talent, we focus on Candidates must have prior experience
Talent future hires, only transaction-oriented
Information Technology (IT) skills.
transaction- oriented IT skills. backgrounds and experience in
statistics and analytical decision
cross-functional business
analytics and advanced
in advanced analytical analysis and
relevant background in the subject.
attraction
“People” maturity dimensions

making. technological capabilities.

We have limited focus on Our employee training touches on a We have training for designated We focus on cross- functional We encourage associates to get
Competency development of analytical skills
through training or hand-on
high-level analytics for limited
functions.
analysts for BI, Analytic
Applications, Data Management,
business analytics and
advanced technological
involved in analytics-driven
experimentations, and seek
experience. and new technology software. capabilities. opportunities to collaborate on business
development analytics across functions.

We currently do We have some ad We have a We have
not have any hoc local dedicated group implemented an
workforce resources helping of individuals and organizational
analytics us generate a defined process structure (Shared
Organization
capability or generic workforce in place for Service Center or a
structure service reports without any generating Center of
organization. specific reporting/ standardized Excellence) for the
organizational workforce right service
structure. insights. level/cost/capability.
While taking workforce decisions, we We realize the importance of We have a well-defined process of We are seamlessly integrated with other
Cross often do not interact with other parts
of the business.
interacting across functions to make
workforce decisions and are looking
engaging business partners to
provide insight in interpreting data
functions for generating business-driven
workforce analytics as a service to other
functional for ways to improve it. and taking business decision. business functions .

Integration
We currently have not identified any Job responsibilities, skills and
job or role responsibility for attending reporting structures are defined to
Job design to workforce analytics. support workforce business
analytics as a core capability.

All of our workforce decisions are The current decision-making culture is We give high importance to There is initial adoption of data We emphasize on acceptance of
based on hindsight and no analytic primarily hindsight driven, but we want data/analytics driven decision mining and predictive modeling analytic applications and predictive
applications. to move to data-based decision making and it is linked to tools. Analytics is the key to modeling by mainstream. Analytics and
Culture making. competitive differentiation. sustainable competitive
advantage.
analytics-driven insights drive strategy
development.


Accelerating progress — Building a high-performing
capability and organization
It’s a journey and regardless of your strategy, most large organizations want to
create an internal capability that is scalable and sustainable. Understanding,
upfront, what are the required components and ―when‖ to invest will allow for an
efficient use of investment dollars.
“People” Maturity Dimensions: Definitions
Strategic Alignment Capability Assessment Service Delivery Model
Build centralized capabilities

Business Intelligence
Phase I Phase II Phase III Phase IV Phase V
Advanced Analytics Enable Business Strategies for Success Method of adding value Focus on
Focus on standardizing

• Further independent local delivery enhancing
In addition to periodical
Low Cost/ Knowledge Transfer/
Underwriting Excellence Marketing and Retention
variable considerations reports, management skills and
Defined Service Level Management Involvement
governance
utilizes data to test
• Improve pricing precision and design • Target the right risks f or non-renewals hypotheses and
• Increase objectivity throughout the • Improve retention of prof itable risks and

Specific (site,
Sophisticated predictive
Site Support Business Partner

unit, region)
improves the quality of
• Modify target variables The organization

Relationship to the business
business operations modeling is used in
underwriting process • Increase cross-sell opportunities produces periodical
scenario based • Distributed to Location(s) for • Aligned with Function/ Unit deploying
• Enhance risk selection and risk • Modify independent • Identif y geographic and product reports which
Operations
variables Analytics are used on management uses in
analysis, data points
management to
Local Service Needs • Line/Management Focus operationally
avoidance capabilities expansion opportunities an ad-hoc basis to decision making
opportunities f or • Required for Local Input/ • Knowledge & Know-How
• Improve pricing competitiveness in • Develop Univariate • Enhance recruiting of prof itable improve business improving operations Data Capture or Local Transfer
prof itable segments operations and mitigating risks
Reporting System producers Programs
Underwriting

• Improve underwriter negotiation
Analytics are not used
• Decision/Action Intensive
• Document Univariate
in business operations
• Manual or End-User
Marketing

capabilities
Analysis results Intensive

(company-wide)
• Discuss and document Business Analytics Capability
model validation Business Analytics Enablers
Operational Efficiency Enhanced Decision Making Transaction Processing Center of Expertise

Generic
• Reduce transaction costs techniques • Increase f raud detection capabilities People Process Technology Data Security / Governance
• Consolidated Organization • Expertise Focus — Ability
• Straight through processing of select risk IT • Improve monitoring of underwriting to Leverage
What kind of What is the impact of What solutions do I How do I get the most How are analytical • Operational Focus
segments perf ormance organization do we analytics on how we do need, and when? How out of my internal and decision made? Who
need? How will we business? Can we do I stitch together the external data? should be accountable • Standardized Services • “Best Practice”
• Improve ease of doing business with • Enhance ability to react to market f orces Development
agents sooner
design our organization improve our decision- required technology f or f acilitating the • Process Intensive Focus on
to leverage current support process to more components to enable analysis and leveraging
• Could Cover Countries or • Issue/Knowledge Intensive
• Improve claims management activities • Increase inf ormation processing analytical capabilities ef f ectively manage our data-driven decision its insights? enhancing
Region • Organized by Region
Focus on segregating skills and
and understand what customers, employees, making?
• Improve customer service capabilities and data governance
gaps we have? distributors and
suppliers? and optimizing efficiency governance

Roadmap Development
Prioritized Opportunities
Phase Year 1 Year 2 Year 3
Roadmap
Develop New and Renewal
Model Develop New and Renewal
Underwriting Models for LOB 2 and Recalibrate Models for LOB 1
Development Underwriting Models for LOB 1
LOB 3
Score LOB 1 New and Renewal
Interim Scoring Business Off-Site at Deloitte
Consulting
Develop and Deploy Scoring
Engine for LOB 2 and LOB 3
Integrate LOB 2 and LOB 3 Models
Technology Develop and Deploy Scoring
into Policy Administration Systems
Integration Engine for LOB 1 Integrate LOB 1 Models into Policy
for New and Renewal Business
Administration Systems for New
and Renewal Business

Develop Communications Training
Develop Communications Training
and Conduct Pilots for LOB 2 and
and Conduct Pilots for LOB 1
Communication LOB 3 Monitor, Assess, and Revise
& Training Training as Necessary
Launch Communications Training
Launch Communications Training
to all LOB 1 Underwriters
to all LOB 2 and LOB 3 Underwriters

Develop New and Renewal Develop New and Renewal
Business Rules, Pricing Rules, and Business Rules, Pricing Rules, and Monitor, Assess, and Revise
Reason Messages for LOB 1 Reason Messages for LOB 2 and Business Rules and Pricing Rules
Business
LOB 3 as Necessary
Integration Establish Performance Metrics for
LOB 1 Establish Performance Metrics for Monitor Performance Metrics
LOB 2 and LOB 3


Deploying point solutions:
Solving specific problems

Traditional, bottom-up approach

Typically, a bottom-up approach creates a gap between data and business
problems by emphasizing the data, leading to a common complaint:

―We have a lot of data, but no useful information.‖

Relevant, real-time Market pressures
workforce data needed to Profitability Cost containment
make informed decisions. Credit crunch Growth
Customer demographic shifts Shrinking workforce
Technological change Evolving workplace
Workforce data is often not Globalization Risk and regulatory compliance
available. Business drivers
do not dictate what data is
collected and how.
Having relevant data to inform
decision making
GAP
Data sits in multiple
repositories. It is not Translating data into a
translated into a useful useful format
business format and does
not correlate with critical
Company’s data repository
business drivers.


Alternative, strategic approach

A top-down approach can bridge the gap between data and business problems by
providing a repeatable framework for achieving resolutions.

A top-down approach Market pressures
determines that business Profitability Cost containment
drivers dictate which workforce Credit crunch Growth
Customer demographic shifts Shrinking workforce
metrics are necessary to make
Technological change Evolving workplace
informed decisions.
Globalization Risk and regulatory compliance

Predetermined Workforce Using data
Workforce Solution Sets
Solution Sets incorporate to enable
leading-practice lessons to Workforce better
Organization
provide leaders with the planning Workforce business
design and Retention
information they need to take and transition decision
modeling
optimization making
action.
Leadership Training & Workforce
Existing internal and external Recruiting
development learning productivity
data can be leveraged for
relevant workforce data to
populate the predetermined
Workforce Solution Sets. Company’s data repository


Using analytics to help solve the HR business issues

Deloitte has worked with our clients to develop and deliver innovative analytical
solution sets that are tied directly to today’s pressing business workforce issues.

Descriptive reporting Retrospective analytics Predictive analytics

Solutions set Benefit
Workforce planning and Increases accuracy of predicted revenue and talent demand by
optimization incorporating valuable third-party data

Workforce transitions Allows for enhanced compliance and financial oversight through
centralized reporting

Recruitment analytics Confirms that every resume is reviewed and considered in the
recruitment process

Retention risk analytics Changes the paradigm to a proactive strategy that mitigates risk by
predicting the attrition problem among critical workforce

Leadership development Provides an insight into the recognizable characteristics of those who
modeling will thrive in leadership roles

Organization development Simulates to-be structures to right size the organization with optimal
modeling management layers and spans of control


Workforce planning and
optimization

Workforce planning and optimization — Creating more
business value
Workforce planning and optimization forecasts and visualizes the supply
and demand of individuals for critical roles and provides the foundation to
evaluate the actions needed to meet the corresponding talent
management objectives.
From lagging… …to leading practices
• Once a year, annual planning • Continual monitoring and planning
• Macro-level planning • Micro-level planning at employee level
• Reactive organization • Proactive organization
• Ad-hoc reporting • Enterprise-level reporting
• Time-intensive and labor-intensive • Automated and real-time data visibility
• Historical view of data • Forecasting and scenario planning
• Internal data only (HR, finance, • Internal and external data with
operations, sales) macroeconomic insights
• Limited alignment with strategy • Integration with business and
HR strategy


Workforce planning and optimization process

A broad approach to planning considers combinations of data from multiple sources:

Step 1:
Data collection
Data sources Step 2a: Supply
projector
Internal
Visualize the organization
HR down to the individual
level and calculate
―inflow‖ and ―outflow‖ Step 4: Report and
Finance trends (i.e., attrition, hires, Step 3: Scenario monitor
mobility) planner Provide real-time data,
Operations Allows for ―what if‖ enterprise data to
Step 2b: Demand planning leadership and
Internal stakeholders
projector
benchmarks
Incorporate
Sales pipeline macroeconomic
data and drivers to
External project workforce demand
for the organization
Macroeconomic
data

Industry specific

Accelerate workforce planning and optimization
Labor market Deloitte’s supply, demand, and scenario planning approach leverages
existing systems and data to help organizations make business decision
Benchmarks on talent solutions.


What is new in demand estimation?

Current approach
• Develop one annual plan
• Labor- and time-intensive process to develop plan
• Plan is closely monitored, but adjustments are infrequent because it requires
same investment of labor and time

Current approach to workforce planning

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb
1
FY start
Long FY plan Plan in action
planning developed
process


What is new in demand estimation?

Proposed approach
• Develop annual plan and monthly forecasts
• Internal and macroeconomic data incorporated into plan
• Prior month’s information may be incorporated into next month’s forecast,
enabling frequent comparisons between the forecasted and actual demand
• Adjustments to the plan can be made regularly as new information is available
Proposed approaches to workforce planning
Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb

1 FY start
Shorter Plan Plan in action
planning developed (more accurate with macroeconomic data)
process
2

New data included
for Updated plans (monthly or as
reforecasted model needed)

Demand model application — Using reforecasting
capabilities
Demand estimation models are ran frequently to reforecast projections (e.g., monthly updates)
1,700,000
1,600,000 Project Hours
1,500,000
Actuals
1,400,000
Baseline Plan (3/xx)
1,300,000
Model Fcst 0
1,200,000
Model RFcst 2
1,100,000
Model RFcst 4
1,000,000
Model RFcst 6
900,000
800,000
Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Salary estimation Salary excess Year-end headcount Opportunity cost
Apr-Mar Required $108,873,457 1,139
Client Plan (@ Mar XX) $133,463,223 $24,589,766 1,698
ModelFcst0 $124,386,621 $15,513,164 1,499 ($9,076,602)
ModelRFcst2 $121,124,778 $12,251,321 1,436 ($12,338,444)
ModelRFcst4 $117,157,213 $8,283,756 1,312 ($16,306,009)
ModelRFcst6 $113,911,222 $5,037,765 1,167 ($19,552,001)


Recruiting and predicting
performance

Recruiting/talent acquisition — Sourcing more
competitively
Companies still struggle managing the top of the recruiting pipeline…how to more efficiently
manage and optimize prospects and suspects. How do we identify qualified candidates who
most resemble our best employees while decreasing recruiting cost and time?

25,000 Applicants People Process Technology Data


12,500 career profiles   
6,250 background checks    
3,500 candidate interviews    
2,000 new hires    

Defining your target (what you are trying to
replicate) is extremely important in modeling. By
segmenting the group of hires, you can define and
compare smaller subsets such as high performers
and/or long-term employees. This insight can be
1,000 Employees at Year-End
invaluable throughout the entire hiring process.
(Yield: ~4%)


Traditional recruiting data

Traditional application/recruiting data can make it difficult for recruiters to
differentiate between prospects.

Fred Bill Joe
• Twelve years of work experience • Fifteen years of work experience • Twenty five years of work
• Four previous employers in past • Two previous employers in past experience
10 years 10 years • One previous employer in the
• Current employer is small • Currently unemployed past 10 years
company • Has completed no relevant • Current company is a
• Has completed several relevant courses large company
courses • Attended community college

Who would be the most successful?
Who would be the long-term employee?
• Traditional recruiting data makes it difficult to differentiate
people
– Simple set of rules comparing work experience and/or education and
training levels
– Uniform approach across candidate base


Advance analytics — More detailed view

Expanding the data elements from internal/external sources provides a more
comprehensive and detailed view.
Fred Bill Joe
• Twelve years work experience • Fifteen years work experience • One employer in past 10 years
• Length of residence — two years • Length of residence — 10 years • Twenty five years work
• No children • Household size is four with experience
• Currently renting a home small children • Current company is large
• Four previous employers in past • Owns home company in a different industry
10 years • Reading: Science Technology • Attended community college
• Foreclosure/bankruptcy • Urban single cluster courses in relevant topic area
indicators • Premium bank card • Renting a home
• Medium-estimated household • Medium/high-estimated • Length of residence — one year
income household income • Household size = one
• MVR negative correlations • No MVR data • Revolve large monthly balances
• Owns pickup/SUV • Owns two midsized cars • Suburban Striver Psychographic
• Hobbies — Sports • Hobbies — Techie Cluster
• Low regional economic growth • Medium regional economic • High-estimated household
growth income
• MVR neutral correlation
• Owns three or more cars
• High regional economic growth

Predictive models built from these and hundreds of other data elements can better
quantify the likelihood and reasoning of future individual employee events.


More detailed view enables better recruiting

Workforce Analytics uses new and traditional sources of information to quantify
the likelihood and reasoning behind future employee events. If effectively
implemented, it allows scarce resources to be better focused, resulting in
measurable benefits.

Fred Bill Joe
Likelihood of 40% less likely than average to 60% more likely than average 30% more likely than average
future event be a successful hire and stay to be a successful hire and stay to be a successful hire;
with the company for three with the company for three however, low retention
years years indicators

Top three • Suboptimal employment • Optimal past employment • Suboptimal employment
reasons history history history
• Low household • High household • No household
responsibilities responsibilities responsibilities
• Poor financial indicators • Good financial indicators • Higher financial indicators

Possible • Unlikely pursuit — Third tier • Actively pursue — Primary • Possible Pursuit — Second
actions tier tier


Summary: Using advanced workforce analytics to make
business-driven Human Resource decisions
The marketplace shows a developing
interest/demand for analytics in HR as
evidenced by:
– Continued investment in technology
infrastructure
– New type of HR leaders
– Challenging economy is forcing organizations to
embrace change
– Dashboard overload

Use an HR business analytics maturity model
when implementing reporting and workforce
analytics solutions. This helps reduce risk,
optimize spend and facilitate an integrated
approach.


Summary: Using advanced workforce analytics to make
business-driven Human Resource decisions (cont’d)
Workforce planning and optimization forecasts
and visualizes the supply and demand of
individuals for critical roles and provides the
foundation to evaluate the actions needed to
meet the corresponding talent management
objectives.

Predictive models built from hundreds of data
elements can better quantify the likelihood and
reasoning of future individual employee
behavior and events.


Contact information

Russell Clark
Director
Deloitte Consulting LLP
rclarke@deloitte.com

John Houston
Principal
Deloitte Consulting LLP
jhouston@deloitte.com


"This presentation contains general information only and is based on the experiences and research of Deloitte practitioners. Deloitte is not, by means of
this presentation, rendering business, financial, investment, or other professional advice or services. This presentation is not a substitute for such
professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision
or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte, its affiliates, and related entities shall
not be responsible for any loss sustained by any person who relies on this presentation.

About Deloitte
Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its network of member firms, each
of which is a legally separate and independent entity. Please see www.deloitte.com/about for a detailed description of the legal structure of Deloitte
Touche Tohmatsu Limited and its member firms. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP
and its subsidiaries.

"This presentation contains general information only and is based on the experiences and research of Deloitte practitioners. Deloitte is not, by means of
this presentation, rendering business, financial, investment, or other professional advice or services. This presentation is not a substitute for such
professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision
or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte, its affiliates, and related entities shall
not be responsible for any loss sustained by any person who relies on this presentation.

Copyright © 2010 Deloitte Development LLC. All rights reserved.
Member of Deloitte Touche Tohmatsu Limited

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