The Right Data Now the Future of People Analytics May 2015

1

The Right Data Now! The Future of People Analytics

Human Capital Management Institute

About Human Capital Management Institute

HCMI Background:

Specialized in HR analysis & metrics

Deep expertise in Analytics & Planning

Board made up of CFOs and HR heads

Over 40 years of experience

What We Do:

Answer complex human capital questions

Quantify human capital

Transform workforce data to intelligence

Enable HR and Finance to talk

2

We believe organizations can and must, find better ways of measuring their investment in human capital. Our vision of the future is one with human capital information as impactful to

business decision making as financial information is today.

We Bring Financial Discipline, Standards and Rigor to Workforce Analytics


SaaS Analytics & Workforce Planning Software w Consulting w Training w Benchmarking

The Future of Talent = Analytics Attraction, Development, Retention and Performance

3

Analytics Adoption Over Time

Source: Gartner 2014

Analytics Are No Longer a Nice-to-Have

Human Capital Management Institute 4

Polling Question


A. We measure joiners(new hires), leavers (terminations), and total staff headcount

B. We measure recruiting time to fill and cost per hire

C. We measure turnover rate and management span of control

D. We measure quality of hire and ROI of training

E. We measure workforce productivity and Human capital ROI

What are you Measuring Today

What to Measure Measurement Trick #31

Measurement Best Practices: 1. Metrics that link to business results

2. Metrics that are actionable

3. Metrics that identify, quantify, and clarify issues across the employee cycle

4. Metrics to capture leading versus lagging indicators


Asking the Right Questions Are you measuring the right things


What If you could answer the following?

1. Which workforce HR metrics link to business results?

2. What is our workforce productivity? Is it improving? How do we rank?

3. Is it better to build, buy or rent talent?

4. What is truly the right size and cost of workforce?

5. What is our quality of hire (i.e. Top Talent)?

6. Do we know drivers of employee turnover and retention?

7. Are leaders effectively managing talent? Do leaders correlate to employee engagement, retention and performance? YES, but you MUST prove it

Examples: Talent Analytics ROI


15% productivity gain and lower costs ($55.0 Billion Package Delivery Co. )

Predicting sales stars pre hire {$1.0 Billion Bank}

ROI of sales training {$2.0 Billion Retail Co.}

Location optimization for talent growth {large West Coast Regional Bank}

Employee engagement service level revenue impact {$1.0 Billion public Airline}

40% voluntary turnover reduction {public, financial services co.}

ROI of internal vs. external hires {public bank}

$1.1 Billion Annual

$264 Million Annual $1.1 million per sales person

$250 Million Annual $250k per Salesperson

$200 Million 10 years

$96 Million Annual $5 per flight premium

$12 Million Annual majority sales + operations positions

$6 Million Annual

Reporting and Data Quality Overview

Workforce data is complex, but from the right combinations, a fact-based story can emerge

Auditing and cleansing workforce data is foundational

Management buy-in, governance and analytic skills are critical

Define metrics and standardize reporting

HRIS, ERP and workforce system providers do not know what HR data is critical.

If you rely on software and technology vendors for workforce wisdom, it will be a long and expensive wait.

Focus &

Resources

(Center of

Excellence)

Business

Complexity &

Structure

Measurement

& Analytic

Capability

Speed, Systems

Integration &

Automation

Standards,

Processes & Data

Quality

Reporting,

Scorecards &

Accountability

Workforce

Cost and

Productivity

Workforce

Knowledge

Business,

Workforce &

HR Strategy

Linkage

Where are we today?

Where do we start? How can we tell?

What does it all mean?

How do we improve?

I have the foundation, but where are my insights?


Introduction

Keys to Reporting Success:

Building a House for Data Driven Decisions

Excludes systems considerations

Linked Business and Workforce Strategy

(HR Value Creation & Workforce Optimization Model)

Workforce Planning Human Capital Analytics

Measures + Metrics Benchmarks

One Foundation

for Analytics

& Planning

Predictive Workforce

Management

Tools

Classification Tools Standards

Demand

&

Supply

Po

lici

es

&

Wo

rkfo

rce

Pra

ctic

es

Critical

Roles

&

Skills

Predictive

Modeling

Metrics

to Recruit,

Train &

Retain

Measuring & Reporting

Cost

Modeling

Root

Cause

Analysis

Ta

len

t M

an

ag

em

en

t

& P

ract

ice

s

Clean Data

+ Standards =

Reports & Measures

Analytics &

Workforce Planning

Capabilities

Analytic Framework Foundation to Roof

Workforce Planning and Analytics

2 PATHS, 1 HOUSE

Foundation

Awareness

Excellence

Reports

Data Quality

Manager data Temp & contractor data Turnover data

Geographic data

Performance mgmt data

Employee career path / succession data

Compensation data Recruiting data

Strategic Plan data by unit Job/Position data Employee basic data

Data

Driven

Decisions


Core

HR standards and data quality are the foundation for advanced workforce analytics and planning

11

The Most Important Metrics for Human Capital

Source: Softscape Inc. Survey 2008

The Real Impact and

Focus


The Metrics Journey Basic to Advanced Metrics

Base Data - No Metrics

Calculated Metrics (e.g. turnover rate)

Simple Metrics ( e.g. headcount, terminations )

Combined Source Metrics (e.g. Time to profitability)

Insightful Metrics (e.g. Revenue per FTE)

Advanced Metrics combined calculated metrics (e.g. Career path ratio)

Index Metrics (e.g. New hire success rate)

Complex Index Metrics (e.g. Quality of Hire)

How do you Stack Up?

12 Human Capital Management Institute 12

Start

World Class Analytics

Data Driven Decisions!

Data Errors

Lost HR Credibility

The Analytics & Planning Journey

Analytics journey steps

Pitfalls along the way

Journey path and goal

13 Human Capital Management Institute

Roadblocks and Pitfalls on the Path

Data Gaps, Inconsistent Data

Executive Support

Standards/Governance

Job Framework/Mapping

Resources and Analytic Skills

Data Integration

System/Tool Limitations

ROI and Success Stories

Avoid Analytics Journey Pitfalls

14

Establish Center of Excellence

Establish Reporting Standards

Benchmarks, Goal Setting, Forecasts

Basic Analysis (i.e. variances)

2 3 4 5 6 1 Create Talent Strategy,

select key metrics, align to Business

Strategy

Deliver predictive

insights, quantify impact

Analyze root causes of

workforce problems

Report key metric trends

Centralize disparate data

sources

Standardize metric definitions,

benchmark results

Case Study Roadmap Example: Global consulting company with 20,000+ employees


Adopt a Framework Set Goals/Define End

State Assess Capability GAPs/

Opportunities Design/Launch Scorecard Establish Data Standards:

Data & Transactions, Integrated Data Asset Single Version of the Truth

Clean up Historic Data

Trend Analysis Use of Advanced Metrics Advanced Reporting Basic Workforce Planning

Predictive Analytics Integrate Planning &

Analytics Report Automation $$$ ROI

The Right Way Roadmap steps

The Wrong Way Roadmap steps

Yes goal

1 Standard HR

Metrics, reports & benchmark

results

2

Centralize disparate data

sources

3

Align metrics to HR Strategy

4 5 6 Deliver

predictive insights, quantify

impact

Analyze root causes of

workforce problems

Report key metric Trends

No

No ROI or Business Alignment. Start over

Start at the Beginning, Build a Roadmap, Stay on the Path

Needed for an HR analytics function = COE Center of Excellence (COE) at a Glance

Key Responsibilities Ensure data integration & accuracy Produce timely and accurate reporting Establish and maintain metrics, reporting and analysis standards Use advanced analytics to produce rigorous and actionable insights that drive business results Provide consulting and guidance, develop HR expertise in interpreting and acting on data

Key Role Functions Technology Analytics / Reporting Research/ Business Linkage HR Consulting

15

Mission Provide Business and HR Leaders with timely, accurate and actionable workforce insights and reporting to make predictive data-driven decisions that improve business outcomes

Workforce Analytics COE


< 3 Months 3 - 6 Months 6 - 12 Months 12 - 24 Months 24 - 36 Months 36+ Months

Em

plo

ye

e S

ale

s P

rod

uct

ion

Employee Tenure

Annual Difference Between All and No Courses No Courses Some Courses All Courses

High

Case Study: ROI of Sales Training A $3.0 Billion+ Retail organization with 6,000 sales people at 2,000 locations

Average

Low

At all levels of tenure, training by the sales manager significantly increases employee sales production.

70% of EEs

10% of EEs

20% of EEs

r2 = .63

Employees who completed some courses have 45% higher sales production than those who completed no courses.

Employees who completed all courses have $250,000

USD or 75% higher sales production than those who did not complete any courses.


Best Practices of HR Analytics Programs

Focus on solving business issues first before HR issues

Find the talent you need to execute

Focus on questions rather than answers or available data

Aim small; seek out quick wins (define formulas, publishing KPIs, etc)

Integrate workforce data to business data (financial, customer, operations etc..)

Tell a complete story:

Quantitative with strong numbers

Visual with powerful visual charts

Qualitative with a story and real world examples from the business


Contact Information:


Jeff Higgins, CEO [email protected]

For more information on products and services:

www.hcminst.com

SOLVE Software Human Capital Training and Financial Statements Consulting

Human Capital Workforce Data Workforce Metrics Handbook Integration Blueprint Planning

Workforce Intelligence Consortium Group

@HCMI


The Right Data Now the Future of People Analytics May 2015

Documents

Transcript of The Right Data Now the Future of People Analytics May 2015