hr analytics - paads2016

HR Analytics

PanaEk Warawit

p.warawit@infomobius.com, @p_warawit

• Thai, Bangkok based

• B.Eng.(Electronics) & M.Sc. (MIS)

• 20 Yrs w/ P&G

• Most assignments related to Business Intelligence

• Asia BIM Competency Leader

• Trainer in EA, AM, BT

• Currently with InfoMobius

• Principal Business Intelligence Consultant

• Writes & speaks in the topic of

• Business Intelligence, Big Data, Business Analytics

• p.warawit@infomobius.com

• @p_warawit

♥ Married to Nay

♥ Only son – Kuang, 23

Hobbies & Interests

♦ Marathoner

♦ TED Thai Translator

♦ Reading / Blogging

♦ Internet / Coding

♦ CourseraMy strengths: Input, Connectedness, Intellection, Learner, Relator

Datafication of HR is Inevitable

Logistics &

Purchasing

Financial &

Budgeting

ERP

& Supply

Chain

Finance & ERP

Customer

Analytics

(Data

Warehouse)

Customer

Segmentation

Market

Basket

Web Buying

Behavior

Consumer & CRM

Recruiting

Learning

Performance

Talent Mgt

Workforce

Planning

Predictive

Models

For

Talent/HR

Talent,

Leadership, HR

The Industrial

Economy

The Financial

Economy

The Customer

Economy and Web

The Talent

Economy

Early 1900s 1950s-60s 1970s-80s Today

Steel, Oil, RailroadsConglomerates

Financial Engineering

Customer Segmentation

Personalized Products

Globalization, Demographics

Skills and Leadership Shortages

Source: http://www.slideshare.net/hrtecheurope/josh-bersin-datafication-of-hr

5 Ways the Workforce Will Change in 5 Years

• Freelance employees will approach the 50% mark

• Flex-work becomes a new normal

• Career 'impatience' a driving factor

• The new workforce works small

• Gen X may have its day

Source: http://mashable.com/2014/08/25/workforce-in-5-years

“The goal is simple: put the right people with the right skills in the right work, provide them with the necessary training and development opportunities, and engage and empower them to perform at their highest possible level"

"... higher quality, productivity, customer satisfaction, and market share --and they're more profitable too."

- HBR, August 2013

Recruiting and

Workforce

Planning

Comp and

Benefits

Performance

Succession

Engagement

Learning

& Leadership

HRMS

Employee

Data

Engagement

& Assessment

+

Sales Revenue

Productivity

Customer

Retention

Product

Mix

Accidents

Errors

Fraud

Quality

Downtime

Losses

Groundbreaking New Insights &

Tools for Managers to Make Better Decisions=

Data management, analytics, IT, and business consulting expertise

+

The Goal of HR Analytics:

Bring People & Business Data Together

Source: http://www.slideshare.net/hrtecheurope/josh-bersin-datafication-of-hr

Business Success Stories

Moneyball

• True story on how Oakland Athletics changed the baseball and sport analytics since 2002

• A film in 2011, based on the book of same name

Lessons from “moneyball”

• What is the problem? (8:27-12:44)• Opinion-based Selection• Understanding real business issue• Tactical vs Strategic

• Player Analytics (27:00-28:55)• Clear Business Objectives• Player performance index• Compare with price to find “undervalued” players

• Implementing Strategy (31:28-35:18)• Data-based decision• Decision justification• Focus on outcome

Metrics vs Analytics

Metrics on HR’s processes & transactions

In traditional HR view

The people side of business

outcome

vs

Metrics

• A system or standard of measurement

Analytics

• The systematic computational analysis of data or statistics

Moving from metrics to analytics

Moving from metrics to analytics

Metrics Analytics

• What is my headcount? • What are the key characteristicsof top performers?

• How many people did we hire? • What are our best recruiting sources for top performers?

• How many people resigned? • Who of our top performers is at risk of leaving?

Source: Bersin by Deloitte Talent Analytics Maturity Model®

Level 4: Predictive AnalyticsDevelopment of predictive models, scenario planning

Risk analysis and mitigation, integration with strategic planning

4%

Level 3: Advanced AnalyticsSegmentation, statistical analysis, development of “people models”;

Analysis of dimensions to understand cause and delivery of actionable solutions

10%

Level 2: Proactive – Advanced ReportingOperational reporting for benchmarking and decision making

Multi-dimensional analysis and dashboards

30%

Level 1: Reactive – Operational ReportingAd-Hoc Operational Reporting

Reactive to business demands, data in isolation and difficult to analyze

56%

Talent Analytics Maturity Model®

Advancing Takes Effort

Level 2

Advanced Reporting

Level 3

Advanced Analytics

Level 4

Predictive Analytics

Level 1

Operational Reporting

Level of Value

Level of Effort

Choke Point for Most

Organizations

Source: http://www.slideshare.net/hrtecheurope/josh-bersin-datafication-of-hr

Talent Analytics - Examples

• Retention Analytics

• Recruiting Effectiveness

• Total Cost of Workforce

• Employee Movement

Talent Retention

• Retention ≠ Turnover

• Turnover alone is not sufficient

• Lots of reasons people turnover – some good / some bad

• Once someone has left it is hard to get them back

• One number tells you nothing about how to change the outcome

Common Retention Metrics

Common Metrics• Turnover

Shortcomings• Do not provide

insights on why• Does not allow for

meaningful preventive action

• Not all turnover is bad!

Talent Retention Analytics

Turnover by performance by tenure

Turnover by performance by tenure

Turnover by performance by tenure

Turnover by performance by tenure

Analytics: Segmentation of Turnoverby performance by tenure

Focus on relevant & value driven issues

Gauge recruitment & onboarding effectiveness

Cost and disruption of new hire turnover

Shedding top performers, critical & vulnerable roles

Poor performer tenure and turnover

Delivering on Employment Brand

Recruiting Effectiveness“Recruitment is the HR function that has the most positive impact on revenue creation and profitability…”

Boston Consulting Group

• Effective Hiring ≠ Time to hire

• Speed is highly dependent on the market conditions effecting type of talent

• Prioritizing speed over quality can have negative results

• Effectiveness is not a single concept• For example, hourly paid staff vs.

executive level hires

Common Recruiting Metrics

Common Metrics

• Time to fill

• Open Requisitions

• Cost to Hire

• Quota Attainment

Shortcomings

• Do not answer strategic questions about quality and value• Do not provide insight into hiring connections to productivity

(revenue creation and profitability

Recruiting Analytics

Analytics applies powerful visualization techniques to put critical business answers in front of decision makers – in an intuitive way.

Total Cost of Workforce

“Total workforce costs average nearly 70% of a company’s operating expenses.”

- Society for Human Resource Management

Common Compensation Metrics

Common Metrics

• Salaries

• Total Direct Compensation

• Market Compensation

• Comparison Ratio

Shortcomings

• Do not support strategic decisions about compensation

• Do not identify areas for optimization

Create a Cost Hierarchy:

Total Cost of Workforce

(TCoW)

o Total Salaries

o Total Benefits

Direct Compensation

Contingent Labor

Costs

Build from the bottom

Direct

Compensation

Indirect

Compensation

Deferred

Compensation

Contingent

Labor Costs

Total Cost of

Workforce

(TCoW)

Total Cost of Workforce Analytics

TotalCostofWorkforce 1. Understandthetruecostoftheworkforcewhichallowsanychangestotheworkforceinsupportofthebusiness

strategytobemeasured.Providesabasisforcomparingworkforcecoststothecompetition.

WorkforceCost

Segmentation

2. Identifythedirect,indirect,contingent,benefits,leave,

equity,etc.costsassociatedwiththeworkforcesothatthevariouscostimpactscanbecomparedtodeterminewheretofocustoreducecosts,investtoattracttalent,

etc.

Employmentmovementimpactsoncompensation

3. Understandhowentriestoandexitsfromanorganizationimpactthetotalcompensationexpenses

Build costs into your plans

Employee Movement Analytics

Structure Network Organization

• Structure is the organizational hierarchy, distribution of work, and business units

• Network is the relationships and connections between people within the organization

• No matter how correct your structure, if the network is missing your organization will not perform at its best

Common Movement Metrics

Common Metrics

• Headcount / FTE

• Turnover

• Internal Moves

• External Hires

Shortcomings

• Do not provide insight into impact of employee movement

• Do not correlate movement to other factors

Employee Movement AnalyticsAnalytic

Value

Movementinandoutoforganizationalunits

1. Ensurethebusinessunitsthatmakethemostdifferencetoyourbusinessareincreasingintalentquality,andnot

experiencing“braindrain”

Buildversusbuy 2. Trackpromotions,lateralmoves,andtherelativeperformanceofindividualstoachievebetterresultsataloweroverallworkforcecost–internalcandidatesoften

performbettermorequicklyandstaylongerthan“stars”whoareparachutedinfromoutside

Leadershipandsuccession

modeling

3. Trackingemployeemovement,promotions,andkey

skills/experienceprovidesinsightintotheorganizationalpathwaysthathavedevelopedyourtoptalent,andallowyoutoidentifyotherlikelysuccessioncandidates–

researchbyJacFitz-Enzfoundadirectcorrelationbetweenbettersuccessionmanagementandrevenue

Visual

DashboardsAdvanced

Analytics

Predictive

Models

Data

Integration

Data

Dictionary

Data

Quality

Time and

Seasonality

Big Data

Tools

Data

Governance

Ownership

Reporting

Tools

Disparate

Systems

Visual

Skills

Stats and

Data Skills

The Ugly Side: Data Management

The Ugly Part of The Story

HR Data Challenges

• Human-reported in nature

• Qualitative vs Quantitative

• Subjective & vulnerable to biases

• Difficult to distinct between luck vs individual performance• C.A.R. (Context Action Result) concept might helps but up to some extent

What’s next?

Adding new data types to better analytics

• Volometrix – Enterprise Analytics

• Smart Employee Badge• Youtube: Smart employee ID badges track workers every move

www.humanyze.com

• Corporate Tryouts • HBR Article: How Companies Are Using Simulations, Competitions, and

Analytics to Hire

• Idea - Kaggle for CEOs

Thank You