hr analytics - paads2016
TRANSCRIPT
• 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
♥ 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