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BigData in HR How to build a world-class Talent Analytics function
Josh Bersin Principal, Deloitte Consulting LLP May, 2013
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Research & BigData Working Group
8 years of research into the measurement, operations of L&D, leadership, recruiting and HR
20 leading practitioner organizations advising us on strategy
Our goal: education and best-practices on how to build an analytics function
Develop assessment services and tools to help you understand how to advance your program
Continue to study state of the market and the best-practice solutions
http://www.bersin.com/hrbigdata2012
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Agenda
Why BigData in HR is Needed Defining BigData in HR What we have learned The Four Stages Case Studies Where we are
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Todays Global Talent Challenges
We have entered a global economy where talent and skills shortages challenge world economic and business growth around the world.
- Klaus Schwab, Chairman, World Economic Forum
Despite the high unemployment rates in many countries, more than 65% of global leaders cite talent and leadership shortages as their #1 business challenge.
- Bersin & Associates TalentTrends, Fall 2012
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2013: A Nexus of Change
nexus (Noun)
A connection or series of connections linking two or more things.
A connected group or series: "a nexus of ideas".
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A Nexus of Talent Challenges
Agile Management & Leadership Models
A New Generation of HR Practices and New Type of HR Organization
New Technology
Social Tools, Analytics
Need for Improved HR skills and capabilities.
Business Speed and Scale
Disruptive Competition
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Shift toward Emerging Markets
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Borderless Workplace
Team Model of Work
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Specialization Contingent Work
New Job & Career Models
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21st Century Models of
Leadership
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Competition for Talent
Social Sourcing & Recruiting
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How the Workforce has Changed
From The Shift Index by Deloitte
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Young, Diverse Workforce .
By 2013, 47% of employees will be those born after 1977. -- US Census Bureau
In 2012, 32% of employees are planning on leaving their employers, vs. 19% two years ago
Only 55% of employees believe their employer is a sound long term place to work vs. 65% over last three years.
People under the age of 35 are twice as likely to be looking
for new work as older workers.
- Mercer October 2011, Towers Watson July 2012
Has Created Challenges in Engagement
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Increasing Work Specialization Expertise drives competitive
advantage
Specialization improves quality and reduces cost
Deep skills developed through deliberate practice and reinforcement
Deep skills come from a range of developmental experiences
Intelligent leadership paths, career paths, training, work assignments, understanding high-performing competencies are all drives of success.
Back Office, Operational, Contingent Employees
Functional Specialists / Front-Line Employees
Top Management
Senior Management
Middle Management
Senior Specialists First Line
Management
The Experts
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Agenda
Why BigData in HR is Needed Defining BigData in HR What we have learned The Four Stages Case Studies Where we are
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Do YOU know.
What characteristics drive high performing sales people? What work assignments will lead to strong leadership? What attributes of a job candidate will lead to perfect fit? Why retention is low in certain locations and jobs? What is the real result of poor on the job safety? Why some of your top people leave for competitors What compensation and rewards will drive most value? .
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BigData in HR Defined Big data is a collection of data so large and complex that
it is difficult to process using traditional data processing applications.
- Wikipedia
The typical HR system has more than 400 data elements about your own employees, and this data is being updated nearly every day.
We all have BigData opportunities within our own HR, training, recruiting, and talent organizations.
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Analytics is Definitely Coming to HR The Evolution of Business Analytics in other Functions
The Industrial Economy
The Financial Economy
The Customer Economy and Web
The Talent Economy
Early 1900s 1950s-60s 1970s-80s Today
The Waves of Business Analytics
Steel, Oil, Railroads Conglomerates Financial Engineering Customer Segmentation Personalized Products
Globalization, Demographics Skills and Leadership Shortages
Logistics and Supply Chain
analytics
1980s Financial and
Budget Analytics
Integrated Supply Chain
Integrated ERP and Financial
Analytics
Finance & Logistics
Customer Analytics CRM
(Data Warehouse)
Customer Segmentation
Shopping Basket
Web Behavior Analytics
Predictive Customer
Behavior - CRM
Customer & Marketing
Recruiting, Learning,
Performance Measurement
Integrated Talent Management Workforce Planning
Business-driven Talent analytics
Predictive Talent Models HR Analytics
Talent & Leadership
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This Science is Coming to HR
Definition of Science: Systematic knowledge of the world gained through observation and experimentation.
What is Not Science
Making talent decisions on the basis of gut feel, beliefs, or philosophies.
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How do Companies Hire People? 2/3 of hiring done without any significant assessment
Background checking: 79% Managerial interviews: 64% Interview training: 47% Behavioral assessments: 34% Reference calls: 32% Skills-based assessments: 25%
% of Organizations Which Regularly Use Following Assessment Practices
Bersin & Associates High-Impact Talent Acquisition Study, Fall 2011, 158 organizations responded
2/3 use no real assessment process
at all leaving the process to
hiring managers or recruiters
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Big Insurance
A $33 billion insurance company has developed a behavioral assessment based on a set of beliefs held by the top executives
Top sales people need college degrees from top rated schools, they should have good grades, and they should have experience selling high value products.
But the data proves otherwise.
Insurance Company
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Results of Data Analysis
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Insurance Company
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Data Showed Six Things Matter:
Very Highly Correlated with Success 1. No typos, errors, grammatical mistakes on resume. 2. Did not quit school before obtaining some degree 3. Had experience selling real-estate or autos 4. Demonstrated success in prior jobs 5. Ability to succeed with vague instruction 6. Experience planning time and managing lots of tasks
The Belief System
Was Wrong
Within six months of implementing a
new screening process
revenues went up by $4 million
What Did NOT Matter
Where they went to school What grades they had The quality of their references
Insurance Company
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Moving to Predictive Analytics
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Agenda
Why BigData in HR is Needed Defining BigData in HR What we have learned The Four Stages Case Studies Where we are
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The Big Aha! In HR, talent, leadership, and capabilities you already have
most of the information you need to deliver breakthrough new solutions for your organization.
What most organizations do not have is the organization structure, skills, leadership, and tribal knowledge to use this information yet. Many of the skills are likely available in your organization.
This marketplace is rapidly evolving and over the next two years
companies who do not implement a BigData in HR strategy will fall behind those that do.
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We Dont Measure the Right Things
Source: Bersin & Associates 2012 High-Impact Learning Organization (HILO)
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Focus on The Problem, not the Data Business problem first, then focus on arranging and using the data
Why is turnover high in some areas?
What drives sales productivity?
Why is their fraud in some branches?
What sales or service processes drive account renewal?
What is the impact of training on long term productivity?
How do we assess the right candidates for sales?
What will our talent gaps be next year based on retirement?
Business Problem Data
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The Yahoo Question
Are the people working from home getting enough work done?
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Treat Measurement as a Process Why you must build an analytics function, not a set of tools
Measurement as Process, not a Project
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The Four Keys to Success 1. Reliable
- Data must be true and validated over time - Seasonal changes, organization changes, must be handled
2. Actionable - Reports must be detailed enough to let managers take action - Drill, filter, group data so it is relevant and meaningful - Goal is a business-driven dashboard (red/yellow/green)
3. Scalable - The process of collecting and analyzing data must scale - Your outputs must be useful for people at all levels
4. Understandable - People must be able to visualize and understand what you find - Line managers, executives, and employees must use the data
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The Rich Sea of Data Opportunities Workforce Plan
Scenarios
Time and Cost To Hire
Internal Mobility
Employer Brand, Alumni
Managerial Grievances
Span of control
Skills Certifications
Open Positions
Development Plans
Tenure Education, etc.
Retirement Projections
Age, geography, Skill level
Talent Demand Plan
Onboarding Effectiveness Turnover
Ratings Rankings
9-box Grids
Succession Depth
Seniority Skills Depth
Promotional Readiness
Employee Opinion
Employee Engagement
Employee Value Prop
Innovation Programs
Readiness
Demographics
Supply, Demand
Recruiting Onboarding
Performance Succession
Engagement
Spending Satisfaction With HR svc. HR/L&D
Staff Allocation HR/L&D
Spending Systems Usage/$
Succession Depth
360 and Other Assessments
Proficiency vs. Leadership Comp.
Successor Readiness Leadership
Budget by Group
Comp by level/perf
Compa Ratios
Perf-Pay differentials Compensation
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Understanding HR measures
Hundreds of HR measures Many easy to find Many not easy to find
Need for data dictionary Basic principles for success
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HR Programs & Processes (Status and maturity of HR Processes )
Learning Program Effectiveness I Total Rewards Effectiveness I Performance Management Effectiveness I On-Boarding Time to Productivity I Recruiting Effectiveness and Effieicney I Candidate Pipeline I Total Rewards
Workforce Demographics (Facts and statistics about employees, alumni, and contractors)
Payroll and Benefits | Demographics I Background I Experience I Tenure I Organization Structure I Spans of Control I
Capabilities, Talent, & Leadership (Capabilities, leadership, progression, career, talent.)
Leadership Pipeline | HiPOs I Stack Rankings I Pivotal Role Pools I Mobility | Compa Ratios I Rewards I Skill gaps I Certifications | Readiness I Turn-over I 360s I Technical Skill Pools I Career Progression | Development Plans | Succession Depth and Pools
Workforce Performance (How people impact the business)
Financial results by person and unit I Net Promoter scores I Performance and Goal attainment I Innovation/Patents | Product measures
Engagement & Culture (Employee engagement, wellness, and satisfaction including external view)
Engagement I Management Grievances I Turn-Over I Referral Rates I Exit Interviews I Development Plans | Diversity and Inclusion
Bersin HR Measurement Framework
HR, Recruiting, and L&D Effectiveness
Organizational Readiness
Talent & Leadership Supply Workforce Planning
Manager and Employee Dashboards
Scenario & Future Planning
HRMSs Payroll and Employee Demographic and System of Record Data
Applicant Tracking | Recruiting System
Applicant, source, recruiting data
Performance & Talent System
Performance, development planning, succession, talent pool data
Learning Management System
Learning, certification, skills delivery, content, learning organization data
Compensation System(s)
Salary, benefits, budget, bonus and comp related data, payroll feeds
Workforce Planning System
Scenarios, talent supply, demand org charting
Third party data:
assessments, employee
engagement, external brand, social networks
External Data and B
enchmarks
(External B
enchmarking of all H
R M
easures) Internal H
R M
easures I HR
Program
Effectiveness I
Workforce M
easures I TM M
easures I People P
erformance
Mea
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ata
Cle
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Sta
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ata
Ana
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Ana
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Talent Acquisition, Brand, Sourcing (How well you are reaching candidate audiences)
Employment Brand | Talent Pipeline | Time and Cost to Fill | Quality of Hire
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How HR Data is Typically Organized
Recruiting and Workforce Planning
Comp and Benefits
Performance Succession Engagement
Learning & Leadership
HRMS Employee
Data
HR Operations
Your goal is to integrate this information, over time, into a credible, actionable, scalable, understandable
Talent Analytics function one which delivers relevant Information, models, and tools to line leaders and executives
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HR Manages a Plethora of HCM Products 87% have more than two systems 20% have more than 6 systems 7% have more than10 solutions 18% of large companies report use of more than ten HCM different systems
57% plan to procure new software within the next 18 months 61% will both replace and procure new solutions 23% will solely replace existing solutions;16% will solely add new products.
33% will replace standalone TM applications 22% with an integrated suite. 10% will replace their existing suites.
Finding the Data is Work
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The Problem with the Systems Market
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Why You Need a Data Dictionary
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Standards Remain Elusive You cannot wait.. you have to develop your own
Other Standards Out There: Bersin by Deloitte Factbooks Turnover Metrics (SHRM) Diversity & Inclusion (SHRM) SAP Book of Data TDR Reporting (Yay!) Engagement Standards (coming) SASB Sustainability Many more
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Tools Alone are Not the Solution
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Agenda
The BigData Priority Why Talent Analytics Guidelines for Success The Four Stages Final Thoughts
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Talent Analytics Maturity Model
Level 1: Reactive Operational Reporting Operational reporting for measurement of efficiency and compliance
Data exploration and integration, Development of data dictionary
Level 2: Proactive Advanced Reporting Operational reporting for benchmarking and decision making
Multi-dimensional analysis and dashboards
Level 3: Strategic Analytics Segmentation, statistical analysis, development of people models;
Analysis of dimensions to understand cause and delivery of actionable solutions
Level 4: Predictive Analytics Development of predictive models, scenario planning
Risk analysis and mitigation, integration with strategic planning 60%
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Level 1: Reactive Operational Reporting Goals:
- Implement a scalable, accurate, easy to use reporting environment - Understand all the data and systems you have to work with
Tasks: - Understand and collect data you have - Build a Data Dictionary - Work with IT to implement standard reporting tools
Key Skills - Patience and database interest - Great relationship with IT - Ability to write, document, and manage projects
Expected Outcome - Standard tools and reports - Ease in responding to any report request - Tools to help managers find their own data
1
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Level 2: Proactive - Advanced Reporting 2
Goals: Develop skills and tools to implement proactive reporting and tools for line managers Look at trends, benchmarks, and results against plan Develop actionable business dashboards
Tasks: Understand all the dimensions of your data (how it will be drilled and filtered) Audience analysis who are your audiences and what decisions do they make? Performance consulting start focusing on one or two major problems Purchase or select benchmarking data
Key Skills Understanding of multi-dimensional reporting Business acumen and relationship with finance organization Strong business alignment and partnership with business leader (or leader) Ability to influence what IT does
Expected Outcome Dashboards used by the business A business unit success
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Level 3: Strategic Analytics 3
Goals: Developing causal models or people models which identify cause and effect Segmenting people into groups which can be analyzed in detail Integrating data with recruiting, performance, compensation, leadership, etc.
Tasks: Building strong relationships with all areas of HR Selecting a key problem to start analytic study Implement analytics project, iterate, and demonstrate results
Key Skills Analytics and statistics skills Information visualization and compelling presentation skills Excellent performance consulting and ability to understand work environment Partnership with line executives and ability to focus on key problems Skills in development of tools across many areas of HR and Talent Management
Expected Outcome A success project which delivers some breakthrough findings Direct change or decision-making tools in the hands of the business
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Level 4: Predictive Analytics 4 Goals:
Putting place models which can predict future scenarios Integrate your work with workforce planning and business planning functions
Tasks: Expand your analytics skills and expertise Directly connect with business planning, finance, and recruiting teams Expand relationship with 3rd party data, engagement, and consulting firms
Key Skills Modeling and deeper statistics skills Finance and business planning Senior experience in organization design Strong relationship with or deep experience in workforce planning and acquisition
Expected Outcome A workforce planning model which describes how performance can be improved Repeatable models which can be extended into new domains Credibility with Finance An integrated, strategic analytics function
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Key to Success
Developing Credibility Strong Relationship with IT Sharing Experience across analytics teams Patience to validate data before it is shared Multi-year analysis to experience seasonal trends Need to present findings in an understandable way Skills in visual design and presentation Focus on business solutions, not HR solutions
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Agenda
Why BigData in HR is Needed Defining BigData in HR What we have learned The Four Stages Case Studies Where we are
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Examples of Breakthrough Solutions
Major Retailer developed integrated people model to correlate relationship between engagement, rewards, leadership capabilities, tenure, skills and revenue.
Major Payroll Provider statistically validated 30+ factors in recruiting which led to 20%+ improvement in sales performance and completely revamped recruiting process
Major Food Service Company identified key drivers of account renewal and upgrade and developed statistically valid measures which have been used to create company-wide dashboard which measure risk on a weekly basis
Major Retail Bank correlated dozens of workforce measures against engagement and branch financials to develop risk management dashboard for small and large branches
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Why is our China Leadership Pipeline Weak? Energy Company
College Degree
Job Level
College Major
Job Type
Home Geography
Work Geography
Hire Date
Org Unit
Position Held
Position Level
Hipo Level
Work Country
Trainings Completed
Date Since
Training
Promotion Type
Date Promoted
Perform. Tier
Tenure
1. Examine Historic Data & Outcomes
2. Build A Predictive Model
MBA vs. Engineering Degree Lack of US Experience Different criteria for success
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2011 - 2012 Advanced Statistics & Social Research Acumen;
Engineering Degree; Customer Research Background; Statistics & Data Mining
Critical Thinking; Story Telling; Data Visualization;
Ability to see data, and decipher insights
2009 - 2010 Business Acumen; HR, Finance, Economics Degree;
Quantitative Research Design & Analysis Passion for Data & Analytics; Strong Technical skills
Consulting & Presentation Skills; Analytical Curiosity; Problem Solving;
Collaborative; Teamwork; Networking Skills
2007 - 2008 Solid Understanding of HR; I/O Psychology Degree;
Employee Research Background; Qualitative Research Design & Analysis; HRIS; SPSS
Strong Communication & Interpersonal Skills; Detail Oriented ; Project Management
The Evolution of Data Skills and Competencies Large Retailer
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2008 Employee Engagement Model Employee Segmentation LVI Learning
2009 Diversity & Inclusion Leadership
2010 Learning & Professional Development Employee Lifecycle Research HR Scorecards Reactive Analytics
2011 Company Health Pentagram Employee Research Cohorts Human Capital
Executive Dashboard
Proactive & Exploratory Analytics
2012 Enterprise Measures of Success Talent Change Adoption Predictive Analytics
The Modeling Journey Retailer
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An Evolved Organization
VP Human Capital Analytics
Director Org Diagnostics &
Design
(2) Sr. Consultant
ODD
Program Manager
Director Workforce Analytics & Research
Manager Workforce Analytics
(2) Sr. WFA Analyst
Manager Employee Research
Analyst Employee Research
Manager Learning Analytics
Consultant Learning
Measurement
Analyst Learning Analytics
Business Operations Specialist
Manager HR Brand Content
Retailer
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Purpose of Department Organizational Research, Analysis, and Planning Department Help to achieve a competitive advantage through
providing strategic HR analysis focused on talent
Build a culture of analytics and planning within the Global Human Resources function
Provide HR Intelligence through the highest quality; most valid and reliable analytical products and services
Manufacturer
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2011 2010 2009
2008
2007
Oct. 2006
Explore Execute
Evolution of Human Capital Analytics Team
Start of department One person
Focus on Advanced HR Studies & Corporate HR Scorecard Audience equal CHRO Report to Director of HR
Functional Excellence Receive goals from CHRO Sourced two part-time I/O
Psychology interns
Two person department (Hired Ph.D. I/O Psychologist)
Added focus on Job Analysis, Competency Assessment, &
Organizational Culture Report to VP of Talent Acquisition & HR
Functional Excellence Audience equal CHRO & Staff
Goals from CHRO
Added focus on Global HR Scorecard, Workforce Forecasting, Performance
Management , and Training Effectiveness Report to VP of Talent Acquisition & HR
Functional Excellence Audience equal mostly HR; but also business
and Functional leaders Receive goals from CHRO & Staff; some
Functional/Business leaders
Strategize Operate
Downsized to one person Added focus on Talent Acquisition
Same reporting structure Audience equal HR, functions, &
business leaders Receive goals from CHRO, Business
Leaders, and Functional Officers Hired two people in India (operations research & BI)
Eight person department Aligned department by business and region
Added focus on predictions, scenario planning, succession planning, HR processes, on-site root-cause
analyses & OD Audience equal HR and non-HR leaders down to the
plant/facility level Report to VP of HR Functional Excellence
Receive goals from CHRO, Business Leaders, and Functional Officers
A great deal of hiring
Fourteen person department Added focus on organizational structure,
potential countries to do business, and labor cost forecasting
Report to VP of Talent Management & Organization Effectiveness
Goals provided by HR and non -HR leaders Audience is the same
Implement HR BI with Oracle (OBIEE), Reporting Service Center
Impress Implement
Manufacturer
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Collaboratively
Identify Solutions
Present Results and Potential
Solutions
Convert Data to Actionable
Information
Collect Data
Formulate Study Plan
Identify Solution
or Problem
Advanced HR/Business Studies
HR Planning through Data Analysis
HR Measurement On-Site Consulting and/or Client Engagements
Centralized HR Reporting, Analysis, and Benchmarking
Building a Culture of Analytics Through Training & Development
DESIGN IMPLEMENT
Key Deliverables Roadmap
20%
15%
20%
20%
25%
40%
5%
10%
5%
40%
2007 2012 Key Deliverables & Time Allocation
Manufacturer
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Building A Culture of Analytics
COMPETENCY
ACC
OU
NTA
BIL
ITY
Know what data is in the system and
how to access it.
Know what data is in the system and
how to access it.
Understand what data is captured in the system and what it represents
Understand how to run reports and create ad hoc
reports
Analyze and interpret data and metrics
Analyze data and evaluate trends
Drill down in order to ask the question
behind the question
Understand the why behind the
what Conduct root cause analysis
Analyze and interpret data and metrics
Translate, analyze and present data to various audiences Identify business
issues that are being impacted
Create actionable HR plans the
positively impact the business
Understand analytics and present data
to tell a story
Analyze and interpret data and metrics
Design solutions to support
specific business strategies
Be anticipatory & participate in whats next
decision making Proactively
initiate actions to improve
organization-wide
performance & avoid incoming
issues Understand leading vs.
lagging indicators
Re-evaluate using
quantitative analyses
Sustain best practices and
eliminate waste
Understand analytics and present data
to tell a story
Establish a plan and execute a
plan with the data
Accessing the data Executing with the data Interpreting the data Presenting the data
Know what data is in the system and
how to access it.
Know what data is in the system and
how to access it.
Manufacturer
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The Skills Issue
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The WhatWorks Approach Talent Analytics Fits into our High-Impact HR Framework
http://www.bersin.com/hrbigdata2012
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Conclusion
BigData in HR is has become a business imperative
Integration of analytics teams and building capability are key, not tools and technology
Analytics is a journey which will change the way you think
Talent analytics will extend to the other business analytics groups in your organization
Expertise and patience is key, but focus on key business problems first
http://www.bersin.com/hrbigdata2012
BigData in HRHow to build a world-class Talent Analytics functionResearch & BigData Working GroupAgendaTodays Global Talent Challenges2013: A Nexus of ChangeA Nexus of Talent ChallengesHow the Workforce has ChangedYoung, Diverse Workforce .Increasing Work SpecializationAgendaDo YOU know.BigData in HR DefinedAnalytics is Definitely Coming to HRThe Evolution of Business Analytics in other FunctionsThis Science is Coming to HRHow do Companies Hire People?2/3 of hiring done without any significant assessmentBig InsuranceResults of Data AnalysisData Showed Six Things Matter:Moving to Predictive AnalyticsAgendaThe Big Aha!We Dont Measure the Right ThingsSlide Number 24Focus on The Problem, not the DataBusiness problem first, then focus on arranging and using the dataThe Yahoo QuestionSlide Number 27Treat Measurement as a ProcessWhy you must build an analytics function, not a set of toolsThe Four Keys to SuccessThe Rich Sea of Data OpportunitiesUnderstanding HR measuresBersin HR Measurement FrameworkHow HR Data is Typically OrganizedFinding the Data is WorkThe Problem with the Systems MarketWhy You Need a Data DictionaryStandards Remain ElusiveYou cannot wait.. you have to develop your ownTools Alone are Not the SolutionAgendaTalent Analytics Maturity ModelLevel 1: Reactive Operational ReportingLevel 2: Proactive - Advanced ReportingLevel 3: Strategic AnalyticsLevel 4: Predictive AnalyticsKey to SuccessAgendaExamples of Breakthrough SolutionsWhy is our China Leadership Pipeline Weak?Slide Number 50Slide Number 51An Evolved OrganizationPurpose of DepartmentOrganizational Research, Analysis, and Planning Department Slide Number 54Slide Number 55Slide Number 56The Skills IssueThe WhatWorks ApproachTalent Analytics Fits into our High-Impact HR FrameworkConclusion