leveraging predictive power with the workforce analytics module lillian thomas, analytics manager...
TRANSCRIPT
Leveraging Predictive Power with the Workforce Analytics Module
Lillian Thomas, Analytics ManagerLuis Unda, Technical Lead
National Institutes of Health
September 18th, 2015
Agenda
NIH Overview
Predictive Analytics – An Introduction
What is SMARTHR?
Showcase of the Workforce Analytics Module
3
About NIH• The National Institutes of Health (NIH), a part of the U.S.
Department of Health and Human Services , is the nation’s medical research agency—making important discoveries that improve health and save lives.
• NIH Mission: to seek fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability.
• Organizational Structure: 27 different components called Institutes and Centers. Each has its own specific research agenda. The Office of the Director is the central office at NIH for its 27 Institutes and Centers, and includes a centralized Office of Human Resources (OHR).
• Size: ~20,000 full-time, federal employees + ~22,000 contractors/ fellow staff
• 300,000 research personnel at over 2,500 universities and research institutions
About Our Analytics Group
Workforce Analytics Branch: Provides the workforce data, analysis and related products and services that enable the organization to make better business decisions around its human capital resources.
Business Intelligence and Advanced Analytics
Business Process Re-engineering
Data Management and Governance
Survey Design and Analysis
Project Management and Consultation
National Institutes of Health (NIH)
Office of the Director (OD)
Office of Management (OM)
Office of Human Resources (OHR)
HR Systems, Analytics & Information Division
(HR SAID)
Workforce Analytics
Branch (WAB)
What is Predictive Analytics? Predictive
analytics utilizes various statistical techniques to predict probabilities and trends based on current and historical facts.
Why Use Predictive Analytics for HR? Strategic Workforce Planning
Forecast staffing mix Identify future gaps, needs, and opportunities
Succession Planning Identify retirements and predict turnover Determine hiring, training, mission critical occupations, and
pipeline needs
Maximize Retention, Engagement and Productivity Top influencers on decisions to stay/leave What factors lead to increased engagement
What is SMARTHR?
In-house developed tool; released in June 2012 by NIH-OHR
Automates redundant and specialized reporting tasks
Bridges reporting gaps across multiple HR and non-HR systems
Allows for custom-designed logic to incorporate data models and data visualizations
Promotes on-demand customer self-service
Granular security, based on business role and organizational scope
Actionable information for Business, Power, and Leadership users
Self-Monitoring Analytics Reporting Tool for Human Resources
SMARTHR Configuration
SMARTHR Power User
Managers/Leadership
Business User
SharePoint / ASP .NETSQL Reporting Services
Office 365* - Excel Power Query, View, Pivot - Excel SQL Server Data-Mining Add-In
Office 365* - Power BI
Data-WarehouseOracleBusiness Objects
Other OLTPsFlat-Files / XML
SQL ServerDatabase Engine
Analysis Services Integration Services
Azure Machine Learning *
Actions & PayDemographicsTime and AttendanceTraining
SurveysOther Supplemental
Diagnostic Capabilities
* CY16 Implementation
Detailed Reports
High Level Dashboards
eOPFMisc. ProgramsWorkflow / USA Staffing *
Other Sources Flat-FilesSharePoint
Insight
Foresight
Hindsight
Benefits of SMARTHR Supports Strategic Workforce Planning
Data driven decisions
Automation and streamline reporting
Allows efforts to be concentrated on strategic analysis
Facilitates descriptive, diagnostics, predictive, and prescriptive analytical capabilities
Minimizing human error and data manipulation
No user costs for NIH users
Securing information (SSO)
Supports mobile workforce
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Workforce Analytics (WFA) Module Background
PURPOSE: Help NIH staff identify workforce trends and projections, to satisfy data requests and facilitate strategic planning.
Filterable by Demographic
s
Features:
WFA Business Need & Requirements
Workforce Analytics Module
Survey results/ Needs
analyses
Customer input
- SMARTHR project
requests- Stakeholder
group requirements
Historical HR data
requests requirement
s
Industry trends
Agency initiatives
WFA Module Benefits Proactive approach through predictive analytics
Streamlines and standardizes recurring report needs
Integrate quantitative and qualitative data Additional insight into current data trends and
workforce issues.
Fill gaps in strategic human capital planning Summary level NIH data Self-service Dynamic by filter criteria
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Facilitates Strategic Planning!
WFA Structure Overview
13
Workforce Demographics•Onboard Count & Trends•Workforce Proportions•Supervisory Status
Turnover Trends
•Separation & Accession Rates•Employee Satisfaction (Exit Survey & EVS)•NIH OHR Employee Survey Results (OHR only)
Retirement Models
•Actual Retirements•Retirement Eligibility•Adjusted Eligibility Model
Demographics Filters
Predictive Power with WFA
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Workforce Demographics – how will the staffing mix change in the future?
• Are gaps in certain positions, levels, organizations expected?• Where will deficits occur, based on the optimal staffing mix for the future?
Turnover Trends – what will staff churn look like in the next three years?
• What recruitment and succession management needs look like?• What factors contribute to turnover patterns and how might those change in the future?
Retirement Models – when will critical staff leave the organization?
• How can leadership plan for knowledge transfer and backfill of critical positions?• In what ways may the organization change, based on the generational shift of the workforce?
Future of Workforce Analytics Module
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Prescriptive Analytics• Heat Maps• Action Planning• Targeted Groups
Cross Collaboration/ Community of Practice
• Best Practice Sharing• Community Templates• Interactive Planning
Expanded Data Connections
• Data Fields (Compensation, Training, Performance)• Social Media• Additional Opinion Data
Dynamic Modeling
• Conditional, Scenario-based Modeling• Organization-specific Models for More Predictive
Power• Analysis on Opinion Data (Factor Analysis, Prediction)
Power User • Combine with Organization-specific Data• Enhanced Graphics and Visualizations• On-demand Models and Dashboards
SMAR
THR
Wor
kfor
ce A
naly
tics
Mod
ule
Future of WFA – Heat Map Example
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Heat Map
Prescriptive
Analytics(Target areas to obtain & maintain optimal
workforce)
Predictive Models(Future Scenarios, Gap Assessment)
Workforce Data (Turnover Trends,
Retirement Eligibility)
Survey Information
(Exit, EVS, Pulse) Heat maps will highlight
components of the mission-critical workforce that are at
the most risk for turnover based upon survey feedback, historical trends, workforce
demographics, and projections.
Contacts
Lillian ThomasAnalytics ManagerHR Systems Analytics & Information Division (SAID)Office of Human Resources (OHR)Office of the Director (OD)National Institutes of Health (NIH)Phone: 301.594.0924Email: [email protected]
Luis D. UndaInformation Technology Specialist, Technical LeadHR Systems, Analytics & Information Division Office of Human ResourcesNational Institutes of HealthPhone: [email protected]
Questions
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Thank you!