1. Leveraging Predictive Power with the Workforce Analytics Module
Lillian Thomas, Analytics Manager National Institutes of Health
September 19, 2016

2. Agenda NIH Overview Predictive Analytics in HR 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 biomedical 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

4. About Our Analytics Group
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)
Analytics Team
Analytics Team:
Provides 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

5. What is Predictive Analytics?
Strategic Decision Making
Key influencers
Expected patterns
Situational impacts
Ideal formula(s)
Historical trends
Predictive analytics utilizes various statistical techniques to predict probabilities and trends based on current and historical facts.

6. 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

7. What is SMARTHR?
Self-Monitoring Analytics Reporting Tool for Human Resources
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

8. SMARTHR Configuration
SQL Server
Database Engine
Analysis Services
Integration Services
Machine Learning *
Business User
Data-Warehouse
Actions & Pay
Demographics Time and Attendance
Training
Detailed Reports
Oracle
Business Objects
SharePoint / ASP .NET
SQL Reporting Services
SMARTHR
Other OLTPs
Power User*
Flat-Files / XML
eOPF
Misc. Programs
Workflow / USA Staffing *
Diagnostic Capabilities
Insight
Foresight
Hindsight
Other Sources
Flat-Files SharePoint
Managers/Leadership
Surveys Other Supplemental
High Level Dashboards
* CY16/17 Implementation

9. 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

10. Workforce Analytics (WFA) Module Background
Filterable by Demographics
Historical Trends
Predictive Statistical Models
Integration of Opinion Data
Data in Context (Comparisons)
PURPOSE: Help NIH staff identify workforce trends and projections, to satisfy data requests and facilitate strategic planning.

11. WFA Business Need & Requirements
Workforce Analytics Module
Survey results/ Needs analyses
Customer input
- SMARTHR project requests
- Stakeholder group requirements
Historical HR data requests requirements
Industry trends
Agency initiatives

12. WFA Module Benefits Proactive Approach (Predictive)
Streamlined and Standardized yet Customizable
Integrated – Data Storytelling
Strategic Approach

13. WFA Structure Overview
Demographics Filters
Workforce Demographics
Onboard Count & Trends
Workforce Proportions
Supervisory Status
Turnover Trends
Separation & Accession Trends
Employee Satisfaction & Engagement (Surveys)
Retirement Models
Actual Retirements
Retirement Eligibility
Adjusted Eligibility Model

14. Predictive Power with WFA
Are gaps in certain positions, levels, organizations expected?
Where will deficits occur, based on the optimal staffing mix for the future?
Workforce Demographics – how will the staffing mix change in the future?
What recruitment and succession management needs look like?
What factors contribute to turnover patterns and how might those change in the future?
Turnover Trends – what will staff churn look like in the next three years?
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?
Retirement Models – when will critical staff leave the organization?

15. WFA Demo
WFA DEMO

16. Future of Workforce Analytics Module
Heat Maps
Action Planning
Targeted Groups
Prescriptive Analytics
Best Practice Sharing
Community Templates
Interactive Planning
Cross Collaboration/ Community of Practice
Data Fields (Compensation, Training, Performance)
Social Media
Additional Opinion Data
Expanded Data Connections
Conditional, Scenario-based Modeling
Organization-specific Models for More Predictive Power
Analysis on Opinion Data (Factor Analysis, Prediction)
Dynamic Modeling
Combine with Organization-specific Data
Enhanced Graphics and Visualizations
On-demand Models and Dashboards
Power User

17. Future of WFA – Heat Map Example
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)
Identify components of the mission-critical workforce that are at the most risk for turnover based upon survey feedback, historical trends, workforce demographics, and projections.

18. Q&A Lillian Thomas Analytics Manager
HR Systems Analytics & Information Division (SAID)
Office of Human Resources (OHR)
Office of the Director (OD)
National Institutes of Health (NIH)
Phone: