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Become a Data-Driven HR Function
Build the foundation for HR Analytics to improve the organization’s decisions.
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Contributors
- Alec Levenson, Senior Research Scientist, Center for Effective Organizations, Marshall School of Business at the University of Southern California
- Andy Charlwood, Professor of HRM, University of Leeds
- Edward Houghton, Senior Research Advisor, Human Capital and Governance, CIPD
- Glen McLellan, Director, Total Compensation & Workforce Analytics, Centric Health
- Heidi Epley, HR Strategy and Analytics Manager, Caterpillar Inc.
- Irwin N. Jankovic, PhD, Strategic Program Manager HR, Metropolitan Water District of Southern California
- John Boudreau, Research Director, Centre for Effective Organizations and Professor, Marshall School of Business at the University of Southern California
- John Sullivan, Professor of Management, San Francisco State University
- Junia Freitas, Senior Manager, Global Talent Analytics, Scotiabank
- Mark Benton, WFM Budgeting and Planning Manager at The Co-operative Food
- Nikki Langille, HR Country Manager, AT&T
- Omer Aziz, CHRO, Flight Network
- Robert Carlyle, Senior Director, Strategic Workforce Management, RBC
- Sam Hill, Founder and Managing Consultant, Workforce Dimensions
- Valarie Dillon, Executive Director, Human Resources & Volunteer Services, Scouts Canada
Your Challenge
- Over a third of HR departments struggle to move beyond basic measurement and metrics (McLean & Company, 2018 HR Trends Report).
- HR has more data than ever before, but often does not know what to measure or what to do with the data.
- Unreliable data and lack of analytic capability are significant barriers to moving forward.
Our Advice
Critical Insight
- You don’t need advanced analytics to add value. Reliable data combined with metrics that matter enables HR to add value right away while also preparing HR for advanced analytics in the future.
- Select metrics that matter to clients to include in dashboards. This focuses HR resources on what will have the highest impact and address client needs.
- Perfect data and dashboards miss the point. Clean data just enough to use for decision making, and iterate dashboards based on client feedback.
Impact and Result
- Create a data plan that identifies metrics that track progress towards specific client needs to ensure that data adds value to the organization – right away.
- Build the foundation for data-driven HR by addressing key gaps in data governance, analytic capability, and data adoption.
- Build dashboards that drive action by leveraging data analysis, insight generation, storytelling, and data visualization best practices.
1. Assess the foundation
Assess the current state and gaps in HR analytics.
2. Select metrics that matter
Prioritize clients and prepare to build dashboards.
4. Plan for the future
Develop procedures to standardize HR data and insights for adoption.
Guided Implementations
This guided implementation is a ten call advisory process.
Guided Implementation #1 - Assess the foundation
Call #1 - Discuss the results of the HR Metrics & Analytics Foundation Assessment and identify gaps.
Call #2 - Identify and prioritize clients for metrics and analytics.
Guided Implementation #2 - Select metrics that matter
Call #1 - Identify and prioritize client needs.
Call #2 - Review selected metrics and discuss cadence of dashboard delivery.
Guided Implementation #3 - Create a dashboard
Call #1 - Review prototype dashboard to ensure it incorporates best practices in data visualization and storytelling.
Call #2 - Discuss stakeholder feedback.
Guided Implementation #4 - Plan for the future
Call #1 - Review the future state plan to produce initial dashboard(s) and build the foundation for data-driven HR.
Call #2 - Discuss appropriate data governance mechanisms for your organization.
Call #3 - Prepare a business case for additional analytics resources.
Call #4 - Determine solutions to data adoption barriers.
Book Your Workshop
Onsite workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost onsite delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Identify Clients and Prioritize Foundational Gaps
The Purpose
- Develop an overarching understanding of the importance and relevance of HR analytics.
- Comprehend the gaps within data governance.
- Evaluate the challenges that often face HR when it comes to data adoption.
Key Benefits Achieved
- Data governance gaps prioritized.
- Barriers to data adoption appraised.
Activities
Outputs
Identify and prioritize clients.
- Prioritized list of clients
Draw desired future state and current state of HR metrics and analytics.
- Future state established
Review data governance results.
Review data adoption results.
Revisit client list.
- Assessment results reviewed and key gaps identified
Module 2: Create a Dashboard Prototype
The Purpose
- Identify client needs.
- Select targeted metrics for each goal.
- Design a feasible dashboard scheme.
Key Benefits Achieved
- Client needs outlined in terms of objectives, workforce decisions, and workforce trends.
- Identified the method of dashboard production that is organizationally appropriate.
Activities
Outputs
Identify client needs.
- Client needs identified
Brainstorm metrics.
Prioritize and select metrics.
- Key metrics selected
Determine cadence and number of dashboards.
- Dashboard aligned to organization capability and needs
Design a dashboard prototype.
- Dashboard prototype
- Client needs and metrics documented in workbook
Module 3: Create a Future State Plan
The Purpose
- Assign responsibilities to achieve the future state of data governance.
- Set up HR with the knowledge and skills to uphold analytical procedures.
Key Benefits Achieved
- Data governance roles assigned.
- Data audit process drawn out.
- HR analytical competencies and gaps identified.
Activities
Outputs
Assign accountability for data governance.
- Data governance accountabilities documented
Build a metrics library for key metrics.
- HR Metrics Library
Create a data audit process.
- Data audit process developed
Identify required competencies for HR metrics and analytics.
- Analytic competencies itemized
Address data adoption barriers.
- Data adoption barriers addressed
Finalize the future-state plan.
- Future-state plan documented in the HR Metrics Workbook
