The datafication of HR 101

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Information about The datafication of HR 101

Published on March 16, 2016

Author: HRTechWorld

Source: slideshare.net

1. The Datafication of HR 101: Graduating from Metrics to Analytics Jan Schwarz, Business Development & Co-Founder Visier Jeremy Ames, CEO Hive Tech HR

2. Agenda • What is the “datafication” of HR? • What’s driving it? • Why is data-driven HR stuck in neutral? • How can HR move up the workforce intelligence maturity curve? • How can I start?

3. Quick Intro - Jan • Co-Founder, Visier • Global role across direct and partner channels • CS Background • 8 years in large enterprise technology • 12 years as an entrepreneur in software technology and applications • Twitter @janschwarz

4. Quick Intro - Jeremy • Founder and President of Hive Tech HR • 19 years in IT, 14 in Employer Services/HR • Former International HR Information Management (IHRIM) Association Board of Directors • Current SHRM HR Mgmt. and Technology Expertise Panel member • Frequent speaker/writer on HR and HR Tech • Twitter@TheHCMGuy

5. Where are our recruiting bottlenecks? How can we retain critical employees? What if we hired more senior or junior roles? How well did we plan? Are we on track? Why? Why not? How do our total workforce costs breakdown in our plan? Should I give my team member a raise? What are our total workforce costs and how are they changing? How can we connect Total Rewards to our bottom line? How will turnover impact our future workforce? Which workforce scenario will best meet our business goals and budget? Where should we allocate people to support the business? Which Critical Talent is at risk of resigning? Who should I promote? Workforce Analytics Workforce Planning Workforce Intelligence Datafication: Making both HR and the business better

6. BersinbyDeloitte Operational Reporting Reactive Reporting of Operational & Compliance Measures • Focus on Data Accuracy, Consistency, Timeliness Advanced Reporting Proactive Reporting for Decision-Making • Analysis of Trends & Benchmarks • Customizable, Self-Service Dashboards Advanced Analytics Statistical Analysis to Solve Business Problems • Identification of Issues & Actionable Solutions • Centralized Staffing & Integrated Data Predictive Analytics Development of Predictive Models • Scenario Planning • Integration with Business & Workforce Planning • Data Governance Model Level 1 Level 2 Level 3 Level 4 Source: Bersin by Deloitte, 2014 4% 10% 30% 56% Bersin by Deloitte’s Maturity Model

7. What is driving the datafication of HR?

8. Better HR results, better business results “New research makes it increasingly clear that companies with more diverse workforces perform better financially.” “Companies that have strong capabilities in HR topics show significantly better financial performance than companies that are weaker in those areas.” “Eight years of research … has consistently found a strong correlation between effective HR program design and financial performance. Indeed, the link goes beyond correlation: Effective HR programs are a leading indicator of financial performance.”

9. Better analytics, even better results “Our research demonstrates that the journey to a mature analytics function may not be easy, but it does pay off in better talent outcomes and efficiency gains. In financial terms, the stock prices of these organizations outpaced the S&P 500 by 30 percent, on average, over the last three years.” “… we found little differences between Top Performers and all others, leading us to recognize that the effect of HR technologies for Top Performers as a competitive advantage has minimized… Quantified Organizations, through their HR practices and technology adoption, they support an environment of data-driven decision making. Quantified Organizations have 79% greater ROE (return on equity) than the Not Quantified Organizations.”

10. 80% say their company cannot succeed without an assertive, data-driven CHRO, who takes a strong stance on talent issues and uses relevant facts to deliver an informed point of view

11. 78% say their company cannot succeed without a CHRO who takes on responsibility for contributing directly to business performance

12. Datafication is no longer optional relative to your competition.

13. Why is data-driven HR stuck in neutral?

14. So much data, so little insight

15. 78% say their company cannot succeed without a CHRO who takes on responsibility for contributing directly to business performance

16. HR’s readiness to take on talent challenges: Analytics one of the biggest gaps Culture and engagement Learning & development Diversity & inclusion Talent acquisition 22% 28% 30% 31% 31% 32% 37% 38% 40% 41% Reskilling HR Leadership gaps Performance management HR Technologies Workforce capabilities Talent analytics But only 22% say they are “ready” to effectively leverage talent analytics 75% of organizations say that talent analytics is important Source: Global Human Capital Trends Study 2015, Deloitte

17. • Transactional HR systems (e.g. your core HRMS) are not designed for analytics • Siloed data & costly / complex data integration • Reporting engine, not analytics engine • Inability to perform multi-dimensional analysis • Incomplete view of workforce costs • Limited workforce planning HR system roadblocks

18. • More than 50% of data warehouse projects have failed (Gartner) • Between 70-80% of corporate business intelligence projects fail (Gartner) • The average price for a data warehouse is $2.3M (IDC) • The time to implement a data warehouse ranges from 12-36 months Data warehouse or business intelligence roadblocks Modern workforce intelligence solutions will not require you to build or manage a data warehouse.

19. How can HR move up the maturity curve with workforce intelligence?

20. “We believe that the next step in HR is to focus on HR from the Outside In. In this view, strategy is a window through which HR professionals align their work to forces and stakeholders outside their organization.” Dave Ulrich

21. Make what the business wants what HR wants A strategic HR organization creates talent strategies that align to business outcomes through the use of data and analytics.

22. Connect workforce insights to business results Workforce Intelligence

23. Remember: Developing a data-oriented skillset and mindset takes time Making data easy-to-consume and fit an HR Business Partner’s daily workflow is key

24. How can I start?

25. Answer just three questions WHAT? SO WHAT? NOW WHAT? How does this impact our business? Does it matter? What do we do, and how do we know we are being successful? Analyze the situation to understand what has happened?

26. Retention WHAT? SO WHAT? NOW WHAT? How does it impact customer satisfaction? How can we improve retention of top performers? What is our retention rate for top performers?

27. • Discover what drives resignations to create programs to increase retention Retention

28. Engagement WHAT? SO WHAT? NOW WHAT? How does engagement correlate with profitability for those business units? How can we improve engagement in underperforming business units to increase profitability? What is our employee engagement score by business unit?

29. Engagement • Discover what drives employee engagement to create programs to increase engagement

30. • What workforce metrics (such as pay per FTE, resignation rates, performance ratings, etc.) are most correlated with an increase in revenue (or customer satisfaction, patient readmission, sales achievement,…) per full-time employee? Relate workforce insights to business results

31. Relate workforce insights to business results • How does turnover compare to sales across locations over last 12 months? • How do tenure and performance relate to the profit of business units? • How do headcount, turnover rate, and total cost of workforce compare to revenue by location? • What employee attributes most contribute to a high customer satisfaction score? • Does employee engagement impact profitability? • Does increasing the compa-ratio for top performers in critical roles increase revenue growth?

32. Store revenue by state vs. turnover 7.5% 8 % 11% 7.6% 7.6% 4.8% 5.2% We need to reduce turnover in Nevada so that we can reduce risk to store revenue

33. Workforce metrics that impact customer satisfaction Tenure managers Age Absence 1st year turnover Training hours Variable pay Female ratio Customer Satisfaction KPI Metrics with positive correlation to Customer SatisfactionMetrics with negative correlation to Customer Satisfaction We need to reduce turnover and absence so that we can increase satisfaction, which will drive revenue.

34. “Now is a unique opportunity for HR professionals to position themselves as fact-based strategic partners of the executive board.” McKinsey & Company, March 2015

35. Thank you Jan Schwarz Jan.schwarz@visier.com Jeremy Ames Jeremy.Ames@HiveTechHR.com

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