Data-Driven Organizations

Transcription

1 Data-Driven Organizations People Analytics Mark Arian Alan Guarino New York, April 5 th 2018

2 The Rising Influence of People Analytics 1. THE FUTURE IS NOW 2. LINKING TALENT & BUSINESS PERFORMANCE 3. SOME REAL CHALLENGES 4. SUPERIOR ANALYTICS EXECUTION 2018 Korn Ferry. All rights reserved 2

3 1. The Future is Now From AI for job interviews preparation Data analytics for better behaviors and decisions. Live feedback using 3 AI engines: words, tone & pace, face expressions analytics Korn Ferry. All rights reserved 3

4 1. The Future is Now What does an agile / digital leader look like? Leaders drivers #1 request from KF clients. Competencies Experience Traits Drivers Self-service analytics: benchmark of leaders profile. Source: Korn Ferry Institute 2018 Korn Ferry. All rights reserved 4

5 1. The Future is Now Big Data analytics to solve perennial pay equity issue. KF Pay Data Average headline gender pay gap is: 17.6% Comparing people at the same level, in the same company and same function, average gap is: 1.6% 2018 Korn Ferry. All rights reserved 5

6 HARD SOFT 1. The Future is Now The 4 th industrial revolution is underway. New digital workers Traditional employee life cycle AI Programmatic algorithms Gamification Predictive analytics Machine Learning APIs Neuroscience Big Data Virtual Reality Nanotechnology Blockchain Wearables Internet of Things (IoT) 3-D Printing Bots Recruit Manage Open labor market Talent Market Place Supply Exit 33% of contingent workers in many large companies Demand 2018 Korn Ferry. All rights reserved 6

7 Linking Talent & Business Performance 1. THE FUTURE IS NOW 2. LINKING TALENT & BUSINESS PERFORMANCE 3. SOME REAL CHALLENGES 4. SUPERIOR ANALYTICS EXECUTION 2018 Korn Ferry. All rights reserved 7

8 2. Linking Talent & Business Performance Talent analytics payoff for HR Organizations more active* with HR data analytics are 2x as likely to improve their recruiting and leadership pipeline. 3x as likely to realize cost or efficiency gains. 3.5x as likely to get the right people in the right jobs Korn Ferry. All rights reserved 8

9 2. Linking Talent & Business Performance People to Profit Pipeline Analytics & People Interventions Embedding talent analytics into business processes: how much of the $ strategy is talent? 2018 Korn Ferry. All rights reserved 9

10 2. Linking Talent & Business Performance Key success drivers People to Profit Pipeline Full talent and business analytics Business Strategy Pivotal Roles & Talent What are the critical jobs? What is Best in Class? Assessment How good are talents against the strategy and Best in Class? How competitive rewards are? Analysis & Planning How to address gaps (recruit, develop, contingent, structure )? Execution How effective are the talent processes? Business Outcomes What are talent outcomes (retention, engagement, succession) and business results? New and better answers to those questions thanks to more data and computing power Korn Ferry. All rights reserved 10

11 2. Linking Talent & Business Performance Big, more granular data Employee engagement 6.9 million employee respondents across all industries within the last 3 years from over 350 organizations 165,000 assessments of Decision Styles Over half a million employees rated as a part of multi-rater feedback by over 5 million raters Assessments of Emotional Intelligence High volume Talent Q pre-hire assessments 56,000 KF4D Search & Enterprise 53,000 assessments of leadership potential 62,000 learning agility assessments 88,000 business simulations assessing leadership readiness Over 78,000 assessments of Organizational Climate created by leaders and the Leadership Styles they employ in the last three years Structured and unstructured data. Internal and external data. Cloud base, virtual data warehouse. Asynchronous, always on Korn Ferry. All rights reserved 11

12 PEOPLE DRIVERS ORGANIZATION ENABLERS 2. Linking Talent & Business Performance Discretionary Energy and Performance PURPOSE & VISION 3. Meaningful purpose, vision & goals 4. Aligned top team 5. Clear business model 6. Strong and adaptive culture CHOICE & FOCUS 7. Winning strategy 8. Consistent operating model 9. Effective organization structure ACCOUNTABILITY & FAIRNESS 10. Doable jobs 11. Fair rewards and benefits, aligned with strategy VISIBLE & EFFECTIVE LEADERS D I S C R E T I O N A R Y E N E R G Y SUPERIOR PERFORMANCE CLARITY 12. Clear expectations 13. Coherent performance management CAPABILITY 14. Right people and bench 15. Clear talent strategy 16. Succession management 17. Continuous learning COMMITMENT 18. Full engagement 19. Career systems 20. Diversity and inclusion LEADERSHIP 2018 Korn Ferry. All rights reserved 12

13 EBITDA Margin % 2. Linking Talent & Business Performance Discretionary Energy and Performance Client example Life Science Sector Potential profit improvement of $2.5b with ~ $900m through Capability Median DE Capab V&P Com. Lead. A&F C&F Clarity Company A Company B Best-in-Class Additional EBIDTA Margin % Additional EBIDTA USD M Company C 30 Company E Average EBITDA 35 Company D Client 25 Company F Discretionary Energy Index Client s 13

14 2. Linking Talent & Business Performance Discretionary Energy Impact on performance Two portfolios constructed for High and Low DE Annualized Shareholder Returns (%) Sharpe Ratio - Risk-Adjusted Returns - Higher is better Credit Ratings - Used to assess sustainability of business performance - Lower is better High DE final value: 124.9k 20% Low DE final value: 113.2k 13% Korn Ferry. All rights reserved 14

15 The Rising Influence of People Analytics 1. THE FUTURE IS NOW 2. LINKING TALENT & BUSINESS PERFORMANCE 3. SOME REAL CHALLENGES 4. SUPERIOR ANALYTICS EXECUTION 2018 Korn Ferry. All rights reserved 15

16 3. Some Real Challenges Spectrum of data and analytics What data? Which platform? What analytics? How to utilize? Graphs GPS output Machine-generate data, sensors, IoT Raw data, observations Scientific data, neuroscience, physics Social media data, blogs, tweets, likes Streaming, real-time continuous data Structured data, tables, records Time series Text, survey verbatim Unstructured data, human language, audio, video Connected systems, cloud Databases Data warehouses IT systems Mobile, VR devices Operational systems Real-time Reporting platforms Self-service simulation platforms AI - Machine Learning, neural network analysis Distribution, ranking Forecasting Geospatial analytics Networks analytics Optimization Probability Reporting, visualization Social media analytics Sorting, rules engines Statistics Text analytics What-if simulations / game theory Alerts, risk management, turnover Anticipation, prediction Awareness building, feedback Decisions, choices Insight, foresight, learn Needs anticipation, workforce planning Negotiation Recommendation, prescription Talent decision, hiring, promotion, rewards, perform. management Trade-offs analysis, investment 16

17 3. Some Real Challenges Separating the signal from the noise Most of data scientists activities is about cleaning and structuring data Korn Ferry. All rights reserved 17

18 3. Some Real challenges Continuous learning : package delivery client example Data analytics Decision Behavior Data analytics Decision Outcome Delivery delays and traffic accidents. More accidents in left turns. Design new routes with very few left turns. Drivers continue to turn left to ensure quick delivery. High number of accidents continues. Behaviors have not changed. Link district managers incentives to compliance with new recommended routes. 100% compliance. Meaningful reduction of accidents. Less delays Korn Ferry. All rights reserved 18

19 Achievement Positive outlook Empathy Emotional self awareness Inspiring leader Organizational awareness Adaptability Conflict management Team Work Coaching, mentoring Influence 3. Some Real Challenges Data quality and bias: financial services leaders example Some data issues Overconfident Financial Services leaders example Garbage in garbage out. Correlation doesn't imply causation. Comparison of Self-Others Gaps on Emotional and Social Competencies (ESCI). Financial Services Other industries AI-ML Black Box. Distorted, biased or skewed internal or self-reported data, influencing outcomes. Spotty, fragmented, wrong, incomplete, not clean. Costly data access and management. FSS leaders N= 1,021; Other industries leaders N=12, Korn Ferry. All rights reserved 19

20 3. Some Real Challenges Data analytics ethics Data analytics value chain Data sources Data management Modelling & algorithms Insights & applications Monetization Will we hit a point of knowing too much about employees? Can data analysis begin to shape outcomes in real time? Can we avert misbehavior and manipulation before it happens? New practices: Cyber-security Off-limits PIP - GDRP Culture 2018 Korn Ferry. All rights reserved 20

21 The Rising Influence of People Analytics 1. THE FUTURE IS NOW 2. LINKING TALENT & BUSINESS PERFORMANCE 3. SOME REAL CHALLENGES 4. SUPERIOR ANALYTICS EXECUTION 2018 Korn Ferry. All rights reserved 21

22 4. Superior Analytics Execution Talent managed as assets 2018 Korn Ferry. All rights reserved 22

23 Learning agility Fixed mindset Adaptive Proactive 4. Superior Analytics Execution Embracing data analytics for business performance Disrupters Data as a competitive advantage Followers Most organizations today Static Data as a dormant asset Own, past data Traditional HR analysis (e.g., retention) Structured data Search for insights Talent optimization Analytics capabilities Open, unstructured data Advanced analytics Business optimization 23

24 4. Superior Analytics Execution Towards analytics v.2 Emerging: Discretionary Energy People to Profits Pipeline Strategic Workforce Planning v.2 Integrated data and analytics Talent Supply Chain analytics Always-on analytics; AI-ML Today: Talent scorecard Market calibration High potential identification Leadership & talent gaps Success drivers Engagement and retention 24

25 4. Superior Analytics Execution Data analytics has a competitive advantage Executive Search candidates who rank in the top third of Korn Ferry assessment are 1.8x more likely to be high performers on the job. Investment in science, data and analytics Percent of group that were subsequently high performers on the job 32% 48% 59% Bottom third assessment Middle third assessment Top third assessment 2018 Korn Ferry. All rights reserved 25

26 4. Superior Analytics Execution Linking business performance to talent analytics How will you use your analysis and insights for business impact? Do you have the right analytics talent and organization? What analysis will give you the answers you need? What data do you need? Define Build analytical capabilities Learn from the insights. Enact decisions based on analytically derived results How can data analytics help you execute your strategy? Identify critical business issues key data sources 2018 Korn Ferry. All rights reserved 26

27 Thank you.