Using Data to build commitment for change Using Data to enhance diversity education

1. Research & Measurement Cox Ch 4 • Using Data to build commitment for change • Using Data to enhance diversity education • Diagnosing Climate for Diversity • Measuring Progress • Caveats on using research for organizational change

2. Using Data to build Commitment • Resistance toward diversity initiatives due to • Fear of losing power/control/resources • Misunderstanding the benefits of diversity • Not understanding the need for diversity initiatives • Overcome resistance by • Developing business case • Focusing executives on need for change • Promoting shared leadership w/unions

3. Using Data to build Commitment • Build a Business Case • Use data to show link between diversity management and company success • Articulate advantages of diversity • Cox Ch 1 • Improved Problem solving, Increased Creativity & innovation, Increased Organizational flexibility, Improved Quality of Human Resources, Improved Marketing strategies • Stephan & Stephan • Higher Annualized returns, Improved Interpersonal skills

4. Using Data to build Commitment • Focusing executives on need for change • Read employee responses to diversity climate surveys • Understand magnitude of discrepancy between practices and core values of organization • Promote shared leadership w/unions • Use data to convince union leadership that diversity management is not just the responsibility of management, but of employees at all levels

5. Using Data to Enhance Diversity Education • Create case scenarios for training with employee responses to diversity climate surveys • Know the 3 advantages on p. 64 • Use results of organizational change efforts from another organization to demonstrate value of diversity related change • Use published research data while making a point during training • e.g., Effect of race on performance ratings

6. Diagnosing Climate for Diversity • Why diagnose climate? • Guides plan of action • Provides baseline for measuring progress • Measure the right things • Include those components that are easy to measure & relevant to organization • Use expert external consultant

7. Components of Diversity Climate Individual-Level Measures • Amount of • Prejudice • Stereotyping • Ethnocentrism • Diversity-relevant traits • Level of inter-group conflict • Group-identity strength • Quality of inter-group communication • Cultural differences and similarities

8. Components of Diversity Climate Organization-Level Measures • Identity profile of workforce • Mode of acculturation • Content of organizational culture • Power distribution among groups • People management practices & policies • Openness of informal networks

9. Diagnosing Climate for Diversity • Calibrate Carefully • Compare w/organizations identified as world leaders in climate for diversity • Note disadvantages • Compare with other units within the organization • Compare across time • Triangulate Methods • Use interviews, surveys, direct observations, objective information • Note advantages of interviews

10. Measuring Progress • Use multiple indices (similar to Brief et al) • Turnover • Absenteeism • Interview/survey data • Levels of change in diversity profiles • Percent implementation of action plans • Positive job-offer response ratio • Levels of identity group related to complaints/litigation costs • Successful accommodations for persons w/disabilities • Compare across different identity groups, organizational units etc.

11. Measuring Progress • Communicate results & action steps • Number and types of indices used depend on the level of analysis • Time periods for measurement depend on • Realistic expectations of speed of change • Intrusiveness of measurement • Necessity of feedback for further action • Type of index used depends on org’n type

12. Caveats on using research • Don’t exaggerate claims made by data • Data presenter should have a thorough understanding and be prepared to answer detailed questions • Present data in user-friendly manner • Explain connection b/w data and conclusions • Ensure accuracy of data