Make work fair: data-driven design for real results

Introduction: design for fairness

The mythos we need to debunk

Part I: Make it count : motivating action. Data as an engine for change

Goals that promote desirable behavior

Incentives to drive results

Transparency and accountability

Part II: Make it stick : finding and developing talent. Talent attraction to cast a wide net

Applicant screening for accuracy

Hiring the best person for the job

Career advancement that works for all

Part III: Make it normal : embedding fairness. Work arrangements to level the playing field

Norms that create equal opportunities

Culture that fosters thinking

Conclusion : change for good.