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最新個案
- A practical guide to SEC ï¬nancial reporting and disclosures for successful regulatory crowdfunding
- Quality shareholders versus transient investors: The alarming case of product recalls
- The Health Equity Accelerator at Boston Medical Center
- Monosha Biotech: Growth Challenges of a Social Enterprise Brand
- Assessing the Value of Unifying and De-duplicating Customer Data, Spreadsheet Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise, Data Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise
- Board Director Dilemmas: The Tradeoffs of Board Selection
- Barbie: Reviving a Cultural Icon at Mattel (Abridged)
- Happiness Capital: A Hundred-Year-Old Family Business's Quest to Create Happiness
Data-Driven Diversity
內容大綱
Many companies today recognize that workforce diversity is both a moral imperative and a key to stronger business performance. U.S. firms alone spend billions of dollars every year to educate their employees about diversity, equity, and inclusion (DEI). But research shows that such training programs don't lead to meaningful change. What's necessary, say the authors, is a metrics-based approach that can identify problems, establish baselines, and measure progress. Company managers and in-house lawyers often worry that collecting diversity data may yield evidence of discrimination that can fuel lawsuits against them. But there are ways to minimize the legal threats while still embracing the use of metrics.The authors suggest first determining your risk tolerance and then developing an action plan. You will need to track both outcome metrics and process metrics and act promptly on what you find. Starting with a pilot program can be a good idea. You should also build the business case for intervention, control expectations through careful messaging, and create clear protocols for accessing, sharing, and retaining DEI data.