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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
Deciding How to Decide
內容大綱
Most businesses rely on traditional capital-budgeting tools when making strategic decisions such as investing in an innovative technology or entering a new market. These tools assume that decision makers have access to remarkably complete and reliable information--yet most strategic decisions must be made under conditions of great uncertainty. Why are these traditional tools used so often even though their limitations are widely acknowledged? The problem is not a lack of alternatives. Managers have at their disposal a wide variety of tools--including decision analysis, scenario planning, and information aggregation tools--that can help them make smart decisions under high degrees of uncertainty. But the sheer variety can be overwhelming. This article provides a model for matching the decision-making tool to the decision being made, on the basis of three factors: how well you understand the variables that will determine success, how well you can predict the range of possible outcomes, and how centralized the relevant information is. The authors bring their framework to life using decisions that executives at McDonald's might need to make--from the very clear-cut (choosing a site for a new store in the United States) to the highly uncertain (changing the business in response to the obesity epidemic).