Download to read offline
Common Topic Futrures Thinking and Systems
- 1. Strategic Foresight andForecasting 2023 December Common 201
- 2. Scenario Planning What areScenarios - Rich data=driven, stories about tomorrow What is Scenario Planning - A strategic planning methods that some organization use to make flexible long-term plans Purpose of Scenario Planning - Ordering perceptions about how the future may play out - Considering wider range of possibilities about where its industry may head in the future --- more innovative view about the future opportunity and risks - The point of scenario planning is not to predict the most probable future - The objective is to develop and test strategic choices under a variety of plausible futures
- 3. 4 Characteristics of Scenario Planning Storiesof the Futurue Outside-in Approach Patterns of Change
- 4. The Scenario DevelopmentProcess
- 5. 3 Forecast Planning vs.Scenario Planning
- 6.
- 7. Forecasting Technique 7 Quantitative method TimeSeries This method analyzes historical data points, such as sales figures or stock prices, to identify patterns or trends over time. Regression Analysis This technique assess the relationship between a dependent variable and one or more Econometric Model This techniques is focuses on using statistical methods to analyze economic data and test economic theories.
- 8. Forecasting Technique 7 Qualitative method DelphiMethod This structured technique involves a panel of experts who provide their forecasts and assumptions anonymously Market Research Surveys, focus groups, and interviews are common tools used to gather qualitative data from customers, Scenario Analysis This technique involves developing multiple, plausible scenarios based on different assumptions about future conditions.
- 9. Forecasting • Uncertainty ofthe future • Quality of data • Model limitations • Human Bias • Complexity of Systems • Time Horizon Challenges 8 Limitation
- 10. Forecasting • Misuse offorecasts • Social Impact • Transparency and Accountability • Equity and Bias • Environmental impacts and sustainability • Data privacy 8 Ethical Considerations
- 11. The End Tiffany Wilson ofPresentation
Editor's Notes
- #10 Ethical Considerations in Forecasting Misuse of Forecasts: Manipulation: Forecasts can be misrepresented to support specific agendas. Overconfidence: Presenting forecasts as definitive can mislead stakeholders. Social Impact: Forecasts can influence decisions that disproportionately affect vulnerable populations. Predictions about sensitive topics (e.g., crime, public health) may stigmatize groups. Transparency and Accountability: Ethical forecasting requires clear communication of assumptions, limitations, and uncertainties. Lack of transparency can erode trust and lead to misuse of results. Equity and Bias: Algorithmic forecasts may reinforce existing inequalities if based on biased data. Ethical concerns arise when forecasts impact resource allocation (e.g., healthcare, education). Environmental and Intergenerational Impacts: Forecasts that prioritize short-term gains may neglect long-term sustainability. Ethical forecasting should consider the well-being of future generations. Privacy Concerns: Data-driven forecasts often rely on personal or sensitive data. Ensuring data privacy and security is critical to maintaining trust and ethical standards.