On National Teacher Day, meet the 2024-25 Kenan Fellows
302 unit1 forecasting
1. February 5, 2013
Volti, Unit 1 information, chapters 1-3
• The Nature of Technology
• Winners and Losers: The Differential Effects
of Technological Change
• The Sources of Technological Change
2. February 5, 2013
Forecasting
• Any individual or organization affected by
technological change inevitably engages in
forecasting (financial, economic, etc.)
• Goal is not always to predict future
• examine trends
• predict likely scenarios
• develop contingency plans
3. February 5, 2013
Methods of Forecasting
• Summarized from Martino’s Technological
Forecasting: An Introduction handout (PDF
available in Course Documents area)
• Examples may overlap with more than one
method
4. February 5, 2013
Extrapolation
• Projecting a pattern that has been found in
the past, to anticipate potential outcomes in
the future
• Examples: Moore’s Law / El Nino
• Examples?
5. February 5, 2013
Leading Indicators
• Using one time series to anticipate / obtain
information another time series
• Assumption is that both time series share
similar behaviors, but with a time-lag
• Example: “What the barometer is doing today
is what the rain clouds will do tomorrow”
6. February 5, 2013
Causal Models
• Finding cause and effect relationships
• Contextualizing first two methods
• Example: understanding why the barometer
itself works, in order to better understand why
there will be rain clouds tomorrow.
7. February 5, 2013
Probabilistic Methods
• Forecasting using any combination of the first
three methods, then arriving at a range of
possible values
• Example: 70% chance of showers
Notes de l'éditeur
Example: planning for Y2K bug back in late 1990s. No one was entirely certain what would definitely happen if we did nothing, so most companies did as much as possible to overcompensate against any potential problems that might arise as a result of it.
El Nino: Name given to the occasional development of warm ocean surface waters along the coast of Ecuador and Peru. When this warming occurs the tropical Pacific trade winds weaken and the usual upwelling of cold, nutrient rich deep ocean water off the coast of Ecuador and Peru is reduced. The El Nino normally occurs around Christmas and lasts usually for a few weeks to a few months. Sometimes an extremely warm event can develop that lasts for much longer time periods.
For presidential election: “As Ohio goes, so goes the nation”
A leading indicator for PC sales would be that there is usually more demand from July - September. A causal model would examine why this is the case: back-to-school shopping season
