NAME: ________________________

Qualitative Forecasts Test

Question Types


Prompt With


Question Limit

of 16 available terms

6 Written Questions

5 Multiple Choice Questions

  1. Sales people provide a range of forecasts for a given SKU.
    Optimistic, Pessimistic, Most likely
    Forecasts for SKUs aggregated by sales manger for given product line or geographical area. Higher level planners than aggregate product line or geographic forecasts to arrive at projections for a given planning horizon.
  2. Data as a historical series is not available, or is not relevant to future needs.
    An unusual product or a unique project is being contemplated.
    Forecast horizon is longer than the safe extrapolation of a quantitative method.
    Trying to forecast beyond 1 or 2 years.
  3. Overcome groupthink issues. Anonymity is maintained will not see who said what. Leader contacts experts, sent survey to respond to. Each expert can edit and read the report and resend new answers till the report is okay by everyone.
  4. Purchase intentions
  5. Model that people can pick up on if someone might go to the movies or not etc.

5 True/False Questions

  1. What are the cons to sales force composites?Information collected and organized from sales force.
    Have daily contact with the customer.

          

  2. What are the problems with qualitative forecasts?Little mathematical skill required.
    Wide acceptance.
    They can: identify systematic change more quickly, better predict the effect of such change on the future. Pick up on "broken legs"

          

  3. When are these assumptions more realistic?Information collected and organized from sales force.
    Have daily contact with the customer.

          

  4. What are the pros to sales force composites?Information collected and organized from sales force.
    Have daily contact with the customer.

          

  5. What are the pros of Jury of Executive Opinion?Forecasting is done quickly and easily, without need of elaborate statistics. May be the best means of forecasting feasible in the absence of adequate data.