Which of the following is a qualitative forecasting method?

Qualitative forecasting is an estimation methodology that uses expert judgment, rather than numerical analysis. This type of forecasting relies upon the knowledge of highly experienced employees and consultants to provide insights into future outcomes. This approach is substantially different from quantitative forecasting, where historical data is compiled and analyzed to discern future trends.

When to Use Qualitative Forecasting

Qualitative forecasting is most useful in situations where it is suspected that future results will depart markedly from results in prior periods, and which therefore cannot be predicted by quantitative means. For example, the historical trend in sales may indicate that sales will increase again in the next year, which would normally be measured using trend line analysis; however, an industry expert points out that there will be a materials shortage at a key supplier that will force sales downward.

Another situation in which qualitative forecasting can be useful is in the assimilation of large amounts of narrowly-focused local data to discern trends that a more quantitative analysis might not find. For example, a construction company needs to know what style of home to build in a certain area, and relies on a local population expert to find out that the area in question is being abandoned by younger families and replaced by an older, retirement-age group. Consequently, the builder constructs smaller one-level homes with fewer bedrooms.

This approach also works well when a course of action must be derived from inadequate data. In this case, a qualitative analysis will seek to link disparate data to construct a more broad-based view, sometimes incorporating intuition to construct this view.

Another situation in which qualitative forecasting can provide value is when management modifies historically-derived trends based on expert opinions. In this case, quantitative methods are used to create a preliminary forecast, which is then adjusted with a qualitative review. In theory, the result should be a forecast derived from the best of both methods.

Qualitative Forecasting Biases

The results produced by qualitative forecasting can be biased, for the reasons noted below.

Recency

Experts may tend to give greater emphasis to recent historical events in extrapolating future trends.

Personal Worldview

Experts may have constructed their own views of how the industry works, and tend to throw out newer influences impacting that market.

delphi method, Forecasting, market research, panel consensus, qualitative forecasting, visionary forecasting

Qualitative forecasting techniques, individually or in combination, enables organizations to analyze the current scenario, recognize changing trends in the market, and to connect that information to potential future strategies.

Which of the following is not a qualitative forecasting technique?

    a. Surveys of consumer expenditure plans
    b. Perspectives of foreign advisory councils
    c. Consumer intention polling
    d. Time-series analysis
  • The first step in time-series analysis is to

      a. perform preliminary regression calculations.
      b. calculate a moving average.
      c. plot the data on a graph.
      d. identify relevant correlated variables.
  • Forecasts are referred to as naive if they

      a. are based only on past values of the variable.
      b. are short-term forecasts.
      c. are long-term forecasts.
      d. generally result in incorrect forecasts.
  • Time-series analysis is based on the assumption that

      a. random error terms are normally distributed.
      b. there are dependable correlations between the variable to be forecast and other independent variables.
      c. past patterns in the variable to be forecast will continue unchanged into the future.
      d. the data do not exhibit a trend.
  • Which of the following is not one of the four types of variation that is estimated in time-series analysis?

      a. Predictable
      b. Trend
      c. Cyclical
      d. Irregular
  • The cyclical component of time-series data is usually estimated using

      a. linear regression analysis.
      b. moving averages.
      c. exponential smoothing.
      d. qualitative methods.
  • In time-series analysis, which source of variation can be estimated by the ratio-to-trend method?

      a. Cyclical
      b. Trend
      c. Seasonal
      d. Irregular
  • If regression analysis is used to estimate the linear relationship between the natural logarithm of the variable to be forecast and time, then the slope estimate is equal to

      a. the linear trend.
      b. the natural logarithm of the rate of growth.
      c. the natural logarithm of one plus the rate of growth.
      d. the natural logarithm of the square root of the rate of growth.
  • The use of a smoothing technique is appropriate when

      a. random behavior is the primary source of variation.
      b. seasonality is present.
      c. data exhibit a strong trend.
      d. all of the above are correct.
  • The greatest smoothing effect is obtained by using

      a. a moving average based on a small number of periods.
      b. exponential smoothing with a small weight value.
      c. the root-mean-square error.
      d. the barometric method.
  • The root-mean-square error is a measure of

      a. sample size.
      b. moving average periods.
      c. exponential smoothing.
      d. forecast accuracy.
  • Barometric methods are used to forecast

      a. seasonal variation.
      b. secular trend.
      c. cyclical variation.
      d. irregular variation.
  • A leading indicator is a measure that usually

      a. changes at the same time and in the same direction as the general economy.
      b. responds to a change in the general economy after a time lag.
      c. changes in the same direction as the general economy before the general economy changes.
      d. has all of the properties listed above.
  • If 3 of the leading indicators move up, 2 move down, and the remaining 6 are constant, then the diffusion index is

      a. 3/6 = 50%
      b. 3/11 = 27%
      c. 5/11 = 45%
      d. 6/11 = 55%
  • A single-equation econometric model of the demand for a product is a ________ equation in which the quantity demanded of the product is an ________ variable.

    Which of the following is a quantitative forecasting method?

    The simple moving method, weight moving method, exponential smoothing method, and time series analysis are quantitative forecasting techniques that are usually used by economists and data analysts.

    What is the most common example of qualitative forecasting?

    Market research is a popular qualitative forecasting method used in business. It forecasts future demand through consumer surveys and questionnaires.

    What are the 4 types of forecasting model?

    While there are a wide range of frequently used quantitative budget forecasting tools, in this article we focus on the top four methods: (1) straight-line, (2) moving average, (3) simple linear regression, and (4) multiple linear regression.

    What are the 3 types of forecasting?

    There are three basic types—qualitative techniques, time series analysis and projection, and causal models.