Forecasting is an important part of marketing and business planning. There are many techniques for forecasting, including both qualitative and quantitative methods. Qualitative methods include surveys, expert opinions, and market experiments, while quantitative time series methods analyze past trends and patterns to predict the future. Effective forecasting requires understanding factors like demand trends, seasonality, elasticity, and uncertainty. The summary provides an overview of key concepts and challenges in forecasting for marketing and business.
26. The telephone has too many shortcomings to
be seriously considered as a
means of communication. The device is
inherently of no value to us.
Western Union internal memo, 1876
27. People will tire of talkers. Talking is no
substitute for the good acting we had
in silent pictures.
Thomas Alva Edison, 1925, on new movies
with sound
28. Every woman is frightened of a mouse.
MGM head Louis B. Mayer in 1926, to a young
cartoonist named Walt Disney
29. I think there is a world market for maybe five
computers.
Thomas Watson, IBM Chairman, 1943
30. 640k ought to be enough for anybody.
Bill Gates, Microsoft founder, 1981
31. Forecasting is an accurate picture of the future.
Forecasting represents the best judgement of the future.
Forecasting serves as a framework for interpreting present events.
Forecasting identifies factors with which the corporation must cope.
Forecasting provides a sorting rule among corporate choices.
Forecasting forces examination of current strategic assumptions.
Forecasting sets up guideposts to mark the path into the future.
Forecasting offers aid in decision-making.
Forecasting offers directions for action.
Forecasting is a measure of uncertainty.
Forecasting combines art and science.
Forecasting is not an exercise in mathematics; it is an expression of the
art of management.
32.
33. • Forecasting customer demand for products
and services is a proactive process of
determining what products are needed
where, when, and in what quantities.
Consequently, demand forecasting is a
customer–focused activity.
34.
35.
36.
37. 5 main characters
• Average
Demand tends to cluster around a specific level.
• Trend
Demand consistently increases or decreases over time.
• Seasonality
Demand shows peaks and valleys at consistent intervals. These
intervals can be hours, days, weeks, months, years, or seasons.
• Cyclicity
Demand gradually increases and decreases over an extended period
of time, such as years. Business cycles (recession/expansion) product
life cycles influence this component of demand.
• Elasticity
Degree of responsiveness of demand to a corresponding
proportionate change in factors effecting it.
38. • PASSIVE FORECASTS
• Where the factors being forecasted are
assumed to be constant over a period of time
and changes are ignored.
• ACTIVE FORECASTS
• Where factors being forecasted are taken as
flexible and are subject to changes.
39. Forecast Categories
• MICROECONOMIC METHODS (QUANTITATIVE)
- involves the prediction of activity of particular firms,
branded products, commodities, markets, and industries.
- are much more reliable than macroeconomic methods
because the dimensionality of factors is lower and often can
easily be incorporated into a model.
• MACROECONOMIC METHODS (QUALITATIVE)
- involves the prediction of economic aggregates such as
inflation, unemployment, GDP growth, short-term interest
rates, and trade flows.
- is very difficult because of the complex interdependencies in
the overall economic factors
56. TIME SERIES MODELS
• Past data is used to make future predictions .
• Known or Independent variables are used for
predicting Unknown or dependent variables,
using the trend equation- “ Predictive
analysis”
• Based on trend equation, we find ‘Line of
Best Fit’ and then it is projected in a scatter
diagram,
57. MOVING AVERAGE METHOD
• Data from a number of consecutive past
periods is combined to provide forecast for
coming periods. Higher the amount of
previous data, better is the forecast.
• Since the averages are calculated on a
moving basis, the seasonal and cyclical
variations are smoothened out.
58. EXPONENTIAL SMOOTHING
Used in cases where the variable under forecast
doesn’t follow a trend.
2 Types- Simple and Weighted
1- Simple smoothing- simple average of specific
observation called order.
2- Weighted smoothing- weights assigned in
decreasing order as one moves from current
period observations to previous observations.
59. REGRESSION MODEL
It is a statistical technique for quantifying the
relationship between variables. In simple
regression analysis, there is one dependent
variable (e.g. sales) to be forecast and one
independent variable. The values of the
independent variable are typically those
assumed to "cause" or determine the values of
the dependent variable.
91. • The defined daily dose (DDD) is a statistical
measure of drug consumption,defined by the
World Health Organization (WHO). ... The
WHO's definition is: "TheDDD is the assumed
average maintenance dose per day for a drug
used for its main indication in adults."