2. MEANING:It is an art and science of predicting future events.
Forecasting may involve taking historical data and
projecting them into the future with some sort of
mathematical model.
It is a mathematical model adjusted by a manager’s
good judgment. Effective planning in both the short
and long run depends on a forecast of demand for the
company’s products or services.
3. TYPES OF FORECASTS
Organizations use three major types of forecasts in planning future
operations.
• Economic forecasts: It addresses the business cycle by predicting
inflation rates, money suppliers, housing starts, and other planning
indicators.
• Technological forecasts: These are concerned with rates of
technological progress, which can result in the birth of exciting new
products, requiring new plants and equipments.
•Demand forecasts: These are projections of demand for a company’s
products or service. These are forecasts , also called sales forecasts,
drive a company’s production, capacity, and scheduling systems and
serve as inputs to financial, marketing, and personnel planning.
4. THE STRATEGIC IMPORTANCE OF
FORECASTING
The forecast is the only estimate of demand until
actual demand becomes known. Forecasts of
demand therefore drives decision in many areas.
Let’s look at the impact of product forecast on
three activities:1.
2.
3.
Human Resources.
Capacity
Supply Chain Management
5. HUMAN RESOURCES
Hiring, training, and laying off workers all depends on
anticipated demand. If the human resource department must
hire additional workers without warning, the amount of
training declines and the quality of the workforce suffers. A
large Louisiana chemical firm almost lost its biggest customer
when a quick expansion to around-the-clock shifts led to a
total breakdown in quality control on the second and third
shifts.
CAPACITY
Capacity is inadequate, the resulting shortages can mean
undependable delivery, loss of customers, and loss of market
share. This is exactly what happened to Nabisco when it
underestimated the huge demand for its new low-fat
Snackwell Devil’s Food Cookies.
6. SUPPLY CHAIN
MANAGEMENT
Good supplier relations and the ensuring price advantages for
materials and parts depends on accurate forecasts. e.g, auto
manufacturers who want TRW Corp. to guarantee sufficient airbag
capacity must provide accurate forecasts to justify TRW plant
expansions.
7. SEVEN STEPS IN THE FORECASTING
SYSTEM
1.
2.
3.
4.
Forecasting follows seven basic steps. We use Disney World as an
example of each step:
Determine the use of the forecast: Disney uses park attendance
forecasts to drive staffing, opening time, ride availability, and food
suppliers.
Select the item to be forecasted: For Disney World, there are six main
parks. A forecast of daily attendance at each is the main number that
determines labor, maintenance, and scheduling.
Determine the time horizon of the forecast: is it short, medium, or
long term? Disney develops daily, weekly, monthly, annual, and 5-year
forecast.
Select the forecasting model: Disney uses a variety of statistical
models like, including moving averages, econometrics, and regression
analysis. It also employs judgmental, or nonquantitative, models.
8. 5.
6.
7.
Gather the data needed to make the forecast: Disney’s
forecasting team employs 35 analysts and 70 field personnel to
survey 1 million people/businesses every year. It also uses the
firm called Global Insight for travel industry forecasts and gathers
data on exchange rates, arrivals into the U.S., airline specials,
Wall Street trends, and school vacation schedules.
Make the forecast.
Validate and implement the result: At Disney, forecasts are
reviewed daily at the highest levels to make sure that the model,
assumptions, and data are valid. Error measures are applied; then
the forecasts are used to schedule personnel down to 15-minutes
intervals.
9. QUANTITATIVE FORECASTING
METHODS
Time Series Models
Such models predict on the assumption that the future is a function of the past.
In other words , they look at what has happened over a period of time and use a
series of past data to make a forecast.
Types:
1) Moving Averages(Simple and Weighted)
A moving average forecasts uses a number of historical actual data values to
generate a forecast. Moving averages are useful if we can assume that market
demands will stay fairly steady over time.
Simple Moving Average= ∑ Demand in previous n periods
n
• When some past periods are to be given more weightage then Weighted Moving
Average is used
Weighted Moving Average = ∑(Weight for period n)(Demand in period n)
∑ Weights
10. Problems faced by this method:
• Increasing the size of n smoothens out fluctuations better, but it makes the
method less sensitive to real changes in the data.
• Moving averages can’t pick up trends very well. Because they are averages ,
they will always stay within past levels and will not predict changes to either
higher and lower levels.
• Moving Averages require extensive records of past data.
Exponential Smoothing
It is a sophisticated weighted moving average forecasting method that is still
fairly easy to use. It involves very little records keeping of past data .The
basic exponential smoothing formula is:
Ft=Ft-1 + α(At-1 – Ft-1) (0<=α>=)
• Α is high when more weightage is given to recent data and α is low when
low weightage is given to recent data.
• This method is widely used in business and an important part of
computerized inventory control systems.
11. Associative Models
Such models usually consider several variables that are related to the
quantity being predicted. Once these related variables have been found ,a
statistical model is build and used to forecast the item of interest, e.g; the
sales of Dell PCs may be related to the Dell’s advertising budget, the
company’s prices, competitor’s prices and promotional strategies. In this
case PCs sales would be called the dependent variable and the other
variables would be called the independent variables.
• Most common approach is Least Square Method or Linear-Regression
Analyses.
12. FORECAST ERROR
Forecasting error can be determined by comparing the
forecasted values with the actual or observed values. If ft
denotes the forecast in period t ,the forecast error (or
deviation)is defined as ;
Forecast error = Actual demand – Forecast value
= At - F t
Mean Absolute Deviation (MAD) – This value is computed by
taking the sum of the absolute values of the individual
forecast error and dividing by the no. of periods.
MAD = ∑ |Actual – Forecast |
n
13. Qualitative Forecasting
Methods
DELPHI METHOD - To overcome the limitation of above method, a
committee is formed. A moderator creates a questionnaire & distributes
to the participants. The identity of committee members is concealed.
Their responses are summed up. A new set of questions is prepared.
Steps involved-1.
2.
3.
4.
5.
6.
7.
Choose experts to participate from different areas.
Their questionnaire or email obtain forecasts.
Summarize the results.
Redistribute results with another new questionnaire.
Summarizes again- refining forecasts.
Carry on 3 to 6 rounds
It results in forecasts that most participants have ultimately agreed to in
spite of their initial disagreement.
14. EDUCATED GUESS
•Judgment based on experience & intuition to estimate a sales forecast (by one
person
•Used for short term forecast when cost of forecast inaccuracy is low.
•Such forecasts have to be made very frequently.
SURVEY OF CUSTOMERS
•Suitable when a company has few customers e.g. Automobile/defense
contractors. Estimates are gathered from customers directly .
EXECUTIVE COMMITTEE CONSENSUS
•Forecast made by a committee of knowledge executive from different
departments. Such forecast are compromise forecast not reflecting the
extremes.
•People from a lower level may not speak freely to refute the estimates of
people saving above them.
15. SURVEY OF SALES FORCE
Used for existing product when salespeople sell directly to customers & a good
communication system exists in an organization.
Estimates of future regional sales are obtained from sales people.
These are refined by managers & total sales for all regions is estimated
on its behalf.
MARKET RESEARCH
Suitable for new products or introduction of exiting product in new market
segments. Then mail, questionnaires, surveys, telephone interviews- hypothesis is
tested
HISTORICAL ANALOGY
For a new product a generic or existing product is used as a model. The
analogies may be complementary product/substitutes. Knowledge of one product
sales during various stages of its product life cycle is applied to the estimate of
sales for a similar product.
16. QUESTIONS:
Q1.) Define qualitative & quantitative forecasting
methods.
Q2.) Define forecast accuracy.
Q3.) Name three underlying reasons why operations
management must forecast.
Q4.) Describe how forecasting is integral to business
planning .
Q5.) Name the four components or data patterns of longrange demand in forecasting.
Please refer to the notes:
