This document discusses demand forecasting techniques used to predict future demand for products and services. It covers qualitative methods like executive opinion and surveys, as well as quantitative time series and causal models. Time series methods explained include moving averages, trend projection using least squares, and exponential smoothing. Causal models relate demand to factors like income, price, and leading economic indicators. The document notes uncertainties in demand forecasting arise from limitations of past data, unrealistic assumptions in models, and changes that are difficult to predict.

1. PROJECT
ENGINEERING AND
ECONOMICS
SEMINAR
DEMAND FORECASTING,
UNCERTAINITIES OF DEMAND FORECASTING
AND MARKET PLANNING
GROUP 12 : ROLL NUMBER 4,13,17,19,28,42

2. DEMAND FORECASTING

3. INTRODUCTION
The prediction of probable demand for a product or a service
on the basis of the past events and prevailing trends in the
present is called DEMAND FORECASTING
Demand forecasting may be used in production planning,
inventory management, and at times in assessing future
capacity requirements, or in making decisions on whether to
enter a new market.
Demand forecasting involves techniques including both
informal methods, such as educated guesses, and
quantitative methods, such as the use of historical sales data
and statistical techniques or current data from test markets.

4. OBJECTIVES OF DEMAND
FORECASTING
The objectives of demand forecasting are different in case of short
run and long run forecasts.
• SHORT RUN FORECASTING : A period not exceeding one year.
Objectives :
1. To evolve a suitable production policy
2. To plan the purchase of raw materials
3. To plan short term financial requirements
4. To determine appropriate price policy
5. To fix sales targets

5. • LONG RUN FORECASTING : A period lasting more than 3
years
OBJECTIVES :
1. Expansion of new unit or construction of new unit
2. To plan long term financial requirements
3. To plan Man power requirements

6. HOW IS DEMAND FORECAST
DETERMINED ?
DESCRIPTION QUALITATIVE APPROACH QUANTITATIVE APPROACH
Applicability Used when situation is vague
& little data exist (e.g., new
products and technologies)
Used when situation is stable &
historical data exist
(e.g. existing products, current
technology)
Considerations Involves intuition and
experience
Involves mathematical
techniques
Techniques 1.Jury of executive opinion
2.Sales force composite
3.Delphi method
4.Consumer market survey
1.Time series models
2.Causal models

7. QUALITATIVE FORECASTING METHODS
Qualitative
Method
Description
Jury of executive
opinion
The opinions of a small group of high-level managers are pooled and
together they estimate demand. The group uses their managerial
experience, and in some cases, combines the results of statistical
models.
Sales force
composite
Each salesperson (for example for a territorial coverage) is asked to
project their sales. Since the salesperson is the one closest to the
marketplace, he has the capacity to know what the customer wants.
These projections are then combined at the municipal, provincial and
regional levels.
Delphi method A panel of experts is identified where an expert could be a decision
maker, an ordinary employee, or an industry expert. Each of them will
be asked individually for their estimate of the demand. An iterative
process is conducted until the experts have reached a consensus.
Consumer market
survey
The customers are asked about their purchasing plans and their
projected buying behaviour. A large number of respondents is needed
here to be able to generalize certain results.

8. QUANTITATIVE FORECASTING METHOD
There are two forecasting models here –
(1) THE TIME SERIES MODEL :. A time series is a s et of evenly
spaced numerical data and is obtained by observing responses
at regular time periods. In the time series model , the forecast is
based only on past values and assumes that factors that
influence the past, the present and the future sales of your
products will continue.
(2) THE CAUSAL MODEL: causal model uses a mathematical
technique known as the regression analysis that relates a
dependent variable (for example, demand) to an independent
variable (for example, price, advertisement, etc.) in the form of a
linear equation.

9. TIME SERIES METHOD
1. MOVING AVERAGE METHOD : MA is a series of arithmetic means and is used if little
or no trend is present in the data; provides an overall impression of data over time.
A simple moving average uses average demand for a fixed sequence of periods and
is good for stable demand with no pronounced behavioural patterns.
𝐹 𝑡 = 𝑆𝑡 + St-1 + ….. + St-n+1
n
F – Forecast S – Sales n – Period t – time of forecast
YEAR SALES FORECAST (3’P) FORECAST (5’P)
2001 28
2002 29
2003 28. 5
2004 31.0 (28+29+28.5)/3 = 28.5
2005 34.2 (31+28.5+29)/3 = 29.5
2006 32.7 (34.2+31+28.5)/3 = 31.23 (34.2+31+28.5+29+28)/5 = 30.14

10. 2. TREND PROJECTION METHOD : The Trend Projection Method is the most classical
method of business forecasting, which is concerned with the movement of variables
through time. This method requires a long time-series data. The trend projection method is
based on the assumption that the factors liable for the past trends in the variables to be
projected shall continue to play their role in the future in the same manner and to the same
extent as they did in the past while determining the variable’s magnitude and direction.
The trend projection method includes three techniques based on the time-series data :
(a) Graphical Method
(b) Least Square Method
(c ) Box Jenkins Method
The analyst chooses a plausible algebraic relation (linear, quadratic, logarithmic, etc.)
between sales. And the independent variable, time. The trend line is then projected into the
future by extrapolation.
This method is popular because it is simple and inexpensive. The basic assumption is that
the past rate of change will continue in the future. Thus the techinique yields acceptable
results so long as the time series shows a persistent tendency to move in the same
direction.

11. Estimation of Trend by the Method of Least Squares
The annual sales of a company are as follows:
Year 1991 1992 1993 1994 1995
Sales ‘000 45 56 58 46 75
Using the method of least squares, fit a st. line trend and estimate the annual
sales of 1997.
Year Sales
y
1990 = 0
Time-
Deviation
x
x2 xy Estimated
Trend’000
Y=45 + 5x
1991 45 1 1 45 50
1992 56 2 4 112 55
1993 78 3 9 234 60
1994 46 4 16 184 65
1995 75 5 25 375 70
n = 5  y = 300  x = 15  x2 = 55  xy = 950

12. n = 5  y = 300  x = 15  x2 = 55  xy = 950
 y = n.a. + b  x …1
xy = a x + b x2 …. 2
Substituting the computed values
we have,
300 = 5a + 15b ….3 (x 3)
950 = 15a + 55b …. 4
Multiplying (3) by 3 we have
900 = 15a + 45b
950 = 15a + 55b
Therefore, 10b = 50, b = 5
Substituting b = 5 in (3)
300 = 5a + 15(5)
300 = 5a + 75
5a = 225 a = 45
St. line equation is Y = a + bx
Substituting the values of a and b,
Y = 45 + 5x
Therefore,
Y1991 (x=1) = 45 + 5(1) = 50
Y1992 (x=2) = 45 + 5(2) = 55
Y1993 (x=3) = 45 + 5(3) = 60
Y1994 (x=4) = 45 + 5(4) = 65
Y1995 (x=5) = 45 + 5(5) = 70
Y1996 (x=6) = 45 + 5(6) = 75
Forecast for the year 1997
Y1997 (x=7) = 45 + 5(7) = 80
i.e. Rs.80,000/-

13. 3. EXPONENTIAL SMOOTHING : In this method, forecast are
modified on account of errors . It is an easily learned and
easily applied procedure for approximately calculating or
recalling some value, or for making some determination
based on prior assumptions by the user, such as seasonality.
Ft – Forecast for period ‘t’
Dt – Actual demand for period ‘t’
Error = Dt – Ft
 - Smoothing Parameter which usually lies between 0 and
1
Ft+1 = Ft +  (error) = Ft +  (Dt – Ft)

14. EXPONENTIAL SMOOTHING : EXAMPLE

15. CASUAL METHOD :
Forecast on the basis of cause and effect relationships that are expressed quantitatively. Some of the
important methods are:
1. CHAIN RATIO METHOD: This method applies a series of factors to determine the demand.
2. CONSUMPTION LEVEL METHOD: This method is used for those products that are directly
consumed. This method measures the consumption level on the basis of elasticity coefficients.
The important ones are :
• Income Elasticity: This reflects the responsiveness of demand to variations in income. It is
calculated as:
Where
E1 = Income elasticity of demand
Q1 = quantity demanded in the base year
Q2 = quantity demanded in the following year
I1 = income level in the base year
I2 = income level in the following year
E1 = [Q2 - Q1/ I2- I1] * [I1+I2/ Q2 +Q1]

16. • Price Elasticity: This reflects the responsiveness of demand to variations in
price. It is calculated as:
Where
EP = Price elasticity of demand
Q1 = quantity demanded in the base year
Q2 = quantity demanded in the following year
P1 = price level in the base year
P2 = price level in the following year
3. END USE METHOD: This method forecasts the demand based on the
consumption coefficient of the various uses of the product.
4. LEADING INDICATOR METHOD: This method uses the changes in the
leading indicators to predict the changes in the lagging indicators.
5. ECONOMETRIC METHOD: An advanced forecasting tool, it is a
mathematical expression of economic relationships derived from
economic theory.
EP = [Q2 - Q1/ P2- P1] * [P1+P2/ Q2 +Q1]

17. UNCERTAINITIES OF DEMAND
FORECASTINGDemand forecasts are subject to error and uncertainty which arise from three different
sources:
Ø DATA ABOUT PAST AND PRESENT MARKET : The analysis of past and present markets,
which serve as the springboard for the projection exercise, may be vitiated by the following
inadequacies of data:
1. Lack of Standardization: Data pertaining to market features like product, price,
quantity, cost, income, etc. may not reflect uniform concepts and measures.
2. Few observations: observations available to conduct meaningful analysis may not be
enough.
3. Influence of abnormal factors: Some of the observations may be influenced by
abnormal factors like war or natural calamity.
Ø METHODS OF FORECASTING : Methods used for demand forecasting are characterized by
the following limitations:
1. Inability to handle unquantifiable factors: most of the forecasting methods, being
quantitative in nature, cannot handle unquantifiable factors which sometimes can be of
immense significance.
2. Unrealistic assumptions: Each forecasting method is based on certain assumptions. For
example, the trend projection method is based on the mutually compensating affects
premise and the end use method is based on the constancy of technical coefficients.
Uncertainty arises when the assumptions underline the chosen method tend to be
realistic and erroneous.
3. Exercise data requirement: In general, the more advanced a method, the greater the
data requirement. For example, to use an econometric model one has to forecast the
future values of explanatory variables in order to project the explained variable.

18. Ø ENVIRONMENTAL CHANGES: The environment in which a business functions is
characterized by numerous uncertainties. The important sources of uncertainty are
mentioned below:
• Technological Change: This is a very important and very hard-to-predict factor
which influences business prospects. A technological advancement may create a
new product which performs the same function more efficiently and economically,
thereby cutting into the market for the existing product. For example, electronic
watches are encroaching on the market for mechanical watches.
• Shift in Government Policy: Government resolution of business may be extensive.
Changes in government policy, which may be difficult to anticipate, could have a
telling effect on the business environment.
• Development on the International Scene: Development on the International Scene
may have a profound effect on industries.
• Discovery of New Sources of Raw Material: Discovery of new sources of raw
materials, particularly hydrocarbons, can have a significant effect on the market
situation of several products.
• Vagaries of Monsoon: Monsoon, if plays an important role in the economy of a
country, is somewhat unpredictable. The behaviour of monsoon influences, directly
or indirectly, the demand for a wide range of products.

19. COPING WITH UNCERTAINITIES
Given the uncertainties in demand forecasting, adequate efforts, along the
following lines, may be made to cope with uncertainties.
Ø Conduct analysis with data based on uniform and standard definitions.
Ø In identifying trends, coefficients, and relationships, ignore the abnormal and
out-of-the-ordinary observations.
Ø Critically evaluate the assumptions of the forecasting methods and choose a
method which is appropriate to situation.
Ø Adjust the projections derived from quantitative analysis in the light of
unquantifiable, but significant, influences.
Ø Monitor the environment imaginatively to identify important changes.
Ø Consider likely alternative scenarios and their impact on market and
competition.
Ø Conduct sensitivity analysis to access the impact on the size of demand for
unfavourable and favourable variations of the determining factors from their
most likely levels.

20. MARKET
PLANNING

21. SITUATIONAL ANALYSIS : SWOT
ANALYSIS
SWOT ANALYSIS focuses on Strengths, Weaknesses, Opportunities and Threats as the key
drivers or inhibitors of any business. To ensure this format helps inform meaningful
interpretation and conclusions, the information you use should be as accurate as possible.
• STRENGTHS AND WEAKNESS are critical factors to the effectiveness and success of a
business. Most often these are internal to the business and are elements that a business
can control. They can be either actual or perceived i.e. level of distribution is actual
while brand image is perceived. In marketing terms, actual and perceived factors can be
equally important and their relative merits should be assessed within the overall
analysis. Examples of strengths would include high brand awareness, good reputation
for quality, good service levels, high margins or unique product positioning. Weaknesses
would include unsatisfactory product delivery, poor relationship between price and
quality, lack of unique selling point, low investment in marketing or weak internal cost
control. Promoting strengths can be an effective strategy for growth and can lead to
improved competitive advantage. Equally, redressing a weakness puts the business in a
stronger position to capitalise on the effect of its marketing activity.
• OPPORTUNITIES AND THREATS are external and, therefore, more out with the control of
the business. They can arise from competitive activity, channel pressure, demographic
changes, political, technological or legislative developments. Understanding and pre-
empting these external factors is key to building strategy. For example, the ageing
population and rise of out-of-home eating are two major changes, which will impact on
food expenditure in the coming decades. The implications of these should be considered
within the overall company strategy in term of e.g. product range, distribution channels,
and product delivery. Identifying opportunities and threats can focus strategic planning
both in the short and long term. Well informed, creative forward planning is a key
business advantage and can lead to innovation far beyond the company’s apparent
capabilities.

22. SWOT ANALYSIS EXAMPLE
1. STRENGTHS
• Knowledge. Our competitors are retailers, pushing boxes. We know systems, networks,
connectivity, programming, all the Value Added Resellers (VARs), and data management.
• Relationship selling. We get to know our customers, one by one. Our direct sales force
maintains a relationship.
• History. We’ve been in our town forever. We have the loyalty of customers and vendors. We
are local.
2. WEAKNESSES
• Costs. The chain stores have better economics. Their per-unit costs of selling are quite low.
They aren’t offering what we offer in terms of knowledgeable selling, but their cost per square
foot and per dollar of sales are much lower.
• Price and volume. The major stores pushing boxes can afford to sell for less. Their component
costs are less and they benefit from volume buying with the main vendors.
• Brand power. Take one look at their full-page advertising, in color, in the Sunday paper. We
can’t match that. We don’t have the national name that flows into national advertising.
AMT is a computer store in a medium-sized market in the United States. Lately it has
suffered through a steady business decline, caused mainly by increasing competition
from larger office products stores with national brand names. The following is the
SWOT analysis included in its marketing plan.

23. 3. OPPORTUNITIES
• Local area networks. LANs are becoming commonplace in small businesses, and
even in home offices. Businesses today assume LANs are part of normal office
work. This is an opportunity for us because LANs are much more knowledge and
service intensive than the standard off-the-shelf PC.
• The Internet. The increasing opportunities of the Internet offer us another area of
strength in comparison to the box-on-the-shelf major chain stores. Our customers
want more help with the Internet and we are in a better position to give it to them.
• Training. The major stores don’t provide training, but as systems become more
complicated with LAN and Internet usage, training is more in demand. This is
particularly true of our main target markets.
• Service. As our target market needs more service, our competitors are less likely
than ever to provide it. Their business model doesn’t include service, just selling
the boxes.
4. THREATS
• The computer as appliance. Volume buying and selling of computers as products in
boxes, supposedly not needing support, training, connectivity services, etc. As
people think of the computer in those terms, they think they need our service
orientation less.
• The larger price-oriented store. When they have huge advertisements of low prices
in the newspaper, our customers think we are not giving them good value.

24. BREAK EVEN ANALYSIS
Breakeven analysis is used to determine when your business will be able to cover all its
expenses and begin to make a profit. It is important to identify your startup costs, which
will help you determine your sales revenue needed to pay ongoing business expenses.
EXAMPLE :
If you have $5,000 of product sales, this will not cover $5,000 in monthly overhead
expenses. The cost of selling $5,000 in retail goods could easily be $3,000 at the
wholesale price, so the $5,000 in sales revenue only provides $2,000 in gross profit. The
breakeven point is reached when revenue equals all business costs.
To calculate your breakeven point, you will need to identify your fixed and variable costs.
• Fixed costs are expenses that do not vary with sales volume, such as rent and
administrative salaries. These expenses must be paid regardless of sales, and are often
referred to as overhead costs.
• Variable costs fluctuate directly with sales volume, such as purchasing inventory,
shipping, and manufacturing a product.
To determine your breakeven point, use the equation below:
Break even point = fixed costs/ (unit selling price – variable costs)

25. MARKETING STRATEGY : 5 PS OF
MARKETING
Market
Planning
PRICING
PROMOTION
PLACE OR
CHANNEL OF
DISTRIBUTION
PEOPLE
PRODUCT

26. TERMINOLOGIES RELATED TO PRICING
• EX-FACTORY PRICE : Ex-factory price refers to the cost a manufacturer charges for
a distributor or other buyer to purchase products directly from the source. This is
a quote for the goods alone. It does not include shipping, handling or taxes. This
practice is common when working with raw materials for secondary
manufacturing.
• TAXES AND DUTIES : a duty is a kind of tax levied by a state. It is often associated
with customs, in which context they are also known as tariffs or dues. The term is
often used to describe a tax on certain items purchased abroad.
• TRADE MARGINS :A trade margin is the difference between the actual or
imputed price realised on a good purchased for resale (either wholesale or retail)
and the price that would have to be paid by the distributor to replace the good at
the time it is sold or otherwise disposed of.
• DISCOUNTS : Reduction of cost price of the product
• EXPORT PRICE : Price fixed for the export products or services which the exporter
intends to sell in the overseas market is called export pricing.

27. PRICING TECHNIQUES
a. Cost – Plus Method – it is the simplest method. The cost of the product
is figured out and tacked on a little something for profit.
b. Market-Oriented Method - this is not based on cost, but on the
interaction of demand and supply,
c. “Loss” Leader Strategy - Some products may be sold at a losing
preposition to attract customers to go to their stores. The mark-up is
taken from other products.
d. Psychological Pricing – Stating the price on a lower scale.
e. Value for Money Pricing – this pricing approach is not aimed at
maximizing profit per single purchase but in bulk of quantity/frequent
sale. This sales tactic is an ideal mechanism in tapping potential sales
through more purchases, thus clearing inventory gluts and crating an
image of fresh supply. This pricing concept targets either or both the
diet and price conscious consumers.

28. f. Pricing Factor Segmentation – the “seller” subdivides the market into groups
responsive to price and price deals, product quality,etc.
Ex. No left-over, No sharing buffets – 50%
Discount per pack
50% Discounts on all products at 8:45p.m. everyday
This strategy favors both the consumer and the seller. On the part of the consumers,
they get the benefit of quality and good tasting products at reduced prices. On the
other hand, the seller avoids wastage and minimizes cost of storage.
g. Marked Down Pricing – in cases where demand is limited and competition is
intense, the usual mark-up pricing approach is temporarily suspended in favor of a
markdown to capture a segment of the market. The concept behind the
markdown pricing is the “thought” that the lower you can make your price, the
more you sell, and you generate revenues sufficient to cover costs and provide a
profit.
h. Bonus-Pack Pricing – for the end-users, this is commonly used so that they will buy
more than the required quantity. A good example is the :
“Buy 34 at the price of 30