Demand forcasting

1. UNIT - II: DEMAND
FORECASTING AND FACILITY
PLANNING:
Demand Forecasting Need and Importance, Process, Methods of demand
forecasting; Facility Location Factors and Theories; Facility Layout Principles and
Types; Capacity Planning Long-range, Types, Capacity Requirement Planning

2. Demand forecasting
•Demand forecasting is the process of making
estimations about future customer demand over a
defined period, using historical data and other
information.

8. Disney world practice

13. Demand pattern

15. Time series demand forecasting
Time-series forecast is a method that relies on historical data and assumes if
the historical data is the good indicator to forecast the future, it will be
appropriate if the demand pattern is not varied significant in each year.

17. Simple Moving Average (SMA)
• A simple moving average (SMA) is an arithmetic moving average
calculated by adding values and then dividing that the number of
time periods in the calculation average.
Equation = Mt = 1/n[Dt1+Dt2 ……………Dtn]
 Mt= Simple moving average forecast
 n = Number of moving period
 D= Actual Demand

18. Exponential smoothing
• Exponential smoothing is a technique used to detect significant changes in data
by considering the most recent data. This method is used in making short-term
forecasts.
• Ft= Ft-1+α (Dt-1-Ft-1) where
Ft –Smoothed forecast
Ft-1-Previous period forecast
Dt-1-Previous period Demand
α – Smoothing Constant 0 to 1
• Forecasts produced using this method are accurate and reliable and they predict
for the next period. The forecast shows projected demand and actual demand.
• The smoothing constant put on each observation decreases exponentially over
time (the most recent observation has the highest weight).
• This is often better than moving average models that allocate the same weight to
all the relevant historical months

19. • 1. It is easy to learn and apply.
 Forecast for the most recent time period.
 The actual value for that time period.
 Value of the smoothing constant
• 2. It produces accurate forecasts.
 The forecast is considered accurate as it accounts for the difference between actual projections and what
actually occurred
• 3. It gives more significance to recent observations.
• 4. It produces forecasts that lag behind the actual trend.
• This method has “smoothing” in its name because it neglects the ups and downs associated with random
variation
• 5. It cannot handle trends well.
• Exponential smoothing is best used for forecasts that are short-term and in the absence of seasonal or
cyclical variations. As a result, forecasts aren’t accurate when data with cyclical or seasonal variations are
present.

20. Demand Forecasting by Regression Analysis
• In regression method, the demand function for a product is estimated
where demand is dependent variable and variables that determine
the demand are independent variable.
• Linear regression is a statistical method used to help predict future
values from past values. It is commonly used as a quantitative way to
determine the underlying trend and when prices are overextended.
• The overall regression equation is Y = bX + a,
• where: X is the independent variable (number of sales calls) Y is the
dependent variable (number of deals closed)

22. Adaptive exponential smoothing
Adaptive exponential smoothing incorporates seasonal variations
when assigning probability to events.
 Seasonal variations are changes in inventory levels, profits and sales
volume throughout various times of the year.

23. Examples of Adaptive Forecasting
• For example, a business using adaptive exponential smoothing
incorporates heightened sales figures and inventory demands for the
Christmas shopping season when forecasting probable events. The
variables in this type of adaptive forecasting can change over time,
which allows the business an opportunity to plan for fluctuating
demand throughout a given year.

24. Graphical Method
• Helps in forecasting the future sales of an organization with the help of a
graph. The sales data is plotted on a graph and a line is drawn on plotted
points.
• The Figure shows a curve which is plotted by taking into the account the
sales data of XYZ Organization. Line P is drawn through mid-points of the
curve and S is a straight line. These lines are extended to get the future
sales for year 2010 which is approximately 47 tons. This method is very
simple and less expensive; however, the projections made by this method
may be based on the personal bias of the forecaster.

26. Econometric modelling of demand forecasting
• This technique combines sales data with information on outside forces
that affect demand. Then you create a mathematical formula to predict
future customer demand. The econometric demand forecasting method
accounts for relationships between economic factors.
• An econometric model is one of the tools economists use to forecast
future developments in the economy.
• Let us assume that demand is a function of Gross National Product
(GNP), price and advertising. In regression terms we would assume
that all three independent variables are exogenous to the system and
hence are not influenced by the level of demand itself or by one another.

27. Thus is econometric form we can have;
• Demand = f (GNP, price and advertising)
• Cost = f (production and inventory levels)
• Selling expenses = f (advertising and other selling expenses)
• Price = f (cost and selling expenses)
•Regression equation

29. Qualitative Methods

30. Market research
The market research demand forecasting technique uses customer
surveys and questionnaires in order to predict future demand. This
forecasting technique is ideal for businesses that do not have
historical sales data available such as when a new product is released.
While there are many ways to perform market research, most
businesses use one or more of five basic ways : surveys, focus groups,
personal interviews, observation, and field trials.
The demographic data from this method, will help you target future
marketing efforts. Market research is particularly helpful for young
companies that are just getting to know their customers.

31. Focus Group Approach
• The focus group works extremely well for this challenge if the group
size is relatively small—in the eight to 12 person range. If much larger,
the group should be divided into multiple groups. Focus groups
provide the opportunity for members to share information equally,
avoiding domination by any one individual.
 Explain the demand forecasting task.
Discuss the rules.
Explain the importance of the process.
Identify the different factors that have contributed to the
performance.
Identify other factors that have contributed to the performance.
Discuss the linkage.
Repeat the process for each factor
Provide a confidence estimate.

32. Historical analogy method of forecasting
An approach to sales forecasting in which the past sales results of a similar
product are used to predict the likely sales of a similar new product.
Historical analogy method mainly forecasts the demand for a new product, it
may be accurate and cheap. It bases on forecasts and past data of any similar or
relevant existing products, then according to the product situations to develop a
best fit forecast.
For examples, forecasting the demand of iPhone 6 phone cover, can base on the
sales of iPhone 6, forecasting the demand of iPhone 6 will base on the sales of
iPhone 5; or to forecasting the demand of an new type of camera film can base
on the sales of the company’s latest camera.
The weakness of this is that it relies on analogy being correct, and there is no
guarantee that the new product demand will match.

42. Factors Influencing Facility Location
If the organization can configure the right location for the manufacturing facility, it will have sufficient access to the
customers, workers, transportation, etc. For commercial success, and competitive advantage following are the critical
factors:
 Customer Proximity: Facility locations are selected closer to the customer as to reduce transportation cost and
decrease time in reaching the customer.
 Business Area: Presence of other similar manufacturing units around makes business area conducive for facility
establishment.
 Availability of Skill Labor: Education, experience and skill of available labor are another important, which determines
facility location.
 Free Trade Zone/Agreement: Free-trade zones promote the establishment of manufacturing facility by providing
incentives in custom duties and levies. On another hand free trade agreement is among countries providing an
incentive to establish business, in particular, country.
 Suppliers: Continuous and quality supply of the raw materials is another critical factor in determining the location of
manufacturing facility.
 Environmental Policy: In current globalized world pollution, control is very important, therefore understanding of
environmental policy for the facility location is another critical factor.

45. ALFRED WEBER’S THEORY OF THE LOCATION OF INDUSTRIES
Alfred Weber (1868–1958), with the publication of Theory of the
Location of Industries in 1909, put forth the first developed general
theory of industrial location. His model took into account several spatial
factors for finding the optimal location and minimal cost for
manufacturing plants.
The point for locating an industry that minimizes costs of transportation
and labor requires analysis of three factors:
The point of optimal transportation based on the costs of distance to
the ‘material index’ the ratio of weight to intermediate products (raw
materials) to finished product.
The labor distortion, in which more favorable sources of lower cost of
labor may justify greater transport distances.
Agglomeration and degglomerating.

46. Agglomeration or concentration occurs when there is sufficient demand
for support services for the company and labor force, including new
investments in schools and hospitals. Also supporting companies, such as
facilities that build and service machines and financial services, prefer
closer contact with their customers.
Degglommeration occurs when companies and services leave because of
over concentration of industries or of the wrong types of industries, or
shortages of labor, capital, affordable land, etc. Weber also examined
factors leading to the diversification of an industry in the horizontal
relations between processes within the plant.
The issue of industry location is increasingly relevant to today’s global
markets and trans- national corporations. Focusing only on the mechanics
of the Weberian model could justify greater transport distances for cheap
labor and unexploited raw materials. When resources are exhausted or
workers revolt, industries move to different countries.

58. Capacity planning
• Capacity planning is the process of determining the production capacity
needed by an organization to meet changing demands for its products.
• Example
• On an assembly line in a car factory, for example, a painting robot might
be able to paint 10,000 cars in a day. Considering this type of capacity is
also important for workforce capacity planning.
• The four steps for capacity planning are:
• Understand current capacity.
• Project future demand.
• Identify where additional capacity could come from.
• Assess your risks.