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Forecasting
1.
2. Acknowledgement
We the members of group no . 1 would like
to thank our “Production Management And
Material Management” Prof . Sadaf Shaikh
for giving us such wonderful topic
“Forecasting” For presentation and guidance
to complete project which helped us a lot
gain more knowledge through this project ,
3. Group Members
Prachi Lad
Satya Jaiswal
Shruti Kajrolkar
Sumit Mehta
Vinay Mehta
Chiranjivi Palita
5. Introduction
Definition:
“The use of historic data to determine the
direction of future trends.”
"Prediction is very difficult, especially if it's
about the future."
By Nils Bohr
6. Features of Forecasting
Forecasting in concerned with future
events,
It shows the probability of happening
of future events,
It analysis past and present data,
It uses statistical tools and techniques,
It uses personal observations,
7. Forecasting Methods
Forecasting
Qualitative
Or
Judgmental
Quantitative
Or
Statistical
Projective Causal
8. Qualitative Method
Qualitative forecasting techniques are
subjective, based on the opinion and
judgment of consumers, experts.
10. Delphi method
Delphi method employs a panel of experts in
arriving at the forecast & proceeds through a series
of rounds.
11. Advantages
Large number of participation
Focuses on ideas
Anonymity for participant
Identification of priorities
12. Limitations
Time consuming
Complexity
Enthusiasm of participant
Problem to keep statement value-free
13.
Staff
(Administering
survey)
Decision Makers
(Evaluate responses and
make decisions)
Respondents
(People who can make valuable
judgments)
14. Market Research
A systematic approach to determine external
consumer interest in a service or product by creating
and testing hypotheses through data-gathering
surveys
15.
Characteristics :- Use surveys & interviews to
identify customer preferences
Strength :- good determinant of customer
preferences
Weakness :- It can be difficult to develop a good
questionnaire
16. Product Life cycle
analogy
the stages shows that products go
through from development to
withdrawal from the market
Based on the experiences of similar
product in the past, one can make
decision
18. Product Life Cycles
Sales
Development Introduction Growth Maturity Saturation Decline
Time
19.
Stages of the Expanded Product Life Cycle
1. Research and development
2. Product introduction
3. Development of the market
4. Exploitation
5. Market maturation
6. Market saturation
7. Market decline
20. stages No. of
competitor
s
Market
growth (%)
Profit Market
size
investment
R & D Unknown 0 0 0 Growing
Product
Few Highest 0 Small High
introduction
development Growing
fast
High Low Small High
Exploitation Moderate
growth
Good Growing Modest High
maturity Stable Low High Largest Stable
saturation Stable None Lowering Stable Decline
decline Reducing Negative High &
low
Declining Stopped
22. Expert judgment
Gather a group of experts together,
Describe overall program in enough detail so experts can provide an
estimate.
Each member of the expert group then does an independent of the
resources needed.
Estimates are gathered anonymously and compared,
If there exists significant divergence among the estimates, the estimates
will be returned to the expert group,
The expert group then discusses the estimates and the divergence and
works to resolve differences, and
The expert group once again submits anonymous, independent estimates
which continues until a stable estimate results.
27. Cross Impact Analysis
Methodology developed by Theodore Gordon and
Olaf Helmer in 1966
To help determine how relationships between events
would impact resulting events and reduce
uncertainty in the future
First format of the method was a card game titled
‘Future’
28. Use of Cross Impact
Analysis
1960s
Central
Intelligence
Agency (CIA)
Mid-1970s
Futurists
By 2006
Businesses as
well as
intelligence
analysts
29. Futures Forecasting Steps
1st •consider the number and type of events
2nd •take the initial probability of each event
3rd •generate conditional probabilities
4th •test their initial conditional probabilities
5th •run the analysis to determine future scenarios
30.
31. Applications
Researchers can use Cross Impact Analysis for a
wide variety of applications-
Futurists have already used the methodology for
forecasting events in specific industries, politics,
markets, and even entire communities
In intelligence analysis, analysts can use the method to
predict events, conditions, or decisions based on a
wide variety of variables and conditions at local,
national, and international levels
32. Scenario analysis
Scenarios focus on the joint effect of many factors
When you explore the factors together, you realize
that certain combinations could magnify each other’s
impact or likelihood
Numerous organizations have applied scenario
planning to a broad range of issues, from relatively
simple, tactical decisions to the complex process of
strategic planning and vision building
33. Scenario forecasting
process
1st • Decide drivers for change/assumptions
2nd •Bring drivers together into a viable framework
3rd •Produce 7-9 initial mini-scenarios
4th •Reduce to 2-3 scenarios
5th •Draft the scenarios
6th •Identify the issues arising
34. Use of scenario planning
by managers
In terms of the overall application by forecasting,
they can be divided into three main groups of
activities
Environmental analysis
Scenario planning
Corporate strategy
The central part represents the specific techniques-which
differentiate the scenario forecasting process
from the others in long-range planning
35.
36. Decision tree
A decision tree is a decision support tool that uses a tree-like
graph or model of decisions and their possible
consequences, including chance event outcomes, resource
costs, and utility
A decision tree consists of 3 types of
nodes:
Decision nodes - commonly represented by
squares
Chance nodes - represented by circles
End nodes - represented by triangles
37. Influence diagram
A decision tree can be represented more compactly
as an influence diagram, focusing attention on the
issues and relationships between events
38. Combining Forecasts
Combination of Delphi and Cross Impact Analysis
Usually, analysts consider the average prediction or
scenario as the most likely to occur
The two are so closely related, that analysts often use
the two techniques in combination or as part of a
larger methodology
39.
Combination of Delphi and scenarios
Scenario planning concerns planning based on the
systematic examination of the future by picturing
plausible and consistent images
Delphi, in turn, attempts to develop systematically
expert opinion consensus concerning future
developments and events
The output of the different phases of the Delphi method
can be used as input for the scenario method and vice
versa
40. Advantages
A combination makes a realization of the benefits of
both tools possible
In practice, usually one of the two tools is considered
the dominant methodology and the other one is
integrated at some stage
41. Models of pricing
Cost- plus pricing
Creaming or skimming
Premium pricing
Dynamic pricing
42.
Value to the customers
Advanced tools
Product’s life-time durability
43.
Cost is fact ;
Price is policy;
Value is concept
