construction project initiation and feasibility study part...
TRANSCRIPT
Project and Construction Management
Lecture #2
Construction Project Initiation and Feasibility Study
Part 1: Introduction and Market Assessment
Department of Civil Engineering, Sharif University of Technology
By: Dr. Amin Alvanchi and Dr. Hamed Kashani
Construction Engineering and Management
Outline
Introduction to Initiation Phase
An Overview of Feasibility Study
Feasibility Study: Market assessment
Identify the actual need and product specification
Identify target market
Collecting supply and demand information
Forecasting the market
2
3
Introduction to Initiation Phase
4
Construction project lifecycle
Initiation
Organization and planning
Design
Construction
Operation
Maintenance
Demolition
Construction
Project
Lifecycle
Project initiation phase or فاز آغازین
The Project Initiation Phase is the 1st phase of the Construction
Projects lifecycle, as it involves starting up a new project.
Construction project initiation phase is the most crucial phase in
the project lifecycle, as it's the phase in which project scope (=
main characteristics) and project boundaries are defined.
In project initiation phase we are framing the project.
Many failures in projects happen because project is not properly
initiated and defined!
5
Project initiation phase
Project initiation phase is also called pre-planning phase!
Most projects stop at this phase!!!!! Why?
In this phase the project’s high level objectives, scope, purpose and
deliverables (or outputs) are defined. Main steps to be followed are:
6
Why this project? شناسایی نیاز به اجرای پروژه
Project Feasibility Studies انجام مطالعات امکان سنجی پروژه
Project Charter منشور پروژه
7
Before formally continuing different steps of the project we
need to informally justify the original need for the project!
Questions to be answered at this step:
What are the main incentives/ purpose of the project
idea?
Who or what groups are the project’s main clients?
How this project is going to benefit project clients?
What are the main requirements/ characteristics?
What are the main assumptions and limitations?
Initiation: Why this project?
8
A simple examples: Chitgar lake project.
What are the main incentives/ purpose of the project idea?
To bring a new type of attraction to the Capital.
Who or what groups are at the main focus (main project customers)?
Tehran citizens.
How this project is going to benefit project clients?
Spend their leisure time in the park and close the lake, do water activities and
enjoy the new view for the city.
What are the main requirements/ characteristics?
Be easily accessible, have a certain capacity to accommodate visitors, has a
sustainable source of water, water quality should follow a certain standard.
What are the main assumptions and limitations?
Is limited between Tehran-Karaj and Hemat high ways, it is funded by Iranian
financial institutes, it is going to be constructed by Iranian construction
companies.
Initiation: Why this project?
9
Why “Imam Khomeini airport metro” project is built?
Your are encouraged to discuss your ideas with your
classmates!
In-class practice
10
Sample answers:
Main incentives: bringing prosperity to Imam Khomeini airport, reducing
traveling cost and time for passengers and airport staff
Main customers: passengers and airport staff living in Tehran and
neighboring areas
How does it work: Passengers and airport staff can get to any metro
station in Tehran’s metro network and can go to the airport by change
one or two lines
Main requirement: To have luggage friendly cabins and stations, to
have reasonable travelling time and sequence, to easily get connected
with other metro routes, easily linkable to city center and main hotels
Main assumptions and limitations: Ticket price should be cheap
compared to cabs and shuttle buses, should have 24 hours services.
In-class practice
11
When we could (informally) convince ourselves that this
project is needed we then need to formally justify the
project’s feasibility by conducting a project feasibility study
Significance of project necessities and needs identified at
this step is the key factor to persuade project owners to go
to the next step.
Needs identified at this step are going to get more detailed
at the feasibility study step.
Initiation: Why this project?
12
Before start undertaking a project we need to make sure that the
project is feasible and justified!
A feasibility study (FS) is a structured assessment of the usefulness
and practicality of a proposed project. It aims to objectively and
rationally uncover the strengths and weaknesses of a proposed
project.
An FS evaluates the project's potential for success over its lifecycle!
FS report is an important document, it draws a big picture of the
project from the beginning to the end.
FS is the most elaborated step in the initiation phase, our main focus
on the rest of this lecture is on different aspects of feasibility study.
Initiation: Feasibility study
13
When FS confirms a project’s feasibility, the project is formally initiated
by preparing a project charter document.
A project charter outlines high level scope and requirements of a
project as identified and investigated at prior steps, i.e., feasibility
studies. Project charter usually includes:
High level project description, purpose and justification,
High level project outputs and deliverables,
Measurable project objectives and related success criteria,
High-level requirements,
High-level risks,
Main milestone schedule,
Summary budget,
Initiation: Project charter
14
Initiation: Project charter
High level scope and requirements outlined in a project
charter is an important base for the planning the project at
the next phase!
Sample project charter 1, 2 & 3.
Project manager is usually introduced in the project charter.
To formally initiate a project owners usually sign the project
charter and announce it to the project manger.
15
Initiation: In brief
Project initiation is the first phase of a project
We cannot expect a successful project if its initiation phase is not
properly done.
Among different steps in initiation phase FS stays at the core. It has
more details and requires more attention to be followed!
Results from FS determines the decision for continuing or discontinuing
our efforts for doing the project.
We are going to discuss more about different aspects of FS in next few
sessions!!
16
An Overview of Feasibility Study
17
Depending on the type, requirements and limitations of a project,
feasibility studies might analyze different aspects of projects such
as market, technical aspect, financial aspect, environmental
aspect, social aspect, cultural aspect and security aspect.
Most feasibility studies at least assess market, technical, and
financial standing of projects.
Depending on the complexity and size of a project, level of details
in feasibility studies varies.
Conceptual design and master plan are usually two main outputs
expected from a complete feasibility study.
Sample feasibility study reports 1, 2, 3 & 4.
Feasibility study
18
Feasibility study Versus Prefeasibility study
In some cases and to avoid spending much money on running a full-
fledged feasibility study and to determine whether it is worthwhile to
proceed with a complete feasibility study we might decide to conduct a
prefeasibility study first.
A prefeasibility study follows similar steps as feasibility study but
compared to a feasibility study it is done in less details.
In prefeasibility study we depend more on general information available
in the literature for the project rather than digging into specific and
realistic project information which is required for a feasibility study.
Initiation: Feasibility study
19
Feasibility study Versus Prefeasibility study, Examples:
Prefeasibility: Use technical information of project facilities from
technical handbooks
Feasibility: Get technical information of project facilities form facility
suppliers
Prefeasibility: Consider an average cost of the land in the area
Feasibility: Get an expert to evaluate the project’s land price!
Prefeasibility: Use an average cost of materials
Feasibility: Get invoices for the cost of materials to be delivered to the
project’s location!
Sample prefeasibility study reports 1, 2, & 3.
Initiation: Feasibility study
Initiation: Feasibility study
Stages:
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Feasibility
Study
1. How is supply and demand for the project’s
product?
(Market Assessment)
2. What is the project’s specification and how
should it be built?
(Technical Assessment)
3. Is the project cost effective?
(Financial Assessment)
4. Should we build or not to build the project?
(Conclusion)
Don’t proceed to the next step if project fails in feasibility study!
21
Feasibility Study:
Stage 1. Market assessment
Initiation
Organization and planning
Design
Construction
Operation
Maintenance
Demolition
Construction
Project
Lifecycle
Market assessment: steps22
Where are we standing?
Why this project?
Project Feasibility
Studies
Project Charter
1. Market assessment
2. Technical assessment
3. Financial assessment
4. Conclusion
2.Identify the target market
3.Collect supply and
demand information
4.Use the information
collected for forecasting the
market
1.Identify the original need
and product spec
Init
iati
on
Initiation
Organization and planning
Design
Construction
Operation
Maintenance
Demolition
Construction
Project
Lifecycle
Market assessment: steps23
2.Identify the target market
3.Collect supply and demand
information
4.Use the information collected
for forecasting the market
1.Identify the original need and
product specification
24
Stage 1. Market assessment
Step 1. Identify the original need and product
specification
Identify the original need
The original need or purpose urging us to define and implement
a project should be first well recognized.
We are often biased on conventional or usual methods for
fulfilling our needs; however, it might not be the case.
Example:
Wrong expression: We need to build an overpass for this
intersection.
Right expression: We need to reduce this intersection’s traffic load!
There are many other methods to be used for reducing the traffic,
e.g., under-pass, better managed traffic light, smart traffic light and
blocking a straight flow for one direction.
25
Identify the original need
What might be original need and main incentives for following projects?
To build a new school,
Sample answers:
We are short in school capacity in the area, quality of training is
decreased!
Student in the neighbourhood need to travel a long distance to go
to school in another neighbourhood’s school, …
To build a new hospital,
Sample answers:
We are short in hospital capacity in the area, quality of medical
care is very low in the current hospital because of the high load!
The closest hospital takes more than an hour from this
neighbourhood, …
26
Determine objective specification
Do your best to set objective (or measurable) specification for the
expected project’s product! We can then do our best to fulfill the product
specification when implementing the project!
Example 1:
We need to reduce the intersection’s traffic load?
We built an overpass.
As a result the traffic is reduced.
SO: Have we met our purpose of the project! Am I right?
Before answering the question we need to know how much traffic reduction
we needed and then check if this reduction has been reached!
Possible answer can be: Average rush hour speed (17:00 to 19:00)
increases from 10km/h to 20 km/h! Have we reached this reduction?
27
Determine objective specification
Example 2:
There is a need for a new leisure facilities to be built in the
neighbourhood because of the increasing population in the area
and lack of a leisure facility in the area.
Before we proceed to the next step we need to more accurately
specify the project’s specification:
What group of people? Families, youths, singles, seniors, middle
ages, men, women
What kind of leisure activities: sport, cultural, scientific, social, etc.
What kind of sport activities: football, pool, horse riding,
volleyball, basketball, etc.
28
In class practice
Place yourself as the owner of the following projects.
1) In your perspective what has been the original need for
each project?
2) What can be the objective specification of the project
products?
Building metro lines in Tehran
Constructing Tehran-Shomal highway
29
In class practice
Building metro lines in Tehran
Sample Answers:
Original need: More convenience for the city travellers and better
quality public transportation, traffic reduction, less air pollution, less
fuel consumption
Objective specification:
Reduce public transportation travel time by 30%
Encourage people to use 20% less car driving
Increase average car speeds during the rush hours by 10%
Reduce average annual air pollution by 20%
30
In class practice
Constructing Tehran-Shomal highway
Sample Answers:
Original need: Reducing traffic and travelling time, reducing
number of accidents and hazards on the road, better economy for
the northern cities
Objective specification:
Reducing travel time to average of 2 hours during high traffic and
holiday seasons
Reducing number of accidents on the road by 80%
Improving economic situation of the northern cities by 10%
31
Determine objective specification
A main success criteria after project implementation is whether
project could properly deliver product specifications:
Examples:
Has new overpass increased rush hour traffic speed from
10km/h To 20km/h?
Does new leisure facility have football, pool, basketball and
volleyball court?
Has the new school reduced average students daily
commute from one hour to 15 minutes?
32
33
Stage 1. Market assessment
Step 2. Identify target market
Identify target market
Where does the demand originate from? And Where is the target
market?
A country wide: e.g., a new refinery project
A province or a region: e.g., a new dam project
A city or neighbourhood: e.g., a new highway in the city
Foreign countries: e.g., a new petrochemical complex project
A specific foreign country: e.g., Iran-Pakistan gas pipeline project
34
Identify the target market
Questions:
Who are the target of the Pardis suburb’s Mehr residential building project?
People of Pardis, Rood-e-hen, and Boom-e-hen? Low income Tehran
citizens?
Who are the target of Milad tower project?
Tehran’s public? Tehran’s rich citizens? Foreign tourists? Tehran’s north-
west neighbours?
Who are the target of Niayesh tunnel project?
Tehran’s north-east population working at west? Tehran’s north-west
population working at east?
Who are the target of Setareh Khalij-e Fars refinery project?
Southern cities cars? Tehran and other main cities cars? Southern cities to
be developed? Export?
35
Identify target market
There are not always simple answers to these questions? Specially in the absence of
dependable databases! Sometimes we need to directly gather field information (e.g.,
distributing questionnaires, doing call survey, online survey, etc.)
Example: To be able to determine target demand Niayesh tunnel project, city might
need to design a survey to collect related information of the cars using alternative
highways, e.g., Hemmat, Resalaat, Chamran and Modarresset. A possible answer
can be:
40% people living in north-east and work in west
35% people living in north-west and work in east
10% people from all over the city passing occasionally
5% people living in suburb on the east (e.g., Pardis, Roode-hen, Boome-hen, and
Davand) working in west of tehran
5% people living in Karaj and work in the east of Tehran
5% variety of different clients.
36
37
Stage 1. Market assessment
Step 3. Collecting supply-demand information
Market elements
A project need is calculated based on two main market elements:
Supply and Demand
A construction project need is created when Demand for the output (product or
service) of a project exceeds its supply: Net need = Demand - Supply
So, for evaluating the actual need we should quantify supply and demand.
In most cases quantification of supply is easier than quantification of demand:
For Supply we have:
Quantification of supply = Measuring capacity of completed and in progress
projects
For Demand we have:
Hidden demands.
Example: Currently I avoid some intra-city travels because of traffic => I will
start my travels (or add to the travel demand) if traffic is reduced!
38
Market elements
Competing alternatives to respond demands.
Example: Economic condition enhancement may shift travel demands to
flight and reduce interest in railway travelling! New railway project might fail
as a result of economic changes!
Demand origins are often more distributed compared to the supply.
Example: Every single household within the city demands for electricity. But
how many power plants do we have to supply the city’s demand?
Demands are dynamically changing.
Example: Past research studies indicate that construction of new streets and
highways within cities (in a recursive manner) has increased the driving
demand of the city:
High traffic -> New street/ highway construction -> Traffic reduction
-> More satisfaction -> More interest in using cars -> High traffic
Other factors such as market strategies, price, cultural change, technological
change, etc. can play a role in shaping demands.
39
How to collect supply information
What is the current supply/ serving capacity?
What is the capacity of in-progress projects?
What is the capacity of to be started projects?
A residential building?
Example: Suppose a 300 unit residential building complex project. To estimate
supply or serving capacity of residential buildings in the target
neighbourhoods we need to collect number and type of houses (i.e., one
bedroom, two bedroom, etc) as well as the population of the target
neighbourhoods. We also need to collect the information from in-progress
residential projects as well as projects are about to be started!
Question: Which government body is the source of information here?
Question: If you are going to build a four storey building with 8 unit residential
building how are you going to approach estimation of supply/ serving
capacity?
40
How to collect supply information
A commercial building?
Example: Suppose a new 500-store mall project. For the supply estimation we
need to collect information of competing malls and stores as well as in
progress and to be built projects in the target neighbourhoods. In this project
we need to collect supply information based on the type of different retail
stores.
An infrastructure project?
Example: Suppose an intra-city highway project. For the supply estimation we
need to first identify different alternative routes including streets highways and
metro and their capacities. Any other in-progress or to be built alternative
route also should also be considered.
41
How to collect supply information
An industrial project?
Industrial projects have more dynamic supply market compared to other
types of construction projects because of portable nature of the project’s
product. In many cases any shortage in supply or serving capacity of the
product can be responded through product imports. So, tracing changes
in supply capacity of foreign suppliers also might be required.
New customs regulations and laws also can change the supply/ serving
capacity. In cases that target markets are foreign countries, tracing
regulation changes in the target market is more difficult and politically
affected
Question: Who is the source of this information?
42
Common sources of data collection
There are different public sources of information which help us to collect
supply (and demand) information:
- Portal of Iran National Census Center (مرکز آمار ایران)
(http://www.amar.org.ir/) is useful source of data which can be used in
many cases.
- Portal of Ministry of Industry, Mine and Trade is another source of
information (http://www.mimt.gov.ir/) for industrial construction projects.
-Portal of Ministry of Roads and Urban Development
(http://www.mrud.ir/Portal/Home/) for building and road information.
- Portal of Iran Customs Administration
(http://www.irica.gov.ir/Portal/Home/) is another source of information for
import and export stats!
43
Quantify the need44
Quantify the need45
Quantify the need46
Quantify the need47
Quantify the need48
Quantify the need49
Quantify the need50
Quantify the need51
Quantify the need52
Quantify the need53
Common sources of data collection
Although major parts of information are provided online, direct
connection to the related departments of organization in charge
is very useful and can result in getting more detailed
information!
54
How to collect demand information
Despite all complexity involved in estimation of market demand, we need
to find a way to collect data and estimate it!!!
Depending on the nature of a project and availability of related data,
different methods might be used for collecting the market demand.
Direct data collection:
In this method of data collection we directly count number expected
project’s clients. For example in road, bridge and tunnel construction
projects by directly counting number of cars travelling in alternative
routes we can estimate demand for the project. There are different
automated car counting systems developed for this purpose.
55
How to collect demand information56
How to collect demand information
Use of historical data:
In this method of data collection data published by regulating bodies (as listed
before) are used.
Example: For collecting fuel demand we can get past fuel consumption from
Energy Ministry as:
57
Year 1384 1385 1386 1387 1388 1389 1390 1391
Consumption (M m3) 24.27 26.87 24.17 24.50 23.62 22.37 21.88 23.24
How to collect demand information
Demand calculation by using norms and related data:
In this method of data collection data published by regulating bodies (as listed
before) are used.
Example 1: Suppose Mehr residential suburb in Pardis is going to accommodate
250,000 population and average electricity power supply required for every
person during peak hours according to in the country Energy Ministry is 500 w,
total power demand for the suburb is going to be:
250,000 x 500 w = 125 Mega W
Example 2: Suppose Mehr residential suburb in Pardis is going to accommodate
250,000 population. Our population structure shows that primary school students
are 8% and high school students contribute 8% of the total population. So we
have: 250,000 x 8% = 20000
with the normal capacity of 250 students for each school, there is a demand for
80 primary and 80 high school in Pardis-Mehr-suburb
58
How to collect demand information
Use of supply data:
This method specially can be used for projects with importable/ exportable
products (e.g., steel, cement, fuel, cord, etc.). In general we have:
Local Supply + Foreign Imports = Local Consumption+ Foreign exports
So we can calculate Local Consumption (≈ local demand) as:
Local Consumption = Local Supply + Foreign Imports - Foreign exports
So, by collecting Local Supply, Foreign Imports and Foreign exports we can
calculate the local demand.
Import>Export => Lack of local supply => There local needs which is
not responded by local supply
Export>Import => Local supply surplus => Export opportunity
59
How to collect demand information
Example: Table below presents cement local consumption calculated
based on historical production, import and export data collected from
government online portals:
60
Year Production (M Ton)* Export (M Ton)** Import (M Ton)** Consumption (M Ton)
A B C = A+C-B
1385 35.31 0.49 0 34.82
1386 39.97 0.3 0 39.67
1387 44.39 0.38 0 44.01
1388 52.14 4.1 0 48.04
1389 61.62 6.5 0 55.12
1390 66.46 7.9 0 58.56
1391 70.26 11.30 0 58.96
*
**
From Minstry of Industry, Mine and Trade
From Iran Customes Administration
61
Stage 1. Market assessment
Step 4. Forecasting the Need
Why forecasting?
In many cases market information collected represent supply and
demand information in the past or (if we are lucky) for the current
market situation. But, we need to evaluate the project needs by the time
project gets complete and thereafter.
The forecasting is done fort the time of project completion and during
the project’s operation!
Remember: Forecasts are usually wrong!!!
We are trying to not to be too wrong.
A forecast is considered more accurate if it also includes a range (high and low) and a confidence level
Accuracy fades when we go further in the time
62
Why forecasting?
Remember: Never replace historical data with forecasts!
Example: Cement demand
63
Year Production (M Ton)* Export (M Ton)** Import (M Ton)** Consumption (M Ton)
A B C = A+C-B
1385 35.31 0.49 0 34.82
1386 39.97 0.3 0 39.67
1387 44.39 0.38 0 44.01
1388 52.14 4.1 0 48.04
1389 61.62 6.5 0 55.12
1390 66.46 7.9 0 58.56
1391 70.26 11.3 0 58.96
1392 ? ? ? ?
1393 ? ? ? ?
1394 ? ? ? ?
1395 ? ? ? ?
... ? ? ? ?
Forecasting methods
Quantitative forecasting methods
In the presence of dependable past data quantitative methods are
used by manipulating past data using different time series methods.
Some prevalent methods are: Moving Averages, Weighted Moving
Averages, Regression, and Seasonal Series
Qualitative forecasting methods
It is usually done in the absence of dependable past data and is
dependent on a specific market experts judgements.
Some prevalent methods are: Delphi, Scenario Writing and
brainstorming.
64
Forecasting methods
Discussion: While Quantitative forecasting methods relate the
forecasted values with the trend of past records, they are missing
recent change of market’s effective factors. The main advantage
of Qualitative forecasting methods is to account for changes in the
market; however, they are inaccurate when it comes to,
mathematically, drawing future trends.
In the presence of past data and when there is no significant
change in market players, use quantitative methods.
In the absence of past data and highly fluctuating market with
changes made to the market players, use qualitative methods.
65
Quantitative forecasting methods66
Identify data pattern:
At the beginning of the quantitative forecasting plot data (or time series) you
collected on a scattered diagram to see type of trend data has.
In MS Excel scattered diagrams can be drawn by using scattered diagram
feature.
67
Identify data pattern: Prevalent data (or time series) patterns
Quantitative forecasting methods
68
Moving average:
This method is a good candid method for non recognizable (or stationary)
patterns. For forecasting demand for time t (Dt) average last n data items:
Dt = (Dt-1 + Dt-2 + ... + Dt-n) / n
Example:
Forecasted values converge to a value after a while.
88 89 90 91 92 93 94 95 96 97
D 5.0 3.0 12.0 7.0 6.0 7.0 8.0 7.0 7.0 7.3
n=4
Data Forecast
0
4
8
12
16
0 2 4 6
Quantitative forecasting methods
69
Weighted moving average:
It is a similar method to moving average, just more weight is given to more
recent data items.
Dt = (a Dt-1 + b Dt-2 + ... + z Dt-n) / (a + b + … +z)
Having: a > b > … > z
Example:
D93 = (5 * 6 + 3 * 7 + 2 * 12 + 1 * 3) / 11 = 7.1
Again in this method forecasted values converge to a value after a while.
88 89 90 91 92 93 94 95 96 97
D 5.0 3.0 12.0 7.0 6.0 7.1 7.2 6.9 7.0 7.0
n=4
a=5 b=3 c=2 d=1
Data Forecast
Quantitative forecasting methods
70
Regression:
In regression method we relate demand values over time (Dt) to a linear function
of time (t):
Dt = a + b t + t.
It is a suitable method in cases we a see a linear trend in our data.
Regression methods have extensive
theoretical background which are
discussed in detail in many statistical
books.
Thanks to computer programs (e.g.,
M.S. Excel) which have made it easy
use without entering into its complexity.
Quantitative forecasting methods
Regression:
Initialize data analysis and regression add-in in MS Excel:
71
Quantitative forecasting methods
72
Regression:
Initialize data analysis and regression add-in in MS Excel:
Quantitative forecasting methods
73
Regression:
Initialize data analysis and regression add-in in MS Excel:
Quantitative forecasting methods
74
Regression:
Example:
Year Demand1 Demand2
88 5.0 5.0
89 3.0 5.5
90 12.0 6.3
91 7.0 7.0
92 6.0 8.9
Quantitative forecasting methods
75
Regression:
Example:
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.282216261
R Square 0.079646018
Adjusted R Square -0.227138643
Standard Error 3.723797345
Observations 5
ANOVA
df SS MS F Significance F
Regression 1 3.6 3.6 0.259615385 0.645499621
Residual 3 41.6 13.86666667
Total 4 45.2
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -47.4 105.9942137 -0.447194223 0.685050159 -384.7208937 289.9208937 -384.7208937 289.9208937
X Variable 1 0.6 1.177568116 0.509524665 0.645499621 -3.147547298 4.347547298 -3.147547298 4.347547298
For Demand 1
Quantitative forecasting methods
76
Regression:
Example:
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.964780125
R Square 0.930800689
Adjusted R Square 0.907734252
Standard Error 0.462961481
Observations 5
ANOVA
df SS MS F Significance F
Regression 1 8.649 8.649 40.35303266 0.007892377
Residual 3 0.643 0.214333333
Total 4 9.292
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -77.16 13.17774133 -5.855328166 0.009931067 -119.0974542 -35.22254578 -119.0974542 -35.22254578
X Variable 1 0.93 0.146401275 6.352403691 0.007892377 0.464085803 1.395914197 0.464085803 1.395914197
= -77.16 + 0.93 * Year 9.33
Year 93
For Demand 2
Quantitative forecasting methods
After class practice
Forecast demand 1 and demand 2 up to year 1403 using
the proper technique (between weighted moving average
and regression) using MS Excel (send the result to the TA
before midnight):
77
Year Demand1 Demand2
91 4.0 6.0
92 12.0 6.3
93 7.0 8.0
94 6.0 8.9
95 8.0 9.3
96 9.0 10.0
78
Seasonal Series:
Seasonality corresponds to a pattern in the data that repeats at regular intervals.
Forecasting seasonal series with central moving average or CMA method:
1) Calculate data item factors:
Suppose i=1, 2, 3, …, n represents number of periods or cycles and j = 1, 2, 3,
…, N represents number of seasons within every period. Dij represents demand
of season j in period i.
Calculate the sample mean or average of total Demand or Dav = (S S Dij) / (n.N)
Quantitative forecasting methods
i=1 i=2 i = 3 = n
j=1
j=2
j=3j=4
j=5=N
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Forecasting seasonal series with CMA method (cont’d):
Calculate data item factors by dividing data items by sample mean: Fij = Dij / Dav
2) Remove seasonal effects or normalize the items:
Calculate seasonal factor or seasonal average for every season of j or
Savj = S Fij / n , for every j= 1, 2, …, N
To remove effect of seasonal factor for every single data item (or normalizing the
data), divide every data item by its related seasonal average as:
Nij = Fij / Savj
3) Predict normalized values using a prediction method:
Now that seasonal effect has been removed from data, use a proper method for
predicting normalized values.
4) Return values to their seasonal pattern:
Once forecast is made convert values to their seasonal form by multiplying each
forecasted item to the sample mean of Dav and its related seasonal factor of Savj.
See example on Excel file!!
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Forecasting seasonal series with CMA method-Example:
Year Demand
90-S1 15.0
90-S2 14.0
90-S3 10.0
90-S4 13.0
91-S1 16.5
91-S2 14.5
91-S3 10.6
91-S4 14.6
92-S1 17.6
92-S2 16.1
92-S3 11.4
92-S4 15.7
93-S1 20.1
93-S2 17.5
93-S3 12.3
93-S4 16.4
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Forecasting seasonal series with CMA method-Example (cont’d):
Demand Factors
Dij Fij=Dij/Dav
90-S1 1 1 15.0 14.7 1.02 1.2 0.868 1
90-S2 1 2 14.0 0.95 1.1 0.902 2
90-S3 1 3 10.0 0.68 0.8 0.902 3
90-S4 1 4 13.0 0.88 1.0 0.871 4
91-S1 2 1 16.5 1.12 0.953 5
91-S2 2 2 14.5 0.99 0.935 6
91-S3 2 3 10.6 0.72 0.960 7
91-S4 2 4 14.6 0.99 0.979 8
92-S1 3 1 17.6 1.19 1.016 9
92-S2 3 2 16.1 1.10 1.038 10
92-S3 3 3 11.4 0.77 1.026 11
92-S4 3 4 15.7 1.07 1.052 12
93-S1 4 1 20.1 1.37 1.163 13
93-S2 4 2 17.5 1.19 1.126 14
93-S3 4 3 12.3 0.84 1.112 15
93-S4 4 4 16.4 1.11 1.098 16
YearDav=
Avg(Dij)
Savj=
Avgj(Fij)
i:
period
j:
season
Nij=
Fij/Savj
Normalized
Period
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Forecasting seasonal series with CMA method-Example (cont’d):
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Forecasting seasonal series with CMA method-Example (cont’d):
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.949318257
R Square 0.901205153
Adjusted R Square 0.894148379
Standard Error 0.03043512
Observations 16
ANOVA
df SS MS F Significance F
Regression 1 0.118295287 0.118295287 127.7077963 2.01337E-08
Residual 14 0.012968151 0.000926297
Total 15 0.131263438
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 0.841451117 0.015960311 52.72147221 1.66678E-17 0.807219653 0.87568258 0.807219653 0.87568258
X Variable 1 0.01865281 0.001650576 11.30078742 2.01337E-08 0.015112676 0.022192943 0.015112676 0.022192943
= 0.841451 + 0.018653 * Year 1.158548883
Year 17
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Demand Factors
Dij Fij=Dij/Dav
90-S1 1 1 15.0 14.7 1.0 1.2 0.868 1 Use Reg Multiply by
90-S2 1 2 14.0 1.0 1.1 0.902 2 Formula Savj and Dav
90-S3 1 3 10.0 0.7 0.8 0.902 3 Intercept
90-S4 1 4 13.0 0.9 1.0 0.871 4 0.8414511
91-S1 2 1 16.5 1.1 0.953 5 X Variable 1
91-S2 2 2 14.5 1.0 0.935 6 0.0186528
91-S3 2 3 10.6 0.7 0.960 7
91-S4 2 4 14.6 1.0 0.979 8
92-S1 3 1 17.6 1.2 1.016 9
92-S2 3 2 16.1 1.1 1.038 10
92-S3 3 3 11.4 0.8 1.026 11
92-S4 3 4 15.7 1.1 1.052 12
93-S1 4 1 20.1 1.4 1.163 13
93-S2 4 2 17.5 1.2 1.126 14
93-S3 4 3 12.3 0.8 1.112 15
93-S4 4 4 16.4 1.1 1.098 16
94-S1 ? 17 1.159 20.0
94-S2 ? 18 1.177 18.3
94-S3 ? 19 1.196 13.3
94-S4 ? 20 1.215 18.1
Nij-
Predicted
Dij-P=
Nij-P*Dav*SavjYear
Dav=
Avg(Dij)
Savj=
Avgj(Fij)
i:
period
j:
season
Nij=
Fij/Savj
Normalized
Period
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M.S. Excel Forecasting:
In reality time series may follow a variety of trends:
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M.S. Excel Forecasting:
Mathematical formulas have been developed for different trends. The most
famous mathematical methods have been incorporated in statistical and data
manipulation computer programs (e.g., MS Excel.)
Linear trends:
It is an alternative method to regression.
Y = m.X + c (where m is slope and c is the intercept or value of y at x=0)
Use Slope and Intercept functions for calculating m and c and then
calculating the values.
Alternatively you can use Trend function to directly calculating the forecast
values. Example:
c = INTERCEPT(B2:B6;A2:A6) = -77.16
m = SLOPE(B2:B6;A2:A6) = 0.93
Forecast in Year 95 =TREND(B2:B6;A2:A6;95) = 11.19
The same as
regression
calculation
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M.S. Excel Forecasting:
Exponential Functions:
Exponential functions are based around the formula y = b.m^x
So for forecasting the trend we need to estimate b and m values.
LOGEST is the function for calculating exponential trends.
First index of return function represents m and the second index is b.
Example:
m = INDEX(LOGEST(B2:B6;A2:A6;TRUE;FALSE);1) = 1.48
b = INDEX(LOGEST(B2:B6;A2:A6;TRUE;FALSE);2) = 1.93
Forecast for year 6 = b * m ̂6 =
Forecast for year 10 = b * m ̂10 = 94.3
19.9
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M.S. Excel Forecasting:
Polynomial Functions:
Polynomial functions are based around the formula
y = a.x^n + b.x^(n-1) + c.x^(n-2) + … + m
Excel has a specific function dealing with Polynomial functions: LINESTfunction.
Form: = LINEST( Known Y Values, Known X Values^{1,2,3,..n})
Where n represents maximum power of x.
For example for a polynomial trend of power 3 such as:
y = a.x^3 + b.x^2 + c.x +m
We can :
= LINEST(A2:A10, B2:B10^{1,2,3})
Different parameters are stored as different indexes and we need to apply index
function to be able to return their values. For example returning parameter 2 or b
in the polynomial function we have:
= INDEX(LINEST(A2:A10, B2:B10^{1,2,3});2)
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M.S. Excel Forecasting:
Polynomial Functions (cont’d):
Example: a=INDEX(LINEST(B2:B6;A2:A6 ^ {1,2,3};TRUE;FALSE);1) = 0.3
b=INDEX(LINEST(B2:B6;A2:A6 ^ {1,2,3};TRUE;FALSE);2) = -3.2
c=INDEX(LINEST(B2:B6;A2:A6 ^ {1,2,3};TRUE;FALSE);3) = 11.6
d=INDEX(LINEST(B2:B6;A2:A6 ^ {1,2,3};TRUE;FALSE);4) = -5.4
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M.S. Excel Forecasting:
Logarithmic trends:
Excel does not provide function for Logarithmic trends.
However you can first transfer logarithmic trends to linear trends
Then you can use linear TREND or LINEST functions to estimate them.
For Logarithmic trends, instead of X values use LN of X values in LINEST
function
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Delphi:
The Delphi method is a structured communication technique, originally
developed as a systematic, interactive forecasting method which relies on a
panel of experts. The experts answer questionnaires in two or more rounds.
After each round, a facilitator provides an anonymous summary of the experts’
forecasts from the previous round as well as the reasons they provided for
their judgments. Thus, experts are encouraged to revise their earlier answers
in light of the replies of other members of their panel. It is believed that during
this process the range of the answers will decrease and the group will
converge towards the "correct" answer. Finally, the process is stopped after a
pre-defined stop criterion (e.g. number of rounds, achievement of consensus,
stability of results) and the mean or median scores of the final rounds
determine the results.
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Scenario Writing:
In Scenario Writing, the forecaster generates different outcomes based on
different starting criteria. The decision-maker then decides on the most likely
outcome from the numerous scenarios presented. Scenario writing typically
yields best, worst and middle options.
Brainstorming:
Brainstorming comes in handy in many situations where creative, cognitive
thinking is required. In brainstorming sessions efforts are made to find a
conclusion for a specific problem (e.g., in our case forecasting demand) by
gathering a list of ideas spontaneously contributed by the session participants.
They try to generate ideas and to solve problems casually, free from criticism
and peer pressure. They are often used when time constraints prevents
quantitative forecasts. Of course it is subject to more biases and should be
viewed skeptically by decision-makers.
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a) Collect residential buildings supply and demand information (at least) for years of
1388 to 1396. For each data present your references! (40%)
b) Draw supply and demand on a diagram. (20%)
c) Use a proper forecasting method for residential buildings supply and demand and
estimating steel (used in buildings) supply and demand up to year 1405. (40%)
Note: It is fine to only using linear or random forecasting, based on the data trend!
Due: two weeks
Home assignment 2
Thank you!