Sp2750 Unit 1 Work Assignment

Sp2750 Unit 1 Work Assignment
I work for Directorate of Navy Platform Systems, HNE. Stacey D. Wehmeier, Director Cost and
Schedule Estimation passed on your details to touch base and find out on wheather your Directorate
would be able to provide assistance by answering the questions on inflation forecasting and analysis
and its application as listed under the below task section. The task is due on 25th Sep 2015.
I have also included brief background information to understand on the scope of this task.
Task:
As the outcome of one of the NATO's ST–SC meeting in April 2015 nations among the ST–SC team
were requested to address a serious of questions that would enable in further developing of the
NATO's working paper on Inflation, Spatial Density and Software.
– This task request will be focussed on providing input for the development of Inflation Working
Paper (WP) currently in draft phase. The recent version of the WP is attached for your reference
purpose only.
– ... Show more content on Helpwriting.net ...
It is copied across from the NATO ST–SC meeting minute, April 2015 (Action item "8" from the
"Action List" at the last page of the minute due on 25th Sep 2015). The copy of the minute is
attached for reference purpose only.
"Provide Summary Level Paper (limit 10 pages) "Purpose and Practice of Inflation Forecasting by
Nation" – for insertion after the "Measures of Inflation"
1. Why do nations need inflation forecasting and analysis?
a. Budgeting (e.g. Ensure realistic budgets due to uniqueness of shipbuilding)
Note: Include a description of the internal government/defense/navy budgeting process
b. Approvals / Gates / Milestones
c. Risk Analysis
d. Ongoing Cost effectiveness analysis to support the decision maker
e. Contract proposal
... Get more on HelpWriting.net ...

The Operation Management Approach To Total Quality Management
Operation Management is the study of how people organize themselves for productive enterprise .In
order to be effective and efficient, an operation manager must possess a series of attitudes and skills
to push his/her company forward to reach goals and objectives. Operation management consists of
the four functions, that is, planning, organizing ,controlling and leading. These functions help in the
analysis of the activities done by the organization.
Operation is also about creating goods and services and it is known as the transformation process
which turns a range of inputs into the desired output (services) having the requisite quality level.
Management is the process which makes the combination and transformation of various resources
used in the operations scheme of the organization .If the same concept is extended to services
management, then the ... Show more content on Helpwriting.net ...
TQM does not prescribe a number of steps that must be followed in order to achieve high quality but
rather should be considered a framework within which organisations can work.
3.1.2.Just– In– Time
William J. Stevenson, in Production/Operations Management, defines the term just–in–time
manufacturing as "a repetitive production system in which processing and movement of material
and goods occurs just as they are needed,usually in small batches" (Stevenson, 1996). However,
just–in–time (JIT) is more than an inventory system. JIT manufacturing is a philosophy by which an
organization seeks continually to improve its products and processes by eliminating waste (Ptak,
1997)
3.1.3The Six Sigmas
Six sigma is a quality management approach that places heightenedmanagerial attention on
customer satisfaction and on seeking businessprocess improvements.

Case Study Of Roug Rough Cut Capacity Planning
1. INTRODUCTION
Consumer demand for a product can be fulfilled entirely in the master production schedule if
supported by production capacity according to production requirements. Master production schedule
can be easily realized if consumer demand is constant, but in fact companies often experience
fluctuations in the demand of consumers who tend to be unstable. Based on research Liske F. (2012)
that capacity planning is done well can meet the demand of existing customers as well as be able to
increase the company's revenue. Based on research Ria Amalia (2012) that consumer demand can be
met by adding machines at work center that is experiencing a shortage of capacity.
PT. XYZ is a plastics company in Indonesia, are often unable to meet consumer demand for
polyethylene plastic products. This resulted in the company can not make a profit in accordance
with what is expected, and also difficult to foster consumer confidence. ... Show more content on
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RCCP allocate capacity needs for labor departments, individuals, or work center based on workload
data in the past. This technique is used to explain / verification of capacity in each work center
where the comparison between the required engine load with the available capacity in each work
center. This study will use a rough cut capacity planning approach to help resolve the problem of
shortage of production capacity at PT XYZ.
This study aims to determine the work center that is experiencing a shortage of production capacity
and production capacity planning proposed as an alternative work center to optimize production
capacity but with minimal production costs by using Rough Cut Capacity Planning

Importance Of Demand Forecasting On Sales And Operations...
Abstract
This research paper was developed with the main purpose of presenting an overview that define and
explain the importance of demand forecasting aligned with the Sales & Operations Planning. In
addition, through the analysis of the content presented in this paper, readers will be able to
understand each aspect involved with the topic in discussion as well as its application against the
competitive business market faced by companies worldwide. More importantly, by analyzing the
content presented in this research paper, readers will also be able to learn and comprehend that when
well applied, forecasting methods within the sales & operations planning can be key business tools
for companies in their path for success.
1. ... Show more content on Helpwriting.net ...
How to do that then? The answer is simple: By planning and forecasting sales and demand. When
doing that, the company is able to anticipate events; through the use of a learning cycle it becomes
able to project its production based on a projected demand. 2. Sales & Operations Planning (S&OP)
– Concept and Purpose
Before applying the forecasting method within the sales and operations planning, it is important to
know what is an S&OP and its purpose. Sales & Operations Planning is an integrated business
process that generates competitive advantage by attempting to understand future scenarios and
involving a multifunctional team responsible for defining and executing a set of operational plans,
with its main focus on maximizing business results and improve customer service. Depending on the
business, S&OP is referred with a different name such as aggregate planning, staffing planning
(service business) or production planning.
The main objective of S&OP is the coordination and planning of resources, taking in consideration
quantity, type, and timing. The time frame or horizon is dictated by "how long in the future the firm
needs to have an estimate of resource needs in order to act appropriately to secure those resources"
(Chapman, 46). Taking the example of finance departments, in order to plan for a financing process
and/or investment activities, they

Operations Management Essay
Journal 2
1. It has been said that forecasting using exponential smoothing is like driving a car by looking in
the rear–view mirror. What are the conditions that would have to exist for driving a car that are
analogous to the assumptions made when using exponential smoothing?
When driving a car, everyone knows where one should be looking. Straight ahead most of the time
and with some side glances from time to time. An occasional glance into the rear–view mirror is
recommended. Any quantitative forecasting method always uses historical data to make forecasts.
Exponential smoothing is a method used in forecasting to eliminate the effect of any random
deviations in the data trend. Also, like any forecasting method, it assumes that the ... Show more
content on Helpwriting.net ...
But even this is not possible in case of a new product or innovation. A forecast of sales, demand,
cash, requirements and several such business valuables are extremely essential for a business in
order to be able to appropriately plan and conduct its operations in an effective and efficient manner.
Yet, forecasts cannot be made accurately as there are several factors and changes in the current
environment that leads to variations in forecasts and impacts or causes a manager to make changes
in the forecasts.
3. When a new business is started, or a patent idea needs funding, venture capitalists or investment
bankers will want to see a business plan that includes forecast information related to a profit and
loss statement. What type of forecasting information do you suppose would be required?
Whenever a business plan is made for funding, the purpose is to sell a product or service that
already exists in the market and is different from that trying to market an invention. In any profit and
loss statement, the difficult part is the profit part or actual revenue stream. The costs part is easy to
estimate in both cases. In the first case, there will be historical data available from the existing
market players while in the second case, the investor should be able to estimate what share of the
market that one expects to capture. This would be either from the existing market players, or from
the excess unfulfilled demand that may exist in the market. If grabbing the market

Forecasting Method
Abstract
Companies forecast in different ways and for different reasons. For the sake of my current employer,
some of the reasons to why they forecast is to ensure that there are plenty of cellular phones in stock
or even to make sure that the company has enough numbers to assign to customers when they
purchase wireless service from us. The following paper will compare and contrast various
forecasting methods while also elaborating on the method that my current employer use for
forecasting sales and mobile identification number (MDN) requirements.
Forecasting Assignment
Forecasting is the ability to plan ahead for future expectations of what the future may hold. For
example, business forecast every year for what they feel that ... Show more content on
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Casual relationship is "a situation in which one event causes another. If the event is far enough in the
future, it can be used as a basis for forecasting." A good example of this would be a casual
relationship between student enrollment and teachers in a university. If the enrollment of students is
higher than normal than it would cause for additional teachers to be hired and vice versa. This is
considered a casual relationship since additional teachers would not have been hired if enrollment
was not up therefore the high enrollment causes the increased staff.
Now that I have defined each of the forecasting methods discussed within this paper, I will now
compare them to each other. Of the methods discussed in this paper, Delphi has no comparison to
any of the other three methods of forecasting. Delphi forecasting is used in conjunction with experts
and hypotheses rather than gathering information from other sources and analyzing them. At the
same time, Time series and Casual relationship forecasting has similarities because each is
dependent on another aspect. Though Time series focuses on the seasonal aspects of things, casual
relationship could very well be dependent on the seasons. For example, the Time series forecasting
is big on farmers for planning their crops; however bad weather would cause a casual relationship
between the two. This reasoning is due to the fact that the forecast

Application Of A Consultant For Excellent Consulting Group
Purpose: Introduction/background of problem
As a consultant for Excellent Consulting Group, we were tasked with developing and
testing different forecasting techniques. In case study number three we utilized linear regression
as a form of forecasting. The information used to test this assessment was gathered by our client
who collected data on sales of one of its products, a lottery app for smart phones and hits on its
website. This information was gathered over a 12–month period and includes the hits and sales
for the corresponding months. The consulting manager at Excellent Consulting Group has
requested we go the next step and analyze additional forecasting methods. As consultants we
feel it is important to do a ... Show more content on Helpwriting.net ...
The same data will be utilized in this case study but simple exponential smoothing will be utilized to
help analyze the data. The information we decided to focus on for the purpose of this case was the
sales data from our client`s lottery app. We will use this information to calculate the mean absolute
percentage error (MAPE) for the first twelve months assuming the calculation for January represents
its actual sales. Two different alphas 0.15 and 0.90 are utilized in order help determine our
assessment.
In the below spread sheet the formatted data are to the left and the data are arranged by months
and sales. Immediately to the right of this information is the excel chart utilizing alpha 0.15 to
forecast and analysis the data. To the right of that is similar information but the alpha utilized in
this scenario is 0.90. The analysis with the lowest MAPE will help us determine which
forecasting equation achieves the best outcome for our analysis. Looking at the diagram it
appears that utilizing 0.15 is a better forecasting method than utilizing 0.9. As you can tell, mean
error (ME) were almost four times higher using the alpha 0.9. The

average sales minus forecast sales using alpha 0.15 totaled –33.404. The mean percentage error
(MPE) average utilizing alpha 0.15 was –0.105 and –0.061 utilizing alpha 0.9. The MAPE

Case Study
CASE ANALYSIS: WILKINS, A ZURN COMPANY: DEMAND FORECASTING
Submitted By Group 3: Arunava Maity, Firoj Kumar Meher, Parvez Izhar, Pooja Sharma
The Case Scope:
  Section 1: Identification of current forecasting techniques used in the demand forecasting of
existing and new products. Section 2: Idenitification of a better forecasting technique which can
ease the process and improve the reliability and accuracy of the sales forecast.
The Case Background Notes:
 Wilkins Regulator Company had built its strength on the below high–quality products. Plumbing
Municipal waterworks Fire production  Irrigation customer markets  The general plumbing
customer market represented approximately half of its sales revenue and the irrigation ... Show more
His colleague Connors uses judgment for developing sales forecast. He makes sure that factors such
as economic downturn (mild recession) is considered in demand forecasting to predict accurate
sales. Barge is not sure how to incorporate occasional/seasonal price and promotions that is used to
sell of excessive finished goods inventory. In case, prices are reduces, sales will go high and Wilkins
will be more competitive. Berge makes a statement that the fire valves are leading economic
indicators, but not sure if it is correct. However, using the data this can be proved to be wrong.
Barge wonders if he can use United States economic information–Unemployment Rate data and the
bank prime load rates or the number of new housing starts to eliminate the effect of macroeconomic
factors in sales forecasting. Since both PVB and Fire Valves are mostly or entirely sold in US
market, why is he confused to use them. Barge is not sure how to forecast "new" products such as
new fixed pressure fire valves. He has an idea of using sales history for a like–product such as
adjustable –pressure fire valves but both Barge and Connors believes that the new product fixed –
pressure valves would have dramatic growth (as per the increasing demand), but Berge does not
think that it can be concluded from historical data of older products.
 
 

Our

Business Strategy And Look At The Progress Of Achieving...
I would review our corporate strategy and look at the progress of achieving our objectives. I would
assign a team to analyze our current processes and evaluate them in order to discover areas that are
doing well and areas that require improvement. We could then decide how to solve these problems
while also continuing to reach our objectives. I would employ constraint management and the theory
of constraints in order to identify factors that are limiting our systems performance and are
restricting output. The theory of constraints would be utilized to increase our profits by improving
and speeding up workflow. A team would be assembled to manage constraints and adjust the
processes to be less constrained with shorter setup times. The Drum–buffer–rope system can help
regulate and control flow so production does not get backed up and the manufacture of our soup and
cracker products can run more efficiently. Since we are adding new soups, we need to make product
mix decisions such as how many cans of each soup should be produced at any given time. The
contribution margin, or the amount each product contributes to profits and overhead, is important to
making product mix decisions. The cash cow products should be favored and run more often in
order to increase profits. Rebalancing the assembly line is necessary because we have a new
product, chicken noodle soup, so we need to plan our schedules to include this new product and its
setup times, cost, number sold and

Business Operational Forecasting : An Overview
Business operational forecasting entails estimation or prediction of future states in business
operations such as sales, profits and expenditures. Forecasting techniques have evolved to be
invaluable tools used in corporate planning and predictions as business businesspeople are able to
anticipate future economic trends from a knowledgeable standing point. In this regards for instance,
if predictions show a dim future, business can cut down on its productions quotas, inventories and so
forth. However, if the predictions show an economic boom, businesses can reposition themselves by
putting necessary measures in place to gain maximum returns from it. Operational forecasts
therefore aid business organizations and people in adapting to ... Show more content on
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In this case, the number of customer turnover is the independent variable (X) while the sales are the
dependent variable (Y). The linear regression entails indentifying the best fitting line through the
data points in a scatter plot which of the form, Y(x)=b_0+b_1 x, where Y is the predicted value, b0
is the regression constant, b1 is the regression coefficient and x is the independent or predictor
variable . The linear regression equation is then used to predict year two sale results using year two
customer data for any given month. Using excel, the following regression line and equation were
obtained for the dataset;
The above scatter plot shows a positive correlation between the independent and dependent variable.
From the above, the regression equation for the dataset is y = 0.648x + 111.6. The R squared value
determines how close the data variables fit in the regression line. A value of 1 shows a perfect
correlation between the variable while a zero shows no correlation. However, the above R–squared
value is close to one indicating a good fit.
Polynomial regression analysis – unlike simple linear regression, polynomial regression assumes

Supply Chain Management : Chapter 10
Supply Chain Management: Chapter 10 (p. 249): Questions: 1, 4, 5, & 13
(1) What is the difference between supply chain management and demand management?
According to Schroeder, Goldstein, & Rungtusanatham (2013), supply chain management is the
process that is used by a company to ensure that its supply channel that supplies and materials are
processed through is moving and operating in an efficient and cost effective manner. However,
demand management is when decisions made affect the amounts of one or more products that are a
part of the supply chain.
(4) How do lead times and forecast errors affect supply chain performance?
Lead time is the time between the initiation and completion of a process. It affects supply chain
performance because the longer the lead time the longer it will take for materials to move through
the supply chain. Forecasting errors affect the supply chain because the calculations formulated in
forecasting are not exact science, but it is only an approximation that can be almost on target or the
figures can be way off target. Lead times and forecast errors can both cause the bullwhip effect
which is when there is an increase in variability of orders received in the up side of the supply chain,
which then affects the amount of inventories the upper end of the supply chain holds on to according
to Schroeder, Goldstein, & Rungtusanatham (2013).
(5) Why is increased coordination needed to manage supply chains? Give three examples.
Increased

Forecasting Methods And Techniques For Planning For...
Organizations incorporate forecasting methods and techniques to plan for upcoming business events
and predict what is most likely going to happen in the future. They study, analyze, and interpret data
and recent trends to help support their future predictions. Organizations have the decision to either
participate in qualitative forecasting or quantitative forecasting. Some firms are unable to access
past data and can solely rely on opinions and judgment, so they pursue qualitative forecasting
methods. Survey techniques, opinion polls, and the Delphi method are three common qualitative
forecasting methods. These types of forecasting methods are subjective in nature, as organizations
fully understand consumer preferences will not remain consistent. On the other hand, quantitative
forecasting involves the presence of historical data and the assumption of consistent data trends in
the future. The two popular quantitative forecasting methods include the explanatory methods and
time–series methods. These two methods strictly focus on past data and interpret past observations
to better understand why data trends are moving in their respective directions. Lastly, it is
imperative organizations study the moves of other companies in their respective industries and
conclude if the forecasting investment was worth the time and money. Forecasting ultimately
benefits businesses in decision–making, planning, and budgeting. Forecasting is heavily dependent
on the company's ability to make

Forecasting and Demand Planning
Integrated Planning – Module 2
1
Agenda
Forecasting, Factors influencing Demand Basic Demand Patterns Basic Principles of Forecasting
Principles of Data Collection Basic Forecasting Techniques, Seasonality Sources & Types of
Forecasting Errors
Forecasting can be conducted at various levels
Strategic Required for Product life cycle Long–term capacity planning Capital asset/equipment/
human resource management Examples Product line transitions Annual volume out 3–5 years
Buy/build/lease decisions
Financial
Budgeting Financial reporting Working capital management Production scheduling Purchasing
Resource planning Customer service management (product allocations)
Total ... Show more content on Helpwriting.net ...
Characteristics of demand
Factors influencing demand
– General business and economic conditions – Competitive factors – Market trends – Firm‟s own
plans – Government regulations – Technology changes – Others...
Characteristics of demand
Components

Demand Forecasting
Demand forecasting
Demand Forecasting is the activity of estimating the quantity of a product or service that consumers
will purchase. Demand forecasting involves techniques including both informal methods, such as
educated guesses, and quantitative methods, such as the use of historical sales data or current data
from test markets. Demand forecasting may be used in making pricing decisions, in assessing future
capacity requirements, or in making decisions on whether to enter a new market.
Necessity for forecasting demand
Often forecasting demand is confused with forecasting sales. But, failing to forecast demand ignores
two important phenomena. There is a lot of debate in the demand planning literature as how to
measure and ... Show more content on Helpwriting.net ...
Time series forecasting is a collection of methods for projecting forward from historic observations.
A very simple example is a moving average. Of course, different methods are appropriate for
different business conditions. The Holt's Method is most suitable for basic or staple merchandise,
while the Winter's Method works best for seasonal merchandise, and Croston's Method is
appropriate for merchandise with little turnover. In all, there are more than a dozen methods to use,
depending on your current situation. What is common across all methods is that the only data
consumed in producing the forecast is derived of the learnings from previous similar situations.
They permit modeling seasonal demand fluctuations, trend growth or decay, and lifecycle
phenomena. Using time series methods, you need to utilize prior observations of demand. A good
source of these observations is a point–of–sale system. These systems capture sales/transaction
information, so it is necessary to make two adjustments in order to create your time series forecast.
The first is to adjust the sales quantity to reflect the sales that you could have achieved if there had
been no inventory defects. This may be as simple as extrapolating across weeks in which the item
was out of stock, or as complex as dynamically adjusting sales when daily stock values fell

Forecasting Methods Compare and Contrast
Forecast in a simple terms is a prediction thru a statement or claim that a particular event will occur
in the future. It looks like to me that almost the majority of the people, including children, once in
their life time were a forecasters, as sometimes in their past they?ve tried to predict any future event.
This act of making such prediction is therefore, called forecasting. Forecasts are never finished, they
are needed continuously and as the time passes, their accuracy and their impact on actual
performance are meas So it looks like that forecast in itself, is not too complicated, it becomes
complicated once the word ?good? is attached to it. Thus, the forecast has to be well thought and
planned so it can be called good or adequate ... Show more content on Helpwriting.net ...
Delta airline is one clear example as it is the latest one to make use of the chapter 11. The remaining
of this paper will be talking about the different forecasting methods used by the airline industry to
make future prediction of passenger demand. The exactness of forecasts is very critical to the
revenue management system as lousy prediction of demand can lead to an incorrect decision–
making, which in turn leads to a miserable revenue performance. So the airline industry, more than
any other industry, needs an accurate forecasting not only because of the September 11 occurrence,
but also due to a very high price of crude oil, which tends to increase the price of kerosene highly
used by the industry. One study identified as the Improved Forecast Accuracy in Airline Revenue
Management (2001, Richard Zeni) shows that airlines divide passengers into two large categories
based on their sensitivity to price and travel needs. These included business passengers and leisure
passengers. This study has further shown that business travelers have a tendency to make their
arrangements close to their departure date staying at their destination for only a short time.
However, they did not show much flexibility on their plans at all, but they were willingly to pay
more money for their tickets. On the other hand, exactly the opposite happened with leisure
travelers. They usually booked their flights well ahead of their travel date; stayed more time

Forecasting
Forecasting Business forecasting is the process of studying historical performance for the purpose of
using the information gained to project future business conditions so that decisions can be made
today that will assist in the achievement of certain goals. Forecasting involves taking historical date
and using it to project future data with a mathematical model. Forecasts are extensively used to
support business decisions and direct the work of operations managers. In this paper I will introduce
different types of forecasting techniques.
What is Forecasting Forecasting is the art and science of predicting future events. Forecasting is a
statement about the future. "Operations management is designed to support forecasted ... Show more
This technique is part of a set of techniques that are useful in situations where past data do not exist,
causal relationships have not been identified, or some major change has occurred in the forecasting
context which is not accounted for by other techniques. Evidence as to the effectiveness of using
these methods by themselves is mixed, although using them can provide good forecasts, especially
in uncertain environments. The objective of these techniques is to provide rational, honest, and
systematic estimates. (Marketing Profs) Some advantages of jury of executive opinion is it can be
done easily and quickly without a lot of elaborate statistical manipulations and it incorporates a
variety of opinions from executives. (Sales Forecasting) Delphi method. The Delphi method gathers
a panel of experts from different fields to comment upon the research of others in their own and
different disciplines. It is typically used to arrive at high–level predictions. The aim is to account for
the complex factors that affect long–range forecasting by generating a wide range of possible future
scenarios. The method also claims to safeguard against the tendency of group discussions on these
kinds of matters to arrive at a consensus. (Delphi Method) Sales force composite. A method of
developing a forecast that uses the opinions of each member of the field sales staff regarding how
much the

Forecasting Paper
Abstract Forecasts are extensively used to support business decisions and direct the work of
operations managers. The two major types of forecasts are qualitative and quantitative. Within each
of these types are multiple methods and models. Qualitative forecasts are based upon subjective
data. Quantitative forecasts are derived from objective data. Both methods are not suitable for all
situations and circumstances. Each has inherent strengths and weaknesses. The forecaster must
understand the strengths and shortcomings of each method and choose appropriately. One example
of forecasting is the United States Marine Corps use of forecasting techniques, both qualitative and
quantitative, to predict ammunition requirements. ... Show more content on Helpwriting.net ...
Time Series Analysis Forecasting Time series analysis is a series of observations taken at regular
intervals over a specified period of time (Anonymous, n. d.). The following are techniques of time
series analysis: simple moving average, weighted moving average and simple exponential
smoothing, exponential smoothing with trend, and linear regression (Aquilano, Chase & Jacobs,
2005).
Simple Moving Average The simple moving average considers a series of data and uses past
performance to predict future performance (Aquilano, Chase & Jacobs, 2005). It is an ongoing
exercise. When new data becomes available, the oldest data is dropped from the series and forecasts
are recalculated (Aquilano, Chase & Jacobs, 2005).
Weighted Moving Average The simple moving average assigns equal weights to all periods
considered (Aquilano, Chase & Jacobs, 2005). The weighted moving average allows the forecaster
to assigns weights to each period considered (Aquilano, Chase & Jacobs, 2005). The only
requirement is that the cumulative weights must equal 1. This method is particularly suitable for
businesses with wide seasonal variance.
Simple Exponential Smoothing Simple exponential smoothing accounts for the previous period 's
forecasting errors in order to more accurately develop the current forecast by applying a smoothing
constant or response rate (Anonymous, n. d.). Exponential smoothing also

Case Study Northern Napa Valley Winery Inc
Northern Napa Valley Winery Inc. Future Sales Forecast Report
Prepared by: Karriem Pierre
November 20, 2011
Nova Southeastern University
Business Modeling, Fall Semester, Online Course
Professor Phillip S. Rokicki, Ph.D
Executive Summary
Ms. Quintana CEO of Northern Napa Valley Winery Inc. was considering conducting business with
Trans Continental stores to sell excess grapes from the 2008 harvest. Prior to making a decision
Quintana must determine how much of the harvest should be retained for the production of Northern
Napa's own red table wine. Quintana realized that the quantity of red table wine produced is closely
associated to the sales. Ms. Quintana ... Show more content on Helpwriting.net ...
This test was used in order to determine if there were too many or too few runs in a series of data.
After conducting the runs test it produced a z–value of –5.9123, which indicates the amount of
standard errors of the identified number of runs below the expected number of runs. The p–value
indicates how extreme the z value is and with a p–value (0.0001) which is less than .05 or .1 the null
hypothesis of randomness is rejected (Figure 1).
Figure 1: Runs Test for Randomness
|StatTools Report |
|Analysis: |Runs Test for Randomness |
|Performed By: |Karriem Pierre |
|Date: |Wednesday, November 16, 2011 |
|Updating: |Live/Unlinked |
| |Sales |
|Runs Test for Randomness |Data Set #1 |
|Observations |104 |
|Below Median |52 |
|Above Median |52 |
|Number of Runs |23 |

|Median |10933.00 |
|E(R)

Iact Scm Assignment
ASSIGNMENTS FOR LOGISTICS AND SUPPLY CHAIN MANAGEMENT STUDENT'S
NAME: M DEVADAS BABU / E MAIL ID: devdossb@yahoo.com ASSIGNMENT – MODULE 2
Question: What kind of forecasting methods do you think a company with the following products
would use. For each product take up a company of your choice and justify the use of particular
forecasting method for that company.
Answer: Forecasting is based on a number of assumptions:
1. The past will repeat itself. 2. As the forecast horizon shortens, forecast accuracy increases. 3.
Forecasting in the aggregate is more accurate than forecasting individual items. 4. Forecasts are
seldom accurate.
It is through a combination of methods that a company arrives at an ... Show more content on
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Moving average will not give an accurate prediction for other less established products, as it gives
recent data more importance. A product like Colgate tooth paste which has established itself over the
years can afford to adopt Moving Average Technique to arrive at a quick forecast, as the input data
would not vary much over a considerable period. However, for more important strategic decisions
the suggested method is Exponential Smoothing. | Laptop | Dell | Comparison of the performance of
a similar successful product and research on why a particular brand fared poor will give valuable
inputs to arrive at a demand forecast. Historical Analogy is the suggested method for this product. In
case of a new product launch other qualitative methods may also provide useful inputs for a precise
forecast. | Mobile | Nokia | I suggest Historical Analogy for this product. This is a common
technique used to generate new product forecasts when a similar product exists. Electronics and
telecommunication companies often utilize this technique. E.g. The demand for a new cell phone
could be based upon the sales history of an existing model. Qualitative Methods like market
research, Delphi technique etc. and causal method like life cycle analysis may be adopted in case of
a new product launch. To assess the demand of an existing brand, moving average method and
exponential smoothing may also be studied. |

Essay about Business Forecast
Business Forecast
This Paper examines and compares various forecasting techniques used for qualitative and
quantitative business forecasting and their use in Firstlogic Inc., to forecast the demand under
conditions of uncertainty. Time series and Delphi forecasting methods are considered for this
research to evaluate their ability to make effective decisions regarding the future.
Business Forecasting
Business forecasting is the process of studying historical performance for the purpose of using the
knowledge gained to project future business conditions so that decisions can be made today that will
aid in the achievement of established goals. Forecasting plays a crucial role in today's uncertain
global marketplace. Forecasting is ... Show more content on Helpwriting.net ...
It is in these situations that modern methods of business forecasting can be especially useful.
Modern forecasting methods are usually grouped into two main categories: qualitative methods, and
quantitative methods. Qualitative analysis includes the intuitive and knowledge–based approach as
discussed earlier. The decision maker reviews all of the information available, and then makes an
estimated forecast. Quantitative techniques are used mostly when qualitative information is not
available. In contrast, qualitative techniques are based on an analysis of data (Namvar, 2000, p.8).
Delphi Forecasting Method
Qualitative forecasting techniques are: executive committee, the Delphi method, and surveys of the
sales force, surveys of customers, historical analogy, and market research. The objective of most
Delphi applications is the reliable and creative exploration of ideas or the production of suitable
information for decision–making. The Delphi Method is based on a structured process for collecting
and distilling knowledge from a group of experts by means of a series of questionnaires interspersed
with controlled opinion feedback (chase, 2003, P471).
The Delphi method is a variation of the executive committee approach. But the interaction is
indirect, iterative and structured. The basic premise of Delphi method is to identify a group of
experts and each of them are given a set of questions or issues,

Forecasting Model Of Forecasting Models
Forecasting is often defined as the estimation of the value of a variable (or set of variables) at some
future point in time (Goodier, 2010). It can be applied to a number of different situations when there
is uncertainty about the future and the data collected can aid in decisions that need to be made
(Armstrong, 2001). In relation to healthcare, forecasting models have been used to aid their sector's
departments to plan staff rota schedules, ensuring that a sufficient amount of senior staff are
available at any given time throughout the day, week, month and year. As explained previously, a
fundamental factor that causes overcrowding is a limited supply of resources to treat patients,
leading to a longer time spent in an Emergency ... Show more content on Helpwriting.net ...
These models can be characterised as consisting of a time trend, a seasonal factor, a cyclical element
and an error term (Kennedy, 2008.) Unlike casual or economic forecasting, where it is assumed
there is a historical relationship between a dependent and an independent variable will be consistent
in the future, time series models assume the historical components of the model will repeat itself.
Research has been undertaken to develop a generalised forecasting model that uses a method that
can accurately predict future the attendees and resources needed at Emergency Departments.
1.3.3 Long Range Forecasting for Future Attendees An early attempt to predict attendees was
conducted by Milner (1988) who's study on a single Emergency Department within the UK
attempted support to healthcare planning by forecasting annual first, return and total attendances at
EDs for Trent districts and the whole of the Trent region. The data of annual first, return and total
attendances were collected over a training period of 10 years and evaluated over a period of 1 year
using an Autoregressive Integrated Moving Average (ARIMA) method for modelling which falls
into time series model category. This method for forecasting this type of data has been supported by
other researchers, who state that ARIMA forecasting techniques should be considered for a time
series that's contains a trend or seasonal or non–stationary data. The results

Case Report On Australian Banks
Case report 3
Australian banks in Asia
Name : Thi Dai Trang Le (Tracey)
Student ID: LETTO1401
Tutor : Lorna Sedman
Table of Contents
1. Introduction 3
2. Issue identification 3
3. Critical Discussion 4
4. Recommendation 5
5. Conclusion 5
Reference list 6
Introduction:
Asia market are growing faster which is a seductiveness to Australian business. There are Australia's
"big four" banks : ANZ, Commonwealth Bank, NAB and Westpact which are operating in Asia. As
we know, doing business in Asia that is tough. All the foreign banks might to take the high gamble,
they have to face with highly pressures from the stringent regulatory limitation , cultural or business
environment, but these pressures may ... Show more content on Helpwriting.net ...
When a business use scenario planning to explore the macro environment regarding to social,
technological, economic and political issues , it will obtain significant achievement (Ratcliffe,2000).
For instance, nowadays ANZ is considered as the best famous bank for the fact of connection
between Australian banks. Additionally, it is also in a well establishment in Asia market because it
has planning to be active in Asia. It is clear that ANZ will be further to obtain long term sustainable
growth and profitability.
Different from scenario planning, forecasting is concerned with what will happen. Vander Heijden
(2005) shows that the scenario planning is designed to get people to ask question whereas the task of
forecasting is giving the answer (p.6). According to Choi (2011), forecast will be suggested by
managers which helps to strengthen the relationship between returns of future profits. It is also
increasing the company's future profitability. This report will argue that when Australian banks
adopt forecasting and scenario planning, they definitely have enjoyed success in Asia in time.
Critical discussion
Forecasting mode has become a necessity for the organization to lean on. Borousan claimed that

implementation of an accurate forecasting process helps companies is trying to obtain financing
from investors. This method is a prediction based on previous sales performance and analyse of
expected market conditions. There is important thing for

Nichols Company Casae Study
Nichols Company Case Study
OSC 301
Nichols Company Case Study
Joe Williams is the president of Nichols Company (NCO), which manufactures three primary
products and has over 355 employees. In addition, NCO has been having some issues with their
supply chain in the past few months and it has affected their customer service. This paper will
summarize the case study, determine NCO 's appropriate forecasting technique, discuss the impact
of aggregate planning, weigh NCO 's various cost factors associated with carrying inventory, and
make recommendations for improvement. Mr. Williams was approached by his Director of
Marketing, Mr. Barney Thompson, and announced that they had lost a large order due to a backorder
of tubing, which is ... Show more content on Helpwriting.net ...
Furthermore, aggregate planning affects NCO 's production schedule in much of the same way
because the aggregate plan defines the product production and duration.
There are various costs factors associated with carrying inventory. Chase, Jacobs, and Aquilano
(2003) stated that such costs include "storage facilities, handling, insurance, pilferage, breakage,
obsolescence, depreciation, taxes, and the opportunity cost of capital" (pg. 546). Furthermore, in
NCO 's case, they have an issue with carrying excessive inventory on products that do not get
immediately sold; consequently, they have an issue with alleviating the excess inventory. However,
high holding costs tend to favor low inventory levels and frequent replenishment.
NCO should make a few changes to improve their current supply chain troubles. They should
examine how NCO 's marketing department derives their forecasting numbers, and they should try
to run a more effective Just–in–Time (JIT) manufacturing process. First, NCO 's marketing section
should adopt a combination of the Time series analysis and Qualitative, Grass roots forecasting
techniques. If they use historical data along with current market trend inputs from NCO 's sales
force, they will be able to prepare a more accurate forecast. Second, NCO should redesign their
current manufacturing processes and utilize JIT manufacturing principles. Introducing these new
processes should help NCO to produce the correct

Kevin Tenorio. Dr. Stoycheva. Pol 601 Budget Analysis And
Kevin Tenorio
Dr. Stoycheva
POL 601 Budget Analysis and Financial Management
3 May 2017
Final Exam
1. How has the property tax changed over time for local governments? What are the advantages and
disadvantages of the property tax as a revenue source? In response to these questions, make sure to
refer to the main principles of taxation (equity, efficiency, adequacy of revenue, political feasibility,
and cost of administration), tax and expenditure limitations, as well as the importance of revenue
diversification for local government.
Historically, property taxes have been the primary source of the local government's income. In fact,
approximately 70% of the local governments' revenue stems from property taxes (Lee, Johnson, and
Joyce, ... Show more content on Helpwriting.net ...
This could lead to that individual moving to another location, also known as gentrification. Political
feasibility is high since it has historically been a consistent source of revenue. Cost of administration
would be relatively low since property taxes, in terms of keeping track of properties, is relatively
easy because of its tangibility and lack of mobility.
With respect to revenue diversification, local governments have attempted to diversify their sources
of revenue by implementing one or a combination of these taxes: sales taxes, income taxes, game of
chance taxes (gambling, races, lotter, and their derivatives), user charge taxes, and sumptuary taxes
(cigarettes, alcohol, and their derivatives) (Lee, Johnson, and Joyce, 2013). In circumstances that
affect the primary source of revenue, having access to other sources may serve as a buffer for the
local government. However, the problems with these sorts of taxes is uncertainty. Property tax, as
stated earlier is the most reliable while income or sales taxes rely on income/ salaried employees and
consumption of products, respectively.
2. Explain the major forecasting methods used by governments to forecast revenues and
expenditures. Explain Florida's experience with the consensus forecasting process. Discuss which
methods are more likely to be used and for what revenue

Forecasting : Assessment Of Forecasting
Assessment of Forecasting Forecasting is a method of extrapolation of quantitative and qualitative
data to predict future requirements. Qualitative forecasting is subjective, whereas quantitative
forecasting contains projection of historical data. Simply stated, forecasting is a technique utilized in
efforts to match supply with demand. Accurate forecasts are necessary throughout the supply chain
to guide decisions regarding operation activities. "Poor forecasting can result in poor inventory and
staffing decisions, resulting in part shortages, inadequate customer service, and many customer
complaints" (Collier & Evans, 2013, pg.227). Poor forecasting can also result in excess inventory
throughout the supply chain. Since forecasting is such an integeral component of the value chain, it
stands to reason that inadequate forecasting could be the basis for the various quality control issues
General Motors has experienced within its supply chain. In order to analyze forecasting errors and
accuracy, it is essential to understand the basic methods of forecasting. Forecasting methods can be
divided into two broad categories: qualitative and quantitative. The statistical forecasting method is
defined as a quantitative method, "catergorized as time–series methods, which extrapolate historical
time–series data, and regression methods, which extrapolate historical time–series data, but can also
include other potentially casual factors that influence the behavior of the time

Marketing Forecasting : Business Forecasting
Running head: BUSINESS FORECASTING 1
BUSINESS FORECASTING 9
Name
Institutional affiliation
Date
Background of the situation
A lot of people view the world as consisting of a large number of alternatives. Researching for their
future evolved as a way of looking at the alternative futures and identifying the most suitable future.
Business forecasting, is a process designed to assist in decision making as well as planning. The
situation at EBBD being a logistics and distribution entity is that there are ... Show more content on
Helpwriting.net ...
First, there is no way that we can state what the future will be with complete certainty. Regardless of
the methods that we use for forecasting there will always be an element of uncertainty until the
forecast comes to pass (Ord & Fildes, 2013) . Second, there will always be blind spots in forecasts.
For example, we cannot forecast completely new technologies for which there is no existing pattern
or model. Third, providing forecasts to policy makers will help them formulate social policy. The
new social policy in turn will affect the future, thus changing the accuracy of the forecast.
Forecasting on trend analysis identifies and maps past and present experiences along the path of
change that is travelled, and when extrapolated, forecasts a likely heading for the future. (Ord &
Fildes, 2013). Trend forecasts are also based upon the assumption that the future will unfold at about
the same rate of change as it did in the past. Emerging issues forecasting assumptions identifies
possible futures, threats. or opportunities of concern to anticipate in order to take appropriate
strategic actions.
Forecasting methods
The management can use both qualitative and quantitative methods to carry out their forecasting.
Qualitative methods, sometimes used based on judgment, opinion, past experiences or best guesses
to make the forecast. Quantitative methods are also useful in helping the management make
planning decisions. Forecasting plays a significant role

Forecasting Methods
Introduction
All businesses are confronted with the general problem of having to make decisions under
conditions of uncertainty. Management must understand the nature of demand and competition in
order to develop realistic business plans, determine a strategic vision for the organization, and
determine technology and infrastructure needs. To address these challenges, forecasting is used.
According to Makridakis (1989), forecasting future events can be characterized as the search for
answers to one or more of the following questions:
„X What new economic, technical, or sociological forces is the organization likely to face in both
the near and long term?
„X When might these forces impact the firm¡¦s objective environment?
„X Who is ... Show more content on Helpwriting.net ...
Economists relay on this type of forecasting model to forecast business cycles and related
developments. This method could prove inaccurate if the forces that drove past events are no longer
present.
„X Market Research Forecasting: This forecasting method collects data in a variety of ways such as
surveys, interviews and focus groups to evaluate the purchase patterns and attitudes of current and
potential buyers of a good or service. Designers of goods and services use this method to understand
their current customers and the buyers they would like to serve.
„X Dlephi Method: The Delphi method compiles forecasts through sequential, independent
responses by a group of experts to a series of questionnaires. The forecaster compiles and analyses
the respondents¡¦ input and develops a new questionnaire for the same group of experts. This
sequence works towards consensus that reflects input from all of the experts while preventing any
one individual from dominating the process (Chase, 2005).
Quantitative Techniques Quantitative forecasting techniques transform input in the form of
numerical data into forecasts using methods in one of three categories. Each category of quantitative
forecasting methods assumes that past events provide an excellent basis for enhancing the
understanding of likely future outcomes.
„X Time Series Analysis: Time series analysis is based on

Associative and Time Series Forecasting Models
Forecasting Models: Associative and Time Series
Forecasting involves using past data to generate a number, set of numbers, or scenario that
corresponds to a future occurrence. It is absolutely essential to short–range and long–range
planning.
Time Series and Associative models are both quantitative forecast techniques are more objective
than qualitative techniques such as the Delphi Technique and market research.
Time Series Models
Based on the assumption that history will repeat itself, there will be identifiable patterns of
behaviour that can be used to predict future behaviour. This model is useful when you have a short
time requirement (eg days) to analyse products in their growth stages to predict short–term
outcomes.
To use ... Show more content on Helpwriting.net ...
This can be analysed using either the multiplicative or additive method. In the additive version,
seasonality is expressed as a quantity to be added to or subtracted from the series average. For the
multiplicative model seasonality is expressed as a percentage (seasonal relatives or seasonal
indexes) of the average (or trend). These are then multiplied times values in order to incorporate
seasonality.
Associative Models
Also known as "causal" models involve the identification of variables that can be used to predict
another variable of interest. They are based on the assumption that the historical relationship
between "dependent" and"independent" variables will remain valid in future and each independent
variable is easy to predict. This form of analysis can take several months and is used for medium–
term forecasts for products in their growth or maturity phase.
The procedure for this model is to collect several periods of history relating to the independent and
dependent variables themselves, establish the relationship that minimizes mean squared error of
forecast vs actual using linear or non–linear and singular or multiple regression analysis.

So you first predict the independent variable, then look at the established relationships between that
independent variable and the dependent ones to predict what the dependent variables will be. You
then develop an equation that summarizes the effects of predictor variables.
To do this you will need aggregate data which

Forecasting Methodology
Forecasting Methodology
Forecasting is an integral part in planning the financial future of any business and allows the
company to consider probabilities of current and future trends using existing data and facts.
Forecasts are vital to every business organization and for every significant management decision.
Forecasting, according to Armstrong (2001), is the basis of corporate long–run planning. Many
times, this unique approach is used not only to provide a baseline, but also to offer a prediction into
the corporation 's future. In the functional areas of finance and accounting, forecasts provide the
basis for budgetary planning and cost control. Marketing relies on sales forecasting to plan new
products, compensate sales personnel, and ... Show more content on Helpwriting.net ...
Causal tries to understand the system underlying and surrounding the item being forecast. Under
Causal type there are Regression analysis, Econometric models and Leading indicators. Starting
with Regression analysis, similar to least squares method in time series but may contain multiple
variables, basis is that forecast is caused by the occurrence of other events. Econometric models the
forecast attempts to describe some sector of the economy by a series of interdependent equations.
An input/Output model focuses on sales of each industry to other firms and governments; it
indicates the changes in sales that a producer industry might expect because of purchasing changes
by another industry. Leading Indicators type are statistics moving in the same direction as the series
being forecast but move before the series, such as an increase in the price of gasoline indicating a
future drop in the sale of large cars.
Simulation Models are dynamic models; Dynamic modeling in organizations is the collective ability
to understand the implications of change over time. This skill lies at the heart of successful strategic
decision process. The availability of effective visual modeling and simulation enables the analyst
and the decision–maker to boost their dynamic decision by rehearsing strategy to avoid hidden
pitfalls.
Global Insight is a privately held company formed from the two most respected

Types of Forecasting Methods
TYPES OF FORECASTING METHODS
Qualitative methods: These types of forecasting methods are based on judgments or opinions, and
are subjective in nature. They do not rely on any mathematical computations.
Quantitative methods: These types of forecasting methods are based on quantitative models, and are
objective in nature. They rely heavily on mathematical computations.
QUALITATIVE FORECASTING METHODS
Qualitative Methods
Executive Opinion Market Research Delphi Method
Approach in which a group of managers meet and collectively develop a forecast. Approach that
uses surveys and interviews to determine customer preferences and assess demand. Approach in
which a forecast is the product of a consensus ... Show more content on Helpwriting.net ...
We then made a forecast for the subsequent year, and so on right through to the forecast for year 7.
Year Actual Demand (At)
Forecast
(Ft)
Notes
1 100 –– There was no prior demand data on which to base a forecast for period 1
2 300 100 From this point forward, these forecasts were made on a year–by–year basis.
3 200 300
4 500 200
5 600 500
6 700 600
7 700
MEAN (SIMPLE AVERAGE) METHOD
Mean (simple average) method: The forecast for next period (period t+1) will be equal to the
average of all past historical demands.

In this illustration we assume that each year (beginning with year 2) we made a forecast, then waited
to see what demand unfolded during the year. We then made a forecast for the subsequent year, and
so on right through to the forecast for year 7.
Year Actual Demand (At)
Forecast
(Ft)
Notes
1 100 –– There was no prior demand data on which to base a forecast for period 1
2 300 100 From this point forward, these forecasts were made on a year–by–year basis.
3 200 200
4 500 200
5 600 275
6 700 340
7 400
SIMPLE MOVING AVERAGE METHOD
Simple moving average method: The forecast for next period (period t+1) will be equal to the
average of a specified number of the most recent observations, with each observation receiving the
same emphasis (weight).
In this illustration we assume that a 2–year simple moving

Forecasting Effects on Supply Chain
Analysis of Forecasting on Supply Chain
Background:
A supply chain is a network that performs functions from supplier's supplier to customer's customer.
It encompasses all the process involved in delivering the final product to the final consumer. Supply
chain is filled with various uncertainties such as demand, process, and supply. Inventories are often
used to protect the chain from these uncertainties. The higher the variations the more the losses and
every company needs to minimize the variations and uncertainties in its supply chain.
There are various causes of uncertainties. Among them few that can be listed are demand variations
based on the type of product, the suppliers' receipt variations which depend on the ... Show more
It also tells us the effect of forecasting on the planning.
We know about the bullwhip effect and the model shows clear signs of it. How the change in
forecast is affecting the demand given by the manufacturer to its supplier. It shows clear signs within
the firm itself where changes in demand by the customer is encouraging sales people to buffer up
their supply to meet the demand.
The model:
We are considering a mean demand of D, the variations sigma, lead time of 2–8 weeks depending on
the parts.
As we can see the demand has been varying a lot in 2009. This has induced a forecasting error by
the sales people in the manufacturing organization.
It has been assumed that sales people fill the MDS data 3 months in advance for the confirmed
orders. Hence it can be easily seen how the variation in the original forecast, the amount filled in the
MDS and actual shipment delivered to the customer changes.
Findings:
The bullwhip effect increases as the lead time increases. This is because the order level needed and
desired level needed are proportional to the lead time. This causes amplifying of inventory. There
can also be other delays like delaying order placing.
Here as we can see the decentralization has caused different forecast. This issue becomes more
complicated downstream as can be seen from the chart. There is a high increase in the variation of
the demand. The equilibrium depends not only on the quantities ordered

Final Project Auto parts word and excel Essay
Auto Parts Forecasting Case Study
Prepared by: Mariela Tuero
Date: December 13th, 2013
Nova Southeastern University
H. Wayne Huizenga School of Business & Entrepreneurship Assignment for Course: QNT5040
Submitted to: Dr. Ronald Mesia
Submitted by: Mariela Tuero N00046141 3821 SW 129 Ave Miami, FL 33175 305–282–6727
Date of Submission: December 13th, 2013
Title of Assignment: Auto Parts Forecasting Case Study
CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any
assistance I received in its preparation is fully acknowledged and disclosed in the paper. I have also
cited any sources from which I used data, ideas or words, either quoted directly or paraphrased. I
also certify that this ... Show more content on Helpwriting.net ...
(0 pt)
Generates solutions (does not justify conclusions).
(7 pts)
Partially: *generates and justifies solutions based on analysis and context; and *justifies
conclusions.
(15 pts)
Substantially: *generates and justifies solutions based on analysis and context; and *justifies
conclusions.
(17 pts)
Effectively: *generates and justifies solutions based on analysis and context; and *justifies
conclusions.
(20 pts)
Uses prescribed format (including cover sheet and grading rubric) and writing style (language,
grammar, punctuation, and spelling)
(CC8)

Does not use prescribed format and writing style
(0 pt)
May use prescribed format OR writing style (only one)
(3 pts)
Generally uses prescribed format and writing style
(7 pts)
Substantially uses prescribed format and writing style
(8 pts)
Effectively uses prescribed format and writing style
(10 pts)
Uses APA format
(APA Style Manual 6.0)
(CC8)
Does not provide references.
(0 pt)
Does not apply APA style to references.
(1pts)
Partially applies APA style to references.
(3 pts)
Substantially applies APA style to references.
(4 pts)
Effectively applies APA style to all references.
Optimal quality and quantity of citations.
(5 pts)
OVERALL GRADE (100 total possible points):
%
Comments:

Statistical Tools And Methods Of A Cat Corporation...
We shall identify statistical tools and methods to collect data and also analyze data to determine the
appropriate decision for the identified problem in A–CAT CORP forecasting.
There are many statistical tools that you can use to perform analysis on the A–CAT Corporation.
One of the tools to use is Mean; it will help in getting the average sale of voltage regulators per year
and be used for comparison purpose. Standard deviation will be used to measure the
spread/dispersion of data around the mean. A measure of spread gives us an idea of how well the
mean, for example represents the data (Lund Research, 2013). Finally the co–efficient of variation
will be used for comparison of variation since it's more convenient than the others. Another key
statistical tool for the analysis of the data is Excel.
The category of data provided in this given case study is under the historical data category. The
reason because it contains history tables for reporting or analysis purposes. The relationship between
this type of data and the tools is that the table containing sales for the last few years gives the set of
numbers required by the statistical tools for comparison purpose. Results are used to identify the
sales trend.
The co–efficient of variation is the most important tool since it is more convenient compared to the
standard deviation. It is used for comparison of variation. The lower the co–efficient of variation,
the smaller the residuals relative to the predicted value

Business Forecast
Abstract
This Paper examines and compares various forecasting techniques used for qualitative and
quantitative business forecasting and their use in Firstlogic Inc., to forecast the demand under
conditions of uncertainty. Time series and Delphi forecasting methods are considered for this
research to evaluate their ability to make effective decisions regarding the future.
Business forecasting is the process of studying historical performance for the purpose of using the
knowledge gained to project future business conditions so that decisions can be made today that will
aid in the achievement of established goals. Forecasting plays a crucial role in today 's uncertain
global marketplace. Forecasting is traditionally ... Show more content on Helpwriting.net ...
This group then feeds back the responses to other members of the group, while never giving away
the identity of the response. The experts are then asked to respond again, after reviewing the
responses of other respondents. This process may continue until a consensus is reached among the
group. The group may be united to form a final consensus (Namvar, 2000, p.8). Time Series
Forecasting Method
Time series techniques are the most popular quantitative method. These techniques use statistical
methods for projecting from historical data. Quantitative techniques are preferred when appropriate
data are available. The main assumption is that the historical pattern will continue into the future.
The two main types of time series forecasting are average smoothing and exponential smoothing.
The moving average is simply a series of arithmetic averages. Predicting sales for next year is
simple. The actual sales for a certain number of years is added, and then divided by the number of
years used to get the moving average. A weighted moving average is obtained by assigning a
specific weight to previous years. The sum of all weights must equal one. Recent years are given a
higher weight (Namvar, 2000, p.13).
Exponential smoothing is simply a subtype of the weighted moving average. A new forecast is a
weighted sum of actual variables (usually sales) in the current year and the weighted forecast of

Forecasting Hr Needs
MATCHING HUMAN RESOURCE REQUIREMENTS AND
POTENTIAL HUMAN RESOURCE AVAILABILITY
Matching human resources with the present and the future is one of the main problems faced by an
organization. Human resources have a certain degree of inflexibility, both in terms of their
development and their utilization. It takes months to recruit to select to place, and to train the
average employee. In the case of upper management personnel in the organizations, the process may
take up to years to nurture the candidate and making sure of the succession are being put in place.
Making decisions on recruitment and development are strategic and will produce long–lasting
results given the right people are being chosen. Therefore, the management must ... Show more
This information typically includes a brief |
| |assessment of performance and potential, age, length of time served in the current position, and|
| |overall length of service in the organization. |
|Allocation Planning |This technique involves judgments about labor supply and demand by
observing the movement of |
| |employees through positions at the same organizational level. |
(Duane, 1996: 4).
Quantitative Forecasting Techniques
There are several quantitative methods for determining labor supply and demand
| |Technique Description |
|Regression Model |Fluctuations in labor levels are projected using relevant variables, such as sales. |
|Time–Series Model |Fluctuations in labor levels are projected by isolating trend, seasonal, cyclical,
and irregular|
| |effects.

Demand & Inventory Management
Forecasting demand and inventory management using Bayesian time series
T.A. Spedding University of Greenwich, Chatham Maritime, Kent, UK K.K. Chan Nanyang
Technological University, Singapore
Batch production, Demand, Forecasting, Inventory management, Bayesian statistics, Time series
Keywords
Introduction
A typical scenario in a manufacturing company in Singapore is one in which all the strategic
decisions, including forecasting of future demand, are provided by an overseas office. The forecast
model provided by the overseas office is often inaccurate because the forecasting is performed
before the actual production schedule and it is based on marketing survey results and historical data
from an overseas research team. This ... Show more content on Helpwriting.net ...
Bayesian dynamics time series and forecasting techniques can be used to solve inventory problems
because Bayesian inference statistics has the analogue idea that posterior knowledge (actual sales
demand) can be derived from prior knowledge (such as the manager's experience) and the likelihood
(the similar or expected trend) of the product demand (Box and Tioa, 1973; Jeffreys, 1961; Lee,
1988; Press, 1989). In many real life forecasting problems (for example when previous demand data
are not available for newly launched products), there is little or no useful information
This work was carried out while the author was Associate Professor in the School of Mechanical and
Production Engineering at Nanyang Technical University in Singapore.
Integrated Manufacturing Systems 11/5 [2000] 331±339 # MCB University Press [ISSN 0957–
6061]
[ 331 ]
T.A. Spedding and K.K. Chan Forecasting demand and inventory management using Bayesian
time series Integrated Manufacturing Systems 11/5 [2000] 331±339
available at the time when the initial forecast is required. Hence, the early forecast must be based
largely on subjective considerations (such as the manager's experience and the general demand of a

similar or comparable product). As the latest information (actual sales demand) becomes available,
the forecasting model is modified with the subjective estimation in the presence of the actual data.
This

Marketing Research For An Auto Spare Parts Company Wants...
Executive Summary
Ted Ralley (Ted), Director of marketing research for an auto spare parts company wants to ensure
the highest level of accuracy for sales projections for the upcoming business year 2008. Ted is aware
that forecasting can be an expensive undertaking if results are inaccurate, as such he utilized the
most accessible work tool, Microsoft Excel time series forecasting method to run several forecasts
using the historical sales data from the previous four years. He was however tentative about the
results, as he is of the view that economic activity and oil prices plays a significant role in auto parts
sales. To test his theory he has decided to generate additional forecasts using econometric variables.
His forecast decisions ... Show more content on Helpwriting.net ...
The report further stated that industry revenue fell during the recession, but has risen in subsequent
years, as growth in the national level of per capita disposable income and corporate profit aided
increased consumer and business spending on auto parts. Director of marketing research for a large
manufacturing company of auto parts, Ted Ralley is tasked with predicting quarterly sales for 2008.
Aware of the cost to the company if an inaccurate forecast is made, Ted is keen on providing the
most accurate predictions. He believes that econometric variables such as oil prices and economic
activities have positive impact auto parts sales, and is of the opinion that these variables are better
indicators of future sales. Historical data were examined to determine whether economic activity
and oil prices have any effect on auto parts sales, and to verify if these factors are in fact better
predictors of auto parts sales. The interpretation of these results will guide the direction of the
company in the next ensuing business year.
Problem
Are economic activity and oil prices better predictors of auto parts sales?
Analysis
The historical auto parts sales data were analyzed using Excel Data Analysis to help predict the
future of auto parts sales, by observing trends and pattern. A line

Sp2750 Unit 1 Work Assignment

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Sp2750 Unit 1 Work Assignment