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7/27/2019 Forecasting Method Toshiba Corporation ation
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Finding a Suitable Forecasting MethodToshiba Corporation in
Bangladesh
Name of the Course:Operation Management
Course ID:MBA-512
Section: 01
Independent University, Bangladesh
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Table of Content
Topics Page no.
11..00..IInnttrroodduuccttiioonn 03
11..11..Origin of the Report 04
11..22.. Objective of the Report 04
11..33.. MMethodology of collecting data 04
22..00.. PPrroodduuccttss OOffToshiba Corporation 04-05
2.1. History Of Toshiba Corporation 05
2.2. Enterprise Resource Planning (ERP) 06
22..33.. AAddvvaannttaaggee ooffHHaavviinngg EERRPP 06
22..44.. EERRPP iinnToshiba Corporation 6-8
2.5. The Lists of some Dhaka divisions sales centers 08
22..66.. DDiissttrriibbuuttiioonn PPrroocceessss ooffToshiba Corporation 9-10
33..00.. DDaattaa DDeessccrriippttiioonn 10-11
44..00.. MMeetthhoodd,, FFoorrmmuullaa aanndd AAnnaallyyssiiss 11
44..11.. NNaavvee MMeetthhoodd 12
44..22.. SSiimmppllee MMoovviinngg AAvveerraaggee ((SSMMOOAA)) 12-14
44..33.. SSiinnggllee EExxppoonneennttiiaall SSmmooootthhiinngg 14
4.4. Regression Analysis 15-16
5.0. Measuring the Forecasting Error by Mean Absolute Deviation (MAD) 16-18
6.0. Results and Discussion 18-19
7.0. Suggestions: 19
8.0. Bibliography: 20
99..00.. LLiissttss ooffddiiffffeerreenntt ssaalleess aanndd sseerrvviiccee cceenntteerrss ooffLLGG ((BBuutttteerrffllyy)) EElleeccttrroonniiccss
LLttdd ooff
DDhhaakkaa ddiivviissiioonn
21-26
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1.0. INTRODUCTION
Operations Management is basically concern with the design,
operations and improvement of the production system that creates the
organizations primary products & services. Apart from the formal
idea, more broadly operations management focuses upon the process
flows of the production, production planning, control&
implementation, supply chains, project management etc of a
particular firm. It also considers the acquisition, development, and
utilization of resources (the inventory system). Ultimately, allows a
firm to deliver its final products and services as per their clients
demands.
Among the versatile activities of the operations management of a
particular firm .Implying of an efficient forecasting techniques to
predict the future demand of the produced final products & as well as
taking the corrective decisions regarding the production planning and
inventory management could be denoted as one of the major tasks of
the operation management team of that firm. Different forecasting
methods are being used in every aspect of todays modern business.
An accurate forecasting tool allows its users to collect data in order to
predict upcoming future events or behaviors. But as a matter of fact
pin pointing forecast is usually impossible and too many factors
cannot be predicted and taken into certainty. Through intensive
study, it has been found that, forecasting study works best while
recognized models are used together. There are various types of
forecasting methods such as: Qualitative study, Time series analysis,
Causal method etc. For this particular assignment, we have used
some methods of Time series analysis like simple moving average,
single exponential smoothing, regression analysis etc. Various models,
mostly quantitative time series models have been used to determine
the forecasted future monthly sales quantity of Laptops for the month
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of January 2013.For the simplicity of the work, actual monthly sales
data have been taken from the beginning month of the year 2012 till
to the last month of the year 2010 (12Months).Finally in order to
predict the forecasted sales quantity for the 13th
month right after theend of year 2012 (January2013). There are various methods of
measuring errors like MAD (Mean absolute deviation), TS (Tracking
signal), MSE (Mean Squared Error), MSD (Mean Squared Deviation)
and MAPE (Mean Absolute Percentage) etc. But we have used only
MAD (Mean absolute deviation) to measure errors. The more methods
we will use to find the forecasting quantity of sold TOSHIBA Laptops
the more accurate our forecast will be. Though in our assignment we
have used limited methods to forecast, but still, it is our belief that the
accuracy level of this particular assignment is satisfactory.
TOSHIBA delivers technology and products remarkable for theirinnovation and artistry - contributing to a safer, more comfortable,
more productive life.
We bring together the spirit of innovation with our passion andconviction to shape the future and help protect the global environment
- our shared heritage.
We foster close relationships, rooted in trust and respect, with ourcustomers, business partners and communities around the world.
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1.1ORIGIN OF THE REPORT
This report is to find out an appropriate forecasting model for use, in
predicting future quantity for production or order. The origin of the data
used in the method is taken from forecast and the actual sales, for the
period January 2012 to December 2012. Finally the forecast is
calculated for the period of January 2012 to produce
1.2OBJECTIVE OF THE REPORT
The objectives or purposes of this report are listed below:
a. To partially fulfill the requirements of the course named Operation
Management (MBA-512).
b. To develop a suitable and accurate forecasting technique to predict
future monthly Laptops sales quantity for the month of January, 2012
and to find out an appropriate forecasting model for use, in predicting
future quantity for production or order for the year 2013(January) of
TOSHIBA.
1.3 METHODOLOGY:
To prepare the report data have been collected from both primary
sources such as collecting sales data of different sales centers of Dhaka
division and also secondary sources such as Web Site ofTOSHIBA.
2.0 PRODUCTS OF TOSHIBA ELECTRONICS LTD
TOSHIBA offers a wide range of products and services, including
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The products:
Computers & Accessories
Laptops & Ultra booksDesktops
Tablets
Computer Accessories
Customize Your Laptop
Computer Research Center
Hard Disk Drives
Consumer electronics
TelevisionsBlu-rayPlayers
DVDPlayers
HDCamcorders
TVAccessories
Video & Electronics Accessories
Elevators and escalators Home appliances (including refrigerators and washing machines IT services, Lighting Materials and electronic components
Medical equipment (including CT and MRI scanners, ultrasoundequipment and X-ray equipment),
Office equipment, Semiconductors Power systems (including electricity turbines, fuel cells and nuclear
reactors)
Power transmission and distribution systems,and TFT displays
http://www.toshibadirect.com/td/b2c/home.to?src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Laptops-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/desktop-family.jsp?family=all-in-one&src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Desktops-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/customlanding.to?page=Tablets&src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Tablets-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/agrp.jsp?src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Accessories-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/customlanding.to?page=customizable_laptops&src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-BTO-_-BuyDirecthttp://us.toshiba.com/computers/research-centerhttp://us.toshiba.com/computers/storagehttp://www.toshiba.com/tai/interstitial-hdtvs.htmlhttp://www.toshiba.com/tai/interstitial-blu-ray-players.htmlhttp://www.toshiba.com/tai/interstitial-dvd-players.htmlhttp://www.toshiba.com/tai/interstitial-camcorders.htmlhttp://us.toshiba.com/tv/accessorieshttp://us.toshiba.com/video-electronics/accessorieshttp://us.toshiba.com/video-electronics/accessorieshttp://us.toshiba.com/video-electronics/accessorieshttp://us.toshiba.com/tv/accessorieshttp://www.toshiba.com/tai/interstitial-camcorders.htmlhttp://www.toshiba.com/tai/interstitial-dvd-players.htmlhttp://www.toshiba.com/tai/interstitial-blu-ray-players.htmlhttp://www.toshiba.com/tai/interstitial-hdtvs.htmlhttp://us.toshiba.com/computers/storagehttp://us.toshiba.com/computers/research-centerhttp://www.toshibadirect.com/td/b2c/customlanding.to?page=customizable_laptops&src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-BTO-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/agrp.jsp?src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Accessories-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/customlanding.to?page=Tablets&src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Tablets-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/desktop-family.jsp?family=all-in-one&src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Desktops-_-BuyDirecthttp://www.toshibadirect.com/td/b2c/home.to?src=MAKP&cm_mmc=TAI-_-Consumer-_-Footer-_-Laptops-_-BuyDirect7/27/2019 Forecasting Method Toshiba Corporation ation
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Control systems (including air-traffic control systems, railwaysystems, security systems and traffic control systems),
Electronic point of sale equipment,
2.1 HISTORY OF TOSHIBA LAPTOPS
1939 to 2000
TOSHIBA was founded in 1939 by the merger ofShibaura Seisakusho
(Shibaura Engineering Works) and Tokyo Denki (Tokyo Electric). ShibauraSeisakusho had been founded as Tanaka Seisakusho by Tanaka Hisashige
in 1875 as Japan's first manufacturer oftelegraph equipment In 1904, it
was renamed Shibaura Seisakusho. Through the first decades of the 20th
century Shibaura Seisakusho had become a major manufacturer of heavy
electrical machinery as Japan modernized during the Meiji Era and became
a world industrial power. Tokyo Denki was founded as Hakunetsusha in
1890 and had been Japan's first producer of incandescent electric lamps. It
later diversified into the manufacture of other consumer products and in
1899 had been renamed Tokyo Denki. The merger of Shibaura and Tokyo
Denki created a new company called Tokyo Shibaura Denki (Tokyo Shibaura
Electric) it was soon nicknamed TOSHIBA, but it was not until 1978 that the
company was officially renamed TOSHIBA Corporation
2010 to present
TOSHIBA announced on May 16, 2011, that it had agreed to acquire all of
the shares of the Swiss-based advanced-power-meter maker Landis+Gyr for
$2.3 billion
In April 2012, TOSHIBA agreed to acquire IBM's point-of-sale business for
$850 million, making it the world's largest vendor of point-of-sale systems.
http://en.wikipedia.org/wiki/Shibaura_Seisakushohttp://en.wikipedia.org/wiki/Tanaka_Hisashigehttp://en.wikipedia.org/wiki/Telegraphhttp://en.wikipedia.org/wiki/Meiji_Erahttp://en.wikipedia.org/wiki/Hakunetsushahttp://en.wikipedia.org/wiki/Shibaurahttp://en.wikipedia.org/wiki/Landis%2BGyrhttp://en.wikipedia.org/wiki/Landis%2BGyrhttp://en.wikipedia.org/wiki/Shibaurahttp://en.wikipedia.org/wiki/Hakunetsushahttp://en.wikipedia.org/wiki/Meiji_Erahttp://en.wikipedia.org/wiki/Telegraphhttp://en.wikipedia.org/wiki/Tanaka_Hisashigehttp://en.wikipedia.org/wiki/Shibaura_Seisakusho7/27/2019 Forecasting Method Toshiba Corporation ation
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In July 2012, TOSHIBA was accused of fixing the prices of LCD panels at a
high level, in US. While such claims are denied by TOSHIBA, they have
agreed to settle alongside several other manufacturers for a total of $571
million
2.2 Enterprise Resource Planning (ERP)
ERP is business term for the wide set of actions supported by multi module
application that helps the organization to manage various functions and
manage with a particular software and stored data with the help of memory.
Various functions like purchasing, order placing, supplier details, customer
details, guest details in hotels and operations.
ERP also includes application modules like human resource management
and financials. Typically ERP system integrates with a relational database
system.
ERP is a consistent platform it guarantees that there is no inconsistency in
the information that is processed in the organization. ERP is essential for
every firm in the world to get competitive advantage and it is necessary to
train the people to use the ERP. In current scenario lots of companies offers
for every industry like ORACLE, SAP and RAMCO etc.
2.3 Advantages of having ERP:
Every department can work independently and they no need to ask for
help.
Guarantees quick process of information flow in the organization.
Reduces the trouble of paper work.
Serving the customers efficiently and provides prompt services to the
consumer and ensures that less error happens while processing
information.
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It helps to gain competitive advantage.
Easy to access the data in the system and user friendly
Saves time.
Stops stealing information
The most important advantage of Enterprise Resource Planning is its
accounting applications. ERP can integrate revenue information, profit
analysis and cost of manufacturing and other financials.
If a company wants to compete with global players, company should start
implementing ERP. With use of ERP any organizations can get reduce the
cost and lots of time will be saved.
2.4 ERP in TOSHIBA
Enterprise Resource Planning of TOSHIBA gives clear idea about their
operational strategy. Currently company uses ORACLE ERP; they started
using this new ERP from August 2009.
In TOSHIBA every year company spends $ 4 billion for their ERP
implementation and giving training for their workers. Previously company
was using GXS ERP solutions for operations and to consolidate their
supplier information. Since 2001 company was using GXS ERP in theircompany, with the use of that TOSHIBA standing as an example of truly
global organization.
They implemented ERP when they want to cut reporting and analysis period,
improve performance, and reduce maintenance costs and to achieve
complete visibility into global stock and marketing and sales costs.
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After implementing ERP their company moved to third place in Plasma TV
market, and they positioned at 5th place in cell phone segment. Company
maintains their all information in ERP. They are updating each and every
outgoing and incoming raw material and finished goods & unfinished goods.Company sends message to every department with the uses of ERP and
company Chief IT Manager Mr. Wang said that by using ERP company
reduced their order placing times and order processing time and he added
that now company are able to process their order without errors.
Since TOSHIBA is an electronic company they started using ERP before 8
years now company enjoys the benefits of Enterprise Resource Planning.
TOSHIBA selected ERP very carefully because they had higher scare of
information stealing but after using ERP they are maintaining their
information in privacy.
There are some disadvantages in implementation of Enterprise Resource
Planning said by Wong; they spend nearly 2 months to train their employees
and implementation ERP needs more money than any other implementation.
But after start using ERP Company gained their investment within 2 yearsand it reduced the risk involvement in information flows. Company delivers
the product in time they started using ERP because it gives clear cut
information all supplies and finished products. With the use of ERP
company utilizes their supply chain management and customer relationship
management very well.
Hence I found that Enterprise Resource Planning helps company to save the
time and to minimize the errors henceforth it leads to improve the
performance of organization and increases the profit of the organization.
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2.5The lists of some Dhaka divisions sales centers are as
follows:
a.Tejgoan,Farmgate
b.Gulsan 1c. IDBd.Elephentroade. Multiplancenterf. Mirpurg.
Malibagh
h.Rampura
i. Uttaraj. Mohammadpurk.Zatrabaril.Tongim.Gazipur
2.6 Distribution Process of TOSHIBA
TOSHIBA is an international brand worldwide. They have their unique
distribution channel for Bangladesh; they market their product through a
domestic renowned company. TOSHIBA import their product from TOKYO
and the product come to the Chittagong port and then it send to the
warehouse, from where the product delivered to the different showroom
located in the country. Lastly the showroom or the direct sales force can sell
to the end user.
Distributors
Rangs Industries Ltd
113-116, Old Airport Road
Tejgaon, Dhaka 1215
Bangladesh
Tel: +880-2- 812 3883~5, 812 3825
Fax: +880-2-912 3583
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3.0 DATA DESCRIPTION
A time series is a time ordered sequence of observations of a variable. Time
series analysis uses only the time series history of the variable beingforecasted in order to develop a model for predicting future values.
Analysis of time series that are requires the analyst to identify the
underlying behavior of the series. This can often be accomplishing by
merely plotting the data and visually examining the plot.
Toshiba Corporation is one of the worlds famous Companies in producing
and supplying digital goods like laptops, pc technology, Blu-ray records, e
Imported Warehouse
TOSHIBAShowroom
TOSHIBA
Showroom
TOSHIBA
Showroom
END-USER
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books records, tablet and other products. The main operation ofToshiba
Corporationis
Transforming Toshiba
Group into a top-level diversified electric/electronic manufacturer withstrong competitive powerToshiba Group aims to become an even stronger
global contender by unleashing our powers of imagination to anticipate,
ahead of others, and capitalize on the coming trends in the world business
environment.
Producing digital products, providing better services to customer to reach
every single home in the world and it ultimately influences the
companys overall turnover, profit and good will. In this module we select
per month TOSHIBA laptops sold quantity as our variable of interest. We
want to identify the seasonal fluctuations pattern in selling quantity of
Laptop as well as trend in data series and then incorporating this
information to develop an appropriate forecasting technique. Here we
use monthly sold quantity or number of pieces sold of Laptops in
Toshiba Corporation from January 2012 to January 2013 which
generates a sample size of 13 observations.
As we said earlier, the data are monthly sold quantity of laptops of
TOSHIBA COPRPORATION Ltd from January 2012 to January 2013.
Thus a total of 13 observations are used in this analysis.
4.0METHOD, FORMULA AND ANALYSIS:
The purpose of this report is to compare the results of several forecasting methods to
determine which model appears most appropriate for the given time series. The use of
historical data contains hidden information which may prove useful in our attempt to
forecast future number of Laptops sold quantity of per month. Our implicit assumption
is that the underlying variables which influence Microwave Ovens sold quantity in the
past will continue to influence in future. The computation method of different
forecasting model is done with the help Microsoft Excel. In this report we examine the
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forecasting accuracy of several models, including Naive, Moving Average, Trend or
Regression Analysis, Exponential Smoothing (single). We have also used MAD as
measures of accuracy.
4.2 SIMPLE MOVING AVERAGE
When demand of a product is neither growing, nor declining rapidly, and it
does not have any seasonal effect, then this method is applicable.
Formula is:
Ft = (At-1 + At-2 +At-3 +----------------------------------+ At-n)/n
Where
Ft = Forecast for period t.
N= No. of periods to be averaged.
At-1 = Actual occurrences in the past period.
At-2 = Actual occurrences in the two period ago.
At-n= Actual occurrences up to n period ago.
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S/N Month Year Period Actual sell
(pcs)
3 Months MA
Forecast (pcs)
1 January 2012 1 245
2 February 2012 2 213
3 March 2012 3 1584 April 2012 4 170 206
5 May 2012 5 194 180
6 June 2012 6 169 174
7 July 2012 7 155 178
8 August 2012 8 254 173
9 September 2012 9 301 193
10 October 2012 10 271 237
11 November 2012 11 224 275
12 December 2012 12 253 265
13 January 2013 13
F13 Jan 2013= 253+224+271 = 250 pcs (When 3 Month MA Forecast)
3
Chart 1: Graphical representation of Simple Moving Average
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10 11 12 13 14
sell
Period
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SINGLE EXPONENTIAL SMOOTHING
Single exponential smoothing calculates data by computing exponentially
weighted averages and provides short-term forecasts. This procedure works
best for data without a trend or seasonal component. Each new forecast is
based on the previous forecast plus a percentage of the difference between
that forecast and the actual value of the series at that point. That is:
Next forecast = Previous forecast + (Actual- Previous forecast)
Where (Actual- Previous forecast) represents the forecast error and is a
percentage of that
Error, then more concisely,
Ft = Ft-1 + (At-1- Ft-1) or Ft = At-1+ (1-) Ft-1
Where,
Ft = Forecast for the next period (week, month, quarter, year, etc.),
Ft-1 = Forecast for the previous period,
At-1 = Actual demand/sales for the previous period
A = Smoothing constant (0-1)
Let,
Smoothing Constant: Alpha () =0.6
Smoothing Constant: Alpha () = 0.4
Smoothing Constant: Alpha () =0.35
Ft = At-1+ (1-) Ft-1 = 0.6 (253) + (1-0.6) 265 = 257.8 or 258 pcs= 0.4 (253) + (1-0.4) 265 =260.2 or 261 pcs= 0.35(253) + (1-0.35) 265 = 260.8 or 261 pcs
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4.4 REGRESSION ANALYSIS
Regression analysis is useful when the trend is increasing or decreasing. The forecast follows
the basic regression formula which is Y= a + bx, where Y is the forecast for the month found
by the value of a, b and period x.
S/N Month Year Period
(X)
Actual sell
(Y)
XY X2
1 January 2012 1 245 245 1
2 February 2012 2 213 426 4
3 March 2012 3 158 474 9
4 April 2012 4 170 680 16
5 May 2012 5 194 970 25
6 June 2012 6 169 1014 36
7 July 2012 7 155 1085 49
8 August 2012 8 254 2032 64
9 September 2012 9 301 2709 81
10 October 2012 10 271 2710 100
11 November 2012 11 224 2464 121
12 December 2012 12 253 3036 144
13 January 2013 13 169
14 X=91 Y=2547 XY=17843 X2
=819
Forecast for the next month would be:
XY n xy
b = X
2- nx
2= 17843-12(7.5)212.25 = - 8.75 or 9 (approximately)
819- 12(7.5) 2
a = y- b x = 212.25- (-9) (7.5) = 144.75
So, Forecast for the next period, Y13 Jan 2013 = a + b (13) {As Y= a + bx}
Y13 Jan2011 = 144.75 + (9)13 = 261.75 or 262 pcs
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Chart 2: Regression Analysis System
5.0 Measuring the Forecasting Error by - Mean Absolute Deviation (MAD)
There may be difference between actual sales and forecast amount. It is necessary not only
to forecast, but also to measure error for future adjustment.
Forecast Error is measured using Mean Absolute Deviation (MAD)
MAD= I At-Ft I
N
Where n= no. of periods.
At = Actual sales in period t.
Ft = Forecasted sales in period t
0
50
100
150
200
250
300
350
Sell
Sell
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S/N Month Year Period Actual
sell
(pcs)
3 Months
MA
Forecast
I At-Ft I
1 January 2010 1 245
2 February 2010 2 213
3 March 2010 3 158
4 April 2010 4 170 206 36
5 May 2010 5 194 180 14
6 June 2010 6 169 174 5
7 July 2010 7 155 178 238 August 2010 8 254 172 82
9 September 2010 9 301 193 108
10 October 2010 10 271 237 34
11 November 2010 11 224 275 51
12 December 2010 12 253 265 12
13 January 2011 13
When Moving Average Length is 3
So, MAD = 365/9 = 40.55 or 41 Pcs
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Graph 3: Mean Absolute Deviation (MAD)
6.0 RESULTS AND DISCUSSION
The observed the results are combined and shown as follows:
Serial
no
Forecasting
methods
Results Error by MAD
01 Single
moving
average
F13 January 2011= 250 pcs
(When 3 Month MA Forecast)
02 Single
exponential
smoothing
258 pcs (When = 0.6)
261 pcs(When = 0.4)
261 pcs(When = 0.35)
Period
0
50
100
150
200
250
300
350
1 23 4 5 6 7 8 9 10 11 12 13
Period
Sell
3 months Forecast
Forecast Error
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03 Regression
analysis
262 pcs