Application of Operations Management Techniques in AsusTek Computers Ltd

8/12/2019 Application of Operations Management Techniques in AsusTek Computers Ltd.

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MBA 512 (Sec-1)

(Operation Management)

Topic:

Application of Operations Management techniques in AsusTek Computers Ltd.

Submitted to:

Dr. M. Ahsan Akhter Hasin

Instructor, Operations Management

Prepared by:

0 S. M. Nahid Newaz ID: 0420185

02 Md. Shamsul Arefin ID: 082033

0 Md. Khalequezzaman ID: 043010

0 Kazi Mahtab Hossain ID: 0820407

Submission Date:12/12/2013


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Table of Contents

No. Topic Page No

1.0 Introduction of Operations Management

1.1Role of Operations Management in organizations1.2Forecasting Method1.3Origin of the report1.4Objective of the report

1-3

2.0 Products of Asus

2.1History of AsusTek Computer Inc.2.2 Distribution Process of AsusTek Computer Inc.

3-5

3.0 Enterprise Resource Planning (ERP)

3.1 Avail of having ERP

3.2 ERP in AsusTek Computer Inc.

5-8

4.0 DATA DESCRIPTION 8

5.0 Procedure, Observation and Data Analysis

5.1 SIMPLE MOVING AVERAGE

5.2 SINGLE EXPONENTIAL SMOOTHING

5.3 REGRESSION ANALYSIS

9-13

6.0 Measuring the Forecasting Error by - Mean Absolute

Deviation (MAD)

13

7.0 RESULTS AND DISCUSSION 15

8.0 Conclusion 16

9.0 Bibliography 17


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Letter of Transmittal

To,

Dr. M. Ahsan Akhter Hasin

School of Business

Independent University, Bangladesh

Subject: Letter of Transmittal

Dear sir,

We take pleasure in submitting for your consideration on the Assignment on Application of

Operations Management techniques in HP Bangladesh.

We would like to express our gratitude to our instructor Dr. M. Ahsan Akhter Hasin, who gave

us this opportunity to prepare this assignment.

We commend this assignment to you to give high priority to its response to the findings and

recommendations.

Yours sincerely,

S. M. Nahid Newaz

ID: 0420185

Md. Shamsul Arefin

ID: 0820330

Md. Khalequezzaman

ID: 0430102

Kazi Mahtab Hossain

ID: 0820407


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1.0 Introduction of Operations Management

Operations management is an area of management concerned with overseeing, designing, and

controlling the process of production and redesigning business operations in the production of

goods or services. It involves the responsibility of ensuring that business operations areefficient in terms of using as few resources as needed, and effective in terms of meeting

customer requirements. It is concerned with managing the process that converts inputs in the

forms of materials, labor, and energy into outputs in the form of goods and or services.

1.1 Role of Operations Management in organizations

Operations management provides versatile activities of a particular organization. Operations

Management Implies 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. It 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.

1.2 Forecasting Method

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, andRegression Analysisetc. Various models, mostly quantitative

time series models have been used to determine the forecasted future monthly sales quantity

of Laptops for the month of November 2013. For the simplicity of the work, actual monthly

sales data have been taken from the November month of the year 2012 till to the second last

month of the year 2013 (12Months). 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


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only MAD (Mean Absolute Deviation)to measure errors. The more methods we will use to

find the forecasting quantity of sold Asus Laptops the more accurate our forecast will be.

Although 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.

AsusTek Computer Inc.

AsusTek Computer Inc. pursues technological and aesthetic perfection throughcontinuous innovation. We place ourselves in our customers shoes to develop a deep

understanding of, and genuine empathy for, their needsenabling us to create user

experiences that transcend the norm.

AsusTek Computer Inc. Places great importance on employee virtues. Fivecharacteristics have been identified as key to the smooth development of processes and

relationships. The five ASUS virtues are: Humility, Integrity, Diligence, Agility and

Courage.

AsusTek Computer Inc. a technology-oriented company with a global staff of more thanten thousand and blessed with one of the world's top R&D teams, is renowned for high-

quality products and cutting-edge innovation. As a leading company in the new digital

era, ASUS offers a complete product portfolio to compete in the new millennium.


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1.3 Origin of the report

This production research report study is all about an appropriate forecasting model for a

specific companyAsusTek Computer Inc. Asia Pacific- Bangladesh, in predicting future

quantity for production or order. The origin of the data used in the method was takenfrom forecast and the actual sales, for the period November 2012 to October 2013.

Finally the forecast is calculated for the period of November 2013.

1.4 Objective of the report

The purposes of this report are:

1. To develop a suitable and accurate forecasting technique to predict future monthlyLaptops sales quantity for the month of December, 2013 and to find out an

appropriate forecasting model to use in predicting future quantity for production or

order of the year 2013 (December) of Asus.

2. To partially fulfill the requirements of the course named Operation Management.

2.0 Products of Asus

Asus offers a wide range of products and services.

The products line:

Computers & Accessories

Laptop Desktop Mobile Phones Tablets Personal digital assistants (PDAs), Servers, Computer monitors,


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Motherboards, Graphics cards, Sound cards, Optical disc drives, Computer networking devices, Computer cases, Computer components and Computer cooling systems.

2.1 History of AsusTek Computer Inc.

AsusTek Computer Inc. was founded in Taipei in 1989 by T.H. Tung, Ted Hsu, Wayne Hsieh

and M.T. Liao, all four having previously worked at Acer as computer engineers. At this

time, Taiwan had yet to establish a leading position in the computer-hardware business. Intel

Corporation would supply any new processors to more established companies like IBM first,

and Taiwanese companies would have to wait for approximately six months after IBM

received their engineering prototypes. By 2009, AsusTek Computer Inc. was receiving Intel

engineering sample ahead of its competitor.

2.2 Distribution Process of AsusTek Computer Inc.

Asus is an international brand worldwide. They have their unique distribution channel for

Bangladesh. They market their product through a domestic renowned company. Asus import

their product from China 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.


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Head Office (Dhaka) Branch Office (Dhaka)

AsusTek Computer Inc. AsusTek Computer Inc.

19/2, West Panthapath, BCS Computer City,

Salim Center (3rd~5th & 7th floor), IDB Bhaban (1st floor),

Dhanmondi, Dhaka-1205. Shop no. SR-123/6,

Tel.: (88-02) 8123273~5, Agargaon, Dhaka.

8123283~4, Phone: (88-02) 8123281,

Fax: (88-02) 9145687, 9120045 9133776.

Mailto: [email protected]

Distributor

Global Brand Pvt. Ltd.

19/2, West Panthapath (3rd~5th & 7th floor)

Dhanmondi, Dhaka-1205, Bangladesh

E-mail: [email protected],

[email protected],

3.0 Enterprise Resource Planning (ERP)

Systems integrate internal and external management of information across an entire

organizationembracing finance/accounting, manufacturing, sales and service, customerrelationship management, etc. ERP systems automate this activity with an integrated software

application. ERP facilitates information flow between all business functions inside the

organization, and manages connections to outside stakeholders.


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Enterprise system software is a multi-billion dollar industry that produces components that

support a variety of business functions. IT investments have become the largest category of

capital expenditure in United States-based businesses over the past decade. Enterprise

systems are complex software packages that offer the potential of integrating data and

processes across functions in an enterprise. Although the initial ERP systems focused on

large enterprises, there has been a shift towards smaller enterprises also using ERP systems.

Organizations consider the ERP system a vital organizational tool because it integrates varied

organizational systems and enables flawless transactions and production. However, an ERP

system is radically different from traditional systems development. ERP systems can run on a

variety of computer hardware and network configurations, typically employing a database as

a repository for information.

3.1 Avail 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.

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.


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3.2 ERP in AsusTek Computer Inc.

Enterprise Resource Planning of AsusTek Computer Inc. gives clear idea about their

operational strategy. Currently company uses ORACLE ERP; they started using this new

ERP from August 2009.

In AsusTek Computer Inc. every year company spends $ 3.7 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 their company, with the use of that AsusTek Computer Inc.

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.

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 AsusTek Computer Inc. is an electronic company they started using ERP before 8 years

now company enjoys the benefits of Enterprise Resource Planning. AsusTek Computer Inc.

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 years and 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


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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.

4.0 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 being forecasted in order

to develop a model for predicting future values. Analysis of time series that are requires the

analyst to identify the underlyingbehavior of the series. This can often be accomplishing by

merely plottingthe data and visually examining the plot.

ASUSis one of the worlds famous Companies in producing and supplying digital goods like

laptops, pc technology, server, tablet and other products. The main operation of ASUS is

Transforming ASUS into a top-level innovative and diversified electric/electronic

manufacturer with strong competitive power. ASUS 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.

Here we use monthly sold quantity or number of pieces sold of Laptops in ASUS from

November 2012 to October 2013 which generates a sample size of 12 observations.

As we said earlier, the data are monthly sold quantity of laptops of ASUS from November2013 to October 2013. Thus a total of 12 observations are used in this analysis.


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5.0 Procedure, Observation and Data 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 toforecast future number of Laptops sold quantity of per month. Our implicit assumption is that

the underlying variables which influence Laptops 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 forecasting accuracy of several models,

including Moving Average, Regression Analysis and Exponential Smoothing (single). We

have also used MAD as measures of accuracy.

5.1 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.

S/NMonth Year Period Actual sell

(pcs)

3 Months MA

Forecast (pcs)

1 November 2012 1 120 -


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F13 Nov. 2013 = 254+290+271 = 272 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

SIMPLE MOVING AVERAGE

Period sell

2 December 2012 2 145 -

3 January 2013 3 117 -

4 February 2013 4 153 127

5 March 2013 5 178 138

6 April 2013 6 142 149

7 May 2013 7 165 158

8 June 2013 8 186 162

9 July 2013 9 200 164

10 August 2013 10 254 184

11 September 2013 11 290 213

12 October 2013 12 271 248


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5.2 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 ofthe 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 percentageof 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

= Smoothing constant (0-1)

Let,

Smoothing Constant: Alpha () = 0.60



Ft = At-1+ (1-) Ft-1 = 0.60 (271) + (1- 0.60) 248 = 261.8 or 262 Pcs.

= 0.40 (271) + (1- 0.40) 248 =257.2 or 258 Pcs.

= 0.25(271) + (1- 0.25) 248 = 253.75 or 254 Pcs.


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5.3 REGRESSION ANALYSIS

Regression analysis is useful when the trend is increasing or decreasing. The forecast

followsthe basic regression formula which is Y= a + bx, where Y is the forecast for the

month foundby the value of a, b and period x.

S/N Month Year Period

(X)

Actual sell

(Y)

XY X2

1 November 2012 1 120 120 1

2 December 2012 2 145 290 4

3 January 2013 3 117 351 9

4 February 2013 4 153 612 16

5 March 2013 5 178 890 25

6 April 2013 6 142 852 36

7 May 2013 7 165 1155 49

8 June 2013 8 186 1488 64

9 July 2013 9 200 1800 81

10 August 2013 10 254 2540 100

11 September 2013 11 290 3190 121

12 October 2013 12 271 3252 144

X=78 Y=2221 XY=1654

0

X2 =650

Forecast for the next month would be:

XY n x y

b= X2 n x2 = 16540 12 (6.5) 185.08 = 14.7116 or 15 (approximately)

650 12 (6.5) 2


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a = y - b x = 185.08 - (15*6.5) = 87.58 or 88

So, Forecast for the next period, Y13 Nov. 2013= a + b (13) {As Y= a + bx}

Y13 Nov. 2013= 88 + 15*13 = 283 Pcs.

Graph 2: Regression Analysis System

6.0 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= |At-Ft| / 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


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S/N Month Year Period Actual

sell

3 Months MA

Forecast (Pcs.)|At-Ft |

1 November 2012 1 120 -

2 December 2012 2 145 -

3 January 2013 3 117 -

4 February 2013 4 153 127 36

5 March 2013 5 178 138 14

6 April 2013 6 142 149 5

7 May 2013 7 165 158 23

8 June 2013 8 186 162 82

9 July 2013 9 200 164 108

10 August 2013 10 254 184 34

11 September 2013 11 290 213 51

12 October 2013 12 271 248 12

Total Deviation 310

When Moving Average Length is 3

So, MAD = 310/9 = 34.44 or 35 Pcs. (Approximately)


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Graph 3:Mean Absolute Deviation (MAD)

7.0 RESULTS AND DISCUSSION

The observed the results are combined and shown as follows:

Serial

no

Forecasting

methods

Results Error by MAD

01 Simple

Moving

Average

F13 November 2013= 272pcs

(When 3 Month MA Forecast)

02 Single

Exponential

Smoothing

262 pcs (When = 0.60)

258 pcs (When = 0.40)

254 pcs (When = 0.25)

0

50

100

150

200

250

300

350

1 2 3 4 5 6 7 8 9 10 11 12 13

Period Sell 3 months Forecast Forecast Error


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03 Regression

Analysis

283 pcs

The purpose of forecasting is to reduce the risk in decision-making. For our chosen company

ASUS, appropriate forecasting technique examining help to identify the peak order-

producing-delivering-customer service season, and help managers plan accordingly to handle

the peak load very effectively and efficiently. Forecasting also helps in scheduling staff and

resources and in financial planning. To forecast future quantity for producing or quantity for

order to sell of any home products or appliances; it must have a forecasting method that is

reliable and accurate. It must also minimize costs, of course, but lowest cost is not an

absolute priority, given the serious financial ramifications of forecast error. The forecast

should be cost-effective; the benefits should overweight the costs. Therefore it makes a great

deal of sense to experiment with various forecasting models to determine which model

generates the most reliable results.

8.0 Conclusion

To that end this report examines the forecasting accuracy of several models, including ,

Simple Moving Average, Exponential Smoothing, Regression Analysis, By examining these

models using MAD, as measures of accuracy, our evaluation shows that Regression analysis

is giving moderate result(rationally acceptable ) in terms of the original data and resulting

less error comparatively to other forecasting techniques .


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9.0 Bibliography

Sources used in this report have followed theories and information from the following books

and corporate office:

1. Chase; Aquilano and Jacobs (2000), Production and Operations Management:

Manufacturing and services(8thed.), Irwin- McGraw Hill.

2. ASUS Bangladesh (2013), ASUS Products. Retrieved November 26, 2013, from

http://www.asus.com/bd/.

Documents

Application of Operations Management Techniques in AsusTek Computers Ltd