26762598 trend analysis in maruti suzki

8/2/2019 26762598 Trend Analysis in Maruti Suzki

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BIRLA INSTITUTE OF TECHNOLOGY NOIDA EXTENSION CENTRE UTTAR PRADESH

PROJECT

ON TIME SERIES

OFMARUTI SUZUKI INDIA LTD.

SUBMITTED BY:-

AJEET KUMAR MBA/4547/10

AKHIL KUMAR MBA/4548/10

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ACKNOWLEDGEMENT

We would like to express our sincerest gratitude to all the people whohave contributed towards the successful completion of our project.

We would like to extend our heartfelt thanks to our faculty for nurturing acongenial yet competitive environment in the department, whichmotivates all students to pursue higher goals. Our sincere thanks for hisguidance and expertise in making this project a reality.

Last but not the least, we would like to extend our thanks to all theteaching and non-teaching staff members of our department, and to all

our colleagues who helped us with the ever daunting task of gatheringinformation for the completion of project.

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CERTIFICATE

This is certify that the major project report entitled Time series of

Maruti Suzuki India Limited has been submitted to Birla Institute Of

Technology, Noida by mutual cooperation of Ajeet kumar(Roll No: -

4547) & Akhil kumar(Roll No:-4548).

Ritu Jain

Faculty of

QTM

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TABLE OF CONTENTS

S.NO. TOPICS PAGE NO.1. Introduction: Project Overview 5 7

2. About the company: Maruti SuzukiIndia Limited

8 13

3. Problem Faced 14

4. Various methods of Trend Analysis 14 - 24

5. Solutions to the Problems 25

6. Limitations of the Applied Methods 26 28

7. Appendix 29 - 30

8. Bibliography 31

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PROJECT OVERVIEW:

TIME SERIES: A time series may be defined as a sequence of repeated measurement of thevariables made periodically through time.

-Cecil H. Mayers

COMPONENTS OF TIME SERIES: Secular Trend (Long term variations or secular variations)

Seasonal variations Cyclical variations or cyclic variations

Irregular variations

TREND ANALYSIS:

It refers to the concept of collecting information and attempting to spot a pattern, ortrend, in the information. In some fields of study the term trend is often used topredict future events.

It is the process of analyzing companys financial ratios over time. An aspect oftechnical analysis that tries to predict the future movement of a stock based on pastdata. Trend analysis is based on the idea that what has happened in the past givestraders an idea of what will happen in the future.

There are three main types of trends: short-, intermediate- and long-term.Trend analysis tries to predict a trend like a bull market run and ride that trend untildata suggests a trend reversal. Trend analysis is helpful because moving withtrends, and not against them, will lead to profit for an investors.

The trend analysis module allows you to plot aggregated response over time. This isespecially valuable, if you are conducting a long running survey and would like tomeasure differences in perception and responses over time.

The following data points can be measured on Y-axis:

1. MEAN and MEAN PERCENTILE2. STANDARD DEVIATION and VARIANCE

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The TIME FACTOR on X axis can have the following granularity:

1. Daily

2. Weekly

3. Monthly

4. Quarterly (Jan-Mar, Apr-Jun, Jul-Sept, Oct-Dec)

5. Yearly

Trend Analysis can be extremely valuable as an early warning indicator of potentialproblems and issues with product line and service level changes that impactcustomers. If you see a dip in the "mean" for a Continuous Variable satisfactionquestion after a particular "marketing event" you can immediately start investigatingthe dip and explore causes of the decrease in satisfaction levels. It can also be usedto gauge response rates over time.

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OBJECTIVES OF MEASURING TREND

There are four main objectives of measuring Trend in a time series data:

1. To study past growth or decline of the series. On ignoring the short term

fluctuations, trend describes the basic growth or decline tendency of the data.2. Assuming that the same behavior would continue in future also, the trend

curve can be extended for forecasting future.3. In order to analyze the influence of other factors the trend may first be

measured and then eliminated from the observed values.4. Trend values of two or more time series can be used for their comparison.

METHODS OF MEASURING TREND:

There are four methods of measuring trend ant they are:

Free Hand method or Graphical method. Semi-Average Method.

Method of Moving Averages.

Method of Least squares.

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MARUTI SUZUKI INDIA LTD.

COMPANY HISTORY:

Maruti Suzuki India Ltd. (MSIL) was established in Feb.1981 through an act ofparliament as a government company with Suzuki Motor Corporation of Japanholding 26% stake. The joint venture agreement was signed between government ofIndia and Suzuki Motor Company in October1982. Maruti Suzuki India Ltd., formallyMaruti udyog ltd., a subsidiary of Suzuki Motor Corporation of Japan, is Indiaslargest passenger car company accounting for over 50% of the domestic car market.More than half the no. of cars sold in India wears a Maruti Suzuki batch. It offers 11different ranges of cars. Since inception, Maruti produced and sold over 7.5 millionvehicles in India and exported over 5 lakh units to Europe and other countries.

PRODUCTS:

The company has the portfolio of 11 brands including

MARUTI 800

MARUTI OMNI

ZEN

ALTO

WAGON-R

GYPSY

ESTEEM

BALENO

VERSA

SX4

SWIFT

GRAND VITARA

DEZIRE

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EQUITY STRUCTURE OF MARUTI:

54.21% of SUZUKI MARUTI CORPORATION

45.79% of OTHERS (Financial institutions mutual funds, banks, public etc.)

EQUITY STRUCTURE

54.21%

45.79%SUZUKI MOTO

CORPORATIO

OTHERS

COMPANY AT A GLANCE:

Cars produced and sold : 7,000,000

Domestic cars sales for 2007-08 : 711818 Car exports for 2007-08 : 53024 Recorded profit after tax in 2007-08 : 17308 Total income in 2007-08 : 188238 No. of Maruti Suzuki sales outlets in 393 towns and cities : 600 No. of workshops that provide customers with maintenance

support in 1220 cities : 2628 Employee strength till March 2008 : 7090

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One million promise

Maruti has laid down a clear road map to achieve an annual sale of 1 million cars inthe domestic market and 2 lakh exports by 2010-11. In addition, the managementteam at Maruti Suzuki has identified specific initiatives to serve customers better and

ensure their leadership in the future.

COMPANYS STRENGTH:

One of the Marutis great strength is that they have internal resources to finance bothR & D expansion as well as capital and investments. The higher interest rates andthe risk of making large borrowings till finance capital cost will not affect them.

Maruti Suzuki is recently being rated as the 4th mostreputed automobile company in the world. This has happened

because of the contribution of all the stake holders of Maruti.

BUSINESS HIGHLIGHTS OF MSIL:

SALES GROWTH:

SALES GROWTH

22.60%

11.90%

19.50%

38.60%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

2005 2006 2007 2008

YEAR

SALESGROWTH

SALES GRO

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EARNING PER SHARE & BOOK VALUE

EARNING PER SHARE & BOOK VALUE

18.841.2

59.9

124

189

297

0

50

100

150

200

250

300

350

2003 - 04 2005 - 06 2007 - 08

YEAR

EPS&BOOKVAL

EARNING PE

SHARE

BOOK VALU

EXPORTS & DOMESTIC:

EXPORTS & DOMESTIC

51175 34784 53024

420947

527038

711818

0

100000

200000

300000

400000

500000

600000

700000

800000

2003 - 04 2005 - 06 2007 - 08

YEAR

EXPORTS&DOMEST

IC

EXPORTS (uni

DOMESTIC (u

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PROFIT AFTER TAX AND NET SALES:

PROFIT AFTER TAX & NET SALES

5422 1189117308

90812

120034

178603

0

20000

40000

60000

80000

100000

120000

140000

160000

180000200000

2003 - 04 2005 - 06 2007 - 08

YEAR

PAT&NETSALES

PROFIT AFTER TAX

Mn)

NET SALES

TREND ANALYSIS OF MARUTI SUZUKI

Factors Year 2004 2005 2006 2007 2008

Sales 2089.4 2562.5 2867.1 3425.3 4747.3

Sales Growth 0.226 0.119 0.195 0.386

COGS 1539.7 1939.3 2147.4 2427.1 3500.2

COGS as a % ofSales 0.737 0.757 0.749 0.709 0.737

SG&A 242.6 234.7 289.6 371.8 521.3

SG&A % of Sales 0.1161 0.0916 0.101 0.1085 0.1098

R&D$

- $ - $ -$

-$

-

R&D % of Sales 0 0 0 0 0

Operating Income 307.1 388.5 430.1 626.4 725.8

Operating Margin 0.147 0.152 0.15 0.183 0.153

Employees 3334 3453 7090Revenue perEmployee 626.7 742.1 #DIV/0! #DIV/0! 670

Net PPE 446.8 447.5 459.8 679.4 1025.4

Asset Utilization 0.21 0.17 0.16 0.2 0.22

Inventory 101.2 152.6 197.7 161.3 258.6

COGS/Inventory 15.21 12.71 10.86 15.05 13.54

365 365 365 365 365

DII 24 29 34 24 27

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Accounts Receivable 164.6 144.3 154.1 182.1 173.2

Sales/AR 12.69 17.76 18.61 18.81 27.41

365 365 365 365 365

DSO 29 21 20 19 13

From the above trend it has been found that the

1. The sales of the company have increased from 19.5% in 2007 to 38.6% in2008.

2. Cost of goods sold also increased from 70.9% in 2007 to 73.7% in 2008.3. Operating margin trended negatively from 18.3% to 15.3%.4. Number of employees and revenue from the employees also increased from

2007 to 2008.5. Also there is increment in asset utilization, net PPE, inventory and Days in

inventory.

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PROBLEMS FACED: -

Following problems are found during the study of trend analysis onMaruti Suzuki India Limited (MSIL).

1.) Cost of Goods Sold has been increased from 2004 to 2008 i.e., the expensesincurred for the production of items has increased during this particular period oftime.

2.) Days in Inventory has also been increased from 2007 to 2008 i.e., time ofproduction has increased even after the implementation of new techniques andtechnologies in production process.

Methods under TREND ANALYSIS on basis of which problems arestudied:

1.) By Graphical Method2.) By Least squares method3.) By Semi-averages and4.) By Moving Averages

1.) BY GRAPHICAL METHOD:

The simplest, quickest and easiest method of estimating the trend is to plot theoriginal data on a graph and then to draw a smooth curve through the points so thatit may accurately describe the general long run tendency of the data.

(i) Trend Analysis of COGS using Graphical Method

Year COGS (Y)

2004 1539.7

2005 1939.3

2006 2147.4

2007 2447.1

2008 3500.2

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Trend Showing COST OF GOODS SOLD

0

500

1000

1500

2000

2500

3000

3500

4000

2004 2005 2006 2007 2008

YEARS

CO

COGS(Y)

Linear (COGS(Y))

(ii) Trend Analysis of DII using Graphical Method

Year DII (Y)

2004 24

2005 29

2006 34

2007 24

2008 27

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Trend Showing DAYS IN INVENTORY:

0

5

10

15

20

25

30

35

40

2004 2005 2006 2007 2008

YEARS

DI DII (Y)

Linear (DII (Y)

2.) METHOD OF LEAST SQUARES

Method of Least Squares is a mathematical method which is most widely used andwith its help a trend line is fitted to the data in such a manner that the following twoconditions are satisfied.

(1) (Y-Yc) = 0i.e., the sum of deviations of the actual values of Y and the computed values of Y iszero.(2) (Y-Yc)

2 is least.i.e., the sum of the squares of the deviations of the actual and computed values isleast from this line and hence the name method of least squares. The line obtainedby this method as the line ofbest fit.

The straight line trend is represented by the equation Yc = a + bXWhere,Yc = designates the trend values to distinguish them from the actual Y valuesa = Y intercept or the computed trend figure or the Y variable when X = 0b = slope of the trend line or amount of change in Y variable that is associated

with a change of one unit in X variable.X = represents time

Following points should be specified when any straight line trend is fitted:

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1. Which year was selected as the origin?2. What is the unit of time represented by X? Is it half year, one year or five

years?3. In what kind of units is Y being measured? Is it production in tones, sales in

rupees, price in rupees, and employment in thousands of workers?

Formula for constants a and b

a = Y/Nb = XY/X2

Where,N = represents number of years (months or weeks) for which data are given.The constant a is simply equal to the mean of Y values and the constant b givesthe rate of change.

(i) Trend Analysis of COGS using Least Squares Method

Year COGS (Y) X XY X 2 Yc

2004 1539.7 -2 -3079.4 4 1428.98

2005 1939.3 -1 -1939.3 1 1871.86

2006 2147.4 0 0 0 2314.74

2007 2447.1 1 2447.1 1 2757.62

2008 3500.2 2 7000.4 4 3200.5

N = 5 Y = 11573.7 XY = 4428.8 X2 = 10

Here,Arithmetic mean = 10030/5

= 2006Yc = a + bX

a = Y/N= 11573.7/5= 2314.74

b = XY/X2

= 4428.8/10= 442.88

Linear trend by the Method of Least Squares

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0

500

1000

1500

2000

2500

3000

3500

4000

2004 2005 2006 2007 2008

YEAR

COGS

a

COGS(Y)

Yc

Future Analysis:Yc = a + bX= 2314.74 + 442.88(2009-2006)= 3643.38

This particular data shows that in coming year, COGS will increase which will effectthe revenue of the company.

(ii) Trend Analysis of DII using Least Squares Method

Year DII (Y) X XY X 2 YC

2004 24 -2 -48 4 27.4

2005 29 -1 -29 1 27.5

2006 34 0 0 0 27.6

2007 24 1 24 1 27.7

2008 27 2 54 4 27.8

N = 5 Y = 138 XY = 1 X2 = 10

Here,Arithmetic mean = 10030/5

= 2006Yc = a + bX

a = Y/N= 138/5

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= 27.6b = XY/X2

= 1/10= 0.10

Linear trend by the Method of Least Squares

0

5

10

15

20

25

30

35

40

2004 2005 2006 2007 2008

YEARS

DI DII (Y)

YC

Future Analysis:Yc = a + bX

= 27.6 + 0.10(2009-2006)= 27.9

This particular data also shows that in coming future there will be an increase in DIIwhich will result in delay in production of items

3.) Method of Semi-averages

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The important step of Semi-averages method is that whenever this method is used,the given data is divided into two parts, preferably with the same number of years.

Procedure:

If we are given data even number of years then simply divide the data into twoequal halves. For example, the data are from 2000 to 2005, i.e., over a periodof 6 years, the two equal parts will be each three years, i.e., from 2000 to2002 and from 2003 to 2005.

In case of odd number of years like 5, 9, 13, etc. two equal parts can be madesimply by omitting the middle year. For example, if data are given for 5 yearsfrom 2000 to 2004, the equal parts would be from 2000 to 2001 and from2003 to 2004-the middle year 2002 will be omitted.

Now arithmetic mean is calculated for the two equal parts to get two points.

Each point is plotted at the mid-point of the class interval covered by therespective part and then the two points are joined by a straight line

This gives us the required trend line.

(i) Trend Analysis of COGS using Method of Semi-averages

Year COGS (Y) Semi-average(year)

Semi-average(COGS)

2004 1539.7

2004.5 1739.5

2005 1939.3

2007 2447.1

2007.5 2973.65

2008 3500.2

Here,Average of 2004 and 2005 is 2004.5Average of 2007 and 2008 is 2007.5Average of 1539.7 and 1939.3 is 1739.5Average of 2447.1 and 3500.2 is 2973.65

Trend by the Method of Semi-averages

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0

500

1000

1500

2000

2500

3000

3500

4000

2004 2005 2007 2008

YEARS

COG COGS (Y)

Linear (COGS (Y)

Future analysis:From the above graph, it is shown that due to increase in the trend line values therewill be hike in COGS in coming future.

(ii) Trend Analysis of DII using Method of Semi-averages

Year DII (Y) Semi-average(year)

Semi-average(DII)

2004 242004.5 26.5

2005 29

2007 24

2007.5 25.5

2008 27

Here,

Average of 2004 and 2005 is 2004.5Average of 2007 and 2008 is 2007.5Average of 24 and 29 is 26.5Average of 24 and 27 is 25.5

Trend by the Method of Semi-averages

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0

5

10

15

20

25

30

35

2004 2005 2007 2008

YEARS

DII

DII (Y)

Linear (DII (

Future analysis:By observing the trend line it may be predicted that there would be more chances ofDII to increase in coming future which will result in delay production.

4.) Method of Moving Averages

In the method of Moving Averages, when a trend value is to be determined, theaverage value for a number of years (or month or weeks) is secured and thisaverage is taken as the normal or trend value for the unit of time falling at the middleof the period covered in the calculation of the averages.

Effect of averaging:

To give a smoother curve

Lessening the influence of the fluctuations that pull the annual figure awayfrom the general trend.

We have three types of Moving Averages Method:1. 3-yearly moving average2. 5-yearly moving average and3. 8-yearly moving average

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Note: - It is necessary to select a period for moving average which coincides withthe length of the cycle; otherwise the cycle will not be entirely removed. The periodof moving average is to be decided in the light of the length of the cycle.

(i) Trend Analysis of COGS using 3-yearly Moving AverageMethod

Year COGS (Y) 3-Yearlytotals

3-yearly movingaverage

2004 1539.7_ _

2005 1939.3 5626.4 1875.466667

2006 2147.4 6533.8 2177.933333

2007 2447.1 8094.7 2698.233333

2008 3500.2 _ _

Here,5626.4 is the 3-yearly moving totals of the values given corresponding to the years2004, 2005 and 2006.Similarly for the 3-yearly moving averages

Trend by the Method of 3-yearly Moving Average

0

500

1000

1500

2000

2500

3000

3500

4000

2004 2005 2006 2007 2008

COGS

COGS (

Linear

Future analysis:From the above graph, it is observed that due to increase in the trend line valuesthere will be hike in COGS in coming future which will affect the companys revenue.

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(ii) Trend Analysis of DII using 3-yearly Moving Average Method

Year DII (Y) 3-yearly

totals

3-yearly moving

average

2004 24_ _

2005 29 87 29

2006 34 87 29

2007 24 85 28.33333333

2008 27_ _

Here,87 is the 3-yearly moving totals of the values given corresponding to the years 2004,2005 and 2006.Similarly for the 3-yearly moving averages.

Trend by the Method of 3-yearly Moving Average

0

5

10

15

20

25

30

35

40

2004 2005 2006 2007 2008

DII

DII (Y)

Linear (DII

Future analysis:By observing the trend line it is being predicted that there would be more chances ofDII to increase in coming future which will result in delay production in the company.

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HOW TREND CAN BE USEFUL IN COPING UP THEPROBLEM

As can be seen that trend has helped us to measure the growth or decline of thevarious problems faced by the company and hence is describing the basic growth ordecline tendency of the data.By assuming that the same behavior would continue infuture also, the trend curve can be extended for forecasting future.

Problem of increased COGS: -

As can be seen from the trend Cost of Goods Sold has increased from 2004to 2008. Hence the expenses incurred by the company in producing the itemsthat it sold during a particular period have been increased. This increment isvery large and as the price of steel is increasing there is the possibility ofincrement in the prices of raw material.

COGS will increase in the future in a very steep manner. Being amanufacturing company it is very important for Maruti to lower the value ofCOGS. This can be lowered by strategic sourcing and procurement i.e. bycontinuously improving and re-evaluating the purchasing activities of acompany and also by acquisition of goods and/or services at the best possibletotal cost of ownership, in the right quantity and quality, at the right time, atthe right place and from the right source for the direct benefit or use ofcorporations, or individuals, generally via a contract.

Problem of hiked DII: -

Days in inventory is the time period from the date of execution of the offer topurchase with the employee through the resale closing date. As the days ininventory have increased from 24 in 2007 to 27 in 2008 that means the timeof production has increased even after the implementation of new techniquesand technologies in production process.

DII will also increase in future which again is a bad news for company.According to the trend in future the value can go from 27 to as high as 30 andthis needs to be lowered so as to get more revenue. This can be done byensuring better inventory management. Effective Inventory Managementenables an organization to meet or exceed customers' expectations ofproduct availability while maximizing net profits or minimizing costs.

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LIMITATIONS OF TREND ANALYSIS:

GRAPHICAL METHOD

1.) Subjective method and hence not reliable: -

This method is highly subjective because the trend line depends on the personaljudgment of the investigator and, therefore, different persons may draw differenttrend lines from the same set of data. Moreover, the work cannot be left to clerksand it must be handled by skilled and experienced people who are wellconversant with the history of the particular concern.

2.) Prediction made are not of much value: -

Since freehand curve fitting is subjective, it cannot have much value if it is usedas a basis for prediction.

3.) This method appears simple and direct. However, it is very time consuming toconstruct a freehand trend if a careful and a conscientious job is done.

It is only after long experience in trend fitting that a statistician should attempt tofit a trend line by inspection.

METHOD OF LEAST SQUARES1.) Great care has to be exercised in selecting the type of trend curve to be fitted,

i.e., linear, parabolic or some other type. Carelessness in this respect may leadto fallacious results.

2.) This method is more tedious and time-consuming compared to other methods.

3.) Predictions are based only on long-term variations, i.e., trend and the impact ofcyclical, seasonal and irregular variations is ignored.

4.) Being a mathematical method it is not flexible-the addition of even one moreobservation makes it necessary to do all the computations again.

5.) The method cannot be used to fit the growth curves like Gompertz curve, logisticcurve, etc.

Hence, mathematically methods of fitting trend are not foolproof-in fact; they canbe the source of some of the most serious errors that are made in statistical

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work. They should never be used unless rigidly controlled by a separate logicalanalysis. Trend fitting depends upon the judgment of the statistician, and askillfully made freehand sketch is often more practical than a refinedmathematical formula.

METHOD OF SEMI-AVERAGES

1.) Gives only linear trend of the data irrespective of whether it exists or not.

2.) Only a crude method as effects of other components might be completelyeliminated or not.

3.) The limitations of arithmetic averages shall automatically apply. If there areextremes in either half or both halves of the series, then the trend line will not

give a true picture of the growth factor. This danger is greatest when the timeperiod represented by the average is small. Consequently, trend values obtainedare not precise enough for the purpose either of either of forecasting the futuretrend or of eliminating trend from original data.

For the above reasons if the arithmetic averages of the data are to be used inestimating the secular movement. It is sometimes better to use moving averagesthan semi-averages.

METHOD OF MOVING AVERAGES

1.) Trend values cannot be computed for all the years. The longer the period ofmoving average, the greater the number of years for which the trend valuescannot be obtained. For example, n a three-yearly moving average, trend valuescannot be obtained for the first year and last year, in a five-yearly movingaverage for the first two years and the last two years, and so on.

2.) Great care has to be exercised in selecting the period of moving average. Nohard and fast rules are available for the choice of the period and one has to usehis own judgment.

3.) Since the moving average is not represented by a mathematical function thismethod cannot be used in forecasting which is one of the main objectives oftrend analysis.

4.) Although theoretically we say that if the period of moving average happens tocoincide with the period of cycle, the cyclical fluctuations are completelyeliminated, but in practice since the cycles are by no means perfectly periodic,

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the lengths of the various cycles in any given series will usually vary considerablyand, therefore, no moving average can completely remove the cycle. The bestresult would be obtained by a moving average whose period was equal to theaverage length of all the cycles in the given series. However, it is difficult todetermine the average length of the cycle until the cycles are isolated from the

series.

5.) Finally, when the trend situation is not linear (a straight line) the moving averagelies either above or below the true sweep of the data. Consequently, the movingaverage is appropriate for trend computations only when the purpose of investigation does not call for current analysis or forecasting.

the trend is linear, and

the cyclical variations are regular both in period and amplitudes.Unfortunately, these conditions are encountered very infrequently.

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APPENDIX:

Full forms:

COGS : Cost of goods sold.DII : Days in inventory.MSIL : Maruti Suzuki India limited.O/M : Operating margin.R&D : Research and development.SG&A : Sales, general and administrative expenses

DEFINITIONS:

ASSET UTILISATION:

A ratio that indicates the amount of money invested in non-liquid assets (such asproperty, plant, and equipment) for each dollar of revenue

COGS:The expenses incurred by the company in producing the items that it sold during aparticular period.

DII:The number of days of sales that goods and materials are held in stock by abusiness i.e., it is the time period from the date of execution of the offer to purchasewith the employee through the resale closing date.

EQUITY:The percentage of revenue held as equity.

OPERATING MARGIN:

Operating margin is the operating income as a percentage of sales during a period.

PROCUREMENT:

Procurement is the acquisition of goods and/or services at the best possible totalcost of ownership, in the right quantity and quality, at the right time, in the right placeand from the right source for the direct benefit or use of corporations, or individuals,generally via a contract.

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RESEARCH AND DEVELOPMENT:

It refers to "creative work undertaken on a systematic basis in order to increase thestock of knowledge, including knowledge of human, culture and society, and the useof this stock of knowledge to devise new applications.

S, G & A:

This is the sum of all direct and indirect selling expenses and all general andadministrative expenses of a company. For a manufacturer these are expensesoutside of the manufacturing function. These expenses are reported on the incomestatement of the period in which they occur.

STRATEGIC SOURCING:

Strategic sourcing is an institutional procurement process that continuously improves

and re-evaluates the purchasing activities of a company.

VALUE ENGINEERING:

Value engineering is a systematic method to improve the "value" of goods andservices by using an examination of function. Value, as defined, is the ratio offunction to cost. Value can therefore be increased by either improving the function orreducing the cost.

FORMULA USED IN LEAST SQUARE METHOD:

The straight line trend is represented by the equation Yc = a + bXWhere,

Yc = designates the trend values to distinguish them from the actual Y valuesa = Y intercept or the computed trend figure or the Y variable when X = 0b = slope of the trend line or amount of change in Y variable that is

associated with a change of one unit in X variable.X = represents time

Formula to find constants:

a = Y/Nb = XY/X2

Where,N = represents number of years (months or weeks) for which data are given.

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BIBLIOGRAPHY

Following are the sources of data required in handling and

solving the issues: -

www.marketsimplifies.com

www.oppapers.com

www.moneycontrol.com

www.justauto.com

www.economictimes.indiatimes.com www.indiatelevision.com

B. M. Agrawal

S. P. Gupta

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