Trend Analysis in Maruti Suzki

AMITY BUSINESS SCHOOL AMITY UNIVERSITY UTTAR PRADESH

PROJECT ON TREND ANALYSIS

OF MARUTI SUZUKI INDIA LTD. SUBMITTED TO: Mr. SUMIT SINGH JAISIAL FACULTY (QUANTITATIVE APPLICATIONS IN MANAGEMENT)

SUBMITTED BY: NEHA GHILDIYAL MEGHA SHARMA POOJA SARIN NIDHI MEHTA MEDHA UMA YADAV

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D O4 D 09 D 12 D 34 D 38 D43

ACKNOWLEDGEMENT We would like to express our sincerest gratitude to all the people who have contributed towards the successful completion of our project. We would like to extend our heartfelt thanks to our faculty Mr. Sumit Singh Jasial for nurturing a congenial yet competitive environment in the department, which motivates all students to pursue higher goals. Our sincere thanks for his guidance and expertise in making this project a reality. Last but not the least, we would like to extend our thanks to all the teaching and non-teaching staff members of our department, and to all our colleagues who helped us with the ever daunting task of gathering information for the completion of project.

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CERTIFICATE This is certify that the major project report entitled “Trend Analysis of Maruti Suzuki India Limited” has been submitted to Amity Business School, Amity University, Noida by mutual cooperation of

Neha

Ghildiyal (Roll No: - D 04), Uma Yadav (Roll No: -D 43), Nidhi Mehta (Roll. No: - D 34), Medha (Roll. No:-D 38), Megha Sharma (Roll No: - D 09), Pooja Sarin (Roll No: - D 12) in partial fulfillment for the award of the degree, Master of Business Administration in Human Resource.

Mr. Sumit Singh Jasial

Dr. Parul Jhajaria

Faculty

H.O.D (HumanResource)

Quantitative Applications in Mgmt. 13/10/2008

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TABLE OF CONTENTS S.NO.

TOPICS

PAGE NO.

1.

Introduction: Project Overview

5–7

2.

About the company: Maruti Suzuki India 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 the variables 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, or trend, in the information. In some fields of study the term trend is often used to predict future events. It is the process of analyzing company’s financial ratios over time. An aspect of technical analysis that tries to predict the future movement of a stock based on past data. Trend analysis is based on the idea that what has happened in the past gives traders 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 until data suggests a trend reversal. Trend analysis is helpful because moving with trends, and not against them, will lead to profit for an investors. The trend analysis module allows you to plot aggregated response over time. This is especially valuable, if you are conducting a long running survey and would like to measure differences in perception and responses over time. The following data points can be measured on Y-axis: 1. 2.

MEAN and MEAN PERCENTILE STANDARD DEVIATION and VARIANCE

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The “TIME FACTOR” on X axis can have the following granularity: 1. 2. 3. 4. 5.

Daily Weekly Monthly Quarterly (Jan-Mar, Apr-Jun, Jul-Sept, Oct-Dec) Yearly

Trend Analysis can be extremely valuable as an early warning indicator of potential problems and issues with product line and service level changes that impact customers. If you see a dip in the "mean" for a Continuous Variable satisfaction question after a particular "marketing event" you can immediately start investigating the dip and explore causes of the decrease in satisfaction levels. It can also be used to 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 of parliament as a government company with Suzuki Motor Corporation of Japan holding 26% stake. The joint venture agreement was signed between government of India and Suzuki Motor Company in October1982. Maruti Suzuki India Ltd., formally Maruti udyog ltd., a subsidiary of Suzuki Motor Corporation of Japan, is India’s largest 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 11 different ranges of cars. Since inception, Maruti produced and sold over 7.5 million vehicles 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

SUZUKI MOTOR CORPORATION

45.79% 54.21%

OTHERS

COMPANY AT A GLANCE: • • • • • • • •

Cars produced and sold Domestic cars sales for 2007-08 Car exports for 2007-08 Recorded profit after tax in 2007-08 Total income in 2007-08 No. of Maruti Suzuki sales outlets in 393 towns and cities No. of workshops that provide customers with maintenance support in 1220 cities Employee strength till March 2008

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: 7,000,000 : 711818 : 53024 : 17308 : 188238 : 600 : 2628 : 7090

One million promise Maruti has laid down a clear road map to achieve an annual sale of 1 million cars in the domestic market and 2 lakh exports by 2010-11. In addition, the management team at Maruti Suzuki has identified specific initiatives to serve customers better and ensure their leadership in the future.

COMPANY’S STRENGTH: One of the Maruti’s great strength is that they have internal resources to finance both R & D expansion as well as capital and investments. The higher interest rates and the risk of making large borrowings till finance capital cost will not affect them.

Maruti Suzuki is recently being rated as the 4th most reputed 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 45.00% SALES GROWTH

40.00%

38.60%

35.00% 30.00% 25.00% 20.00%

22.60%

15.00%

SALES GROWTH

19.50% 11.90%

10.00% 5.00% 0.00% 2005

2006

2007 YEAR

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2008

EARNING PER SHARE & BOOK VALUE EARNING PER SHARE & BOOK VALUE

EPS & BOOK VALUE

350 300

297

250 200

EARNING PER SHARE

189

BOOK VALUE

150

124

100 50

41.2

18.8

0

2003 - 04

2005 - 06

59.9

2007 - 08

YEAR

EXPORTS & DOMESTIC: EXPORTS & DOMESTIC

EXPORTS & DOMESTIC

800000 711818

700000 600000 527038

500000 400000

EXPORTS (units)

420947

DOMESTIC (units)

300000 200000 100000 0

51175 2003 - 04

34784 2005 - 06 YEAR

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53024 2007 - 08

PROFIT AFTER TAX AND NET SALES:

PAT & NET SALES

PROFIT AFTER TAX & NET SALES 200000 180000 160000 140000 120000 100000 80000 60000 40000 20000 0

178603 PROFIT AFTER TAX (Rs Mn)

120034 90812

NET SALES

2003 - 04

17308

11891

5422

2005 - 06

2007 - 08

YEAR

TREND ANALYSIS OF MARUTI SUZUKI Factors

Year

Sales Sales Growth COGS COGS as a % of Sales SG&A SG&A % of Sales R&D R&D % of Sales Operating Income Operating Margin Employees Revenue per Employee Net PPE Asset Utilization Inventory COGS/Inventory

2004

2005

2089.4 1539.7

2562.5 0.226 1939.3

0.737 242.6 0.1161

0.757 234.7 0.0916

$ -

$ 0 307.1 0.147 3334

0 388.5 0.152 3453

626.7 446.8 0.21 101.2 15.21

742.1 447.5 0.17 152.6 12.71 Page 12 of 31

2006

$

2007

2008

2867.1 0.119 2147.4

3425.3 0.195 2427.1

4747.3 0.386 3500.2

0.749 289.6 0.101

0.709 371.8 0.1085

0.737 521.3 0.1098

$ $ - 0 0 0 430.1 626.4 725.8 0.15 0.183 0.153 7090

#DIV/0! 459.8 0.16 197.7 10.86

#DIV/0! 679.4 0.2 161.3 15.05

670 1025.4 0.22 258.6 13.54

DII Accounts Receivable Sales/AR DSO

365 24 164.6 12.69 365 29

365 29 144.3 17.76 365 21

365 34 154.1 18.61 365 20

365 24 182.1 18.81 365 19

365 27 173.2 27.41 365 13

From the above trend it has been found that the The sales of the company have increased from 19.5% in 2007 to 38.6% in 2008. 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. 1.

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PROBLEMS FACED: Following problems are found during the study of trend analysis on Maruti Suzuki India Limited (MSIL). 1.) Cost of Goods Sold has been increased from 2004 to 2008 i.e., the expenses incurred for the production of items has increased during this particular period of time. 2.) Days in Inventory has also been increased from 2007 to 2008 i.e., time of production has increased even after the implementation of new techniques and technologies in production process.

Methods under TREND ANALYSIS on basis of which problems are studied:

1.) By Graphical Method 2.) By Least squares method 3.) By Semi-averages and 4.) By Moving Averages 1.) BY GRAPHICAL METHOD: The simplest, quickest and easiest method of estimating the trend is to plot the original data on a graph and then to draw a smooth curve through the points so that it 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

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2008

3500.2

Trend Showing COST OF GOODS SOLD 4000 3500

COGS

3000 2500 COGS(Y)

2000

Linear (COGS(Y))

1500 1000 500 0 2004

2005

2006

2007

2008

YEARS

(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: 40 35 30

DII

25 DII (Y)

20

Linear (DII (Y))

15 10 5 0 2004

2005

2006

2007

2008

YEARS

2.) METHOD OF LEAST SQUARES Method of Least Squares is a mathematical method which is most widely used and with its help a trend line is fitted to the data in such a manner that the following two conditions are satisfied. (1) Σ (Y-Yc) = 0 i.e., the sum of deviations of the actual values of Y and the computed values of Y is zero. (2) Σ (Y-Yc)2 is least. i.e., the sum of the squares of the deviations of the actual and computed values is least from this line and hence the name method of least squares. The line obtained by this method ‘as the line of best fit’. The straight line trend is represented by the equation Yc = a + bX Where, Yc = designates the trend values to distinguish them from the actual Y values a = Y intercept or the computed trend figure or the Y variable when X = 0 b = slope of the trend line or amount of change in Y variable that is associated Page 16 of 31

with a change of one unit in X variable. X = represents time Following points should be specified when any straight line trend is fitted: 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 = Σ Y/N b = ΣXY/ΣX2 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’ gives the rate of change. (i) Trend Analysis of COGS using Least Squares Method

Year

COGS (Y)

X

XY

X2

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

Σ Y = 11573.7

Σ XY = 4428.8

Σ X2 = 10

Here, Arithmetic mean = 10030/5 = 2006 Yc = a + bX a = Σ Y/N = 11573.7/5 = 2314.74 b = ΣXY/ΣX2 = 4428.8/10 = 442.88

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Linear trend by the Method of Least Squares

COGS and Yc

4000 3500

Trend Line

3000 2500

C O G S(Y)

2000

Yc

1500 1000

Actual Line

500 0 2004

2005

2006

2007

2008

YE AR

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 effect the revenue of the company. (ii) Trend Analysis of DII using Least Squares Method

Year

DII (Y)

X

XY

X2

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

Σ Y = 138

Σ XY = 1

Σ X2 = 10

Here, Arithmetic mean = 10030/5 = 2006 Page 18 of 31

Yc = a + bX a = Σ Y/N = 138/5 = 27.6 b = ΣXY/ΣX2 = 1/10 = 0.10 Linear trend by the Method of Least Squares 40 35 30

DII

25 DII (Y)

20

YC

15 10 5 0 2004

2005

2006

2007

2008

YEARS

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 DII which will result in delay in production of items

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3.) Method of Semi-averages 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 two equal halves. For example, the data are from 2000 to 2005, i.e., over a period of 6 years, the two equal parts will be each three years, i.e., from 2000 to 2002 and from 2003 to 2005.

•

In case of odd number of years like 5, 9, 13, etc. two equal parts can be made simply by omitting the middle year. For example, if data are given for 5 years from 2000 to 2004, the equal parts would be from 2000 to 2001 and from 2003 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 the respective 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)

2004

1539.7

2005

1939.3

2007

2447.1

2008

Semi-average (year)

Semi-average (COGS)

2004.5

1739.5

2007.5

2973.65

3500.2

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

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Trend by the Method of Semi-averages 4000 3500

COGS

3000 2500 COGS (Y)

2000

Linear (COGS (Y))

1500 1000 500 0 2004

2005

2007

2008

YEARS

Future analysis: From the above graph, it is shown that due to increase in the trend line values there will be hike in COGS in coming future. (ii) Trend Analysis of DII using Method of Semi-averages Year

DII (Y)

2004

24

2005

29

2007

24

2008

Semi-average (year)

Semi-average (DII)

2004.5

26.5

2007.5

25.5

27

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

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Trend by the Method of Semi-averages 35 30 25

DII

20

DII (Y) Linear (DII (Y))

15 10 5 0 2004

2005

2007

2008

YEARS

Future analysis: By observing the trend line it may be predicted that there would be more chances of DII 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, the average value for a number of years (or month or weeks) is secured and this average is taken as the normal or trend value for the unit of time falling at the middle of 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 away from the general trend.

We have three types of Moving Averages Method: 1. 3-yearly moving average 2. 5-yearly moving average and 3. 8-yearly moving average

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Note: - It is necessary to select a period for moving average which coincides with the length of the cycle; otherwise the cycle will not be entirely removed. The period of moving average is to be decided in the light of the length of the cycle. (i) Trend Analysis of COGS using 3-yearly Moving Average Method 3-Yearly totals

3-yearly average

_

_

1939.3

5626.4

1875.466667

2006

2147.4

6533.8

2177.933333

2007

2447.1

8094.7

2698.233333

2008

3500.2

_

_

Year

COGS (Y)

2004

1539.7

2005

moving

Here, 5626.4 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

4000 3500 3000

COGS (Y)

COGS

2500

Linear (COGS (Y))

2000 1500 1000 500 0 2004

2005

2006 YEARS

2007

2008

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

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

3-yearly average

_

_

29

87

29

2006

34

87

29

2007

24

85

28.33333333

2008

27

_

_

Year

DII (Y)

2004

24

2005

moving

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

40 35

DII

30 25

DII (Y)

20

Linear (DII (Y))

15 10 5 0 2004

2005

2006 YEARS

2007

2008

Future analysis: By observing the trend line it is being predicted that there would be more chances of DII 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 THE PROBLEM As can be seen that trend has helped us to measure the growth or decline of the various problems faced by the company and hence is describing the basic growth or decline tendency of the data. By assuming that the same behavior would continue in future 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 2004 to 2008. Hence the expenses incurred by the company in producing the items that it sold during a particular period have been increased. This increment is very large and as the price of steel is increasing there is the possibility of increment in the prices of raw material. COGS will increase in the future in a very steep manner. Being a manufacturing company it is very important for Maruti to lower the value of COGS. This can be lowered by strategic sourcing and procurement i.e. by continuously improving and re-evaluating the purchasing activities of a company and also by acquisition of goods and/or services at the best possible total cost of ownership, in the right quantity and quality, at the right time, at the right place and from the right source for the direct benefit or use of corporations, 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 to purchase with the employee through the resale closing date. As the days in inventory have increased from 24 in 2007 to 27 in 2008 that means the time of production has increased even after the implementation of new techniques and 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 and this needs to be lowered so as to get more revenue. This can be done by ensuring better inventory management. Effective Inventory Management enables an organization to meet or exceed customers' expectations of product 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 personal judgment of the investigator and, therefore, different persons may draw different trend lines from the same set of data. Moreover, the work cannot be left to clerks and it must be handled by skilled and experienced people who are well conversant 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 used as a basis for prediction. 3.) This method appears simple and direct. However, it is very time consuming to construct 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 to fit a trend line by inspection.

METHOD OF LEAST SQUARES 1.) 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 lead to 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 of cyclical, seasonal and irregular variations is ignored. 4.) Being a mathematical method it is not flexible-the addition of even one more observation makes it necessary to do all the computations again. 5.) The method cannot be used to fit the growth curves like Gompertz curve, logistic curve, etc. Hence, mathematically methods of fitting trend are not foolproof-in fact; they can be 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 logical analysis. Trend fitting depends upon the judgment of the statistician, and a skillfully made freehand sketch is often more practical than a refined mathematical 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 completely eliminated or not. 3.) The limitations of arithmetic averages shall automatically apply. If there are extremes 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 time period represented by the average is small. Consequently, trend values obtained are not precise enough for the purpose either of either of forecasting the future trend or of eliminating trend from original data. For the above reasons if the arithmetic averages of the data are to be used in estimating the secular movement. It is sometimes better to use moving averages than semi-averages.

METHOD OF MOVING AVERAGES 1.) Trend values cannot be computed for all the years. The longer the period of moving average, the greater the number of years for which the trend values cannot be obtained. For example, n a three-yearly moving average, trend values cannot be obtained for the first year and last year, in a five-yearly moving average 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. No hard and fast rules are available for the choice of the period and one has to use his own judgment. 3.) Since the moving average is not represented by a mathematical function this method cannot be used in forecasting which is one of the main objectives of trend analysis. 4.) Although theoretically we say that if the period of moving average happens to coincide with the period of cycle, the cyclical fluctuations are completely eliminated, but in practice since the cycles are by no means perfectly periodic, Page 27 of 31

the lengths of the various cycles in any given series will usually vary considerably and, therefore, no moving average can completely remove the cycle. The best result would be obtained by a moving average whose period was equal to the average length of all the cycles in the given series. However, it is difficult to determine 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 average lies either above or below the true sweep of the data. Consequently, the moving average 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 DII MSIL O/M R&D SG&A

: Cost of goods sold. : Days in inventory. : Maruti Suzuki India limited. : Operating margin. : Research and development. : Sales, general and administrative expenses

DEFINITIONS: ASSET UTILISATION: A ratio that indicates the amount of money invested in non-liquid assets (such as property, plant, and equipment) for each dollar of revenue COGS: The expenses incurred by the company in producing the items that it sold during a particular period. DII: The number of days of sales that goods and materials are held in stock by a business i.e., it is the time period from the date of execution of the offer to purchase with 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 total cost of ownership, in the right quantity and quality, at the right time, in the right place and 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 the stock of knowledge, including knowledge of human, culture and society, and the use of 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 and administrative expenses of a company. For a manufacturer these are expenses outside of the manufacturing function. These expenses are reported on the income statement 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 and services by using an examination of function. Value, as defined, is the ratio of function to cost. Value can therefore be increased by either improving the function or reducing the cost. FORMULA USED IN LEAST SQUARE METHOD: The straight line trend is represented by the equation Yc = a + bX Where, Yc = designates the trend values to distinguish them from the actual Y values a = Y intercept or the computed trend figure or the Y variable when X = 0 b = 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 = Σ Y/N b = ΣXY/ΣX2 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 Levin and Rubin

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