30 zen 2 feb12

8/2/2019 30 Zen 2 Feb12

1/13

ZENITH

International Journal of Multidisciplinary Research

Vol.2 Issue 2, February 2012, ISSN 2231 5780

www.zenithresearc

h.org.in

387

FINANCIAL VIABILITY OF SUGAR FACTORIES IN SOUTH GUJARAT-

A CASE STUDY

DR. MARTINA. R. NORONHA*; PROF. DILIPSINH THAKOR**

*Vice-Principal, P.G.In-Charge,

Head, Department of Accountancy,S.P.B. English Medium College of Commerce,

Surat, Gujarat.**Assistant Professor,

Shree Rang Navchetan Science& Computer Institute,

Valia, Bharuch, Gujarat.

ABSTRACT

The Indian Sugar Industry is marked by co-existence of different ownership and managementstructures. At one extreme, there are privately owned sugar mills in Uttar Pradesh that procure

sugarcane from nearby cane growers. At the other extreme are cooperative factories owned and

managed jointly by farmer.

This article attempts to find the financial viability of sugar factories located in South Gujarat in

India. It uses ratio analysis and discriminant analysis to give the actual prediction equation to

classify new cases.

There is tremendous scope for India to emerge as a significant player in the world sugar trade

[milling and overheads] improvement. If we can make a fair degree of progress on agricultural

efficiency [per hectare output of sugar and cost of production] as well as conversion efficiency,India will surely become a major exporter which will stabilize the industry and reduce its

cyclicality significantly, as well as open up new vistas of growth for the Indian Sugar Industry.

An efficient and well managed future trading mechanism needs to be put in place to facilitateprice discovering both for farmers and millers both in the domestic and global markets

KEYWORDS: co-operatives, discriminant function, viability.______________________________________________________________________________

INTRODUCTION

India is known as the original home of sugar and sugarcane. In global sugar economy, the Indian

Sugar Industry has achieved a number of milestones. It is the second largest producer of sugar inthe world. This industry is the second largest agro processing industry in India after textile. Morethan 45 million people in the rural population of India depend on Sugar Industry for their

livelihood. The Indian Sugar Industry accounts for around 1% of GDP of the country in the

recent past.

8/2/2019 30 Zen 2 Feb12

2/13

ZENITH



www.zenithresearc

h.org.in

388

TABLE I

STATE-WISE DISTRIBUTION OF COOPERATIVES AND OTHER SUGAR MILLS

State

Cooperatives Other Total

Number

of

factories

Installed

capacity

Number

of

factories

Installed

capacity

Number

of

factories

Installed

capacity

AP 8 192 26 716 34 908

Gujarat 17 1071 0 0 17 1071

Haryana 10 353 3 198 13 551

Karnataka 16 551 21 908 37 1459

Maharashtra 82 6,468 20 511 102 6,978

TN 14 546 20 979 34 1542

UP 28 784 78 3753 106 4537

Uttaranchal 4 133 6 279 10 412

Punjab 12 405 8 279 20 684

Other 12 182 15 678 27 861

Total 203 10,684 197 8,302 400 18,985

Source: United Sugar Development Association

Sugar is Indias second largest agro-processing industry with around 400 operating mills. The

203 cooperatives are a dominant component of the Industry accounting for over 56% of the totalcapacity of around 19 mt per annual of sugar. Of the 203 cooperatives nearly 83 (or 41% of total

cooperatives) are concentrated in Maharashtra, followed by Uttar Pradesh with 28 mills of the

197 non cooperative and/or private sugar mills nearly 78 (or 40%) are located in Uttar Pradesh,

followed by Tamil Nadu, Andhra Pradesh and Karnataka.

8/2/2019 30 Zen 2 Feb12

3/13

ZENITH



www.zenithresearc

h.org.in

389

TABLE II

SUGAR INDUSTRY IN GUJARAT

Year No. of workingmills DailyCrushing

Capacity

(T.C.D)

Crushing ofSugarcane (lakh

mts)

Productionof Sugar

(lakh mts)

Recovery%

2006-07 17 65000 133.12 14.11 10.646

2005-06 17 65000 108.87 11.67 10.823

2004-05 17 65000 74.05 07.96 10.760

2003-04 15 65000 97.53 11.66 10.933

2002-03 15 65000 118.27 12.51 10.581

Source: United Sugar Development Association

During the year 2006-07, area for cultivation for sugar was 1.72 hectares, from which 133.12lakh mts crushing was done while during 2007-08, area for cultivation was 1.84 lakh hectares.The sugar mills in Gujarat are located at Vadodara, Bharuch, Surat, Valsad, Navsari, Tapi and

Narmada District. 24 sugar factories of Gujarat are members of the Gujarat State Federation of

Co-operative Sugar Factories Limited out of which only 17 are operational. 13 mills are located

in South Gujarat, 2 in Saurashtra region and 2 are in the Central region.

OBJECTIVE OF THE STUDY

The objective of the study is to measure the viability of the sugar cooperative mills in the South

Gujarat Region.

SAMPLE SIZE

All thirteen sugar factories of South Gujarat are taken for the present study-Shree Khedut

Sahakari Khand Udyog Mandli Ltd., Bardoli, Sahakari Khand Udyog Mandal Ltd., Gandevi,Madhi Vibhag Khand Udyog Sahakari Mandli Ltd.,Madhi , Shree Chalthan Vibhag Khand

Udyog Sahakari Mandli Ltd. Chalthan , Shri Maroli Vibhag Khand Udyog Sahakari Mandli Ltd.,

Navsari, Shree Valsad Sahakari Khand Udyog Mandli Ltd., Valsad, Shree SayanVibhagSahakari Khand Udyog Mandli Ltd.,Sayan , Shree Mahuva Pradesh Sahakari Khand UdyogMandali Ltd.,Bamania , Shree Ukai Pradesh Sahakari Khand Udyog Mandli Ltd.,Khushalpura ,

Shree Ganesh Khand Udyog Sahakari Mandli Ltd., Harising Mahida Bhavan, Vataria, Bharuch,

Shree Kamrej Vibhag, Sahakari Khand Udyog Mandli Ltd.,NaviPardi, Shree Khedut SahakariKhand Udyog Mandli Ltd., Hansot, Bharuch, Shree Narmada Khand Udyog Sahakari Mandli

Ltd., Narmada

8/2/2019 30 Zen 2 Feb12

4/13

ZENITH



www.zenithresearc

h.org.in

390

PERIOD OF STUDY

The period of study is six years i.e. 2001-02, 2002-03, 2003-04, 2004-05, 2005-06, 2006-07.

TOOLS FOR ANALYSIS

Ratio Analysis and Discriminant Analysis is used in the present study.

REVIEW OF LITERATURE

Indian Sugar IndustryA Comparative Study by Dr. G. A. Nikam(2006) is an attempt to findout cost trend, profitability and operational efficiency of the sugar mills of two states, Uttar

Pradesh and Maharashtra. The study also attempts to compare the working of the sugar mills of

different regions of Uttar Pradesh and Maharashtra. Labour Problems and Welfare by M.

Mustafa (1990) is a systematic, comprehensive and analytical study of the problems related tomill workers and welfare measures introduced especially in the sugar industry. Practical Hints

on Sugar Factory Control by Dr. O. P. Talwar (1968) deals with measures to remedy unknownlosses in sugar industry, raise clarification efficiency, minimize losses by various pan boilingschemes, as well as lower the final molasses purity by high speed electrical centrifugation. Sugar

Cane in India by S. V. Parthaswathy (1972) discusses soil, climate, botany of sugarcane, land

preparation, seed, planting and Inter-culture, pests and diseases. Sugar from scarcity to surplusby Hubert (1958)gives factual information on many facets of sugar cane cultivation, irrigation

system, construction of factories, old and new equipment, trouble shooting, comparative value of

different labour forces, role of chemists in scientific quality control and production efficiency.Sugar Industry in India by Prof. Ram Vichar Sinha (1988) analyses the historical background of

Indian Sugar Industry, agricultural economics of sugarcane, problems of cane marketing and

transport, technical performances, utilization of byproducts, labour and relations, policies on

sugar economy, fiscal and financial aspects of the industry .Government and Co-operative SugarFactories by N. R. Inamdar, (1964) is a study of Government and Co-operative Sugar factories

in Maharashtra and contains measures for the promotion of co-operative enterprises.

TABLE III

ANALYSIS CASE PROCESSING SUMMARY

Unweighted Cases N Percent

Valid 78 100.0

Excluded Missing or out-of-range group codes 0 .0

At least one missing discriminating variable 0 .0

Both missing or out-of-range group codes and at

least one missing discriminating variable

0 .0

8/2/2019 30 Zen 2 Feb12

5/13

ZENITH



www.zenithresearc

h.org.in

391

Total 0 .0

Total 78 100.0

TABLE IV

GROUP STATISTICS

Performance of the sugar factories Mean Std.

Deviation

Valid N (list-

wise)

Performing well Return on capital

employed

1.11227 .572754 22 22.000

Gross profit ratio .07150 .055484 22 22.000

Net profit ratio .00004 .006230 22 22.000

Expenses to sale ratio .05312 .030626 22 22.000

Interest coverage ratio 1.10682 .215260 22 22.000

Debtequity ratio 1.97205E1 37.331018 22 22.000

Current ratio .92545 .110399 22 22.000

Fixed asset turnoverratio

2.41318 .541219 22 22.000

Operating profit ratio .06551 .037624 22 22.000

Not performing

well

Return on capital

employed

.15787 .129036 56 56.000

Gross profit ratio .43800 2.662777 56 56.000

Net profit ratio -.03458 .114775 56 56.000


Interest coverage ratio .84182 .760763 56 56.000


8/2/2019 30 Zen 2 Feb12

6/13

ZENITH



www.zenithresearc

h.org.in

392

Current ratio 1.16232 .767124 56 56.000

Fixed asset turnover

ratio

1.53232 .617161 56 56.000

Operating profit ratio 0.6962 .082492 56 56.000

Total Return on capitalemployed

.42706 .536850 78 78.000

Gross profit ratio .33463 2.256757 78 78.000

Net profit ratio -.02482 .098316 78 78.000


Interest coverage ratio .91656 .663659 78 78.000


Current ratio 1.09551 .659678 78 78.000

Fixed asset turnover

ratio

1.78077 .714920 78 78.000

Operating profit ratio 0.6846 .072458 78 78.000

TABLE V

TESTS OF EQUITY OF GROUP MEANS

Wilks

Lambda

F df1 df2 Sig.

Return on capital employed .352 140.098 1 76 .000

Gross profit ratio .995 .413 1 76 .522

Net profit ratio .975 1.984 1 76 .163

8/2/2019 30 Zen 2 Feb12

7/13

ZENITH



www.zenithresearc

h.org.in

393

Expenses to sale ratio .988 .898 1 76 .346

Interest coverage ratio .967 2.570 1 76 .113

Debtequity ratio .998 .153 1 76 697

Current ratio .974 2.065 1 76 .155

Fixed asset turnover ratio .689 34.370 1 76 .000

Operating profit ratio .999 .050 1 76 .823

TABLE VI

WILKS LAMBDA

Test of function (s) Wilks Lambda Chi-square Df Sig.

1 .314 82.739 9 .000

TABLE VII

STANDARDIZED CANONICAL DISCRIMINANT FUNCTION COEFFICIENTS

Function

1

Return on capital employed .902

Gross profit ratio .026

Net profit ratio -.147

Expenses to sale ratio -.066

Interest coverage ratio -.215

8/2/2019 30 Zen 2 Feb12

8/13

ZENITH



www.zenithresearc

h.org.in

394

Debtequity ratio .021

Current ratio -.296

Fixed asset turnover ratio .415

Operating profit ratio .188

TABLE VIII

CANONICAL DISCRIMINANT FUNCTION COEFFICIENTS

(UNSTANDARDIZED COEFFICIENTS)

Function

1

Return on capital employed 2.816

Gross profit ratio .012

Net profit ratio -1.503

Expenses to sale ratio -1.706

Interest coverage ratio -.327

Debtequity ratio .000

Current ratio -.452

Fixed asset turnover ratio .695

Operating profit ratio 2.576

(Constant) -1.790

8/2/2019 30 Zen 2 Feb12

9/13

ZENITH



www.zenithresearc

h.org.in

395

TABLE IX

FUNCTIONS AT GROUP CENTROIDS

Performance of the sugar

Factories

Function

1

Performing well 2.326

Not performing well -.914

Unstandardized canonical discriminant functions evaluated at group means.

TABLE X

CLASSIFICATION RESULTS

Performance of the sugar factories Predicted Group Membership Total

(1)

Performing

well

(2)

Not performing

well

Original Count Performing well

Not performing well

18

0

4

56

22

56

% Performing well

Not performing well

81.8

.0

18.2

100.0

100.0

100.0

94.9% of original grouped cases correctly classified.

The output in Table X is called the classification matrix (also known as confusion matrix).It indicates the Discriminant Function. 94.9% of the 78 objects have been correctly classified. It

is a pointer towards the model being a good one.

The value of Wilks Lambda presented in Table VI judges the Discriminant power of the model.The low value (closer to 0) indicates better discriminating power of the model. Here, the value is

0.314 which is an indicator of the model being good. The probability value 0.0000 indicates thatthe discrimination between the groups is highly significant.

Nine independent (predictor) variablesreturn on capital employed, gross profit ratio, net profitratio, expenses to sales ratio, interest coverage ratio, debtequity ratio, current ratio, fixed asset

8/2/2019 30 Zen 2 Feb12

10/13

ZENITH



www.zenithresearc

h.org.in

396

turnover ratio and operating profit ratio are used to compare the relative importance of the

independent variables. The standardized coefficients in the output also known as StandardizedCanonical Discriminant function coefficients given in Table VII shows that return on capital

employed is the best predictor, with the coefficient of 0.902 followed by current ratio with a

coefficient of -0.296, interest coverage ratio of -0.215, fixed asset ratio of 0.415, gross profitratio of 0.026. The absolute value of each variable indicates its relative importance.

Standardized Canonical Discriminant Function indicates the relative importance of each

predictor variable. Positive results indicate favourable to Group 1 (performing well). Thefollowing variables showed positive results:

1. Return on Capital Employed2. Gross Profit Ratio3. Expenses to Sales Ratio4. Debt Equity Ratio5. Fixed Assets Turnover Ratio6. Operating Profit Ratio

Negative results indicate favourable to group 2 (Not performing well)

1. Net Profit Ratio 2.Interest Coverage 3.Current RatioThe tests of equality of group means (Table V) measures each independent variables potential

before the model is created. According to the results in this table, variables return on capitalemployed and fixed asset turnover ratio in the discriminant model are significant.

The table VIII contains the unstandardized discriminant function coefficients which are used to

construct the actual prediction equation and can be used to classify new cases. The

unstandardized discriminant function for the table is presented below:

Y = -1.790 + roce (2.816) + gross profit ratio (0.012) npr (-1.503) + rxp to sales (-1.706)icr

(0.327) + debt to equity (0.000)current ratio (0.452) + ftor (0.695) + opr (2.576)

Table IX is used to establish the cutting point for classifying cases. Cases which evaluate on the

function above the cutting point will be classified as performing well while those evaluating

below the cutting point will be classified as not performing well.

2.326*22 -.914*56 = -0.012/78 = -0.0001538.

SUGGESTIONS

The Indian Sugar Industry will have a bright future, if its potential is fully developed and isallowed to bloom.

8/2/2019 30 Zen 2 Feb12

11/13

ZENITH



www.zenithresearc

h.org.in

397

The state governments should take a pragmatic view in regard to feeding the power produced by

the sugar factories to the state grids. This will not only enhance the financial viability of sugarfactories but it would also enhance the cane price paying capacity of the factory which would

ultimately benefit the farmers.

Another area of concern which significantly impacts the viability of Indian Sugar Industry is the

high cost of cane. A contributory factor for this is the low sugarcane fields in India and relativelylow overall recovery rates. These inhibiting factors combine to make the per hectare output of

sugar in India much below than obtaining in other developing countries like Brazil which is one

of our main competitor in sugarcane production.

There is tremendous scope for India to emerge as a significant player in the world sugar trade

[milling and overheads] improvement. If we can make a fair degree of progress on agricultural

efficiency [per hectare output of sugar and cost of production] as well as conversion efficiency,India will surely become a major exporter which will stabilize the industry and reduce its

cyclicality significantly, as well as open up new vistas of growth for the Indian Sugar Industry.

The industry has to be free from its shackles to enable investment and pricing decisions to be

taken based upon economic viability. The government needs to restrict its presence to the few

areas which cannot do without its intervention. These include the need for a fairly derived SMPfor sugarcane to be announced on an annual, all India basis. As in other countries like Brazil, the

farmers return on cane should ultimately be linked to the market price of sugar rather than the

cost of production for a low sugar price which will lead to reduced cane cultivation andconsequent shortage of sugar production market availability as also higher sugar and cane prices.

Similarly, a high sugar price will lead to increased cane cultivation, surplus sugar production and

a drop in sugar/cane prices, reversing the increase in cane cultivation.

An efficient and well managed future trading mechanism needs to be put in place to facilitateprice discovering both for farmers and millers both in the domestic and global markets. It shouldalso have a stable relatively long term exim policy supportive of the industry, which will help the

industry to establish its credibility in the global market.

In spite of having the benefit of lowest field production cost, the total cost of sugar production in

India is not lowest in the world. It is also due to higher factory cost. Now, India is facing the stiff

competition from Thailand and Australia in world sugar trade due to their lower factoryproduction cost. Therefore, there is an urgent need to take recourse on top priority to reduce the

factory production cost of Indian Sugar.

The cost of production in Indian sugar industry is higher because it is labour extensive. Manysugar mills are shifting to mechanization and automation but the change is very slow. The pace

of mechanization and automation will have to be accelerated.

India has now attained the status of the largest sugar producing country in the world and has

contributed around 18% to 20% of worlds cane sugar production. In spite of this, the averagecane productivity (i.e. 68.00 M.tonnes per/ha) is much lower than the countries like Kenya 100.2

M.tonnes/ha, Egypt 100.3 tonnes/ha, Columbia 83.5 tonnes/ha, Australia 74.5 tonnes/ha and

8/2/2019 30 Zen 2 Feb12

12/13

ZENITH



www.zenithresearc

h.org.in

398

Hawai 150 tonnes/ha for a crop of 24 months. Therefore, now the time has come for the

sugarcane grower and the sugar industry to concentrate more on high yielding varieties so as toget required sugarcane from the same area under sugarcane crop.

The Indian sugarcane research centre should also develop such varieties which would help toincrease the recovery at least by 1 to 1.5%. Naturally it would yield additional sugar to the tune

of 10 to 15 lakh tonnes of per year.

Modernization of plant and machinery is overdue. Therefore, higher percentage share of lost

hours to available hours automatically leads to under utilization of plant capacity which leads tohigher cost of sugar production. Therefore, the mills should concentrate more on efficient

utilization of plant capacity.

The reluctance of the financial institutions and the banks to provide term loans as well as

working capital has crippled the Indian sugar Industry. These institutions have started looking at

the sugar industry as a very high-risk industry. The scheduled commercial banks havingdeveloped high risk perception of the sugar industry have become extremely weary in enhancing

the cash credit limits to the mills to the requisite levels year after year the arrears of sugarcane

farmers are increasing which has affected the well being of sugarcane farmers. Therefore,

Government should ensure easier and cheaper credit facilities to the sugar industry which isprimarily required by it for timely disbursement of sugarcane prices of millions of sugarcane

farmers.

Soft term loan should also be considered for sugar mills to those who are going for

diversification like cogeneration as well as ethanol production.

Sugarcane is the most versatile crop which provides tremendous potential to the sugar mills to

diversify into various products based on its byproducts i.e. Molasses, Bagasse and Pressmud.Advances in the knowledge of technologies have opened up potentials for multiple uses of

sugarcane and it can now be looked at as raw material for many more products than Sugar

alone like renewable resources of energy and liquid fuels, power generation or cogeneration,paper and paper boards, protein foods and cattle feeds, organic chemicals, bio-manures and

sugar.

It is observed that the state advised sugarcane prices are always higher than the statutory

minimum prices, fixed by the Central Govt. For the natural growth of the sugar industry the

sugarcane prices should be fixed on the basis of recovery percent they have achieved i.e. thiswould help to reduce cost of sugarcane. This will also help to improve the quality of sugarcane

supply to the mills. Ultimately this will increase the sugar production with the help of samequantity of sugarcane crushed during the season. Therefore it is necessary to stop the system of

state advised sugarcane prices scheme here after for the natural as well as qualitative growth ofthe Indian Sugar Industry.

8/2/2019 30 Zen 2 Feb12

13/13

ZENITH



www.zenithresearc

h.org.in

399

REFERENCES

Ajit Narde (2000-2001) Sugar IndiaYear Book Anekant Prakashan, Jaisingpur, Kolhapur.

Choudhary B. Roy(1977 ) Working Capital Management Eastern Law House, Calcutta.

Cooperative Sugar Directory and Year Book (2007) New Delhi

D.G. Haspte(1996) Progressive Sugarcane Farmingin Maharashtra, Gyanshil Prakashan, Pune.

Darda Rajendra (1996) Four Decades of Cooperative Sugar Industry (1950-1990) Jai DattaPrakashan, Kolhapur.

G.A. Nikam, (1993) Future of Sugar Co-operatives in India, Vol. 24 No.10 New Delhi.

Govt. of India(2000) Report of the High Power Committee on Sugar Industry

Gundurao S.N( 1965) Rehabilitation and Modernization of Sugar Factories in India: Part I & II

Inamdar N.R.(1964) Government and Cooperative Sugar Popular Prakashan, Bombay.

I.S.O. Year Book (September 2003) Indian Sugar Vol. VIII No. 6

Kuchal S.C( 2008) Financial Management: An Analytical and Conceptual Approach Chaitanya

Publishing House, Allahabad.

Mangal Singh (1994) Efficient Management of Sugar Factories Somaiya Publication, New

Delhi.

Mishra K.K.(1985)Sickness of Sugar Industry Suneja Publishing Corporation, New Delhi.

Mohite Y.J (1974) Sugar Industry of Maharashtra: A Blue Print for Progress Government of

Maharashtra, Bombay.

Mohsin M (1977) Financial Planning and ControlVikas Publishing House, Delhi.

Nikam G.A(1991) Financial & Cost Analysis of Sugar CooperativesIndu Prakashan, Bombay.

Sen S.R.(1968-69) Report of the Agricultural Price Commission on Price Policy for Sugarcane.

Shivajirao G. Patil, Sugar Cooperatives tryst with destiny Cooperative Sugar, Nov. 1997 Vol.29, No. 3, p.167.

V.B. Jugale (2000) Sugarcane PricingPolicy, Procedure and Operations Atalantic Publishers &

Distributors, New Delhi.

30 zen 2 feb12

Documents