market analysis of edible oils industry

MANAGERIAL ECONOMICS MARKET ANALYSIS OF EDIBLE OILS INDUSTRY WITH SPECIAL EMPHASIS ON ADANI WILMAR LTD. ’S “FORTUNE” BRAND SUBMITTED BY: Group 10, Section A APEKSHA JAIN ESHANI NANDA KRANTI P. SINGH MONIKA SOMANI PRADIP RANGHOLIYA VAIBHAV SAHU FLOW OF THE REPORT ACKNOWLEDGEMENT Ms Simran Sethi, our Economics professor for mentoring and guiding this project till its completion. Mr Vipul Rajyaguru, Senior Manager, Adani Wilmar Ltd, for providing us with useful insights of the industry and the Company including the sales and growth figures.

Members of our group for contributing their hardwork and dedication to the project. And most importantly, all the consumers and retailers who took out some time to fill in our surveys. Introduction Background and Size of the Indian Edible Oil Industry Demand for edible oils Vegetable oil consumption in the country is continuously rising and has sharply increased in the last couple of years to roughly 11. 2 kg/head/year. This is still lower than the world average consumption level of 17. 8 kg and that in neighbouring countries like Pakistan (16. 1 kg).

The developed western world has a per capita consumption of 44 to 48 kg/year. According to projections from the National Council of Applied Economic Research (NCAER), per capita consumption of edible oils is likely to reach 13. 95, 14. 83 and 16. 17 kg by 2009-2010 if the per capita income grows by 4%, 5% and 6% respectively. Major players in the edible oil industry: Marico Agrotech ITC Adani Wilmar Parakh Foods (Gemini brand) Gold Winner and Cargill (Nature Fresh) Ruchi Soya Inds Structure of Adani Enterprises Ltd. {draw:frame} Objective of Study

The objective of this research is to determine the customer as well as retailers preferences regarding different brands of edible oils which result in their market share. It involves the study of consumers’ buying behaviour and attitudes towards a variety of attributes and factors, which help them in decision-making. The brand we chose to focus on was Adani Wilmar Ltd. ’s Fortune brand of oils. We studied the company profile, its market structure, the brand awareness, growth rates and popularity among consumers so as to forecast the future sales and understand the growth trends.

We designed a questionnaire to survey various retailers and consumers to understand the demand and supply situation of the edible oil market. Secondary data from the internet has also been used for effective analysis. Importance of Study The importance of this study is to practically understand the relevance of the concepts of managerial economics in the business organisations and here in the realm of the edible oil industry. The present market scenario was analyzed and future demands forecasted using the simple regression techniques.

Also, a comprehensive study of the major factors involved in this market was conducted so as to see how different and similar a market structure is from the theories. Methodology Primary data collection: The sample size for the survey was around 40-50. We are also grateful to Mr. Vipul Rajyaguru, Sr. Mgr – Adani Wilmar Ltd. , for giving us a greater insight of the edible oil industry and the contribution of AWL to this industry. Secondary data collection: Internet was the major source for secondary data. Apart from understanding the edible oil industry in general and AWL in pecific, our major task was to analyse the consumer demand for AWL’s edible oil brands and project the future sales for the company. We have used the trend projection and exponential forecasting technique to predict the sales. {draw:frame} Company profile Adani Wilmar Limited is a 50:50 joint venture between two recognized Multinational Corporations – the INR 275 Billion (US $5 Billion) Adani Group, the leader in International trading, Power Sector and Private infrastructure, and Wilmar International Limited, Singapore, Asia’s leading Agri business group with revenues exceeding US $16. billion. Adani Wilmar Ltd. ‘s flagship brand Fortune has been repositioned with a new mantra of ‘Joy of Eating’. The objective of this exercise is to craft a unique value proposition for the brand. Fortune, which has maintained its market leadership for last 7 years, hope to further strengthen its market share with this re-positioning. To cater to the burgeoning middleclass, core of Indian consumer market, AWL introduces King’s range of refined oils. It will have under its portfolio, Soya, Sun, Refined Mustard and Cottonseed oil.

Coming from the house of Adani Wilmar, coupled with the planned 360 degree Marketing Support, King’s is set to be the king of its own turf. AWL also has as part of its edible oil portfolio, Bullet brand mustard oils and a coconut oil under the brand name Ivory, a Refined Palmolein Oil under the brand name of Raag Gold, a premium vanaspati brand called Raag, special frying oil called Fryola and Speciality Fats under brand name Jubilee Masterchef. The production and distribution network The company has production infrastructure across the country with a crushing capacity of over 6000 TPD (Tonnes per Day) and Refining capacity of over 5000 TPD.

AWL is one of the very few national players in the Industry to have this massive production infrastructure, with all its plants so strategically located to take advantage of the Import Parity and Domestic crop season. The company also has packing operations at Kadi [Gujarat], Latur [Maharashtra], Jaipur [Rajasthan], Dharwad [Karnataka], Dewas [Madhya Prades], Nagpur [Maharashtra] and Cochin [Kerala]. With 80 branches, 5000 distributors catering to 1 million outlets, AWL’s products reach to 20 million households across India.

Since its launch in 2000, Fortune took just 20 months to become India’s No. 1 edible oil brands, and is still at the top of the charts. Following the success in India, AWL introduced branded Branded Edible oil to Middle-East and is now exporting its products to more than 19 countries in the Middle-East, South East Asia & East Africa. Adani Wilmar has the largest distribution network among all edible oil brands. Its distribution footprint covers the country with various stock-points covering to more than 5000 distributors, 600 Super Stockists and numerous brokers and other trade associates.

AWL’s retail reach extends to more than one million outlets (including bulk pack retailers) and its consumer reach covers over 80 million Indians. In spite of being the newest entrant among the eight largest producers of edible oils, AWL’s products have taken the market by storm, out-performing the others on key parameters such as volume, household penetration and distribution network. {draw:frame} Adani Wilmar Ltd. Brands – A Snapshot Operating Areas {draw:frame} {draw:frame} Legend: Green – Maximum contributing market Yellow – Second most contributing market Blue – Third most contributing market

Market share and Growth rates AWL commands around 19% share in Branded Refined Oils (No. 1 Player) & 7% in Branded Non Refined Oils. The industry is expecting a growth of 20% year on year. With new communication plans and strategic marketing initiatives, it looks forward to being an undisputed market leader. Market Structure This industry is a high volume, medium growth sector characterized by excess/ idle capacities owing to in efficient operations. Imports have been influencing prospects, leading to domestic industry crisis. The market of edible oils shows a monopolistic structure due to the following factors:

Different and many players in the market Differentiated products. Prices charged are different. Data Analysis This part was developed by conducting a survey among the retailers and consumers keeping edible oils as the product. We came across the following results: When customers were asked to rank their preference of edible oil among the popular brands: {draw:frame} So we deduce that Suffola is the most popular brand among consumers surveyed. The second parameter was the importance of price while choosing a particular brand of oil.

Since price is the most important factor that a person considers while choosing any product, this question was more relevant here since oil is an item of necessity in most households and since there is not a major difference in the prices of various competitors in the market, the elasticity of demand for this product depends on how price sensitive the customers are: {draw:frame} Therefore we can conclude that there are two kinds of consumers in this industry- one who are quite price sensitive even though the nature of the product is that it is a necessity and the other category is the one which are not that price sensitive.

Our third question was based on the loyalty part i. e how loyal customers are to a particular brand of oil that they are consuming. {draw:frame} Here we see that the customers are more or less neutral i. e they are not very concerned or considerate towards this factor. Our next question pertained to the knowledge of the customers and retailers as in which brand they thought had the most types of edible oil. (mustard, soyabean, etc) {draw:frame} Here again we see that the major competition is between Suffola and Dhara. Fortune is known for the variety of oils it produces but this aspect is directly related to the popularity of the brand.

Therefore Fortune does not rank very high here as well. This question related more to the customer preferences i. e what were the factors that they considered important while choosing a type of edible oil. {draw:frame} *People may select more than one checkbox, so percentages may add up to more than 100%. So we see that after price, the health factor is the upmost in the customer’s mind while deciding on a particular brand of oil. This question was only for the retailers to see the average demand of Fortune oil in a day. {draw:frame} The last question was based on the popularity of Fortune among its competitors on a scale of 1-5. {draw:frame} Sales Forecasting

Trend projection method: This classical method of business forecasting is essentially concerned with the study of movements of variables through time. It is used under the assumption that the factors responsible for past trends in the variable to be projected will continue to play their part in the future in the same manner and to the same extent in magnitude and direction. There are three techniques of trend projection: Graphical method Least square method Box-Jenkins method *Sales forecast of AWL for the year 2008 using Least Square method (which is same as simple linear regression method)*: {draw:frame} Line of best fit {draw:frame} 1. Trend Projection Method: The straight line trend equation used for projecting future sales is: Where, S = annual sales T = time in years , b are constants The constants a and b are estimated by solving the following two equations: Here, n = 6 ?S = 8211. 38 crores ?ST = 32099. 54 crores ?T = 21 ?T2 = 91 On solving the above two equations we get, a = 696. 63 and b = 191. 98 RMSE Calculation: On the basis of the calculated values of a and b, the predicted sales value for the years 2006, 2007 and 2008 will be: Sp2006 = 696. 63 + (191. 98*7) = 2040. 49 crore Sp2007 = 696. 63 + (191. 98*8) = 2232. 47 crore Sp2008 = 696. 63 + (191. 98*9) = 2424. 45 crore And, the actual sales values for the above three years are: Sa2006 = 2072. 00 crore Sa2007 = 2487. 00 crore Sa2008 = 3497. 00 crore = 636. 69

Sales for 2009 and 2010 can also be forecasted: S2009 = 696. 63 + (191. 98*10) = 2616. 43 crore S2010 = 696. 63 + (191. 98*11) = 2808. 41 crore *2. Trend* forecasting: This method is used when sales (or any dependent variable) have increased over the past years at an increasing rate or at a constant percentage rate. According to a research study by AC Nielson, the company is expected to grow 20% per year. Thus, assuming a constant percentage growth rate for the company, the sales for a particular year can be estimated as – Where, St = sales for any time period t So = sales in the base year g = constant growth rate Taking logarithm on both sides,

In our case, the year 2000 is taken as the base year and g is 20% or 0. 2. We have to project the sales for future years. RMSE Calculation: As per exponential forecasting, the predicted sales value for 2005, 2006 and 2007 will be: And, the actual sales values for the above three years are: Sa2006 = 2072. 00 crore Sa2007 = 2487. 00 crore Sa2008 = 3497. 00 crore = 1061. 52 Sales for 2009 and 2010 can also be forecasted in a similar manner: S2009 = exp (6. 76 + 10*0. 182) = 5324. 10 crores S2010 = exp (6. 76 + 11*0. 182) = 6386. 87 crores *3. E*xponential smoothing: It is a popular technique for short-run forecasting. It uses a weighted average of past data as the basis for a forecast.

It gives higher weight to most recent data and least weight to observations of distant past. The weights for past data are chosen in accordance with their degree of influence on the future. The formula for exponential smoothing is- Where, St+1 = exponentially smoothed forecast Yt = actual sales of previous year St = forecasted sales of last year Now, we apply this method on the available sales data of AWL considering a six period average as the initial forecast for the year 2006: S2006 = (865. 00+1011. 55+1374. 94+1512. 43+1647. 86+1799. 60)/6 We take the smoothing constant, a = 0. 4 Therefore, S2007 = (0. 42072) + (0. 61368. 56) S2008 = (0. 42487) + (0. 61509. 25) RMSE Calculation: = 1077. 406

Sales for the year 2009 can also be predicted as: S2009 = (0. 43497. 00) + (0. 61984. 75) = 2589. 65 cr Calculation of Correlation: This shows that there is a high degree of correlation between the time period and sales i. e more the time period, more are the sales. This means that sales are highly dependent on the time period positively. Calculation of Herfindahl Index Market share of Fortune: 20% Suffola: 27% Nature fresh: 10% Sundrop: 28% Dhara: 10% Others: 5% Herfindahl Index: (20^2)+(27^2)+(10^2)+(28^2)+(10^2)+(5^2) Since the value of H (Herfindahl index) is high, we can say that the concentration ratio is also high in the market of edible oils. Conclusion

The root mean square error value in the least square method is less than that in the exponential forecasting method. Thus, the sales predicted by least square method will be a better estimate of the future sales than that predicted by exponential forecasting method. References Ebsco host (database) Peterson, Lewis and Jain: Managerial Economics Prowess (database) www. adaniwilmar. com www. adani. in www. fundoodata. com www. crisinfac. com APPENDIX (QUESTIONNAIRE) {text:list-item} {text:list-item} {text:list-item} (This means that if your choice of oil is not available, are you ready to buy some other brand) {text:list-item} {text:list-item} {text:list-item} {text:list-item}

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