Demand Forecasting

Demand Forecasting in the Indian Retail Industry

Applied Economics (HS 700) Course Project Report Vijay Gabale (07305004) Ashutosh Dhekne (07305016) Piyush Masrani (07305017) Sumedh Tirodkar (07305020) Tanmay Mande (07305051) March 19, 2008

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Contents

1 Introduction 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Challenges Faced in Demand Forecasting 3 Theoretical Framework 3.1 Judgemental . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Methods Requiring Quantitative Data . . . . . . . . . . . . . . . 4 Existing Surveys 5 Our Survey 6 Conclusion 3 3 4 4 6 6 7 8 12 14

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Abstract The retail business in India is expanding in leaps and bounds. With increasing competition, each retailer needs to correctly cope up with the impending demand. The retail firms need to take into account various factors including the lead time and the seasonality of goods. In this report, we study the various techniques used by retailers in India to perform demand forecasting and analysis. We present a case study done at Lakewood Malls Pvt. Ltd. where we understand that historical data and judgemental techniques are primarily used for forecasting of demand.

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Introduction

The A.T. Kearney Global Retail Development Index showed India on the sixteenth position in 1995. In 2004, the publication said, "Despite India's stiff regulatory environment, it shines as the second star of the year, offering potential similar to that revealed by China 15 years ago." Though the comparison with China is sure to hurt the extreme patriot, she shall become forgiving on reading the mention in the next three year's publications. In the 2007 report, the GRDI mentions, "India: talk turns to action. For the third year, India tops the Index as one of the most attractive countries for global retailers. India's GDP is projected to grow by 9 percent in the fiscal year 2007--its highest growth rate in more than 18 years. Projections for 2008 are more than 10 percent, which will likely surpass China's projected rate of growth for the same period. . . the great Indian 'retail gold rush,' which we predicted last year, is now underway." For an industry that is booming at the scale clearly evident from the A.T. Kearney reports, the parties involved have to look ahead in time and take proactive decisions to remain in business. The competition gets tougher day by day as more companies enter the market, and therefore survival in this market requires a lot of correct decisions involving forecasting of demand. For this project, we conducted a survey with a well known firm in the retail sector--Haiko. We found that Haiko uses only simple forecasting techniques based on data from few previous years.

1.1

Background

Historically,the Indian retail sector has been dominated by small independent players such as traditional, small grocery stores and others. Recently organized, multi-outlet retail concept has gained acceptance and has since then accelerated. Driven by changing lifestyles, strong income growth and favourable demographic patterns, Indian retail is expanding at a rapid pace. Mall space, from a meagre one million square feet in 2002, is expected to touch 40 million square feet by end-2007 and an estimated 60 million square feet by end-2008, says Jones Lang LaSalle's third annual Retailer Sentiment Survey-Asia. Alongside, Indian cities are witnessing a paradigm shift from traditional forms of retailing into a modern organized sector. A report by Images Retail estimates the number of operational malls to more than double to over 412 with 205 million square feet by 2010 and further 715 malls by 2015, on the back of major retail developments even in tier II and tier III cities in India. The top ten players in Indian retail sector are

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* Shoppers' Stop, * Westside (Trent), * Pantaloon (Big Bazaar), * Lifestyle, * RPG Retail (Foodworld, Musicworld), * Crossword, * Wills Lifestyle, * Globus, * Piramals (Pyramid and Crosswords), * Ebony Retail Holdings Ltd. Every good forecast requires not only valid historical data and meticulous documentation of demand but also a fundamental understanding of the methods used. In general, there are three factors that influence the accuracy of demand planning: 1. The product and market constellation 2. The forecasting horizon and lead times 3. The forecasting model and the planning team Only those who comprehend the background and the methods of the models can interpret peculiarities, gauge forecasting errors, and recognize and validate the causal connections between external factors and demand. Another aspect that is equally important is to understand the industry and know the competition. In addition, planners need to be able to bring various departments and the company management together in order to promote the exchange of knowledge - a process that is vital for forecasting.

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Objective

The objective of this project is to study the techniques employed by major players in the retail industry to study the trends and make predictions about the demand of various goods. Further, we want to investigate the difference between theoretical techniques taught in the class and those practically applied.

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Challenges Faced in Demand Forecasting

A small retailer may not need and afford a full-fledged demand forecasting analysis. However, with increasing number of bigger retailers entering the market demand forecasting becomes feasible. Firms face a multitude of challenges due to the following factors: 1. scale of forecast (how many goods to include in the forecast?)

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2. sporadic demand (erratic sales for many items in the store) 3. introduction of new goods 4. changing prices and promotions Largescale forecasting. A big retailer may have thousands of items per shop. Since forecasting is an important yet expensive task, the retailer can not forecast for all goods it sells. Though it is infeasible to manually forecast the demand of all the products, it is possible to use automated tools to do so. In most cases, quality forecasts can be obtained from the automated tool and the

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