design and development of a revenue generation...

Business and Management Research Journal Vol. 2(2), pp. 61 - 76, May 2013 Available online at http://www.resjournals.com/RBM 2026-6804 ©2013 International Research Journals

Full Length Paper

Design and Development of a Revenue Generation Model for Retail Mall: A Case Analysis

*Srinivas Gumparthi1 and T.Roopasree2

SSN School of Management, SSN Institutions, Kalavakkam, Chennai- 603 110

*Corresponding Author's Email: [email protected], [email protected], Tel. (Mob.): 9444104060

ABSTRACT

The malls are part of retail marketing movement in India. There are several malls which have come up in last 4 to five years in every major metropolitan city in India. But most of the mall are facing problem of revenue optimization by utilizing the resources and utilities created in the mall such as space, time, etc., the vendors/brands are given a plot of space against some commercial terms. There are assortments of brands operating from one store. Some brands perform at par with the expectations and some do not. There are neither any criteria’s for brand selection nor any formal system to evaluate their performance. Hence, this study aims at finding out the best suited criteria for brand selection so that it reduces the need for relaying and avoiding vacant floor space by choosing fast moving brands. The company spends extensively on project relaying to reduce the loss faced by brands that end up paying more Minimum Guarantee amount than their net income due to inadequate sales performance. This can be done by selection of performing brands and elimination of non performing brands on the basis of evaluation criteria’s of past performances. Thus unnecessary vacant floor space would also be dealt with, eventually enhancing the profits earned. The analysis involves only Bangalore mall which is located in the MG Road area. The research carried out is a Descriptive Research, and only Secondary data was used for the project. The research basically involves identification of highly performing brands that are beneficial Earnings vise and elimination of non performing brands that block a huge chunk of space. The project also aims at providing each category with an accessible brand bin, from which it would be helpful to identify high yielding brands with respect to its sustainability in the proposed criteria list. The research includes Revenue corresponding to Central brands for the past 2 years. With the data collected from many secondary sources, the data are analyzed with respect to the research objectives. The analysis part builds a model to attain the objective. Based on the data analysis, best performing brands have been identified on the basis of assumptions and constraints based on which conclusions have been given for each sector.

INTRODUCTION INDUSTRY PROFILE Background Today people look for better quality product at cheap rate, better service, better ambience for shopping and better shopping experience. Organized retail promises to provide all these. Retail Market in India today is the second fastest growing economy of the world after China.

Indian market has become the most lucrative market for retail investment in the world. The recent years have witnessed rapid transformation and vigorous profits in Indian retail stores across various categories. This can be contemplated as a result of the changing attitude of

62 Indian consumers and their overwhelming acceptance to modern retail formats. Domestic consumption market in India is estimated to grow approximately 7 to 8% with retail accounting for 60% of the overall segment. Of this 60%, organized retail is just 5% which is comparatively lesser than other countries with emerging economies. The negative phase in exports may have compelled the Indian textile retailers to explore the opportunities in the domestic market substantially causing the outstanding growth in the concerned segment. These indications give a positive notion that organized retailing has arrived in the Indian market and is here to stay.

Evolution of the Indian Retail Sector The origins of retailing in India can be traced back to the emergence of Kirana stores and mom-and-pop stores. These stores used to cater to the local people. Eventually the government supported the rural retail and many indigenous franchise stores came up with the help of Khadi & Village Industries Commission. The economy began to open up in the 1980s resulting in the change of retailing. The first few companies to come up with retail chains were in textile sector, for example, Bombay Dyeing, S Kumar's, Raymonds, etc. Later Titan launched retail showrooms in the organized retail sector. With the passage of time new entrants moved on from manufacturing to pure retailing.

Retail outlets such as Foodworld in FMCG, Planet M and Musicworld in Music, Crossword in books entered the market before 1995. Shopping malls emerged in the urban areas giving a world-class experience to the customers. Eventually hypermarkets and supermarkets emerged. The evolution of the sector includes the continuous improvement in the supply chain management, distribution channels, technology, back-end operations, etc. this would finally lead to more of consolidation, mergers and acquisitions and huge investments. Indian organized retail industry The Indian retail industry is the fifth largest retail destination globally. Comprising of organized and unorganized sectors, Retail industry is one of the fastest growing industries in India, especially over the last few years. Though initially, the retail industry in India was mostly unorganized, however with the change of tastes and preferences of the consumers, the industry is getting more popular these days and getting organized as well.The Indian organized retail industry is valued at about $300 billion and is expected to grow to $637 billion in 2015. Indian economy will grow larger than Britain's by 2022; Japan by 2032 and by 2050 will become the second largest economy of the world after China. India is

on the radar screen in the retail world and global retailers and at their wings seeking entry into the Indian retail market. The market is growing at a steady rate of 11-12 percent and accounts for around 10 percent of the country’s GDP. The inherent attractiveness of this segment lures retail giants and investments are likely to sky rocket with an estimate of Rs 20-25 billion in the next 2-3 years, and over Rs 200 billion by end of 2010. Indian retail market is considered to be the second largest in the world in terms of growth potential.

A vast majority of India's young population favors branded garments. With the influence of visual media, urban consumer trends have spread across the rural areas also. The shopping spree of the young Indians for clothing, favorable income demographics, increasing population of young people joining the workforce with considerably higher disposable income, has unleashed new possibilities for retail growth even in the rural areas. Thus, 85% of the retail boom which was focused only in the metros has started to infiltrate towards smaller cities and towns. Tier-II cities are already receiving focused attention of retailers and the other smaller towns and even villages are likely to join in the coming years. This is a positive trend, and the contribution of these tier-II cities to total organized retailing sales is expected to grow to 20-25%.The organised retail sector, which currently accounts for around 5 per cent of the Indian retail market, is all set to witness maximum number of large format malls and branded retail stores in South India, followed by North, West and the East in the next two years. Tier II cities like Noida, Amritsar, Kochi and Gurgaon, are emerging as the favoured destinations for the retail sector with their huge growth potential.

Further, this sector is expected to invest around US$ 503.2 million in retail technology service solutions in the current financial year. This could go further up to US$ 1.26 billion in the next four to five years, at a CAGR of 40 per cent.

Various formats of organized retail

Hyper marts/supermarkets: Large self-servicing outlets offering products from a variety of categories.They store products of multiple brands comprising food items and non-food items. E.g.: Spencers.

Mom-and-pop stores: They are family owned business catering to small sections; they are individually handled retail outlets and have a personal touch.

Departmental stores: Are general retail merchandisers offering quality products and services.

Convenience stores: Are located in residential areas with slightly higher prices goods due to the convenience offered.

Shopping malls: The biggest form of retail in India, a huge enclosure which has different retail formats. Malls offer customers a mix of all types of products and services including entertainment and food under a single roof. E-trailers: Are retailers providing online buying and selling of products and services.

Discount stores: These are factory outlets that give discount on the MRP.

Vending: It is a relatively new entry, in the retail sector. Here beverages, snacks and other small items can be bought via vending machine.

Category killers: Small specialty stores that offer a variety of categories. They are known as category killers as they focus on specific categories, such as electronics and sporting goods. This is also known as Multi Brand Outlets or MBO's.

Specialty stores: Are retail chains dealing in specific categories and provide deep assortment. These stores focus on a branded product or a product category. E.g.: Bata, Crosswords, Music World Factors contributing to the growth of organized retail

The following factors mentioned below are prime drivers for growth of organised retails in India. 1. Increase in the purchasing power of Indians, 2. Rapid urbanization, 3. Increase in the number of working women, and 4. Large number of working young population

Key players in the Indian retail sector The organized retail sector being the booming sector these days, we see a lot of big players entering the retail market venturing into different formats of retailing. One of the important formats of retailing is LFR (large format retailing).

Pantaloon: Pantaloon is one of the biggest retailers in India with more than 450 stores across the country. It was started by Kishore Biyani- India's largest retailer. The various formats of pantaloon retail are: Pantaloons, Big Bazaar, Food Bazaar, Central etc.Headquartered in Mumbai, it has more than 5 million sq. ft retail space located across the country. It's growing at an enviable pace and is expected to reach 40 million sq. ft by the year 2014. In 2001, Pantaloon launched country's first hypermarket ‘Big Bazaar’.

Tata Group: Tata group is another major player in Indian retail industry with its subsidiary Trent, which

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operates Total, Croma, Westside and Star India Bazaar. Established in 1998, it also acquired the largest book and music retailer in India ‘Landmark’ in 2005. So, took over Landmark’s Lifestyle stores.Trent owns over 4 lakh sq. ft retail space across the country.

RPG Group: RPG Group is one of the earlier entrants in the Indian retail market, when it came into food and grocery retailing in 1996 with its retail Foodworld stores. Later it also opened the pharmacy and beauty care outlets ‘Health & Glow’.Its various formats are: Food World, Music World, Health & Glow, Spencer's.

Reliance: Reliance is one of the biggest players in Indian retail industry. More than 300 Reliance Fresh stores and Reliance Mart are quite popular in the Indian retail market. It's expecting its sales to reach Rs. 90,000 cores by 2010.

AV Birla Group: AV Birla Group has a strong presence in Indian apparel retailing and has introduced ‘More’ outlets for food categories. The brands like Louis Phillipe, Allen Solly, Van Heusen, and Peter England are quite popular. It's also investing in other segments of retail. It will invest Rs. 8000-9000 crores by 2010. Challenges facing Indian retail industry Despite the rosy hopes, some facts have to be considered to positively initiate the retail momentum and ensure its sustained growth. The major constraint of the organized retail market in India is:

The competition from the un-organized sector.

Traditional retailing has been deep rooted in India for the past few centuries and enjoys the benefits of low cost structure, mostly owner-operated, therein resulting in less labor costs and little or no taxes to pay.

Consumer familiarity with the traditional formats for generations is the greatest advantage to the un-organized sector.

Organized sector have big expenses like higher labor costs, social security to employees, bigger premises, and taxes to meet.

Availability and cost of retail space is one major area where Government intervention is necessary.

Liberalizing policy guidelines for FDI needs focus as well.

Proper training facilities for meeting the increasing requirements of workers in the sector would need the attention of both Government and the industry.

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Competition for experienced personnel would lead to belligerence between retailers and higher rates of attrition, especially during the phase of accelerated growth of the retail industry.

The process of avoiding middlemen and providing increased income to farmers through direct procurement by retail chains need the attention of policy makers.

Taking care of supply chain management, mass procurement arrangements and inventory management are areas that need the focus of entrepreneurs.

The tax structure in India favors small retail business.

Lack of adequate infrastructure facilities.

High cost of real estate.

Dissimilarity in consumer groups.

Restrictions in Foreign Direct Investment.

Shortage of retail study options.

Shortage of trained manpower.

Low retail management skill. India is now on the radar of global retailers. Accelerated development of retailing industry in the country and building brand value of domestic products is essential not only for marketing our consumer products more efficiently, but also for the development of our own retailing industry. Future trends

Lifestyle International, a division of Landmark Group, plans to have more than 50 stores across India by 2012–13.

Shoppers Stop has plans to invest Rs250 crore to open 15 new supermarkets in the coming three years.

Pantaloon Retail India (PRIL) plans to invest US$ 77.88 million this fiscal to add up to existing 2.4 million sq ft retail space. PRIL intends to set up 155 Big Bazaar stores by 2014, raising its total network to 275 stores.

Timex India will open another 52 stores by March 2011 at an investment of US$ 1.3 million taking its total

store count to 120. In the first six months of the current fiscal ending September 30, 2009, the company has recorded a net profit of US$ 1.2 million.

Australia's Retail Food Group is planning to enter the Indian market in 2010. It has plans to clock US$ 87 million revenue in five years. In 20 years they expect the India operations to be larger than the Australia operations. LITERATURE REVIEW Constructing business models in environments characterized by high complexity and ambiguity has much in common with Weick’s (1993: 636) notion of sense making: “Sense making is about contextual rationality. It is built out of vague questions, muddy answers, and negotiated agreements that attempt to reduce confusion.” We think that this process is closely related to Prahalad and Bettis’s (1986) notion of a dominant logic, since that logic is intended to reduce ambiguity and make sense of complex choices faced by firms. The choice of business model constrains other choices, selecting out certain possibilities, even as other prospects are logically reinforced.

Research objective of this paper on A Developing Revenue Generation Retail Mall based on three existing areas of literature: 1) empirical studies of retail store execution, 2) literature on the financial performance in the retail industry and 3) empirical studies of execution in other industries such as retail banking and automotive manufacturing. Retail store execution strategies have attracted the attention of researchers in operations management only recently, but this stream of work is most closely related to our paper. Perhaps the first reference on retail store execution is Salmon (1989) who argued that execution in retailing has become more important than other aspects of retail business (e.g., merchandising). DeHoratius and Raman (2006) analyze the relationship between incentives provided to store managers and monthly sales and shrinkage across a chain of stores. The present work, find a positive and significant relationship between brands, type of outlets, movement inventory and sales at the store level.

Ton and Huckman (2005) study the impact of employee turnover on process conformance within retail stores and find that the negative effect of turnover is most pronounced in stores with low process conformance (lesser discipline in process execution and adherence to quality standards.

For the purposes of our paper, we focus only on customer satisfaction studies that are immediately related to our work in retailing and does not survey the literature that studies the design of satisfaction survey instruments, because in this work we had no control over survey

design. The basic tenet of this research stream is that higher service quality improves customer satisfaction, resulting in better financial performance, although the mechanisms by which this improvement happens vary. Iacobucci et al. (1994, 1995) provide precise definitions of service quality versus customer satisfaction. They contend that service quality should not be confused with customer satisfaction, but that satisfaction is a positive outcome of providing good service. Ittner and Larcker (1998) provide empirical evidence at the customer, business-unit and firm- level that various measures of financial performance (including revenue, revenue change, and margins, return on sales, market value of equity and current earnings) are positively associated with customer satisfaction. However, in the retail industry they find a negative relationship between satisfaction and profitability which may be because benefits from increased satisfaction can be exceeded by the incremental cost in retail. Sulek et al. (1995) find that customer satisfaction positively affects sales per labor hour at a chain of 46 retail stores. Anderson et al. (2004) find a positive association between customer satisfaction at the company level and Tobin’s q (a long-run measure of financial performance) for department stores and supermarkets. Babakus et al. (2004) link customer satisfaction to product and service quality within retail stores and find that product quality has a significant impact on store-level profits. To summarize, research on customer satisfaction views employees as facilitators of the sales process who are critical to improving the conversion ratio, by providing information to the customers on prices, brands, and product features and by helping customers to navigate store aisles, finding the product and even cross-selling other products. The unique feature of the retail store execution problem is that it combines the factory and the sales components, but this stream of literature focuses only on the latter.

Empirical studies of execution span other industries as well. For example, retail banking is dominated by the sales function; Frei and Harker (1999) quantify the inefficiencies in process execution due to process design using Data Envelopment Analysis. Frei et al. (1999) study the impact of the aggregate process performance and process variation on the financial outcome using a sample of 135 bank branches. They report that process variation negatively affects financial performance. Another prominent focus on execution which takes the factory viewpoint is found in the automotive industry Marshall Turner, “Increasing the Contribution of Revenue Generating Activities to the Smithsonian Institution Mission” published on January 28, 2008 has helped in forming a framework for the project

Highlighting the need for improvement in different areas of a retail chain

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Suggesting the need for a highly formalized revenue generation pattern

Many models of revenue sharing have been discussed which are used as a base line to formulate a model for the existing situation. Imran K. Jalozie, H.Joseph Wen, H.Lisa Huang , “ A Framework for Selecting E – Commerce Business Models” in which the authors have developed a model on the basis of 12 essential components of E-Commerce business. This idea has been used in the project to formulate the constraints on the basis of which the revenue generation model has been generated. James Little, Brain Coughlan, “Optimal inventory policy within hospital space constraints” published in the journal “Health Care Management Science” on April 11, 2008 has highlighted the need to concentrate more on highly profitable category than spend space on all the available categories of services at the hospital. This thought has also been inculcated in the developed revenue generation model, where the profitability of the existing categories have been analyzed and better performing categories have been identified and also a new category has been advised to be included to increase the profitability.

RESEARCH METHODOLOGY

NEED FOR THE STUDY

PRIL spends extensively on project relaying to reduce the loss faced by brands due to inadequate sales performance, thus losing a major part of its profit on the relaying expenditure. This happens only because there does not have any proper evaluation or selection criteria. The study was intended to prepare a Revenue Generation Model that would help identifying the Performing and Nonperforming brands for each type of commercial term. SCOPE OF THE STUDY The scope of the study was carried out in a Mall (M.G.Road), Bangalore. The study covers the revenue earning patterns of all the categories of Brands for the financial year beginning from July 2007 - June 2008 & July 2008 – June2009.

OBJECTIVE OF THE STUDY Primary Objective To study the existing Revenue Generation process of a Mall (M.G.Road) and develop a Revenue Generation

66 model after identifying and eliminating the inefficiencies in the current practice. Secondary Objectives

To reduce the need for relaying process.

To avoid space vacancy at any point of time in the year.

To choose the fast moving brands rather than Non Performing brands. LIMITATIONS OF THE STUDY The research suffers from the following limitations:

The study does not test people’s preference of brands.

Only two dimensions Revenue & Space occupied are analysed.

The study is confined to brands and categories existing in the mall for the past 2 years.

RESEARCH DESIGN The research design used in this study is Descriptive Research. Descriptive study is undertaken in order to offer to the researcher a profile or to describe the relevant aspects of the phenomena of the variables of interest in a situation. SOURCES OF DATA The sources of data used in this study are secondary in nature.

The secondary sources of data are unstructured interviews with space management department executives to draw the details of the existing process followed.

Revenue details of different brands of different category for the past 2 years have been obtained. METHODOLOGY FOLLOWED The different stages of the project begin with:

Study of the existing Revenue Generation process

The usual process begins with having a talk with the vendors and deciding on the commercial terms. After the negotiations are through, the vendors seek an entry into the mall. Once mall was open, and it started doing good business, a review was done. This review compared mall with the competitors like Shopper’s Stop, Pyramid etc. On the basis of this review, some brands were added and deleted. When the other malls were opened, the company went ahead with the same set of vendors. A 10-15 % annual difference in the vendor occurred from store to store in the past years. It happened due to the periodic review of the performance of the brands.

This periodic review is the random system that exists till today. The category manager heads the auditing. It is done quarterly, half-yearly and annually. It decides whether or not to continue with the brand i.e. its existence. There can be also a change in the commercial agreements and terms. The manager may negotiate with the vendor based on the brand’s performance. They might also ask a vendor to upgrade its potential by relocating the brands.

Identifying the inefficiencies in the current practice.

The inefficiencies that were identified are: A need to formalize the process because if it was not done the vendors would seek an upper hand in negotiating as the company will not know the brands performance, and hence the contract may end up in favor of the vendor. So there arises a need for evaluating the brands on some basis for selection itself, so that the need for relaying reduces. There needs to be a formal system to ensure brand selection and brand performance evaluation. Developing a model after elimination of the identified inefficiencies. Steps in model building 1. Assumptions and Constraints 2. Formulation of Equation 3. Constraint explanation 4. Sensitivity Analysis 5. Alternative Bin creation and elimination of unproductive brands 6. Model Results Assumptions and Constraints used:

Assumptions:

Each brand generates a portion of the Total revenue generated by the contract.

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Table 1: Table illustrating number of brands under each contract type and their corresponding average revenues.

HO V F + V Total

No of Brands 15 9 4 28

Average Revenue 2784610 2376735 3482264 8643609

Total 41769153 21390615 13929056 77088823

Constraints:

Individual brand revenue as against the total category revenue should not increase 15%.

Percentage of space occupied by Individual brand as against the total category space occupied should not be more than the percentage of revenue generated by the brand. Formulation of equation The brand’s commercial contracts with the company are of 3 types

Higher off (HO): In HO contract the brand pays the company the higher value between the MG guaranteed and the percentage sales margin

Variable (V): In V contract the brand pays the company a percentage sales margin

Fixed + Variable (F + V): In F + V contract the brand pays a fixed rent plus a percentage sales margin to the company. It refers to the various terms and conditions that a brand guarantees to do

Minimum guarantee sales: It is the minimum amount of sales that a brand guarantees to do. The better the brand the more sales it can guarantee. Whatever the brand quotes, the company takes in thrice the amount as a deposit from the brand.

Percentage sales margin: It is the percentage of the total sales that a brand gives to the company as a contribution. If the brand does fewer sales than the minimum guarantee, the company still takes the percentage of the MG sale. If the brand does more sale than the MG sales, we take the percentage on the actual sales. Each brand falls into any of the above mentioned 3 terms. The sum of revenue generated under each of these commercial contracts will give us the total revenue generated. Hence, with the above information we can formulate the equation – 2.1:

∑ CiBi = ((No of B1 * Average C1) + (No of B2 * Average C2) + (No of B3 * Average C3))

Constraint Explanation with an example of youth category The youth category has a total of 25 brands, out of which 12 brands fall under HO, 10 brands fall under V and 2 brands fall under F+V. Hence, we multiply the average revenue of each category with the number of brands to obtain the total revenue generated from the respective category. 12 * 2712053 + 10 *2577907 + 3 * 20219193 = 118981285

Here we are eliminating a few brands from each category on the basis of these constraints:

Brands generating less than 2% of the Total Revenue Generated by each Contract. The reason for eliminating brands less than 2% is that, on observation it has been found that these brands occupy more than 25% of the category’s space, so as per Pareto principle (80-20) it would be better to eliminate these less productive brands to be able to allot more space for highly productive brands.

Brands generating more than 15% of the Total Revenue Generated by each Contract. The reason for eliminating brands more than 15% is that, brands having high share of revenue generation are high risk brands, as incase they are decide to leave the mall, a huge chunk of revenue is lost, and it becomes difficult to compensate. Hence it would be better to have an optimized revenue distribution. After the elimination of certain brands on the basis of the above stated constraints, we multiply the revised number of brands with the same average revenue, and get the category revenue that would be obtained with these numbers of brands.

7 * 2712053 + 4 *2577907 + 3 * 20219193 = 89953578

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Figure 1.Sales Volume contribution by various brands

With this it would be easy to find out in which contract new brands can be added to increase the revenue generated. The average being high in contract - 3, it would be preferable to increase the number of brands in this contract. But as the company does not wish to add any new brands to this type. We suggest they add new brands to contract - 1 as it has the next highest average income. Sensitivity Analysis: On the base of revenue substitution: - compare the following 3 outputs

Revenue with all the existing brands (28).

Revenue with top brands only (eliminating least brands) (20).

This is to show revenue increase or decrease in revenue that would happen on wrong or right selection from bin. On the base of space optimization:-

Multiply the space occupied by eliminated brands with the average revenue for that space.

We would seek the additional space available for generating excess revenue, by either lending additional space to existing brands or to new brands. Alternative Bin creation and elimination of unproductive brands: We have suggested the company to add new brands to the contract hence; we have to create a bin which would provide alternative brands that can be introduced. The bin will contain brands for selection and the selection criteria to choose brands would be: Sales Volume It is the amount of revenue generated by a particular brand in one accounting period. There are bulk sales at low price or descent sales at high price; in the end what matters are the sales generated by the brand.(Figure 1) Market share Market share is the percentage or proportion of the total available market or market segment that is being serviced by a company. It can be expressed as a company's sales revenue (from that market) divided by the total sales revenue available in that market. It can

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Figure 2. Market Share of various brands

also be expressed as a company's unit sales volume (in a market) divided by the total volume of units sold in that market. (Figure 2) Brand Performance It refers to the comparison between the target and achieved sales. The target is the MG sales and the achieved being the actual sales happening per month. The deviation is calculated. Some are negative deviation, some are positive. The graph is plotted. (Figure 3). Brand equity Brand equity refers to the marketing effects or outcomes that accrue to a product with its brand name compared with those that would accrue if the same product did not have the brand name. And, at the root of these marketing effects is consumers' knowledge.(Figure 4) Model Results / suggestions made:

Brand retention and elimination criteria’s have been formulated.

Optimum space utilization has been done by allocating space of least revenue generating brands to new brands that would be selected from the bin.

Use of Pareto principle for space utilization and revenue generating brands.

Combination of space and revenue will provide a model that has considered Risk and Revenue. CATEGORY 1 – LADIES WESTERN There are a total of 28 brands in the ladies western category. On comparison of data given in Table 2 it is evident that

Top 5 brands that contribute up to 41% of the total revenue occupy only 23.73% of space.

At the same time, Brands contributing 7.94% of revenue occupy 25.15% of the space.

Hence on eliminating these 9 brands, the company can avail 25.15% of space that can be allocated to new brands or can be utilized for expansion of existing brands. The average being high in F + V, it would be preferable to increase the number of brands in this contract. But as the company does not wish to add any new brands to this contract. We suggest they add new brands to HO as it has the next highest average income.

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Figure 3. Brands performance

Hence, Revenue generated can range between 70966905 to 90356215. (As per revenue substitution sensitivity analysis). 1558 Sq Ft of space would be left over for further use and there are chances of earning 1558 Sq Ft * Rs 12445 = 19389310 (as per space optimization sensitivity analysis). Alternative Brand Bin: 1. Lacoste 2. Gucci 3. Fubu 4. Fila CATEGORY 2– LADIES ETHNIC There are a total of 16 brands in the ladies western category.

On comparison of data given in Table 5 it is evident that

Top 5 brands that contribute up to 82.14% of the total revenue occupy only 50.25% of space.

At the same time, Brands contributing only 6.88% of revenue occupy 28.97% of the space.

Hence on eliminating these 7 brands, the company can avail 28.97% of space that can be allocated to new brands or can be utilized for expansion of existing brands. The average being high in F + V, it would be preferable to increase the number of brands in this contract. But as the company does not wish to add any new brands to this contract. We suggest they add new brands to HO as it has the next highest average income.

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Table 2. Table illustrating the % of revenue contributed by the brand towards the total revenue of the category and % of space occupied by each brand arranged in descending order for convenience of analysis.

revenue wise% Net Contribution Space occupied wise% Net Contribution

1 JEALOUS 10.92 ANNABELLE 510 8.23

2 SCULLERS FOR HER 8.07 REMANIKA 387 6.25

3 ALLEN SOLLY 7.89 AND 310 5.00

4 VAN HEUSEN 7.37 VIBE 301 4.86

5 ANNABELLE 6.97 41% ALL 300 4.84

6 PROVOGUE 5.80 109F 286 4.62

7 AND 5.29 ANJANNE 285 4.60

8 HONEY 5.15 ALLEN SOLLY 270 4.36

9 REMANIKA 4.42 JEALOUS 265 4.28

10 109F 4.07 HONEY 265 4.28

11 RIG 3.77 VAN HEUSEN 250 4.04

12 ANJANNE 3.74 RITU KUMAR 227 3.66

13 BARE DENIM 3.71 BARE DENIM 220 3.55

14 NOI 3.19 UPPER CLASS 220 3.55

15 ALL 2.59 BARE 220 3.55

16 UMM 2.45 ARROW 205 3.31

17 AJILE 2.41 COLOR PLUS 205 3.31

18 RECAP 2.13 NOI 195 3.15

19 UPPER CLASS 2.11 50.83% PROVOGUE 190 3.07

20 ARROW 1.78 SCULLERS FOR HER 175 2.83 23.73%

21 MISS PLAYERS 1.34 UMM 163 2.63

22 WILLS SPORTS 1.22 MISS PLAYERS 150 2.42

23 COLOR PLUS 1.03 AJILE 135 2.18

24 WILLS CLASSIC 0.98 WILLS SPORTS 120 1.94

25 WILLS CLUBLIFE 0.73 RECAP 110 1.78

26 BARE 0.44 RIG 100 1.61 51.11%

27 RITU KUMAR 0.25 WILLS CLASSIC 75 1.21

28 VIBE 0.17 7.94% WILLS CLUBLIFE 55 0.89 25.15%

Table 3.Table illustrating number of brands under each contract type and their corresponding average revenues.

HO V F + V Total


Average Revenue 2784610 2376735 3482264 8643609

Total 27846102 14260410 6964528 49071040

Alternative Brand Bin: 1. Aki Narula

2. Abu Jani 3. Ashima and Leena 4. Ashish Soni

72

Table 4. Table illustrating number of brands under each contract type and their corresponding average revenues.

HO V F + V Total


Average Revenue 3290284 1608299 29023295 33921878

Total 19741704 14474691 29023295 63239690

Table 5.Table illustrating the % of revenue contributed by the brand towards the total revenue of the category and % of space occupied by each brand arranged in descending order for convenience of analysis.

No REVENUE WISE% Net Contribution space occupied wise% Net Contribution

1 NEERU'S 45.89 BIBA 897 14.68

2 BIBA 12.28 NEERU'S 879 14.39

3 MIX N MATCH 10.32 ISHVARAH 509 8.33

4 ISHVARAH 7.31 INDUSTREE 509 8.33

5 W 6.33 82.14% MIX N MATCH 445 7.28

6 TRISHA 3.85 GLOBAL DESI 445 7.28

7 JOLE 2.50 AKKRITI 390 6.38

8 AKKRITI 2.50 W 340 5.56 50.25%

9 GLOBAL DESI 2.13 10.97% ARHA 288 4.71

10 ARHA 1.82 JOLE 250 4.09

11 ASESSA 1.35 KURTA CO 240 3.93

12 BLUE MANTRA 1.34 TRISHA 220 3.60

13 KURTA CO 0.83 BLUE MANTRA 220 3.60

14 INDUSTREE 0.61 ASESSA 215 3.52 20.79%

15 MAAHI MNM 0.52 MAAHI RTS 133 2.18

16 MAAHI RTS 0.41 6.88% MAAHI MNM 130 2.13 28.97%


HO V F + V Total


Average Revenue 3290284 1608299 29023295 33921878

Total 13161136 6433196 29023295 48617627


HO V F + V Total


Average Revenue 2712052 2577906 60657580 65947538

Total 32544624 25779060 181972740 240296424

CATEGORY 3 – YOUTH

There are a total of 25 brands in the youth category.

On comparison of data given in Table 8 it is evident that


73


No REVENUE WISE% Net Contribution SPACE OCCUPIED WISE%

21.21 UCB 650 8.53

2 LEE 15.58 LEVIS 620 8.14

3 LEE COOPER 14.19 LEE 550 7.22

4 PEPE 6.90 PEPE 550 7.22

5 URBAN YOGA 4.66 62.53% WRANGLER 450 5.91

6 LEVIS 4.23 LEE COOPER 400 5.25

7 BARE DENIM 3.88 BARE DENIM 390 5.12

8 AJILE 3.30 KILLER 390 5.12

9 SPYKAR 3.10 AJILE 357 4.69

10 STATUS QUO 2.68 SPYKAR 340 4.46

11 NUMERO UNO 2.45 FLYING MACHINE 328 4.31

12 KILLER 2.40 BOSSINI 292 3.83

13 M SQUARE 2.35 UMM 292 3.83

14 HIEDELBERG 2.09 26.49% STATUS QUO 281 3.69

15 FLYING MACHINE 1.77 USI 255 3.35

16 USI 1.73 NUMERO UNO 252 3.31

17 UMM 1.72 INEXCESS 230 3.02

18 INEXCESS 1.69 HIEDELBERG 227 2.98

19 UCB 1.36 M SQUARE 225 2.95 40.46%

20 BOSSINI 1.08 TOP 10 182 2.39

21 TANTRA 0.66 JUST NATURAL 140 1.84

22 JUST NATURAL 0.54 URBAN YOGA 110 1.44 27.04%

23 TOP 10 0.35 TANTRA 100 1.31

24 KAPPA 0.06 BARE 6 0.08

25 BARE 0.02 10.97% KAPPA 0 0.00 32.49%


HO V F + V Total


Average Revenue 2712052 2577906 60657580 65947538

Total 18984364 10311624 181972740 211268728


HO V F + V Total


Average Revenue 1518575 344248 320631 2183454

Total 18222900 1376992 320631 19920523


Hence on eliminating these 11 brands, the company can avail 32.49% of space that can be allocated to new

brands or can be utilized for expansion of existing brands. The average being high in F + V, it would be preferable to increase the number of brands in this contract. But as the

74


No Revenue wise% Net Contribution Space occupied wise% Net Contribution

21.86 CHALK 300 9.57

2 LEE KIDS 14.68 ZAPP 288 9.19

3 DROP 9.16 RUFF KIDS 275 8.77

4 WEEKENDER KIDS 7.96 GINY & JONY 270 8.62

5 CHALK 7.67 61.33 LILLIPUT 250 7.98

6 ZAPP 7.34 WEEKENDER KIDS 225 7.18

7 ZYXW 6.34 LITTLE KANGAROOS 222 7.08

8 RUFF KIDS 6.16 BARBIE 196 6.25

9 BARE 7214 5.48 DROP 190 6.06

10 LILLIPUT 2.87 LEE KIDS 183 5.84 37.27%

11 AKKRITI 2.47 30.66 PEPPERMINT 155 4.95

12 UCB 1.93 BARE 130 4.15

13 PEPPERMINT 1.92 BARE 7214 130 4.15

14 BARBIE 1.77 AKKRITI 120 3.83

15 LITTLE KANGAROOS 1.38 ZYXW 100 3.19 37.11%

16 BENETTON 0.86 BENETTON 50 1.60

17 BARE 0.14 8.01 UCB 50 1.60 25.62%


HO V F + V Total


Average Revenue 1518575 344248 320631 2183454

Total 10630025 1032744 320631 11983400


HO V F + V Total


Average Revenue 6894620 3529529 15072418 25496567

Total 89630060 17647645 30144836 137422541

company does not wish to add any new brands to this contract. We suggest they add new brands to HO as it has the next highest average income.

Alternative Brand Bin:

1. Hanes 2. Diadora

3. Lotto 4. Kelme CATEGORY 4 - KIDS

There are a total of 17 brands in the Kids category On comparison of data given in Table 11 it is evident that

75


No REVENUE WISE% Net Contribution SPACE OCCUPIED WISE% Net Contribution

1 PROVOGUE 25.34 ALLEN SOLLY 230 4.25

2 SCULLERS 21.09 BASICS 152 2.81

3 COLOR PLUS 11.52 CELIO 610 11.28

4 ALLEN SOLLY 10.42 CLASSIC POLO 190 3.51

5 RIG 5.70 74.07% COLOR PLUS 500 9.25

6 BARE LEISURE 4.23 DOCKERS 30 0.55

7 INDIAN TERRAIN 3.94 F 224 4.14

8 STORI 3.04 JOHN PLAYER 290 5.36

9 JM SPORT 2.57 JM SPORT 205 3.79

10 CLASSIC POLO 2.18 MOUSTACHE 188 3.48

11 JOHN PLAYER 2.15 18.12% PROVOGUE 428 7.92

12 DOCKERS 1.54 RIG 450 8.32

13 MOUSTACHE 1.35 SCULLERS 335 6.20 35.93%

14 F 1.33 STORI 315 5.83

15 CELIO 1.19 WILLS CLUBLIFE 90 1.66

16 BASICS 1.18 WILLS SPORTS 90 1.66

17 WILLS SPORTS 0.66 EASIES 170 3.14

18 WILLS CLUBLIFE 0.52 ALL 300 5.55 34.29%

19 ALL 0.04 INDIAN TERRAIN 300 5.55

20 EASIES 0.00 7.82% BARE LEISURE 310 5.73 29.78%


HO V F + V Total


Average Revenue 6894620 3529529 15072418 25496567

Total 48262340 7059058 30144836 85466234



Hence on eliminating these 6 brands, the company can avail 25.62% of space that can be allocated to new brands or can be utilized for expansion of existing brands. The average being high in F + V, it would be preferable to increase the number of brands in this contract. But as the company does not wish to add any new brands to this

contract. We suggest they add new brands to HO as it has the next highest average income. Alternative Brand Bin: 1. Duke 2. Tentop 3. Cherokee CATEGORY 5 – MENS CASUALS There are a total of 20 brands in the Mens Casuals category

76 On comparison of data given in Table 14 it is evident that



Hence on eliminating these 9 brands, the company can avail 34.29% of space that can be allocated to new brands or can be utilized for expansion of existing brands.

The average being high in F + V, it would be preferable to increase the number of brands in this contract. But as the company does not wish to add any new brands to this contract. We suggest they add new brands to HO as it has the next highest average income.

Alternative brand bin

Duke

FINDINGS As of now no proper pattern has been followed for Brand selection or brand evaluation. The present location that has been analysed is M.G.Road. This being a most happening location, surrounded with many shopping area, the selection of brands at Central becomes more important as the customers have many options available for purchase. It becomes more important to retain customer at the store by providing him many options within the store itself. To increase awareness to customers about all existing brands at Central can be through media inorder to reach wide range of population. A new category called the men’s accessories can be added, which would provide a completeness to the available catgory of apparels. ( belts, ties, cuff links, tie pins etc). RECOMMENDATION The model is recommended to the organization for the analysis of Brand Selection so that the Revenue Generation can be optimized, as well as increasing the profits and for minimizing losses. An organized procedure is always an added benefit to increase the competitive advantage of the company.

CONCLUSION The implementation of a this formal model for Brand Selection and evaluation will not just help the Company in

increasing the Revenue but also will help in reducing the problem of vacant space and need for relaying. REFERENCES Weick Karl (1993). “The Collapse of Sense making in

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