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2012 APPLICATION OF REVENUE MANAGEMENT FOR SALES OF HERO MOTOCORP LTD TEAM MEMBERS AKANXA (27061) MANDEEP KAUR (27022) PRIYAM DUTTA (27102) 3/27/2012 TABLE OF CONTENT S.NO TOPIC OVERVIEW PAGE 4 Background of the company 4 Revenue objectives of the company ( mention in second paragraph any other objectives for the company) 5 What are the Important factors that contribute to revenue 6 Revenue Variable and capacity constraints 6 Auxillaries 6 FORECASTING The need to forecast and the level to forecast 7 Seasonality and other factors that influence forecast 7 Current Forecasting Methods if any 8 Your Proposed forecasting methods and Forecast error 8 PRICING Strategies 9 Types of prices 10 Price revision methods and frequencies 10 Price elasticity and its impact 11 REVENUE CLASS Defining a revenue class for your problem 12 Protections and how they maximize revenue 12 Explain how maximum revenue is achieved by optimising 13 OPTIMIZATION Objective function and defining the problem Solving the problem and EMSRS Assumptions 16 Optimal demand that maximizes revenue 17 Other revenue maximisation methods ( Over booking, upgrading etc) 18 Your recommendations and rules for maximising revenue 18 How to measure the effectiveness of the revenue management process 18 OVERVIEW We have taken Sales of Hero MotoCorp for our study to apply Revenue Management Techniques in order to maximize the revenue. The project involves understanding the existing system of forecasting, pricing, capacities, timings & varieties offered and exploring the possibility of increasing the revenue by using different forecasting techniques, new pricing strategies, introducing new product varieties, protecting the seats, optimization etc. BACKGROUND OF COMPANY Hero MotoCorp Ltd. (Formerly Hero Honda Motors Ltd.) is the world's largest manufacturer of two - wheelers, based in India. In 2001, the company achieved the coveted position of being the largest two-wheeler manufacturing company in India and also, the 'World No.1' two-wheeler company in terms of unit volume sales in a calendar year. Hero MotoCorp Ltd. continues to maintain this position till date. Hero MotoCorp offers wide range of two wheeler products that include motorcycles and scooters, and has set the industry standards across all the market segments. Hero MotoCorp two wheelers are manufactured across three globally benchmarked manufacturing facilities. Two of these are based at Gurgaon and Dharuhera which are located in the state of Haryana in northern India. The third and the latest manufacturing plant is based at Haridwar, in the hill state of Uttrakhand. The Company's growth in the two wheeler market in India is the result of an intrinsic ability to increase reach in new geographies and growth markets. Hero MotoCorp's extensive sales and service network now spans over to 5000 customer touch points. These comprise a mix of authorized dealerships, service & spare parts outlets , and dealer-appointed outlets across the country. The new Hero is rising and is poised to shine on the global arena. Company's new identity "Hero MotoCorp Ltd." is truly reflective of its vision to strengthen focus on mobility and technology and creating global footprint. Building and promoting new brand identity will be central to all its initiatives, utilizing every opportunity and leveraging its strong presence across sports, entertainment and ground- level activation. Vision The story of Hero Honda began with a simple vision - the vision of a mobile and an empowered India, powered by its bikes. Hero MotoCorp Ltd., company's new identity, reflects its commitment towards providing world class mobility solutions with renewed focus on expanding company's footprint in the global arena. Mission Hero MotoCorp's mission is to become a global enterprise fulfilling its customers' needs and aspirations for mobility, setting benchmarks in technology, styling and quality so that it converts its customers into its brand advocates. The company will provide an engaging environment for its people to perform to their true potential. It will continue its focus on value creation and enduring relationships with its partners. Strategy Hero MotoCorp's key strategies are to build a robust product portfolio across categories, explore growth opportunities globally, continuously improve its operational efficiency, aggressively expand its reach to customers, continue to invest in brand building activities and ensure customer and shareholder delight. REVENUE OBJECTIVES OF THE COMPANY To maximize the Revenue for a given capacity for a financial year by Introduction of sales by channel (internet, dealer and company) with different price points Varying price based on Prior Booking and Days Prior Delivery (within 2-3 days,4-10 days,11-15 days, etc) for different sales channels Varying price during peak and non peak seasons Opening and Closing of inventory based on actual demand Pricing differentially for individual and group booking(e.g. corporate booking) IMPORTANT FACTORS THAT CONTRIBUTE TO REVENUE COMPETITION PRICES COST SEASONALITY RAW MATERIAL NEW ENTRANTS DISTRIBUTION COST INVENTORY COST SUBSTITUTES TAXES(PLACES) AVERAGE REVENUE PER BIKE PER QUARTER FUEL PRICES ECONOMIC CONDITION SEASONALITY PROMOTION DEMAND GEOGRAPHICAL CONDITION (LOCATION/POPULATION DENSITY/TERRAIN) REVENUE VARIABLE AND CAPACITY CONSTRAINTS Revenue Variable: Average Revenue Per Motorcycle Per Quarter Constraint: Plant Capacity: 6 crore units Continuous Production throughout the year AUXILLIARIES 1 Year of free servicing with replacement warranty for essential parts Special Seasonal/ Festival Offers and Gift Vouchers(e.g. Scratch Cards) 3 litres of free petrol at the time of delivery of vehicle Accessories availability at different channel points FORECASTING Forecasting is the process of estimating future scenarios in unknown situations. An important field in forecasting is business forecasting whereby future economical and business scenarios are analyzed. Business forecasting is a combination of judgmental, casual and time series (univariate) forecasting methods. Risk and uncertainty are central to business forecasting and accompany forecasting as tools for evaluating the probability of future scenarios and for decision making (e.g. inventory planning, capacity expansion, investments, risk analysis). This is especially so in case of forecasting for the demand levels of motorcycle sales in a region. According to a global research body, 38 percent of producers all over the world complain that one of their main problems is inaccurate demand planning. This is because poor planning has a negative effect on the ability to deliver, on inventory management, on purchasing, and on capacity utilization. In case of motorcycle sales, the need to provide prompt delivery to customers, and yet maintain the accurate level of inventory without adding to the cost, is tantamount. Identifying supply chain lead times and consumer lead times is hugely important in cases of uncertain demand and in case the supply chain lead-time is greater than the customer required lead-time, one may have to order or provide for stock or resources in anticipation of an order. Forecasting is therefore essential in these cases. A major problem for motorcycle business can be when customers want things at a faster rate than one’s capacity to cope with. One should have the ability to forecast peak demand and their average capacity in advance, so that they can cope with the demand and make the sales when it are required to do so. If they want to give high service to their clients, then they need to be able to match their peak demand with peak capacity. LEVEL TO FORECAST The level to forecast is at per motorcycle level. Seasonality: The business of motorcycle sales is highly seasonal based on a number of factors, like the turn of festivals, the level of income available at a person’s disposal, consensus among family members regarding the kind of vehicle being bought, etc. Especially so in India, when the third and fourth quarter of the year augur the best for motorcycle sales. This is the period that overlaps with important festivals like durga puja, diwali, Christmas, Id, and new year. In addition to that, Indians have a tendency to buy goods on new year. So, that factor plays a role too. Other Factors: Other factors include, marketing promotions, or various sales promotion incentives, that may be initiated from time to time, to improve upon sales. Other marketing strategies may include discounts, promotions, competitors strengths, suppliers efficiency, etc. Current Forecasting Method Current forecasting method is a moving average time series method, with exponential smoothing. Exponential smoothing ascribes, exponentially decreasing weight over time. Proposed Forecasting Method The forecasting method used is trend line analysis. This is the practice of collecting information and attempting to spot a pattern, or trend, in the information. In trend analysis, a forecast is calculated by inserting a time value into the regression equation. The regression equation is determined from the time-serieas data using the “least squares method” . PRICING PRICING STRATEGIES Price discrimination: Price discrimination or price differentiation exists when sales of identical goods or services are transacted at different prices from the same provider. In a theoretical market with perfect information, perfect substitutes, and no transaction costs or prohibition on secondary exchange (or re-selling) to prevent arbitrage, price discrimination can only be a feature of monopolistic and oligopolistic markets, where market power can be exercised. Otherwise, the moment the seller tries to sell the same good at different prices, the buyer at the lower price can arbitrage by selling to the consumer buying at the higher price but with a tiny discount. However, product heterogeneity, market frictions or high fixed costs (which make marginal-cost pricing unsustainable in the long run) can allow for some degree of differential pricing to different consumers, even in fully competitive retail or industrial markets. Price discrimination also occurs when the same price is charged to customers which have different supply costs. The effects of price discrimination on social efficiency are unclear; typically such behavior leads to lower prices for some consumers and higher prices for others. Output can be expanded when price discrimination is very efficient, but output can also decline when discrimination is more effective at extracting surplus from high-valued users than expanding sales to low valued users. Even if output remains constant, price discrimination can reduce efficiency by misallocating output among consumers. Price discrimination requires market segmentation and some means to discourage discount customers from becoming resellers and, by extension, competitors. This usually entails using one or more means of preventing any resale, keeping the different price groups separate, making price comparisons difficult, or restricting pricing information. The boundary set up by the marketer to keep segments separate is referred to as a rate fence. Price discrimination is thus very common in services where resale is not possible; an example is student discounts at museums. Time based pricing: Time-based pricing refers to a type offer or contract by a provider of a service or supplier of a commodity, in which the price depends on the time when the service is provided or the commodity is delivered. The rational background of time-based pricing is expected or observed change of the supply and demand balance during time. Time-based pricing includes fixed time-of use rates for electricity and public transport, dynamic pricing reflecting current supply-demand situation or differentiated offers for delivery of a commodity depending on the date of delivery (futures contract). Most often time-based pricing refers to a specific practice of a supplier. Time-based pricing is the standard method of pricing in the tourist industry. Higher prices are charged during the peak season, or during special-event periods. In the off-season, hotels may charge only the operating costs of the establishment, whereas investments and any profit are gained during the high season. (This is the basic principle of the long run marginal cost (LRMC) pricing, see also Long run). Time based pricing is occasionally used by transportation service providers, whereby higher prices are charged during rush-hours, or, alternatively, some types of reduced-rate tickets are invalid at that time. Time-based pricing is recommendable for utilities both in regulated or market based environment. The use of time-based pricing is limited in case of low difference between peakand off-peak demand , unavailability of adequate time-of-use metering. Also, customer response to time-based pricing should be considered (see: Demand response). A regulated utility will develop a time-based pricing schedule on analysis of its cost on a longrun basis, including both operation and investment costs. A utility operating in a market environment, where electricity (or other service) is auctioned on a competitive market, timebased pricing will reflect the price variations on the market. Such variations include both regular oscillations due to the demand pattern of users, supply issues (such as availability of intermittent natural resources: water flow, wind), and occasional exceptional price peaks. Price peaks reflect strained conditions on the market (possibly augmented by market manipulation, see: California electricity crisis) and convey possible lack of investment. TYPES OF PRICES Prior Booking through Dealer: The prices will be floated as based on the trend analysis of historical data of previous year and for different seasons. Internet Booking: The prices will be at 5% discount than that done through dealers. On the Spot purchase: The price will be at 10% premium than the booking done through dealers. PRICE REVISION METHODS AND FREQUENCIES Price revision methods which we have opted are very dynamic in order to maximize the revenue. For optimization of the revenue the inventory is opened and closed at various intervals and artificial demand is created thereby giving an opportunity to increase the average revenue for the same product across: Quarterly/Seasonal: The demand during first quarter is not high and remains more or less same for the next i.e. April to September. Hence to artificially increase the demand the price is reduced and special offers are provided. The demand through internet booking is increased during these two quarters .But the last two quarters sees a drastic increase in demand due festival seasons like Diwali, Christmas, New Year, Pongal, Holi etc. Since the demand is high during these quarters so price is increased. Days Prior Delivery: The number of days prior delivery is segmented such that revenue is maximized. As the days prior delivery increases the average price is reduced. The days prior delivery segments are as follows: Within 1-3 days: Highest Within 4-10 days: High Within 11-15 days: Average Within 15-30 days: Low More Than a month: Lowest Across Channels: There are three channels for sales i.e. internet, dealer and company. The internet provides discounted price in order to create artificial demand. Normal prices are applied at Dealer’s point which though includes the affect of seasonality and days prior delivery. The group purchase is done directly through the company at the most discounted prices due to bulk order. Individual and Group Booking: The days prior delivery method will be applied to both individual and group booking, also other factors would affect the price too. Apart from that the major difference is that huge discount will be provided in case of group booking due to bulk order. PRICE ELASTICITY AND ITS IMPACT Purchasing a motorcycle remains to be a high involvement purchase for most households in India. The fact that most Indians are price sensitive, it is no surprise that a lot of thought goes into the purchase of a motorbike. As such any amount of price reduction is met with overenthusiastic response, especially by the middle class, and the young adults segment who are the major segments targeted in this regard. The fact that there exist a lot many review sites to cater instant comparisons among various brands, as to their features and prices, indicates that the price sensitivity goes up further. Every move of the organization is countered by the competitor and it is not uncommon to find severe price wars within the same. Revenue Class: We have considered 3 revenue classes for our project: 1. Internet Prior –booking 2. Prior- booking through dealer 3. On the spot purchase Internet Prior –booking revenue class: Since the customers will be booking on internet on a company website, this will result in savings for the company on dealership margins and the inventory carrying costs. Hence company can give discounts and charge low price for this revenue class. This new channel will result in the generation of an extra demand for the company. New offers and promotions can be used to generate demand in this channel, especially during off- peak seasons. Customer will be given more choices through this channel, in the form of more colors and new models. The facilities like live-interaction with experts, feature specifications and user reviews will be provided. The loyalty programs like Heromotocorp Club membership and discount cards for services can also be sold in this revenue class. The price for this revenue class will be at 5% discount than the dealer channel. Prior- booking through dealer revenue class: Prior booking will help in reduction of inventory carrying costs and creating artificial demand for high price classes. The price will be varied based on the basis of number of days prior booking is done. The price for this revenue class will be fixed based on the historical trend. On the spot purchase revenue class: We will charge premium of 10% than prior booking revenue class. Customers can go directly to the dealer and purchase the bike. Benefit & Restriction Matrix: Benefits 1 year free service Loyalty programs Discount service card Warranty More colors New models availability Restrictions Internet Booking Yes Yes Yes Yes Yes Yes Dealer Booking Yes No No Yes No Yes On the Spot Yes No No Yes No No Protections: 2% April to June Revenue Class Forecast (units) Error Price Available Protection Units On the Spot 360 7 43274 389 1500 Prior Booking 841 17 39340 912 1111 Internet 120 2 37373 199 199 2% July to September Revenue Class Forecast (units) Error Price Available Protection Units On the Spot 392 8 43506 410 1500 Prior Booking 914 18 39551 953 1090 Internet 131 3 37574 137 137 2% Oct to Dec Revenue Class Forecast (units) On the Spot Prior Booking Error 460 9 43649 450 1500 1073 21 39681 1038 1050 153 3 37696 12 12 Internet 2% Jan to March Revenue Class On the Spot Prior Booking Internet Price Available Protection Units Forecast (units) Error Price Available Protection Units 493 10 43687 479 1500 1150 23 39716 1021 1021 164 3 37730 0 0 Based on the demand and available production capacity for each period, the protections are calculated. The forecast error is assumed to be 2% and forecast is done based on the trend analysis. The objective is to obtain maximum EMSR. For example during off- peak seasons, we will try to sell more through internet channel by giving more benefits. While during peak seasons we will close the internet channel as EMSR of this revenue class is less than other revenue classes. These protections levels will help us in opening and closing decisions on different revenue classes. Optimization: Revenue is optimized by: Introducing new revenue classes Following differential pricing Opening and closing inventory to protect and build artificial demand for certain revenue classes. Apart from increasing revenue, this project will also help the company to increase the profitability by reducing inventory carrying costs and distributor margins. Area Sales without Revenue management for the next financial year will be Rs. 21cr Area Sales with Revenue management for the next financial year will be Rs. 25cr Therefore, Incremental Revenue obtained will be Rs. 4 cr Objective Function: Maximize the sales in Rupees for the next financial year. Problem: The production capacity for each period (i.e. a financial quarter) is limited to only 1.5 cr units and the production has to be continuous. But the demand for motorcycles is less than the production capacity during the first two periods of the financial year and demand is more than the production capacity during the last two periods of the financial year. Hence company has to produce more during first half of the year and carry forward the inventory to meet the demand in the second half of the year. This builds in the more inventory costs for the company and pressure on the sales team to push more inventories to the dealers. Solution: New Revenue classes will be introduced. The internet channel will be used to sell more bikes during off peak periods and the bookings and sales will happen directly on the company website. This will help company to reduce the costs and price the bike lower to generate more demand. This will also reduce the pressure on the dealers as they will not be forced to carry more inventory than the demand in their channel. More offers and loyalty programs will be used to incentivize the customers coming through this channel. The internet channel will be closed when the demand in other two revenue classes will increase during peak seasons. Protections will be built for each revenue class for each period. Protections are calculated on the basis of EMSR calculation for which forecast is done on the trend analysis method and error is assumed to be 2%. For forecasting the actual data is first de-seasonalized and then trend analysis is used for forecasting. The forecasted data is again reseasonalised for each period. The EMSR calculation is attached with the report. Assumptions: 1. 2. 3. 4. We have considered ourselves as the area sales manager of Heromotocorp limited. The area sales is considered to be 0.1% of the total sales of the company. The forecast error is assumed to be 2% The 30% demand is considered to be price inelastic and will like to buy the bike on the spot itself. 5. The opening up of internet as a new channel will bring extra demand of 10% 6. Because of savings in channel partner margins and inventory carrying costs, the company will be able to reduce the price by 5% in the internet channel. Optimal demand: Forecast Internet Prior Booking On the Spot Internet Price Booking Price Spot Price Internet Sales Booking Sales 10% 70% 30% -5% 0% 10% Period April to June July to Sep Oct to Dec Jan to March 120 131 153 164 Units 841 914 1073 1150 360 392 460 493 37373 37574 37696 37730 Price 39340 39551 39681 39716 43274 43506 43649 43687 Spot Sales Sales (in Rs) Total Sales 44,84,760 3,30,85,193 1,55,78,640 5,31,48,593 49,22,194 3,61,49,669 1,70,54,352 5,81,26,215 57,67,488 4,25,77,203 2,00,78,540 6,84,23,231 61,87,720 4,56,73,284 2,15,37,691 7,33,98,695 Area sales with Revenue Management 25,30,96,734 Area Sales without Revenue Management 21,41,50,000 Incremental Revenue (Rs.) 3,89,46,734 Other revenue maximisation methods ( Over booking, upgrading etc): In case of a motorcycle, it is not possible to bring in upgrades, as this is a single commodity in itself. One cannot pay for a lower style of a product, and get a higher or better product. Over booking too is unusual as generally, individuals who had booked for a motorcycle will come to collect it, unlike airlines, where they may book and cancel later. This is a high involvement purchase, thus in all probabilities, one will not give up the chance of getting delivery for the product. Your recommendations and rules for maximising revenue As we had mentioned earlier, opening up various classes for booking for customers will help in expanding the base of customers and get a larger market share. By this we mean, trying to capture more number of customers by various distribution channels like the internet etc, and allowing them various options like prior booking, on the spot prices and special prices on the internet. Though there remains the reason of tangibility factors as to whether at all, this will be a successful method or not remains to be seen, as customers generally prefer to buy a good only after testing it by its look and touch. Yet, it is a cost effective, scalable solution which can tap into hitherto unexplored markets. How to measure the effectiveness of the revenue management process A good point to start is, conducting a cost benefit analysis of the said project and checking whether the costs incurred in putting on place such an elaborate distribution channel is really worth the benefit of obtaining the extra revenue or not. It needs to be tested on a pilot basis at a regional level initially, and might be extended over a year to see the level of revenue increase, whether they are palpable or not. Not only this, that the revenue goes up or not, what needs to be checked, is whether the revenue goes by the level that had been forecast, or is there a specific pattern that it follows. If there is a difference in the pattern of revenue growth estimates need to be revised upwards or downwards accordingly and then a similar cost benefit analysis is proposed to be carried out. If however, the system proves to be ineffective, the internet medium should be scrapped, and the sales team must revert to the original system of physical booking.