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Impact of information technology on revenue management

Paper Type: Free Essay Subject: Business
Wordcount: 2409 words Published: 1st Jan 2015

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The phenomena of revenue management gained importance in recent years due to variable and discriminatory pricing schemes offered by various companies to their customers. Revenue management applies the orderly analytics that predict the behavior of the consumer at micro level and augment the prices and availability of products to the customers thus enhancing the overall revenue for the company. The aim of devising revenue management techniques is to deliver the fine product or service to the appropriate customer at the precise price. This system is based on analyzing the customer’s perception of the value that the product would provide and make straight the availability, placement and price according to that perception.

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This discipline became the need of every business rapidly. There could be many reasons for this. Even a kid whose is out for selling orange juice will have to analyze and predict the appropriate weather and time for selling his product. When we talk about giant businesses, the need for assessing customer demand and subsequently managing that demand is enormous and critical. A revenue management system is answer to the question of such demand.

Information technology has gained rapid importance and improved itself in all aspects from the invention of first computer ENIAC till present. The cost of installing and communicating through IT based equipment has been reduced incredibly. This remarkable reduction made it possible to use information technology equipment in commercial businesses in addition to government and military. (Forester, 1985). As like other field, information technology has played a great role in improving the processes of revenue management. In this paper, we shall study the impacts that information technology has on the revenue management.

This article is concerned with defining revenue management systems and their application. It will also explain that how well it can meet the consumer demand, how well it can be integrated with overall distribution channels and what role information technology is playing to enhance the overall progress of the revenue management systems. We will at the end, try to make some conclusions and recommendations about the development of decision support system of revenue management and how can it be helpful in maximizing the future profits of the company.

Brief history of revenue management

The concept of revenue management is not new to the business world. Every business that is selling some fragile product needs to flex the price of that commodity due to some uncertain environmental change or response to some competitor’s action or customer’s demand. Seats in airplanes, clothes (i.e. for summer and winter), rooms in hotels etc., all require revenue management strategies to be sold in a manner that maximize the overall wealth of the company. This field properly originated in US airline industry in start of 1970s. Bob Crandall of American Airline (AA) who put restrictions on discounted fairs. After that yield management came into practice which is the foundation of revenue management. American Airline, with the help of other airlines further extended the yield management system by offering low fares to the cost sensitive passengers and high priced fares to the time sensitive passengers, giving maximum value to both type of travelers. The impact of practicing yield management was come into knowledge by year 1985. American Airline reported about 48 percent profit growth. This huge success attracted other industries to develop into the field of yield management (Haley and Inge, 2004).

Purpose and benefits of implementing revenue management

We discussed above that yield management evolved into the revenue management. As it became the standardized practice for the companies, its definition progressed. Revenue management is defined as the field which is concerned with answering the demand questions related to consumer behavior and system and set of methodologies required to make them. Revenue can be compared with supply chain management because it aims at lowering the cost of producing and delivering the products hence increasing the profit, so as the goal of revenue management. There need to be certain business conditions that are essential to successfully implement a revenue management system. These conditions include customer heterogeneity, production inflexibility, variable and uncertain demand, management culture, infrastructure of data and information an so on. (Ryzin, 2005) employing a revenue management system benefits the company by unleashing the hidden demand which can lead to great revenue opportunity, helps understanding the customer’s choices between price and product characteristics, increases revenue, suggests discounts on the product when required to build up the market share and helps in developing a sales driven organization whose sole focus is profit maximization. (Cross, 1997)

Jurisdictions of revenue management system

There is wide range of options available to increase revenue through a revenue management system.

Pricing strategy: pricing strategy is related to envisaging the customer’s perceptions about the value of the product and then setting prices to catch that value. Pricing strategy which a company adopts dictates its objectives i.e. what it wants to accomplish. Company then chooses pricing tactics that can respond to the customer’s expectations. Customer price sensitivity analysis, price ratios and price optimizations are example of such tactics. Carefully selected pricing strategy can increase the total revenue and ultimately profitability of the firm. Therefore, revenue management can redefine pricing strategy and can build enhanced pricing tactics (Nagle and Hogan, 2006)

Distribution channels: a company can deliver its products with various channels like online or in shops. Different type of cost and revenue are linked with these channels. Customer of particular nature selects the specific channel for buying the product for example customers who opt for purchasing online are more price sensitive. Revenue management tools can help analyzing the channels and deciding appropriate discount offers to distributing and retailing channels then to consumers without losing the customers’ perception about the value of the product (Phillips, 2005).

Marketing: revenue management tools can help determine the response rate of customers to a particular level of promotional activities. By efficiently promoting the products, a firm can increase its revenues and subsequently the profitability (Phillips, 2005).

Process of Managing Revenues

The revenue management process begins with collecting data on inventory, consumer perceptions and behaviors, product prices etc. The system employed collects and then store the information mentioned before and uses it to optimize prices and channel selection and amount of price promotional activities required. After collection of data, segmentation is done by the system to categorize consumers in to various groups (Cross, 1997). After segmentation, system forecasts the demand by implementation of quantitative analysis of data like time-series model and cross price elasticity (McGill and Ryzin, 1999). When the forecast phase is completed, revenue management system comes into the position of giving different options to the company about in how many different ways can it sell its product to what type of customers (Cross, 1997). Optimization provides answer to two questions. First of all it provide guidance to the company about which factor should be optimized like price or sales. Secondly it tells that what optimization technique is relevant and should be opted. For instance, regression analysis for finding out relationships between variables, discreet choice models for envisage customer behavior and linear programming techniques for setting optimum prices to maximize the total revenue (Phillips, 2005) .

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Information technology advancements and Revenue management

Famous speaker and guest lecturer of Harvard Business School Don Burr regrets that fact that he failed to predict actual role of technology that it can play in successfully implementing a revenue management system. He confesses that “PeopleExpress” collapsed because it hadn’t installed the database management system for the purpose of collecting and storing information required for carrying revenue management processes. He says that my number one preference will be to make sure that my people have the best possible tools of information technology if I would have to start an airline. He says that in his opinion information technology is the only factor which draws the maximum revenues for airline industry as compared to any other factor Cross, 1997).

The tools used to get, store, process and successively share information are included in information technology. As revenue management processes mentioned above require all these tools to manage information relevant to yield management, it is quite clear that using information technology can help boosting the RM system a lot (Reynolds, 2010)

From studying the processes of revenue management we can conclude that revenue management uses Customer Relationship Management (CRM) data, supply chain management data, marketing and pricing data and consumer behavior data to forecast the future demand and customer responses. Information technology helps in making the data collection procedure faster and effective. Information technology provides easy data access tools with the help of graphical interfaces, provides communication, collaboration and networking technologies to obtain data from different systems easily. With the help of sharing feature of networking information among various systems like CRM, supply chain and marketing can be exchanged. RM system can access that information for forecasting purpose. Database management tools like normalization of data, storage of data, data modeling and categorization objective can be achieved effectively and within no time. Oracle DBMS systems are the best example of database management software. A firm can develop its own customize DBMS for this purpose (Lucas, 2001). Software applications have been developed to quantitative forecasting from the data. SPSS and Microsoft Office Excel are the examples but a firm can develop the application according to its own needs. These applications are able to analyze million of statistical data with in few minutes (Hail, 2011). Information technolgy can also be used for the optimization funtion of revenue management. For instance, if the system decides to optimize through linear programming, Excel solver, Model Frontier, Maple, FortMP, Inverse, CPLEX, FortSP, Mathmetica, NMATH, OptimJ, SNOPT and OpenOpt are the examples of optimization software (Wikipedia, 2011). Large fims like American Airline uses customized and speciall puprose applications. Optimization software can help sovling the second problem of optimization function and they are reilable as well as efficient.

Fisrt problem of Optimization fucntion is to choose that which factor should be optimized to get the maximum profitability. Information technolgy aids this fucntion through its efficient decision support systems (DSS). For instance, P&G uses its information system for restructuring of the supply chain by taking help from IS how to restructure the chain. Through this it significantly reduded the cost and increased response to customer and market place (Laudon and Laudon, 2007).

Decision support systems provide managers with analytical tools to model a large quantity of the in semi structured decision making environment. Decision support system database and software is deveopoped to host the data and a sensitivity model is developed to repeatedly analyzy data on “what-If” question. Spread sheet pivot tables are also used sometimes to enhance the decision making process (Laudon and Laudon, 2007). Performance of decision support system relies on the amount of information. In conclusion, we can say that, information technology speeds up the revenue management processes by reducing the time of collecting and analyzing the data, reduces the processing cost by moderating the need for physical elements like buildings and kiosks e.g. in airline online ticket selling, increases volume of business by making the business more reachable to customers e.g. online reservation on airline industry, improves service and product quality through providing dependable service and reduces risk of loss by suggesting appropriate promotional and pricing strategies e.g. airline industry can offer low fares in down season and high fares when business traveling and tourism rate is high (Kimes, 2008).

Future and challenges in Revenue management

Implementing revenue management in an organization is not an easy task. There can be a lot of obstacles like cultural, organizational and reliabilty issues in information systems already developed like supply chain, customer relationship and intelligence. Now a days, revenue management is moving towards more ASP ( Application service provider) plateforms. In future, revenue managemet will be focused on subscription and renting through ASPs rather than developing application systems inside the organization. Future challenges of RM can be its placement inside the organization i.e. whether in marketing or finance department or the organization or may be it will be needing a whole new department to carry out its activities.

Conclusion

We can not deny the importance of technology in setting up a revenue management system. Technological innovation makes a firm close to success in achieving higher profitability. But an efficient revenue management system requires more than just technological innovation, it requires collaboration between the processes and people of the organization (Greenwalt, 2004). Price focus is dominant in traditional RM applications but we expect expansion of non traditional applications (Economist, 2000). Further evidence of expansion can be observed in acquisation of Talus by Manugistics (a supply chain solution provider), (Manugistics, 2000).

 

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