revenue management system

revenue management system

Optimizing Revenue Management Systems: Strategies and Best Practices

1. Introduction to Revenue Management Systems

Thanks to 24-hour media outlets like CNBC, the general public has become more interested in the curious practice of revenue management (RM). Media outlets are always hunting revenue stories and news to churn up. From glamorous fields – luxury hotels, airlines, and high-traffic restaurants – to relatively ordinary ones – every industry and business uses it. To the outside world, RM represents the most exciting of mysterious strategies hidden away in the back rooms of large established companies. Others refer to such strategies as fairness or at a minimum as being unfriendly. RM doubts arise because RM practitioners are not explaining their practices to customers. This leads customers to suspect that they are being taken advantage of. There are times when customers voice criticism stronger that consumers should not be charged different prices for the same product. Nonetheless, businesses are tasked with maximizing current profits and long-term customer relationships. Today’s best-in-class companies leverage technology components to adapt an unprecedented array of RM strategies at once and still affordably customize the required technology components. Small and midsize businesses (SMB) can leverage the lessons learnt by their larger peer companies in their utilization and selection of RM Systems subcomponents.

2. Key Components of a Revenue Management System

A good VRMS (and indeed a good business-to-consumer system) should incorporate transaction, event, and opinion data from the hotel’s various touchpoints to better understand current customers, potential future customers, and manage their different promotion usage rates and booking channels. The VRMS, in combination with the actual management practices and policies related to utilization and other functions, should help provide a strategically directed means to improve ROPO (web shopping resulting in purchasing in alternate channels) and demand caused by seasonality, special events, and changes in direct and indirect competition. Since not all demand is equal (or equally profitable), managers should track and manage their different promotion and booking channels. The majority of customers will come to the site, check rates, and then continue back to the call center, so tracking discount codes or source codes is not worth the investment. Managers can utilize the knowledge of a channel/promotion type that customers see on Google to vary the property’s corporate rate offering to small meetings.

Effective revenue management involves designing and aligning business strategies, tactics, and purchasing, sales, and marketing into effective systems. As systems, revenue management is generally designed by leveraging revenue opportunities, linking purchases to consumer demand, and linking to core business functions to allow better coordination and management of revenue goals with corporate goals. When properly aligned, purchasing, sales, promotion, and pricing systems for hospitality functions can contribute significantly to the achievement of operational goals. In effect, the design, performance, and evaluation of these and other revenue-related control systems are all critical aspects of strategic operation management. Such systems, in turn, involve the ‘traditional’ marketing mix (product, place, price, and promotions) and a great deal of consumer behavioral research.

3. Implementing and Integrating Revenue Management Systems

To successfully implement and integrate an RMS, a company must: 1) Define and communicate the revenue objectives, metrics, and constraints that will be used to guide the RMS. 2) Develop and manage the RMS implementation plan. Training, communication, user documentation, and change management are critical success factors. 3) Get the attention and support of significant users as they are typically resistant to change. Additionally, the RMS benefits and advantages should be well thought out and communicated. 4) Senior management and the recommendation setters are important users of the information generated by the RMS. A company must ensure that the RMS can easily deliver the required information in a timely manner. The reporting requirements often focus on grand totals for the purposes of performing a trend analysis. The reporting must also provide enough detail to support a quick root-cause analysis and the resolution of any ‘negative’ problems. For example, unresolved over-bookings and/or obstruction for high-value customers of getting the seats they need are potentially damaging issues. 5) Establish the appropriate gait for entry to ensure that availability is based on accurate information that is in-sync with the real-time feeder airline inventory. High user confidence in the RMS recommendations is achieved through the use of actual or the most accurate data available. Inaccurate data negatively impacts the RMS reliability and credibility and the business decisions that are based on those recommendations. 6) Measure the effective and accurate dissemination of the ‘right’ information at the right place at the right time to the right person and/or system. The overall goal is to drive the ‘right’ real-time responses and changes. Use the first five years of RMS data comparisons to understand seasonal influences and biases. Be very careful about taking actions based on less than two years of RMS data. The RMS can base its recommendations solely on the actual performance or it can use the actual performance in combination with some expectation to guide the price response. Once the first year of actual performance has been completed, additional systems and data sets are brought into the mix and used as inputs. Be careful about reliance on systems and assumptions when there have been changes to the competitive landscape. Nervousness about any potential appearing negative route performance can prompt actions that may not be suitable or generate the planned effect. Improve the confidence in actual performance trends through diligence and process automation. Minimize the decision loop in response to actual negative performance. The frequent update allows well-groomed historical forecasts to be used to initiate timely responses to new developments in that market. As the departure date approaches, the RMS system is using more current data to guide pricing activities. The recall period indicates how long the return to support the action can be.

This section discusses best practices, critical success factors, and the associated IT solutions for implementing and integrating an RMS. It also provides the basis for the next section where a company determines its preparedness and specifies an appropriate RMS. Finally, strategies for getting sales teams to use the system are emphasized.

4. Advanced Techniques and Strategies in Revenue Management

This paper is about salesforce revenue management in the presence of a perishable, multiple class situation, not typical of what has been traditionally looked at in the literature. We use a versatile state space modeling approach, based on the fractional response approach of Papke and Wooldridge (1996) to handle heteroscedasticity, and provide some empirical evidence about the effectiveness of different options.

Sales force revenue management in timeshare interval markets. Rob Lawson and Vicky Cho. Robert H. Smith School of Business.

Artificial intelligence and other advanced computing methods offer unique and powerful ways of determining optimal rates in a hotel environment. This paper investigates the use of neural networks and genetic algorithms to develop a system that allows a hotel yield manager to explore the demand different room rate combinations would generate. Once the manager indicates the room night ‘sell-through’ desired, the system calculates the best strategies to achieve such a result. The theoretical development and successful application of a spreadsheet-based decision support system suited to hotel room revenue management is detailed. Additionally, the paper investigates several architectures of daily room rate behavior using data from a large hotel located in the Orlando area. Results from the application to data and the architecture development suggest this approach holds the promise of providing a yield management alternative that requires a far less stringent set of restrictive assumptions on consumer demand behavior.

Neural networks and genetic algorithms for artificial intelligence in hotel revenue management. Jonathan Barsky. British Columbia Institute of Technology.

5. Case Studies and Real-World Applications

It is worth noting that case studies rarely offer statistically significant evidence that the estimated impact of a certain decision represents the best (or most relevant) response or strategy when dealing with these types of delicate real-world problems. Due to the tremendous variations in the attributes of most media products, case studies can at best suggest general patterns and insights associated with certain conditions, strategies, or revenue management applications. However, we do believe that the revenue management concepts presented throughout the book are general enough to guide television and entertainment industry decision-makers in determining a tentative attribute configuration of their most relevant media products in order to enhance, whatever the latter, the profitability of the firm.

In this chapter, we present a series of case studies and real data applications showcasing how many of the basic ideas and concepts of revenue management can be applied to real-world decision problems to significantly improve revenues and profits. Most of the case studies and examples included in the book deal with the television and entertainment media industry, which has proven to be a major adopter of revenue management to manage the sale and distribution of perishable products with high short-term demand fluctuations, but very limited applications in the literature.