Revenue Management and Digital Distribution Strategy

Revenue Management and Digital Distribution Strategy 8

 

Running head: REVENUE MANAGEMENT AND DIGITAL DISTRIBUTION STRATEGY1

 

 

 

 

 

Revenue Management and Digital Distribution Strategy

Name of the Student

Affiliate Institution

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Executive summary

In the playbook of hotel management, preserving a well proactive and well-presented strategy is an important aspect. The method selected for distributing the products and services being offered should be regularly and carefully accessed with the manager keeping in mind that their primary goal is maximizing the organization’s profit potential. Looking past OTAs, evaluating the present channel acquisition cost, and looking for ways to increase direct bookings are among the important practices for controlling and enhancing the viability of an organizations distribution and management strategy.

 

 

 

 

 

 

 

 

 

 

 

 

Table of content

Introduction

Literature review

Planning of the event

Data for revenue management project; revenue management

Source of information and methods used to influence on the revenue and digital distribution decisions

Theories used in capacity allocation models

Results and decisions

Conclusion and recommendations

References

appendix

 

 

 

 

 

 

 

 

 

Revenue management and digital distribution strategy

Introduction

The role of digital distribution strategy is connected with the strategic function of revenue management in the hotel industry (Sigala, 2003). Compared with the fact that distribution strategy is something that has been applied for long in the industry, there have been significant changes in how it influences the hostel industry due to the upcoming industrial channels, data sources, and other varying technologies.

Among the new technologies influencing recreational industries and that are large enough to be classified on their own as single factors influencing RM are restrictions to doing business, the complexity of price, channel usage, add-ons, and distribution and technology costs. The division to unique elements has increased job roles leading to the development, execution, and the measurement of their intelligent and comprehensive distribution strategies. The effects of an effective distribution program and the complexity of distribution channels can grow revenue, hence, making it essential for managers to understand how the quality of their roles enhances their entire profitability. If a hotel does not have the right staff and system in place, it is expected to struggle to achieve its full revenue potential. Lack of proper accounting and management for distribution cost affects directly the net revenue results expected from the distribution strategy.

Among the main factors that affect the revenue management and marketing strategy in the hostel industry is functional distribution strategy. The success of the plan depends on the type and quality of people running it and the methods and tools they use.

Literature review

Planning of the event

An event of all stakeholders involved in the steel processing and fabrication industry from different corners of the world was to be held in London during the summer period. The number of the expected guest was approximately 2000 individuals. To make sure that the planning of the event was a success. There was a need for dedicating planning, administration, and marketing team that would help in revenue management and distribution strategy.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Source of information and methods used to influence on the revenue and digital distribution decisions

There are different sources of information that a revenue manager can get their data from. One can use the very available first-hand information from the targeted customers using their rational reasoning to come up with expected issues that have to be solved to ensure that their customers have been satisfied. A buyer or a seller of a service or a product can have multiple questions that are related to pricing and selling (Oliveri, 2017). An example is how to segment the customers, which selling channel is the best, how to manipulate the prices of those channels, how to set prices for different segments, how to differentiate the services offered in the various sections, and how to change their prices over time. All these questions are related to revenue management, and the manager has to come up with the most effective way of making sure that the organization makes profits.

Structural decisions in revenue management revolve in questions like which differentiation and segmentation apply, what selling format can be implemented and what kinds of terms have to be used when making purchases. Such decisions are strategic and are required to be performed frequently. When making revenue management and distribution strategy plans, structural decisions can also have effects on how a hotel can react to quantity and price decisions.

A structural decision can be separated into two different tactical decision areas. The first is price decision related to pricing, in this strategy price is set according to various customer goods and pricing over time. On the other hand, quantity control decisions are used to answer issues related to product rationing and capacity control; whether to approve or not approve buying request of products at a certain price and capacity allocation to varying groups of customers. When revenue management used capacity allocation decisions as the primary tool for controlling demand decision, the method is referred as a quantity based and when applying price based on these demands, it referred to as price based RM (Oliveri, 2017). The two tactics are connected. The two strategies influence each other, and they cannot be used separately. The similarity and differences between the two theories create confusion on which method is mainly to be used, and which have a more significant impact on the theories of revenue management and digital distribution strategy.

Theories used in capacity allocation models

EMSR- d model

The EMSR model is can be described as a heuristic model for revenue maximization for determine the booking limit for each fare classes for future event using average fares and historical demand data. A probability density function is used in the representation of future demand since the demand changes over time.

Since the model is a heuristic model, it cannot be used to solve optimal capacity allocation unless it is set under two classes. The model however shows that the losses in revenue concerning non-optical capacity allocation are not varied. They contain an error of approximately 0.6 to 1.6 percent. The EMSR-b however avoids the pooling effect. Statistical averaging effect or the pooling effect is experienced when demand across classes are aggregated. The EMRS –b formula eliminated this issue by not aggregating protection level and rather aggregating demand.

Linear programming

Linear programming much simpler. It is used in maximization of revenue using two constraints; the first is, the total number of units allocated to each classes does not have to exceed the total capital. Secondly, the number of units to be presented for each fare class has to be less or equal to the demand that was being expected in that fare class.

𝑀𝐴𝑋 ∑ 𝑟𝑖𝑥’

Constraint to: ∑ 𝑥𝑖 ≤ 𝐶

𝑛 𝑖=1 𝑥𝑖 ≤ 𝑑 , 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑖

𝑥 , 𝑑𝑖 ≥ 0

Where xi is the units sold in fare class, I the fare class i, di fare class demand i, ri, revenue for selling units at a fare and c and I, are the total capacity.

 

 

Results

 

 

Table 1: Daily mean per class on each day

 

 

 

 

 

 

 

Discussion

The time horizon for of necessary forecast have an effect on method of selection. Some methods are appropriate for short term forecasting while some other are more suitable for long term. It is therefore important to evaluate different methods in the selection of the best suiting method for each particular forecasting process. Forecast performance can be improved by utilizing advance forecasting methods when there is available booking data. The study indicated that advanced method provided better results than models that depend on historical data. The application of EMSR-b in capacity allocation indicated why demand forecasting in hotel industry plays an important role in RM system. For a manager to compile efficient capacity allocation, demand forecast should provide accurate prediction of the total demand and distribution of total demand across fare classes.

In any market the prices of goods and services do not remain the same throughout the year but fluctuates at different times of the year. The same can be said for the demand for the goods and services that are offered by the different organizations and businesses throughout the year. The hotel industry is no different as the demand for their services changes with the several influencers that play in the market. The data above shows that the different times of the year show different levels of demand from the consumers and hence the procrastination that resulted was based on the previously received guests. The distribution of resources is done based on the number of guests that are expected at the different tomes of the year and the expectation in terms of the revenue that the business expects as states. The highest demand was in day three with most of them being Special Transient Rated Guests who only stay for pone night. If this data was to be used to procrastinate for the planning of the hotel resources and management more resources would be locate the same day with the expectation that most of the guests would stay for one night. Such kind of data would be and is very important for the kind of distribution of resources that the organization undertakes.

 

Conclusion

Despite the fact that revenue management and distribution strategy is mostly linked to airlines, the models are applicable to many service industries including the hotel. The model is basically used as atool for industries that are capacity constrained to manage their inventories effectively. There are six generally agreed strategies that are effective in revenue management and digital distribution strategy. An organization applying RM must have a relatively fixed capacity in short term and it must have a flexible customer segmentation. The products and services should be considered perishable and that the purchase or sell of the products must be done before the actual consumption. Another issue that have to be addressed is that demand changes over time and with an unpredictable level of uncertainty. It should therefore be noted that capacity is fixed, therefore, the marginal cost of additional consumer is low and the cost of capacity variation are high. All this factors have to be considered and for an effective revenue management and digital distribution strategies.

 

 

 

References

Oliveri Martínez-Pardo, G. (2017). Principles of Revenue Management and their applications.

Sigala, M. (2003). Competing in the virtual marketspace: a strategic model for developing e-commerce in the hotel industry. International Journal of Hospitality Information Technology, 3(1), 43-59.