RM Implementation and control

While there are numerous studies about designing RM and it’s detailed components, less attention received process of implementation. Very often managers have broad knowledge about definitions of RM and its actual drivers but lack in methods of implementing their strategies, what as result might lead to fail the whole RM project. Moreover, RM implementation when explained turns to be very straight forward and rational. Following theories of implementation are the most popular and are broadly use in practice.

Donaghy, et. al (1997) used Lewin’s (1951) model of change management, where implementation is considered in three steps framework: unfreezing, change, refreezing. The first phase emphasizes the need to change. In RM context it acknowledges hotel’s workers about the importance of change and how it affects organizational structure. The future benefits of the change should be highlighted in order to cover employee’s anxiety. The second stage is transactional, when restructurization processes occur and implementation of policies, procedures, software systems and marketing. The last stages is responsible for evaluating the implementation and ensuring that new system is resistant to changes. Intuitively, the most important and the toughest phase is second one, especially when resistance from employees occur. Donaghy’s (1997) study showed two reasons for such a resistance. Firstly, resistant are high level managers, when they were not part of decision of implementing RM, while middle managers see RM as too complex, when benefits from implementation are not clearly explained. The second popular model was created by Jone and Hamilton (1992). They believe that proper RM implementation depends on both people and sophisticated technology. Their seven steps approach includes:

  • developing RM culture;
  • analyzing overall demand;
  • establishing the price-value relationships;
  • creating appropriate market segments;
  • analyzing the pattern demand;
  • tracking declines and denials;
  • evaluating and revising system.

Another interesting approach was developed by Kimes and Sheryl (1999). She pointed following steps of implementation[1]:

  • establishing a baseline;
  • understanding the drive;
  • making recommendations;
  • implementing changes;
  • monitoring outcomes.

The last part of implementation was monitoring/evaluating results. Is it very important, because very often implementation is associated with huge investment and therefore investors and shareholders want to know how it affects company’s performance. Moreover, simply measure the net change in revenue before and after the RM system installation will not isolate the benefit attributable to the RMS (Jain and Bowman, 1999, p. 84). Following two different approaches to evaluate RM implementation are widely used in practice.

McEvoy (1997) proposed two step matrix, which helps to evaluate hotel’s performance compare to market, other hotels in the chain or before and after RM implementation. The model consists of two steps and three indicators, which can be obtained from hotel’s income statement and balance sheet. The first two indicators in step one are: operating efficiency (proportion of income before fees to total revenue) and Return on shareholders Equity (ROE). Both are compared as “lower” or “higher” to respectively: average on market and substantial premium over risk free interest rates e.g. government treasury bills. During this step, hotel receives one of the rankings: S, T , E or P, as described in the table below. In step two hotel receives new ranking added to the previous one e.g. SH or TL. The subscript depends if firm’s leverage is higher (H) or lower (L) than average on the market. The financial average is calculated as proportion of long debt to capitalization. The biggest advantage of this approach is feasible and not expensive access to data and possibility to evaluate progress as often as financial reports are generated. However, the biggest disadvantage is sensitivity to special events and marketing campaigns, which may bias influence of RM on performance of the hotel.

Efficiency High Efficiency Low
ROE High (S) Stimulate and/or reproduce. It’s most preferred position and indicates well implemented RM. (T) Target and reconfigure. Hotel in this cell, might have operational problems (like management team or RM strategies), so it should target inefficiencies and improve them.
ROE Low (E) Exit or reconfigure. this classification might have serious problem with cost structure or concept is too costly to produce. Moreover, RM is probably well implemented. (P) Purge and reconfigure or exit. Even if both return and efficiency are unacceptable, there is a bigger chance to improve than in (E). There is operational problem which could be wrong implementation of RM strategy, which decreased both efficiency and returns.


The second method, developed by Jain and Bowman (1999) is isolated from external and internal factors which influence revenues such as seasonality, special events and market trend. Moreover, it takes into consideration occupancy calculated as length-of-stay instead of financial figures. The data needed to this method includes occupancy from four periods, before and after implementing and the same two periods a year before in order to eliminate trend and seasonality. Before calculating the “gain” of RM implementation, we need to calculate the average occupancy of every period (A, B, C and D), and then calculate gain = Od – Ob – Oc + Oa. The bigger obstacle in this method is forecasting Oa and Ob; because they cannot be used in real values, because data one year prior is only one instance of an ensemble of dataset, but forecast will provide the most likely data. The forecasting methods suggested by Jain and Bowman (1999) are Naive forecast, Box-Jenkins forecast, Simple exponential smoothing forecast or Holt-Winter forecast.


[1] Originally this framework was used for implementing RM in restaurants.





  1. Donaghy, K., McMahon-Beattie, U. & McDowell, D. 1997. Implementing yield management: lessons from the hotel sector. International Journal of Contemporary Hospitality Management, vol.  9, no. 2, pp. 50-54
  2. Jain, S. and Bowman, H. (2005) Measuring the gain attributable to revenue management. Journal of Revenue and Pricing Management, vol. 4, no.1, pp. 83-94.
  3. Jone, P., Hamilton D. (1992) Yield Management: Putting People in the Big Picture. Cornell Hotel and Restaurant Administration Quarterly, vol. 33, no. 1, pp. 89-95
  4. Kimes, Sheryl E. (1999) Implementing restaurant revenue management: A five-step approach. Cornell Hotel and Restaurant Administration Quarterly, vol. 40, no. 3, pp. 16-21.
  5. Lewin, K. (1951) Field Theory in Social Science, Harper and Row, New York
  6. Mcevoy, B. (1997) Integrating operational and financial perspectives using yield management techniques: an add-on matrix model. International Journal of Contemporary Hospitality Management, vol. 9, no. 2, pp. 60-65.


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