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KPIs: Seasonality in Context - Hospitality Industry Case Study

The Power of Metrics

In September's column, we discussed the simple technique of deseasonalization which allows us to translate "static" KPIs into more seasonal "dynamic" KPIs. This first article focused on the seasonality indices as they applied to a specific hotel property - Hotel Dreamage - at a Hawaiian location. This month we will investigate how the seasonality indices can be further leveraged by analyzing them within context - i.e., compared to relevant geographic and market segments. This type of seasonality analysis can then be used to develop a more comprehensive understanding of the competitive marketplace and quantify the impact of advertising spend and promotional programs on occupancy rates.

Development of Comparative Seasonality Indices

The methodology for developing seasonal indices for the hotel chain, city, region and market segments parallels the approach we developed last month. Once again, we collect three years of historical hotel occupancy data to calculate monthly indices (see Step 6) for the respective benchmarks. The only difference is that the seasonal indices are developed for higher level aggregations - the context - such as the hotel chain, city and regions. In this case, the region would be the Hawaiian Islands and the city of interest, Honolulu. Further segmentation also profiles the hotel's seasonality vis-à-vis the chain's collective local hotels as well as the hotel luxury market segment. Other market segments could include upper upscale, upscale and midscale hotel segments. Development of these marketplace benchmarks is discussed in Step 6 below. The Hotel Dreamage indices are then compared to these higher level aggregations in Step 7 to determine if the Hotel Dreamage has attracted its fair share of business and tourist trade.

Step 6:  Create marketplace benchmarks

  • Divide hotel-specific seasonality indices by region, city, chains and market segments seasonality indices to create comparative benchmark ratios.

Step 7:  Develop marketplace analysis

  • Compare benchmark ratios to determine if hotel- specific seasonality is in sync with seasonality for region, city, chain and market segments.
  • A benchmark ratio significantly above 1 indicates that the hotel has attracted more than its fair share of business and tourist trade - conversely, a benchmark significantly less than 1 indicates below par impact.

Seasonality Profiling and Analysis

In Figure 1, the seasonality indices for the respective benchmarks have been created and contrasted to the seasonality indices for Hotel Dreamage. A review of the ratios for the individual months provides some interesting insights into seasonality differences. In March, the hotel-to-region ratio of 1.238 and the hotel-to-city ratio of 1.252 indicate that the Hotel Dreamage is outperforming the region and city by 23.8 percent and 25.2 percent, respectively. Since the hotel-to-chain ratio is basically equivalent to the Hotel Dreamage seasonality index (at 1.005), this implies that the chain created an effective promotion program that attracted a disproportionate number of tourists and business travelers during March over the last three years. It is also worthwhile to note that the hotel-to-luxury market ratio at 1.267 shows that Hotel Dreamage's marketing and promotion program was 26.7 percent more effective than other hotels in the same luxury market segment.


Figure 1: Comparative Seasonality Profiles

Alternatively, if you look at October, the storyline is completely opposite. The hotel-to-region ratio of .852 and the hotel-to-city ratio of .844 indicate that the Hotel Dreamage is underperforming the region and city by 14.8 percent and 15.6 percent, respectively. Obviously, other hospitality chains implemented more effective marketing and promotion programs. The comparative ratios for each month can now be mapped to the hotel's respective advertising and promotion activities to determine the impact of the marketing dollar expenditures.

Keep in mind that a KPI seasonality analysis is only as effective and comprehensive as the availability and quality of the source data. In this case, individual hotel and chain data is available from company-specific data warehouses and data marts, while the region, city and market segment is available from organizations such as Smith Research Travel, the World Tourism Organization and the local Chamber of Commerce.    


Kent Bauer is the managing director, Performance Management Practice at GRT Corporation in Stamford, CT. He has more than 20 years of experience in managing and developing CRM, database marketing, data mining and data warehousing solutions for the financial, information services, healthcare and CPG industries. Bauer has an MBA in Statistics and an APC in Finance from the Stern Graduate School of Business, New York University. A published author and industry speaker, his recent articles and workshops have focused on KPI development, BI visioning and predictive analytics. Please contact Bauer at kent.bauer@grtcorp.com.

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