What This Document Is
These are lecture notes covering the Smith Travel Research (STR) Accommodations Report – commonly known as STAR – a foundational data source in hotel operations. The notes detail the structure of STAR reports, the various categorizations used within the data (geographic, scale, class, and more), and how hotels utilize competitive sets for performance analysis.
Why This Document Matters
This document is essential for students in Introduction to Hotel Operations (HADM 1105) at Cornell University, and anyone entering a revenue management or general management role in the hospitality industry. Understanding STAR reports is critical for benchmarking performance, making informed business decisions, and navigating the competitive landscape. It’s used frequently by hotel managers, revenue analysts, and those involved in hotel investment and management contracts.
Common Limitations or Challenges
These notes provide an overview of the STAR report’s components, but they do not offer in-depth data analysis or strategic interpretation. They are a reference for *what* the data is, not *how* to use it to solve specific business problems. Further study and practical application are needed to become proficient in utilizing STAR data effectively.
What This Document Provides
This document includes:
* A history of the STAR report and its delivery methods (monthly, weekly, daily).
* Definitions of Key Performance Indicators (KPIs) tracked in STAR: Occupancy, ADR, and RevPAR.
* A comprehensive breakdown of geographic categorizations used within STAR, from continents to tracts.
* Explanations of non-geographic categorizations like Scale, Class, Location, and Price.
* Details on how competitive sets are constructed and used for benchmarking.
* Information on data sufficiency and modeled data.
This preview *does not* include detailed examples of STAR reports, specific data analysis techniques, or advanced competitive set strategies. It also does not cover all the nuances of data interpretation or the latest updates to STR’s methodologies.