In most countries, the lodging industry accounts for significant part of the economy as a whole. One of the outstanding characteristics of lodging industry is a higher volatility in cash flows than general real estates, while tangible assets, including real estate, accounts for approximately 75% of total assets. Therefore, business and investment risks are higher as well, making accurate data and proper interpretation of it essential in managing them effectively. Among the numerous lodging markets around the world, there are markets actively absorbing liquidity from the capital market, while there are markets otherwise. The biggest difference between them is whether there is a visibility over the market, including current status and historical trends. In other words, the difference is whether business and investment risks can be managed and controlled or not, depending on availability and accuracy of data.
South Korea falls under the category where the visibility is relatively weak, because availability and accuracy of public statistics are not enough to view the entire market. As a result, despite the strong potential under geopolitical conditions, its lodging industry does not absorb the liquidity of the capital market enough to realize the potential. There are two main reasons for this:
First, there are separate regulations and authorities by type of lodging properties, which make it difficult to develop a comprehensive and consistent database. Therefore, there are only limited public statistics available. In particular, the operating performance data is available only for 6% of the entire lodging properties, and the scope of data provided is limited to revenues.
Second, the available data is limited in time window as well, without even consistency due to frequent changes in survey criteria and publication format. For example, the revenue data for hotels is available only from 1997, and the detailed items of the provided data have changed after the change of management authority in 2014, not allowing relevant time-series analysis.
Hotelisys aims to create an environment where the lodging industry can actively absorb market liquidity and effectively manage risks associated with business and investment by providing visibility over the entire Korean lodging market. For this purpose, we provide comprehensive data across the countrywide lodging markets and its value chain. As at the end of 2019, approximately 31,488 accommodations supply 879,698 rooms in Korea, and as of August 2021, Hotelysis provides data on facilities, supply, demand, revenues, costs, financial position, and asset values for 23,273 properties providing 602,741 rooms from 2005 to 2019. The database covers hotels as well as timeshares, motels and extended-stay lodging properties.
The data provided by Hotelysis can be classified into the actual data, the data extrapolated from it and the forecasted data based on them. The actual data and the extrapolated data are previous and current data, where the extrapolated data is extrapolated by AI based upon the actual data at an asset level. In particular, extrapolation by AI is limited to lodging properties having evidence of at least two years of active operation between 2005 and 2019, and the actual operating performance data of the property, whether in part or as a whole, is obtainable from external sources. Once the AI extrapolates data of a lodging property from the actual data, the extrapolated data is validated with data from different sources. Please check Data Sources page for the list of external data we use to obtain actual data and validate extrapolated data. As the mix of actual data and extrapolated data varies by property, we cannot provide the nature of data items when they are provided at a market level. Finally, for the properties with actual and extrapolated data, the forecasted data, which is an estimate for the future in nature, is created by AI also at an asset level. Hotelysis cannot provide any guarantee for accuracy, reliability or suitability of the actual data obtained from external sources, the data extrapolated from it and the forecasted data based upon them.
(1) Actual Data: The actual data provided by Hotelysis can be divided into supply data, operating performance data and financial position data, where the operating performance data can be subdivided into revenue data and expense data. The actual data is collected and combined from different sources, and the data provided anonymously in this process is matched to the identified data through our artificial intelligence algorithms.
(2) Extrapolated Data: The extrapolated data provided by Hotelysis can be divided into operating performance data, financial position data and asset value data, where the operating performance data can be subdivided into revenue data and expense data. The AI algorithms extrapolate the missed parts of the actual data, required for comprehensive analysis, based upon the context of relevant competitive and macro-economic environments.
(3) Forecasted Data: The forecasted data provided by Hotelysis can be divided into operating performance data, financial position data and asset value data, where the operating performance data can be subdivided into revenue data and expense data. The AI algorithms forecast all data items for the future, required for effective business planning, based upon the context of relevant competitive and macro-economic environments.
The extrapolated data and the forecasted data provided by Hotelysis is updated on a regular basis, which may incur changes in the provided analysis. Although the amount of data utilized for direct use or validation purposes is extensive, it is still limited as compared to the size of the entire lodging market. As such, it is not feasible yet to validate all the extrapolated data, and the forecasted data is also impacted by quality of the extrapolated data. However, we are continuously excavating new data from various sources, and the number of properties extrapolated by AI is increasing accordingly. We regularly update our database with them, but this may incur changes in our analysis provided based upon the older version of database. Hotelysis cannot undertake responsibilities for such change, but the analysis provided and its relevant version of database will stay available to the users.
Most of data provided by Hotelysis is monetary and financial data in nature, which can be presented differently subject to the operating and ownership structure of the property. For example, if a lodging property is operated under a lease structure, the depreciation expense may not be included in the lessee’s financial statements, while it will be included in case of an owner-operator structure. The profit for each case will be completely different, even if the operating performance is the same. Hotelysis focuses solely on the property itself, and removes the impact of operating and ownership structure in providing data. In other words, data provided by Hotelysis is on an ownership basis, where the data under a lease structure is converted to that on an ownership basis.
The format of data provided by Hotelysis follows accounting principles. However, there are two different sets of accounting principles we use for the purpose: Uniform System of Accounts for the Lodging Industry (USALI), which is customized for lodging industry, and International Financial Reporting Standards (IFRS), which is used generally over all industries. We use them based upon following criteria.
(1) USALI: We apply USALI for operating performance data, which is presented in the form of an income statement. Although USALI is not a regulatory format for filing purposes, we think it is more effective in analyzing productivity and efficiency of operations for lodging properties.
(2) IFRS: We apply IFRS for financial position data, which is presented in the form of a balance sheet. However, the actual data on a Generally Accepted Accounting Principles (GAAP) is not converted to IFRS and, therefore, users need to be careful in interpreting relevant items.
The asset value data provided by Hotelysis does not represent either a transaction price or an appraised value. It is provided as a reference to assist decision-making in regard to transactions or appraisals. Actual transaction prices are not provided as there are not enough samples of lodging property transactions in Korea. Instead, Hotelysis provides three types of asset value incicators: income value, book value and replacement cost. The income value is calculated as the net operating income divided by an implied cap rate, the book value represents the total asset in the balance sheet, and the replacement cost is estimated for redeveloping an identical facility on the same location. Hotelysis cannot provide any guarantee for accuracy, reliability or suitability of the asset value data provided, nor undertake responsibilities for the outcome of transactions based upon the asset value provided.
If there is any further questions regarding data provided by Hotelysis, contact us at email@example.com. However, please understand that we cannot provide details regarding our own artificial intelligence algorithms.