Covid-19 Recovery Hub

The global hospitality industry has been ravaged by COVID-19, a classic example of a black swan event. While many are looking backwards to compare the current market environment with the post-9/11 or 2008 Great Recession periods, we prefer to look forward – trying to address the tough questions weighing on our collective minds. 

Already there are positive signs of the industry coming back to life!

Whether your are a customer, a hotelier or a traveler- we are here to help you chart a way to recovery. 

Making sense out of chaos

What Happened

The coronavirus outbreak has triggered a global humanitarian and economic crisis.The economic impact of the pandemic is visible across sectors, but its effect has been particularly amplified within the travel and hospitality industry. Travelers are canceling their bookings at an unprecedented scale and speed. Governments around the world have placed severe restrictions via travel bans, shelter-in-place, and social distancing. Travel in this new environment has come to a stand-still, and hotels across the world have been experiencing massive disruptions resulting in record-low occupancy levels and dramatic declines in RevPAR % Change.

The Data Challenge

With the changing market landscape, understanding market dynamics has never been more important. Supply and demand will vary drastically across different markets, it is vital to forecast these ​spatial and temporal trends ​as hotels begin to plan for the rebound in travel demand. At LodgIQ, we are enabling a paradigm shift towards the usage of undiscovered and alternative data using state-of-the-art machine learning and artificial intelligence methods that will forecast recovery in real-time (Occupancy, ADR, RevPAR) for the next 12 months. 

The total scope of the COVID-19 is yet to be understood. The supply of testing has not yet met demand. The economy is experiencing a severe retraction in growth sending the unemployment rate skyrocketing to never seen before levels indicating that travel will be impacted for a prolonged period. To adapt to this COVID-19 reality, a novel forecasting framework is required to explain the consumer traveling behavior as historical trends are no longer applicable leading to the empirical loss of traditional and rigid forecasting methods. Our new forecasting framework must take into account these unforeseen patterns in order to forecast demand in both the short term and long-term.

Our Novel Approach

At LodgIQ, we have continuously thought about how we can leverage Big Data and develop a forecasting framework to reflect the COVID-19 environment. Unlike the last two down turns, where data was very sparse and difficult to collect, there is a vast supply of data available and accessible to analyze and model the path forward. LodgIQ has created a causal forecasting framework​, where we monitor COVID-19 conditions in the world’s major markets, use epidemiological and macroeconomic data, and explore their effects on travel demand and simulate now-casting. By leveraging the data signals buried in the digital world and past downturns, LodgIQ has adopted a ​hybrid approach of machine learning and statistical modeling​. Boosting machines along with linear quadratic estimators are utilized to model complex nonlinear feature interactions. This new forecasting framework ensures we have an end-to-end time series forecasting framework that reduces latency, scales both horizontally (markets), and vertically (dynamic feature selection) handles model decay and supports real-time data processing. 

LodgIQ + Phocuswright Special Collaboration

COVID-19 Market Forecasting

LodgIQ and Phocuswright are teaming up to evaluate the level and duration of disruption, notable differentiating factors, and the projected recovery curves in major markets across the globe. LondonSingaporeSydneyNew York CityBostonDallas, Los Angeles, Key West, and San Francisco are the first destinations of our Phocuswright “Special Series” collaboration, which explores how deteriorating market conditions in March drastically impacted travel in the market.