The packing list for holidays in times of Covid is as likely to require Xanax as it is sunscreen. Whilst the thought of escaping the claustrophobic confines of lockdown for the beaches of the Mediterranean may seem appealing, navigating the ceaselessly changing guidelines and regulations is a stressful business.
The hurdles of unpredictability
Building predictability into travel planning is clearly a priority for travel agents and airlines, whose revenues have been hammered both by their customers’ Covid safety concerns and also by capricious rule makers. Yet in an environment where new disease, quarantine and testing data is constantly influencing governments’ models, is it possible to anticipate what the likelihood is of successfully enjoying a fortnight under the exotic sun over the summer?
Naturally, one impact has been the growth in domestic tourism, with prospective holidaymakers swapping foreign trips for those closer to home, which do not run the risk of a last minute state or national border closure. The rediscovery of local culture and beauty spots have been a boon for battered home markets. But even here, travellers have been disappointed at times, as snap restrictions between certain Australian states and between Australia and New Zealand, for example, have severely dented consumer confidence.
Has the need to travel overcome the desire to visit?
Another trend has seen customers booking trips based on the accessibility of a country rather than the quality of the destination. This is already becoming a standard behaviour for travellers who are booking leave from work weeks in advance whilst only confirming their travel itinerary a few days before they leave. The uncertainty does not stop when on holiday either, as governments introduce new restrictions, often at short notice, which may cause plans to be cut short whilst lying on the sun lounger.
Data has a key role to play in addressing these challenges, both at an individual and sector level. For aspiring travellers, being able to search for potential destinations, especially overseas ones, based on specific criteria is vital. In the case of those who are going to leave the choice about where to go until the last minute, having access to the latest quarantine and testing regimens is a critical component of decision making. However this intelligence is often not easily accessible. Nor is it frequently available in a “compare the market” format that allows users to tweak different criteria to allow comparisons between locations. SafeScore is working on a solution that offers this functionality, aggregating data feeds from multiple, reliable, current data sources, and hopes to launch this service shortly.
Data designed to boost travel
At a sector level, there is a role for machine learning and predictive analytics to identify trends in huge and complex travel restriction data sets. Identifying links between disease events and subsequent government responses will be tough. However, deep learning tools are already being developed to analyse complex systems. Attempts to predict cryptocurrency prices based on real world events and news flows are starting to appear. It will take a while for them to build a proven track record, but the tangible incentives are there for them to succeed. And, if the modellers can crack the cryptocurrency challenge, who is to say that similarly talented teams cannot develop a solution for the multi-trillion dollar global travel industry? Until then, don’t forget the Xanax.