There are particular historical periods in which accidental factors or crisis have a particularly important relevance. Never in the past seventy years have taken on importance as in this 2020 following the Covid-19 emergency.
NB: This is an article from Hotelperformance
Those involved in revenue management are therefore faced with occupancy forecasts, booking pace, revenue and price trends which do not have historical reference. In this scenario therefore trend, pace of sales and rate elasticity assume a fundamental role in order not to lose the compass and limit as much as possible the surfing on sight as this situation imposes on us.
Let me to suggest you a couple of merely analytical strategies for the restart that I have already had the opportunity to introduce with positive results, in order to be able to read in the most correct way the data we have available.
First of all, I obviously suggest reviewing your budgets starting, more than on other occasions, from a careful cost analysis. This is because never as in this moment it is fundamental to be able to identify the break-even point, but also because certain choices must be formulated in the most conscious possible way.
Should I (or can I afford) grant a free service that is perhaps even more expensive than before? What are the fixed costs that I have to incur for a decreased demand? How can I take advantage of the opportunities of a particular channel, without this excessively affects my variable costs?
These are all questions that must be asked and which can be better answered by going to view all the items in your income statement, assessing a greater or lower impact depending on the strategies that are decided, and at least finding a break-even point that allows us to be able to pay the opening costs, but also those relating to the period in which we had to remain closed forcibly.
Then we can monitor the progress of the pick-ups and compare them with what we have to do daily to reach the goal.
Let’s put the case we are analyzing June, as an example we are on 16th and we are missing twenty-five thousand euros to reach the budget, therefore with fifteen days available for sale. Obviously, we must not divide twenty-five thousand euros by fifteen, as the sales window of June 16th is fifteen days, while that of June 30th is one day only. We therefore need a proportional breakdown.
First we need to sum up all the sales windows day by day, then 15 + 14 + 13 + 12 and so on. This can be calculated with the following formula: n * (n + 1) / 2 where n = the number of days left until the end of the month (including today)
15 * 16/2 = 120
We then divide the budget deviation to today by this sum and multiply it by the days available for sale today:
25,000 / 120 * 15 = 3.125,00
The following days will have the same formula after deducted from the budget the quota foreseen in the previous days going to end at the same time as the decrease in the sales window.
Finally, we will have to make an approach with the monitoring of the pick-ups. We can immediately make a comparison between the pick-up data of the previous days with those that we expect for the future: are the pickups of 13th 14th and 15th much higher than what we expect for 16th, 17th and so on?This obviously is a scenario that we can define comforting.
Furthermore we can compare the pick-up trend data from 16th onwards trough a linear regression, therefore follows the trend shown in the previous days with the daily expected revenue for budget if these values are higher they indicate a trend above expectations, otherwise we should take steps to reverse this trend.
This can be a very useful approach for monitoring performance, in a situation in which we find ourselves with poorly reliable data and a climate of particular uncertainty. Constant monitoring is very important: using summary data that allows you to evaluate the good performance of the sale, knowing how to interpret and react promptly in the case that these are not positive is essential for optimizing revenue performance.