It is easy to fall into assumptions. It is human nature, after all, but when do assumptions on revenue management start to work against you.
NB: This is an article from HowsMyRate, one of our Expert Partners
In a recent article, “5 Hotel pricing Mistakes to avoid” Kris Glabinski, President HowsMyRate, took a look at five common pitfalls for Hotel Revenue Managers and Owners. One area covered was the negative effect assumptions have on revenue.
Subscribe to our weekly newsletter and stay up to date
Kris said, “I have come across many cases where Revenue Managers would give their arguments based on assumptions, stereotypes, or simply gossip. In effect, their actions on price are based on those. For an analyst, any assumption is a threat. Because it can only by 50-50 correct.”
So, where does the balance between assumption and analysis lay? Let’s take a look.
In our example, let’s look at a ski resort hotel in peak season. On weekdays it faces low demand however, on the weekends, more demand than it can accommodate. They assumed they could use a minimum stay restriction for all Friday reservations to maximize revenue. This would stop single-night guests when they could have someone booked for the entire weekend.
This assumption seems logical enough. However, it could have a detrimental effect unless supported by proper analysis.
Let’s look at a potential scenario that exposes an issue with the assumption above.
By analyzing the length of stay per day of the week, it has become clear that Friday arrivals had an average LOS of 1.4 days. This means that there was a clear (but small) customer segment arriving on a Friday and a lot larger traffic arriving on Saturday. By assuming that a two-night minimum stay was the solution, it stopped Friday bookers, who had no impact on weekend bookers arriving on Saturday.
So what is the moral of the story here?
Assumptions are helpful; they are based on the experience achieved over many years. However, an assumption not backed up by analysis is essentially just a risky guess. Back up assumptions with analysis.