There are many articles and publications about Restaurant Revenue Management (RRM from now on) that tend to repeat the typical mantra about its definition: sell the right seat, to the right customer, at the right time, for the right price.
NB: This is an article from Revenue Acrobats
There is clear parallelism with the traditional definition of Rooms Revenue Management (sell the right room, to the right customer, at the right time, for the right price) and indeed the two areas are often compared, to explain the application of Revenue to the Restaurant field.
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Not everybody is necessarily knowledgeable on revenue management though, so in this article, we will try to make RRM easier: keeping it simple, but understandable.
When we talk about revenue management applied to the hotel industry, one of the most common misconceptions is to think about it as related to pricing only. As such, people think about the room’s price fluctuations on a daily, even hourly basis, based on demand conditions. This is partially true (we will elaborate on this later on…) but one universally true thing is that the majority of the guests understand and accept price changes at hotels as this is a common practice for flights alike. Thinking about a restaurant applying price changes to its menu based on demand is still far from becoming acceptable, simply because the customers are not familiar with it and it might negatively impact the demand in the long term.
Nevertheless, it is possible to apply different menu pricing when demand is very high e.g. during popular events (Olympics, football, national congresses…). In all these cases, restaurants can implement a “special price” menu and therefore work on the product (menu type) to increase the price and revenue return.
When we said that one common misconception about revenue management is related to considering it a mere pricing activity, it is because revenue has never been about pricing only even when we talk about room revenue. As such, there are different ways and techniques to drive and optimize revenue in both hotels and restaurants by working on the core elements that are at the basis of the discipline and without compromising the market positioning.
- Hotels sell rooms out a fixed daily inventory: total available rooms.
- Restaurants sell table seats out a fixed daily inventory: total available seats.
In the Hotel industry, we calculate the occupancy: occupied rooms/total available rooms.
The level of occupancy has a direct correlation with the pricing strategy and it is influenced by the unconstrained demand (the number of rooms your hotel would be able to sell on a given day, assuming there would be no fixed inventory constraints). To implement an optimal strategy we must factor the optimal level of occupancy and average rate sold, to drive the best possible revenue return based on market conditions.
For a restaurant, both occupancy and unconstrained demand are way more difficult to be calculated.
As we explained, the unconstrained demand for a hotel is an estimate of the total demand that could be accommodated, ignoring rate and capacity constraints – essentially, how many rooms could be sold on a given day if your hotel had unlimited inventory.
Unconstrained demand for a restaurant, takes into consideration the total demand that your restaurant could accommodate on a given day, assuming that there would not be any table seat constraints. How to calculate it? Total definite covers + cancellations + no-shows + covers rejected for each day.
In the restaurant industry, we calculate the covers occupancy: occupied seats / total available table seats.
But there are different ways to calculate occupancy in a restaurant:
- Covers per meal period
- Covers per service hour
- Tables occupancy per service hour
In a restaurant, what you need to understand is the best combination of Table occupancy x Time spent x Revenue generated for each meal period and by day of the week.
Why time spent?
Table seats are the fixed inventory of the restaurant (like the rooms in hotels) but the total calculation of availability has to consider the service hours. So if your restaurant with 10 seats is open for 2 hours per day, the total seat availability is 10 seats x 2 hours= 20 seats. Logically, you could accommodate 20 guests (or more based on the time spent).
When does this calculation of Seat Hour come into place to make a difference?
Revenue generated is the ultimate goal and in RRM we calculate a key performance indicator called REVPASH: Revenue Per Available Seat Hour. It is a standard indicator of the industry and is comparable to the REVPAR at the hotel level.
Available seat hours= the number of seats available during the regular hours of operation.
Assume that your restaurant has 10 seats and it is open from 7 pm to 10 pm and that it generated 500 euro of revenue. RevPASH= 500 / (10×3 hours of operation)= 16,6 euro
The higher the RevPASH, the higher your restaurant is earning from its available seating capacity.
Calculating RevPASH is paramount to identify the most profitable time intervals and the effectiveness of the current seating arrangement.
During the peak days, for instance, we will try to maximize the table mix by accepting the bookings of the more profitable tables in the first part of the evening with the scope of doubling or tripling up the revenue return of the table. At the same time, we would try to push the worst revenue contributors (e.g. big parties that book large tables, stay longer, or are less predictable) later in the evening when there is lower demand compression.
Legenda:
Average check Table: Revenue generated by the table (total sales)ù
Average check Per Person: revenue generated by the table/number of covers
Time spent x table: time between the first order has been taken and the payment issued.
Time spent Min: number of minutes between the first order has been taken and the payment issued.
Rev x Min: Revenue of the table divided by the number of minutes
By analyzing the above example of dinner in a peak period, the average check is not meaningful if it is not compared with the time spent at the table.
The tables of 1 and 2 persons have a good average check but they have a lower revenue contribution per time spent than tables of 4 and 5 persons. The difference in time spent is minimal but the revenue contribution per time spent is higher in the last ones.
Regarding the tables of 7 or more people, we can see that the time spent is longer compared to the smaller tables. However, the average check is normally higher too, and usually, a pre-arranged menu is set in these cases and it can contribute to getting more profit out of this type of customer.
One common issue with the big parties is that if accommodated at peak times during the meal period, they might occupy the table for a long time slot and that would prevent the restaurant from maximizing the revenue opportunity from the service hours. To explain further, if we have the opportunity to sell 2 tables of 4 persons twice during the service, we might get a better revenue return than selling just one table for 8 people that will take longer to be served and indulge more. It is therefore recommended to accommodate big tables during the second part of the evening or out of peak demand times.
What we have seen so far are analyses that involve the optimal sale of seats based on the capacity, optimal mix, and demand. By working on the inventory optimization and sale of your seats, you can get outstanding results in terms of revenue return.
The Average Check (revenue/covers) is another important element in the RevPASH outcome.
