The Rest of the Story: When Revenue Management Details Make a Big Difference

When I was a child my family would pack up the car each summer and hit the road for a three-week road trip.  The destinations were endless- the Grand Canyon, Oregon Coast, Alaska, and many others.  Our parents were brave enough to take on the backseat fighting, restless fidgeting, and headrest kicking that would inevitably ensue as we put thousands of miles in the rearview mirror.   As a result, we had the great fortune to visit the places they’d always wanted to go.

In an effort to placate us, or perhaps to keep their sanity with three young children in the car, they soon introduced us to the wonders of audio books and narrative radio.  One day we listened to Paul Harvey’s “Now for the Rest of the Story,” and I was hooked.  As he laid out the little-known details of well-known stories, the wheels in my head would spin as I raced to beat him to the grand reveal.  It was amazing to me that there were so many unknown details about titans of industry, political masterminds, and other historical figures.

Years later I once again found myself searching for the hidden details as a greenhorn Director of Revenue Optimization at Valley River Inn in Eugene, Oregon (Go Ducks!).  I closely tracked traditional revenue management metrics, could rattle off our top corporate accounts, and knew which Pac-12 fan base was willing spend the most money for their hotel rooms on football weekends (answer- USC).  Yet when it came to figuring out which revenue strategies would produce the greatest impact, I often found myself looking for answers.

I’d pull the right levers (or so I thought), and then wait until the targeted dates actualized to see whether my revenue management strategies resulted in success or failure.  There was some success, and a lot of failure.  And as I searched to find a way to better prognosticate and measure the success of each revenue management strategy, it soon became clear that there were three key analysis types that helped to shine some light on “the rest of the story,” allowing me to align my efforts much more closely with my sales and marketing team members.  

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Average Length of Stay (ALOS)-

To calculate average length of stay, divide room nights for a particular dimension and time period by the corresponding number of reservations.


Average Length of Stay


When applied to hospitality revenue management, ALOS helps to determine attribution for increases or decreases in production.  For example, if production from your top corporate account is down year over year and ALOS for that account is experiencing a similar decline, it may be that their business needs have yielded less production for your hotel even though they continue to patronize your hotel exclusively.  However, if production is down and ALOS during that time period is stable, it may be the case that the account is sending some of their business elsewhere.

Day of Week Productivity-

Measuring day of week production across various dimensions and periods is useful when determining demand patterns.  It may make sense to start at the week part level (weekend and weekday), before drilling down further into each individual day.  For example you may notice that weekday production is down for your corporate negotiated segment–an alarming trend.  However, after you notice that the occupancy on Monday evenings has actually increased for this segment while decreasing on Wednesday evenings due to displacement from more profitable business, your concerns may be appeased.

Average Lead Time-  

To calculate lead time, subtract the numerical value of the booking date from the numerical value of the arrival date.  From there, average the lead time for each reservation by summing the lead time values for a given dimension and time period before dividing by the corresponding number of reservations.


Average Lead Time Step 1

Average Lead Time Step 2


Average length of stay is an invaluable resource in determining the best way to impact future production for a particular period.  For example, if you are projecting a revenue shortfall thirty days out, you should reference average lead time by market segment or rate plan to decide the best tactical approach to fill the hole.

By using the analysis types above you’ll be able to unmask the details behind the trends, and finally deliver the “rest of the story” to your leadership team.  We can’t promise you’ll be as famous as Paul Harvey, but we feel pretty confident you’ll be next in line for salary increases and a larger bonus.

Contact Us today to learn a bit more about how Focal’s analytics platform can help you to transition from analyzing the “what” to understanding the “why” and impacting the “how, when, and where.” 

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