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Fresh from HSMAI > The New RMS: A Buying Guide. Download here

The 6 Demand Forecasting Questions You Should Be Asking Now

“Boy, are we learning the value of forecasting during this pandemic.”

Wendy Lamont, revenue management veteran and EVP for Atlific Hotels, said what many of us have been thinking in HSMAI’s new guide to RMSs.

Here’s what else people are thinking:

  1. Forecasting is BROKEN.
  2. That’s a BIG problem. It’s the most critical piece of my RMS.
  3. My team can’t do our job without a forecast we can trust.
  4. (For some) This is going to make it harder to justify the cost of our RMS to higher-ups.
  5. What exactly should I do about it?

The first thing to keep in mind is that forecasting capabilities are very different from one RMS provider to the next.

Methodologies have critical differences that yield materially different results, even in this tumultuous climate.

Given that demand forecasting is so important (it’s the beating heart of an RMS), many RM leaders are using this time to explore the differences in forecasts, and consider innovative solutions, rather than accept this ‘new nightmare’ of broken forecasts as the ‘new normal’ for their RM team.

To help you on your journey of exploration, we’ve compiled some of the best intel on evaluating demand forecasting – straight from revenue leaders themselves (chronicled in HSMAI’s new guide to RMSs) and from the data experts at OTA Insight.

How to evaluate an RMS provider’s forecast

Here are 6 key questions to help evaluate new RMS partners and to ensure you’re getting the best forecasting from your current provider.

1 - Does your forecast have adjustable weighting?

One of the biggest challenges in 2021 and beyond is figuring out how to handle pandemic-era data.

Eric Gravelle, vice president of revenue management for Diamond Resorts International shared:

“The big debate is: Do you use 2020 data, and how? We’ve had a few markets that had record years, so we don’t want to entirely discount that, but there are places where we can’t rely on the data.”

That’s why it’s so important that forecast models have parameters that can be configured or tuned based on a user’s perspective a.k.a “adjustable weighting.”

And this weighting must enable a response to COVID that’s both robust (for adequacy) but also granular (for precision).

For example, with N2Pricing RMS (Revenue Analytics’s new RMS), those dates and hotels most impacted by COVID are replaced with 2019 actuals and then an appropriate factor (ex: 81%) is applied and used in the long-term forecast.

Further, demand forecasts incorporate both ‘Last Year’ and ‘Recent Time’ curves. Since COVID, more people are making last minute travel decisions, collapsing booking windows. In response, our software has increased forecast accuracy by weighting ‘Recent Time’ more heavily than history.

Importantly, all of our parameters can be modified down to the individual hotel level. For hotels that are experiencing a much shorter booking window now, our software would weight that ‘Recent’ trend curve more heavily. But for hotels whose booking pattern didn't dramatically change, it wouldn’t change that weighting, nor would it 'override' 2020 actuals with 2019 data.

Takeaway: make sure your RMS provider has this kind of ‘dynamic’ forecast with adjustable weighting that’s both robust and precise. You can’t get by without it now.

2 - Can it ingest future demand signal data?

Does your RMS ingest forward-looking demand data? Many RMSs unfortunately don’t.

Said Nikos Karivalis, director of revenue management for Brown Hotels:

“Most RMSs don’t look at upper-funnel data…they’re not looking at more future-looking demand signals like flights, web searches, which is instructive, especially now.”

And with historical data on the fritz, more and more revenue leaders are looking beyond history and bookings to future signals to get a clearer picture of demand and move ahead of the booking curve.

Examples of this data include:

  • Hotel search data. Hotel search data is gathered from OTAs, metasearch sites, and GDS. It tells you the destinations travelers are considering, what dates they're looking at, their length-of-stay, and what type of accommodation they want.
  • Flight search data. This data tells you the volume of travelers expected to travel to your market on a daily basis and where they're coming from.
  • Alternative accommodation availability. Knowing how many alternative accommodation listings you may be up against for different LOS, and at which price point, completes the picture of consumer choice.
  • Dynamic compset. With dynamic competitive set data, you are no longer limited to a static group of pre-COVID competitors but can see how your hotel's rates and availability measure up against a wider selection of competitors that change with market shifts.

Forward-looking data—via predictive market intelligence solutions like Market Insight from OTA Insight—helps hoteliers respond to signs of pick-up before the competition, so they can drive revenue with more informed pricing and marketing decisions.

For example, Julia Vereskun, director of revenue management at Hotel Metropol shared:

“With Market Insight we noticed a new destination was actively searching for Moscow… we launched a digital campaign in Google to target consumers in that destination. We reduced cost per action by 30% and increased the number of bookings by 42.5%.”

To get a sense of the power and value of forward-looking data when forecasting, take a look at Global Market Insight - a free interactive map where you can spot early signs of demand and track recovery at various destinations.

Having this data integrated directly into your RMS, rather than viewing it in a separate system, ensures your demand forecast and RMS pricing recommendations have future demand signals already factored in.

N2Pricing is one of the only RMSs that integrates OTA’s data directly (book a demo and we’ll show you how it works).

Takeaway: make sure your RMS provider can ingest future demand signal data. It’s a valuable supplement to more traditional data sources.

3 - How many models does it use?

Some legacy RMSs use 1-2 models only. Others use dozens or hundreds.

The reality is that more really is better when it comes to modeling demand.

So, in stark contrast to legacy approaches, modern RMSs achieve boosts in accuracy by using a library of thousands of forecast models and a horse race-like “pick-best” process that selects the most accurate algorithm for each hotel and market segment.

This innovation has yielded significant gains in accuracy. Tim Wiersma, CRME and principal of Revenue Generation LLC, noted:

“The RM systems that are having more success are the ones that are doing multiple forecasts. They’re not placing their bets on just one forecast. They’re playing multiple algorithms to come up with a forecast and then tracking the results for accuracy.

If you have fewer forecast models, then it’s an absolute certainty that your forecast accuracy is not optimal. The question is simply: how suboptimal is it?

Takeaway: ask your RMS provider how many models they use and how often those models are updated and retested?

4 – Does it have intraday updates? Can you control the timing of them?

Booking windows have been shrinking steadily for years and COVID shortened them even more.

So, particularly for hotels in dynamic markets, and for most economy and midscale hotels with significant same-day demand, the ability to update the forecast multiple times a day is crucial.

But it’s not just how many times the forecast is updated that’s important. It’s crucial to be able to determine when the forecast is updated.

Jennifer Schneider, vice president of revenue management for Radisson, illustrated:

“Once a day is useless. And how much control do you have over the timing? Overnight means different things in different time zones. If you select one time zone – say, East Coast – and it’s going to update at 6 a.m., you’re interfering with check-in and check-out.”

The best forecasts (like N2Pricing's forecast) are also price sensitive, meaning they will adjust based on where your hotel’s pricing stands against your comp set.

So, intraday forecasts are also important to account for competitor price changes made throughout the day.

Takeaway: make sure your RMS has intraday update capabilities and you can control the timing of updates.

5 - Does it automatically identify special events?

Special event mapping is another manual activity that has long been standard functionality in an RMS.

It remains critical functionality for many 1-property DORMs. But in many RMSs, this functionality has been used less over time as revenue managers manage multiple properties.

And the activity is certainly too detailed and complex for a busy GM.

So, time-strapped users will benefit greatly from an RMS like N2Pricing with more automation, such as an engine that automatically detects special events and appropriately adjusts the forecast to account for them.

Takeaway: if you have multi-property managers on staff, look for an RMS that identifies special events automatically rather than requiring manual mapping.

6 – How quickly does it respond to pacing?

Pace reports are the go-to tool for many revenue managers.

So important, in fact, that the financial forecast follows pacing: they increase their financial forecast when pace is strong and decrease the financial forecast when pace lags.

So, understandably, speed matters a great deal.

And while 1-property DORMs who are manually forecasting their demand based on pace may prefer to adjust the RMS forecast based on their findings, many more people rely on RMSs to do the work for them. RMs and GMs simply don’t have time to manually develop demand projections and feed them into an RMS.

The good news: most RMSs today do increase or decrease the forecast based on how bookings are pacing. The bad news: revenue managers often complain that the response is not nearly quick enough for their purposes.

That’s why it’s important to look for an RMS with a forecast that responds to pace quickly, like N2Pricing.

Takeaway: ask your RMS provider how quickly their forecast adjusts based on pacing.

More help with forecasting and RMSs

We hope this discussion about forecasting was helpful to you and your team. To learn more about how to improve forecast accuracy and other critical things to look for in an RMS, download HSMAI’s new guide to RMSs.

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Dax Cross

Dax Cross, the CEO of Revenue Analytics, is proud to lead an incredible team and to partner with customers across multiple industries to create value and enrich lives. Working together, we have driven over $1 billion in revenue growth.


Dax Cross, the CEO of Revenue Analytics, is proud to lead an incredible team and to partner with customers across multiple industries to create value and enrich lives. Working together, we have driven over $1 billion in revenue growth.

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