Exclusive Feature: Operating in a digital age, companies with data-driven business cultures are more productive and profitable than their competition; This extends to the hotel sector where savvy operators are using data-driven approaches to increase profits amidst market complexity and volatility.

Accurately forecasting demand is critical to a hotel predicting the time frames throughout the year that will bring them higher or lower than normal occupancy, demand and revenue. A good demand forecast assists with pricing decisions, inventory management, staff allocation, property maintenance and hotel operations.

Using data and analytics through accurate forecasting is also the best way for hotels to determine future marketing and revenue strategies that drive success. It is also critical for hotel owners and investors assessing the financial potential, or performance, of a property. However, there’s more to forecast performance than accuracy alone.

Take the coin flip game of 'Heads or Tails', for example. If you had to guess the probability of heads over tails, your answer would be easy: Heads over tails is expected half the time. And 50%, well, that’s technically a perfect forecast. But, as you can already imagine, a perfect forecast isn’t usually achieved with a limited number of actual tosses.

Play the game 10 times in a row—totalling up every time it lands on heads or tails—and you’ll more often than not end up with a percentage different from the original forecast. Why is that? Because a coin is a coin and a flip is a flip. Coins don’t have a memory; the coin doesn’t know or care what happened in the previous tosses.

The outcome of the coin flip scenario would actually be surprisingly similar when applied to a hotel’s own forecast versus reality: Compare 10 Tuesdays in a row by evaluating their 10-day forecast against their actuals. You’ll find that no two Tuesdays are exactly alike, and each are also subject to the independent odds of their individual data elements.

When it comes to forecasting hotel demand, we can never truthfully say we know exactly what’s going to happen; rather, what is most likely to happen. So, then, if we look to demand forecasts to understand our most likely outcomes and ideally the optimal outcome, what inputs help produce a reliable forecast?

While most hoteliers are familiar with forecasting elements such as historical data, recent trends and pacing, there are other considerations not as commonly discussed. One of these is the role “uncertainty” plays in the analytical forecasting process. Uncertainty refers to the amount of unpredictability or volatility that exists for any given day, in any given market, for any given market segment—in relation to the number of days to arrival. It represents “the unknown,” and is best described as noise in the forecasting process.

Unfortunately, demand uncertainty hasn’t received much attention as of late (and, in some instances, is ignored entirely by many revenue technologies). However, it plays a very critical role in a hotel’s forecast performance. One of the reasons it’s impossible to generate a perfect demand forecast is because of this noise—seemingly random or arbitrary fluctuations in demand.

The limitation of technologies using traditional demand forecasting is that they use deterministic models that view all data as exact… including uncertainty. They take exact values as input, and they output exact values. Because of this, their forecasting calculation is unaware of the uncertain nature of the demand.

With a traditional forecast, it’s impossible to cleanly separate signal (data with a predictive value) from noise (data devoid of predictability). Any deviation in demand—however normal it may be—is considered an error since the forecast is an exact number. A high-performance forecast understands the difference between signal and noise where a deterministic model cannot.

So how exactly do advanced revenue management solutions handle this process differently? Unlike traditional methods, advanced revenue management solutions separate the signal and the noise. Rather than attempt to forecast the noise—something futile in its efforts— demand modelling instead improves the forecast by progressively isolating the signal from the noise.

Advanced revenue management solutions train their sights on more accurate forecasts by modelling probabilities and factoring in random behaviour. Without getting too technical, this means an outcome can have any value within a range, and each value has a certain probability of occurring. Think of it like a professional archer with their target.

You can deterministically forecast the most likely point the arrow will hit and it may hit that exact spot 50% of the time. But widen that to a range or diameter of where it may hit and the player will hit within that range 99% of the time.

This is important because if uncertainty is not managed correctly in a hotel’s demand forecast, its subsequent pricing decisions and overall profit performance are left exposed to higher volumes of risk. Solutions that can’t properly understand or quantify uncertainty—and analytically consider them the same as they do the easily-distinguishable demand patterns—ultimately produce sub-optimal forecasts and decisions as a result.

By managing and accounting for uncertainty within the analytical process, these risks are minimised and hotels have better revenue opportunities, better inventory controls and higher hotel profits. After all, the odds of achieving optimal forecast performance without accounting for uncertainty? No dice.

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Charles Wang is the Regional Head of Advisory Services, based in Beijing and working in Asia Pacific and Greater China for IDeaS. He leads a team of professional advisors to deliver trusted revenue management deployment services to hotels and selected industry clients acrossthe Region.

IDeaS: With more than one million rooms priced daily on its advanced systems, IDeaS Revenue Solutions leads the industry with the latest revenue management software solutions and advisory services. Powered by SAS® and more than 25 years of experience, IDeaS proudly supports more than 7,000 clients in 94 countries and is relentless about providing hoteliers more insightful ways to manage the data behind hotel pricing. IDeaS has the knowledge, expertise and maturity to build upon proven revenue management principles with next-generation analytics for more user-friendly, insightful and profitable revenue opportunities, not just for rooms, but across the entire hotel enterprise.

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