To have confidence in your forecast, and ultimately your pricing decisions, you must begin with a solid understanding of available demand in your market.

This starts by applying a scientifically sound approach to assessing your unconstrained demand—demand that is not constrained by the capacity or restrictions of your business and could be sold if your property had an unlimited number of assets available.

For example, picture a 100-room hotel with demand for approximately 100 rooms on a particular date. Okay, straightforward enough. Charge a fair rate, and you should be fine. Now think of the same hotel, only there is demand for around 1,000 rooms. How you optimize your business between these two circumstances may require very different actions.

Ultimately, in both situations, you may reach full occupancy. But the true demand is very different. In the latter case, when the demand is 1,000, you can afford to yield more aggressively, charge higher rates, and still fill up your property.

Find True Demand

“The temptation to form premature theories upon insufficient data is the bane of our profession.” – Sherlock Holmes

Any historical data you reference after the date in question has passed will be influenced by many factors, such as capacity and pricing decisions. It’s important to understand what the demand would have been, had it not been influenced by these constraining factors. This allows us to know the true demand so we can really optimize profits by understanding the demand in the market—instead of looking at constrained demand.

I am sometimes asked why my company IDeaS doesn’t use lost business data to determine unconstrained demand. Perhaps a few decades ago, when demand sources were simple with few channels of distribution, you could have effectively kept track of regrets and denials.

But it’s difficult to track this type of data cleanly and accurately in today’s complex online environment, especially when you don’t know why a person isn’t willing to pay a particular rate. A regret no longer occurs simply because of price but because of a combination of many factors like location, reputation, and online content.

Using lost business data is flawed, adds a lot of bias due to the small sampling of data a business can control, and ultimately may not produce an accurate estimate of demand. IDeaS, therefore, uses scientific methods to understand true demand, and this has consistently proven to have the highest reliability due to the integrity of the data utilized.

Account for Uncertainty

“As far as the laws of mathematics refer to reality, they are not certain; and as far as they are certain, they do not refer to reality.” – Albert Einstein

Demand has a lot of uncertainty. You can think of it as a signal, which is a forecastable part to which noise has been added. The job of forecasting is to isolate the signal and use it to produce a forecast. But what remains, after you have taken the signal out, is random noise. Therefore, you must understand that for whatever forecast you produce, you will be uncertain about it and must account for the random noise.

So, how can IDeaS’ revenue science solutions give you greater confidence in your forecast?

• By avoiding inaccurate or “noisy” data that dilutes the reliability of a demand forecast

• By developing machine-learning, decision-based systems that adapt quickly to changes in your business or the market to continuously improve forecast performance

• By harnessing the power of hundreds of SAS analytics models, finely tuned for specific business scenarios

• By predicting demand by incorporating historic and future data, competitor pricing, and forward-looking market demand intelligence

• By considering demand and how it varies due to pace, season, day of week, year-over-year trends, shift, length of stay and asset type

• By understanding the unique relationships between properties, market segments, and their booking patterns while accounting for uncertainty or volatility in the market

• And by integrating pricing and market demand intelligence data directly into demand forecasts and strategic decisions to optimize revenue performance

When we talk about forecasting at IDeaS, we’re not just talking about forecasting an outcome, but also forecasting the reliability of that outcome. We use the forecast of demand, and the uncertainty, to cope with the risk associated with the uncertain nature of demand in the marketplace in our decision-making process, instead of ignoring it.

Dr. Ravi Mehrotra is the President, Founder & Chief Scientist of IDeaS Revenue Solutions

A pioneer and global technology leader, IDeaS offers industry-leading revenue management solutions for business of all types and sizes in the global hospitality and travel industries. We transform the right data into clear and actionable insight, so that our clients can price, forecast and report with speed and confidence, improving business performance.

www.ideas.com