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Integrating data a challenge and opportunity for Whistler

In England, a company called QuantumBlack bills itself as a "creative data science agency.
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In England, a company called QuantumBlack bills itself as a "creative data science agency." Among other things, QuantumBlack has developed software for a Formula 1 race car team that collects data from thousands of variables, analyzes it and then advises the team on strategy. The information includes structured data, from sensors on the team's cars, as well as unstructured data available from various sources.

"We listen to the engine notes of competitors' cars, on TV. That can tell us their settings. The braking profile of a car on GPS as it goes into a corner can also tell you all sorts of things," Simon Williams of QuantumBlack told The Economist's Intelligent Life magazine.

This data could be analyzed by people, but by then the race would be long over. "If you are taking more than ten seconds to make a decision, you're losing your advantage," Williams said. "Really you need to be under the eight-second mark."

And that's what QuantumBlack's software does. It uses algorithms to analyze thousands of bits of data and produce a strategy, or conclusion. In seconds. While the race is going on.

Compare that to the data — and timing of its release — on business in Whistler. Sure, we find out about room nights sold, skier numbers, gross visitor spending and several other useful measurements, but the information comes well after the fact. Why shouldn't every business in Whistler know on the first of each month how much GST and PST were remitted by Whistler businesses the previous month, and how the numbers break down by sector? There could be daily updates of activity bookings, rounds of golf and occupancy forecasts, tied in with weather forecasts and transportation news that may impact people getting to or from Whistler. Media and social media comments about Whistler could be monitored; with a matrix of strategies for responding should the comments reach a certain threshold.

Tourism Whistler and Whistler Blackcomb are doing many of these things now. But much of the data generated in Whistler is kept in silos. For example, the PST the provincial government is collecting. And each hotel has its own system and deadlines for reporting data. Restaurants and retailers carefully guard their information from their competitors, and everyone else. Trust is, alongside of cost, one of the biggest obstacles to a centralized system of gathering and analyzing data.

Many years ago a former business person of the year suggested at a meeting of Whistler retailers that they all lied to one another about how their business was doing out of fear of giving the other guy an advantage. Why not have everyone write down on a piece of paper how much their business was up or down over the previous year and put the numbers in a hat? The results — strictly percentages that couldn't be linked to any business — would give an overall indication of retail business at that moment.

Nobody dared to take up the challenge.

More recently, the Whistler Chamber of Commerce proposed creating a monthly index of business. A representative handful of businesses from each sector would be asked to supply some key indicators to the chamber. The participating businesses would not be identified and the numbers — which would be made available to chamber members — would provide a performance index of the sector, rather than of individual businesses.

Again, businesses either failed to see the value or failed to trust one another and the experiment seems to have died.

A system of data collection and analysis that included all local businesses could give Whistler a substantial advantage over other resorts. The merits of this type of approach have been seen in the past with the One Whistler organization and, more recently, with the Economic Partnership Initiative. But we are still only scratching the surface of the data generated by Whistler's customers.

As Williams of QuantumBlack told Intelligent Life: "We've hit a crossover point in terms of the cost of storing and processing data versus 10 years ago. Then, capturing and storing data was expensive, now it is a lot less so. It's become economically viable to look at a shed load more data."

And when he says "look at" data he means analyze it through algorithms. This can lead to patterns no one thought existed and can challenge orthodoxies. Nick Meaney has shown that.

As several stories in the media have chronicled in recent years, Meaney's company, Epagogix, has developed an algorithm for movie analysis software that shows there are only three actors who make money for a film. That's not to say that a film will or won't make money, or to judge the quality of the film. But three actors — Brad Pitt, Will Smith and Johnny Depp — have been shown to make money for the film. Others — George Clooney, Matt Damon, Tom Cruise etc. — have been shown, through statistical analysis, not to have had an impact on the profitability of a film.

It's interesting reading, whether you buy the analysis or not. But consider that a segment of the tourism industry that Whistler competes with, cruise ships, has access to integrated, wholesale information from its customers. Every dollar spent and virtually every choice a customer makes while on a cruise ship holiday is recorded and analyzed by the cruise ship company.

Whistler, with its 19,936 pillows (within 500 metres of the lifts), 219 retail shops and 158 restaurants/lounges/bars (as of February 2012), generates more data than a cruise ship, but the data isn't integrated or analyzed in real time.

There are, of course, limitations to integrating data from everyone in the resort. Whistler doesn't have a Formula 1 type of budget. It's also not a cruise ship, with one captain in charge of everything. And there are privacy issues with data.

But companies around the world, including competitors in the tourism business, are finding new ways to integrate and analyze the vast amounts of data now available. And they are adjusting strategies and building new ones based on that data analysis.