Canadian businesses are eyeing data analytics with keener interest than ever before, but many of them have been slow to start using data to make decisions, says a new study from Deloitte Analytics.

In a survey compiled from more than 100 online surveys and 35 interviews with executives of companies in Canada, the U.S., the U.K., and China, researchers for Deloitte found the ‘big data’ buzzword is making an impression. A staggering 96 per cent of executives saying it would be important to their organizations within the next three years.

But within Canada, most companies have been a little slower to bring data analysis into their ways of doing business, says Jane Griffin, managing director of Deloitte Analytics. She says there are a few factors that make Canada less data-friendly than other countries.

“[The survey] shows there was a slower adoption. One, because of the fiscal conservative nature of Canada, and the other is the rate of growth and productivity in the market is a little bit slower than some other countries,” she says, adding in the U.S., it’s been Internet companies leading the charge in analyzing data.

But here in Canada, it’s been mostly banks and governments who are looking at data, not businesses. While Canada wasn’t as hard-hit by the financial crisis of 2008, Canadian banks want to use data to prevent anything similar happening here, Griffin says. And both the Ontario and federal governments are interested in gauging how they can use their data to deliver services to their citizens, she adds.

Still, to understand data, workers need to have the right skills and training to be able to work with the information they have. While most respondents said they felt data will play an important role in the future, 42 per cent said they’re not confident their employees have the ability to drill down into their data and understand what that means for their business.

For Nadia Amoroso, co-founder of data visualization startup DataAppeal Inc., data analytics wasn’t something she specifically studied in school. Her background is in urban design and architecture, but she began to realize data would be important for many different verticals.

“When you hear the word data, it’s not overly exciting. So right away, there’s this kind of blinder, or this kind of cover that tells you, oh, this is something boring or complex,” she says. “What we’re learning now is that if you use data to back things up, it becomes much more of a defense mechanism or something you can bring out to validate … to make decisions.”

A data visualization from Data Appeal, showing carbon dioxide levels along Toronto's Don Valley Parkway.
A data visualization from Data Appeal, showing carbon dioxide levels along Toronto’s Don Valley Parkway.

Her company, DataAppeal, allows a user to upload data files containing addresses and numerical values assigned to those addresses – for example, the number of people visiting a store. DataAppeal then renders those values into a 3D model on Google Earth, showing different shapes on a map to illustrate the meaning of the user’s data.

Now, when she hires new employees in data visualization, she looks for individuals who can not only analyze numbers, but can also creatively present them. Those people should also be able to identify only relevant data, filtering out “unclean” data that is either useless or that inaccurately skews results.

“I’m looking for someone that isn’t just a black-and-white scientist,” she says. “A data scientist should [have] the logic behind it, to understand the information. But at the same time, it’s somebody who can help communicate the story and tell the story. And also somebody who is creative and can convey that information in a much more poetic way.”

Universities are starting to respond to this need by offering more data-related courses, says Glenn Smith, program director of the Database project at Communitech, the hub for commercializing technology in Waterloo, Ont. The Database program collects data from the government, academia, and businesses to find new applications for data analytics.

Smith points to many of the program’s partners, like McMaster University, the University of Waterloo, and York University, all of which are analyzing data and finding applications for it. Plus, there’s no shortage of Canadian talent in math, engineering, and computer science, which are all fields that develop the skill sets required to analyze data, he says.

Smith says he’s not sure that Canada is less interested in data analysis. Rather, as data has become more and more accessible, more people seem to be paying attention to it.

“The Web is the great equalizer. It gives people access to data that they hadn’t had access to before,” Smith says. “[Companies] need to understand how data impacts their business, and what actions they should be taking in light of that understanding. So to me, that’s where it starts.”

Griffin agrees, adding small businesses can also make use of data, as long as they know what they’re looking for. She calls that “identifying the crunchy question.”

“Make sure that the questions you’re asking and using analytics for, are very specific and that you can tie a return on investment to the question,” she says. “For example, how do we target clients and get a higher acceptance rate from our clients with our new product?”

Griffin says small businesses can turn to outside consultants, like Deloitte, which offers managed analytics services. They can also test the waters by doing a pilot phase, seeing if the company they’ve hired to do their data analysis is able to answer their question.

No matter what solution businesses choose, Griffin says it’s clear no one can afford to ignore data in making decisions.

“[Executives] have become accustomed to using Google to answer any question, and they want to do the same from a business perspective,” she says. “It’s no longer acceptable to wait til the end of the month or 10 days past the end of the month to understand what my financial results are … Customers expect the same.”

Watch Deloitte’s video on data analysis here, featuring Tom Davenport, the interviewer for its survey and a visiting professor at Harvard Business School.

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  • http://businesscash.com/ KerryJ

    Workers must focus on how to plan, carry out and communicate analysis of real data sets. And finding the right data to solve such problems.