How To Use Data To Outsmart Your Competitors - InformationWeek

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Data Management // Big Data Analytics
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7/2/2015
11:06 AM
Lisa Morgan
Lisa Morgan
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How To Use Data To Outsmart Your Competitors

The pressure's on to use data to outsmart your competitors. Here are six ways companies can use data to imagine and even re-imagine what's possible.
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Understand What Data Assets You Have 
It's hard to imagine the potential of data when the scope of data assets is not understood. In some organizations, important information is still locked away in silos, or else only a few of the people who should know what data is available actually do know. Alternatively, the scope of data assets may be known, but because some or all of them are not available in a timely manner there are fewer ways to leverage those assets.

For example, a lot of companies use online surveys to learn more about their customers and prospects. Online services such as Survey Monkey allow users to create, manage, and analyze surveys. The survey data gathered by a particular company provides valuable introspective information about that company, but there is also aggregate data across companies that can be used to gauge competitive performance. Survey Monkey collects about 3 million survey responses per day, and it has been collecting data for more than a decade.

'In the past five years we've been thinking about how to use the data we collected,' said software engineering manager David Wong in an interview. 'We had to rethink how we would use that data, [but] the engineering techniques at the time weren't scalable enough [and] you'd have a latency of six months to about a year between the collection, aggregation, and generating of the benchmark product and delivery. If you're looking for immediately contextual information to make a better decision, that's slow. From our perspective, it was almost a big step to say, 'Why can't we make this available in real time?' By asking those sorts of questions, we started re-imagining what the status quo might be.'

In the future, Survey Monkey will use natural language processing (NLP) to analyze verbatim textual responses, which will enable additional capabilities. Wong said such initiatives require a combination of people -- those with data science and engineering expertise who can understand what's possible to do with data, and product-minded folks who can imagine how future surveys might differ from today's surveys.
(Image: Geralt via Pixabay)

Understand What Data Assets You Have

It's hard to imagine the potential of data when the scope of data assets is not understood. In some organizations, important information is still locked away in silos, or else only a few of the people who should know what data is available actually do know. Alternatively, the scope of data assets may be known, but because some or all of them are not available in a timely manner there are fewer ways to leverage those assets.

For example, a lot of companies use online surveys to learn more about their customers and prospects. Online services such as Survey Monkey allow users to create, manage, and analyze surveys. The survey data gathered by a particular company provides valuable introspective information about that company, but there is also aggregate data across companies that can be used to gauge competitive performance. Survey Monkey collects about 3 million survey responses per day, and it has been collecting data for more than a decade.

"In the past five years we've been thinking about how to use the data we collected," said software engineering manager David Wong in an interview. "We had to rethink how we would use that data, [but] the engineering techniques at the time weren't scalable enough [and] you'd have a latency of six months to about a year between the collection, aggregation, and generating of the benchmark product and delivery. If you're looking for immediately contextual information to make a better decision, that's slow. From our perspective, it was almost a big step to say, 'Why can't we make this available in real time?' By asking those sorts of questions, we started re-imagining what the status quo might be."

In the future, Survey Monkey will use natural language processing (NLP) to analyze verbatim textual responses, which will enable additional capabilities. Wong said such initiatives require a combination of people -- those with data science and engineering expertise who can understand what's possible to do with data, and product-minded folks who can imagine how future surveys might differ from today's surveys.

(Image: Geralt via Pixabay)

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