Transitioning to an Analytics-Driven Big Data Strategy

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The combination of big data and analytics offers company executives and managers new ways of visualizing information and pinpointing business trends that haven’t been possible in the past.

strategyFor instance, machine data that’s gathered from a factory floor can reveal whether a change in vibration patterns or operating temperature might be a precursor to a breakdown.

Similarly, visualization tools can help retail executives identify an uptick in sales for a particular product or style of clothing in a geographic market so they can act quickly on those insights to ensure that inventory levels are maintained.

Of course, these are ideal use cases for big data and analytics software.

In fact, managers and employees have become so accustomed to using daily, weekly, and monthly reports that they don’t want to give them up, even if analytics enable them to obtain deeper insights into business and customer trends, according to a blog post by Mary Shacklett.

As Shacklett fairly points out, there is value in using reports and companies shouldn’t be so hasty to toss them aside. A better approach is a hybrid model where the use of reports and analytics can enable senior management to capitalize on current and future knowledge requirements, she says.

This starts with weaning executives and managers from their reports and demonstrating to them how using analytics can be blended in to create new opportunities for more comprehensive and relevant decision making.

One way to help sell senior management on a hybrid approach is by explaining that using real-time data – something not possible with weekly or even daily reports – can be critical for time-sensitive decision making, such as accelerating time to market.

Research reveals that world-class automotive companies can use data and analytics to bring new products to market in about 10 months versus 35 months for the average automaker. If a company can obtain a two-year lead in the market on its competitors, that’s a pretty convincing argument for melding analytics with reports for senior management.

Reports also rarely contain the nuggets of valuable information that senior executives can glean from analytics visualization tools. The need for data visualization is growing as companies are being deluged by data, notes John Sviokla in a Harvard Business Review post.

Sviokla points to three primary benefits of the “superior graphic representation” of data:

  • Great visualizations are efficient – they enable people to look at vast quantities of data quickly.
  • Visualizations can help an analyst or a group gain more insight into the nature of a problem and discover new understanding.
  • A great visualization can help create a shared view of a situation for a team of decision makers and align management on required actions.

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