February 24, 2017
Three essential principles for the data-powered enterprise
By: Narendra Mulani

Focus on outcomes, be selective and accept imperfection

The data-powered enterprise integrates analytics and data to generate tangible outcomes by organizing and curating data, and translating it into valuable insights. However, making sense of the millions and billions of data records at your disposal takes discipline, focus and flexibility. The ability to manage data is a critical part of a larger data-powered enterprise strategy that helps companies draw the right insights and unlock their most sought-after business outcomes—from developing new products to earning customer loyalty.

There are three essential principles companies should embrace to make the journey from data

to insights smoother and maximize their internal and external results.

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1. Think outcomes first

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It may seem obvious, but setting your business goals before you start is an important element of the successful data-powered enterprise. Keeping the desired end results in mind better informs the data you need to achieve them.

Forward-thinking companies that calibrate data strategies to business goals manage analytics from a “master data” perspective. Their data management architecture connects insights to actions through optimal use of the right tools and enablers.

2. Don’t boil the ocean

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Extracting data to meet your business targets doesn’t mean you have to grab every piece of information available. On the contrary, the art of analytics is in being selective about what you need and extracting the right data. Collecting petabytes of data for data’s sake significantly reduces efficiency and defeats the purpose of analytics.

The companies that get analytics right take a highly pragmatic approach to data collection. They first spend time strategizing about what they want to use the data for and then invest in achieving those outcomes economically. They systematically build use cases. They focus on iterating and continuously evolving their approach. And they understand that they don’t necessarily need a massive database to achieve these results.

3. Perfection is not the objective

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With data, as with most business disciplines, perfectionism can be an obstacle. Trying to get your technology, processes and data quality perfectly aligned will result in a long waiting period. Making them fit for purpose to drive the right outcomes is an important step in becoming a data-powered organization.

Companies that manage data well have mastered the tricky area of the hybrid world. They’re handling their legacy data architectures with as much acumen as they do their new architectures—constructs based on big data technologies. They ensure that their legacy enterprise applications, can seamlessly integrate with newer analytics tools.

There is no “once and done” approach to data management. Iteration and flexibility are the best way to cope with continually evolving business processes and technology. At the same time, however, it’s not critical to stay neck and neck with the latest technology. Instead, find the investment stride for technology that’s right for your business.

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