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Bridging the Trust Gap of Data

How can analytics companies get clients to trust data

The art of data science is the coupling of mature discipline of statistics and computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data.

Knee-jerk, emotional and subjective decision-making has been replaced by objective, data-driven insights that allow organizations to better serve customers, drive operational efficiencies and manage risks.

However, despite the recent surging success of data science, there still remains a trust gap between analytic companies and clients.

Despite the frequent declarations from executives about developing data-driven processes with analytics, only one third of decision-makers actually trust their analytics, according to a survey conducted by Forrester Consulting on behalf of KPMG, titled “Building Trust in Analytics.”

Seventy percent of organizations agreed that by using data and analytics, they exposed themselves to reputational risk (e.g. data breaches, mis-selling of products and services)….

This gap between the outward belief in the power of analytics, and the lack of confidence in analytics held by executives, represents a potential problem, especially as investments in big data analytics continues to ramp up.

How do analytics companies bridge this gap?

Well, according to John Landsman, director of strategy and analytics at eDataSource, the answer is in the access and value of the information.

Read the full article in DMNews for more insight into building trust in data.

“Trust will continue to improve, but that will be driven, in part, by the increasing sophistication of marketing managers on the client side who will continually challenge the derivation, validity and actionability of data they’re buying,” said Landsman. “To stay in business, data vendors must rise to those challenges.”