In Data We Trust (Most of the Time)
There’s only one measure of the success of a data-driven organization, one which can make it break it – and that is trust.
Trust is the glue that holds enterprises together. It is the asset that will never age. It is the commodity that will never be commoditized. If decision-makers trust the data they are receiving, you are truly on the way to becoming data driven.
Unfortunately, there is still a sizeable trust gap within today’s enterprises, a recent survey finds, especially when it comes to Data Quality. On average, organizations around the globe believe that 27 percent of their current customer and prospect data is inaccurate.
That’s the word from the Experian Data Quality benchmark report, which surveyed more than 1,400 executives across the globe. While the report author is in the data quality business (and therefore, has a horse in this race) it’s telling that so many executives admitted to having reservations about their organizations’ data.
At this point, less than half of the executives (44%) trust their data enough to make important business decisions, the survey shows. A majority, 52%, still rely on gut feelings, and same percentage even admit that a lack of confidence “in data contributes to an increased threat of non-compliance and regulatory penalties, and consequently, a downturn in customer loyalty.”
The higher you go in the organization, the more skepticism you will find about the validity of data. The aforementioned study found that C-level executives have a higher degree of distrust in their data than those in other roles. On average, they believe that 33 percent of their organizations’ data is inaccurate. At the same time, lack of support from upper management holds back data quality improvement efforts, the survey report’s authors observe. “We believe that although senior leadership conceptually understands the value of good data, the lack of a solid data strategy delays executives from making long-term investments in that area.”
There is good reason to move forward with data quality efforts.
The majority of organizations globally say that they have seen benefits across many areas of their businesses, including increased revenues, employee efficiency, and improved personalization and targeted marketing. For starters, 85% of enterprises said they saw more timely and personalized customer communications as a result of improving data quality . Another 83% say they have seen some improvement in employee efficiency after implementing a data quality solution, and 82% say that they have seen some progress when it comes to revenue growth.