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Inside the circle of trust: Data management for modern enterprises

There’s a lot on the line when it comes to your data quality. From regulation to revenue, it can make or break your company. While organizations today talk a lot about making data-driven decisions, we find that many of them lack the confidence in the quality of their data necessary to drive new initiatives. Given that C-level executives believe that 33 percent of their organizations’ data is inaccurate, it’s easy to understand why. Do you fully trust your data to make important decisions?

For 2017, we’ve conducted our annual survey of more than 1,400 data management professionals from around the globe to understand how data is being used within organizations and how the quality of that data impacts their business priorities. Here’s what we learned:

Data drives business initiatives—good data, that is.

To become truly data-driven, organizations need information they can trust, and that starts with their data quality. Our study revealed that more than 95 percent of U.S. organizations say they use their data to power business opportunities. What types of opportunities are they? By and large, we find that organizations are using their data to increase revenue and to better serve their customers. In fact, more than half of organizations say that serving customers better is a primary use for their data. Additionally, businesses use their data to enhance marketing efforts, reduce risk to their organization, and uncover new streams of revenue.

The only data worth having is trusted.

While most organizations around the globe say that data supports their business objectives, less than half of organizations globally (44%) trust their data to make important business decisions. To that end, our study revealed that 52 percent of organizations say that they rely on educated guesses or gut feelings to make decisions based on their data. This guesswork contributes to an increase in risk to the organization. More than half of organizations globally say that a lack of trust in their data contributes to increased risk of regulatory and non-compliance penalties.

Managing data requires strategic planning.

How are organizations today doing with their data management practices? Our study reveals that more than one in two organizations globally believe their current data governance programs are not effective. In addition, just 18 percent of U.S. organizations have an advanced level of data quality, what we refer to as ‘optimized.’ Furthermore, just one in four organizations globally say that their data quality strategy is reviewed and maintained centrally by a single director.

While organizations acknowledge that data quality is an issue, an inability to form a data strategy around quantifiable business impacts is preventing them from doing anything about it. Silos between departments as they compete for ownership of data assets only makes the problem worse. The solution? A centralized data role, such as a CDO or CIO, should bridge the gap between business and IT to establish a data quality strategy that empowers business intelligence while upholding data governance.

Data quality investments do pay off.

We find that organizations see positive results when they make improvements to their data. Our study revealed a vast majority of organizations (85%) globally experienced more timely and personalized customer communications as a result of improving their data quality solution. Additionally, another 83 percent of organizations globally say that they have seen some improvement in employee efficiency after implementing a data quality solution, and another 82 percent say that they have seen some progress when it comes to revenue growth.

What data management projects can we expect in 2017?

Looking toward the year ahead, organizations around the globe have big plans for their data programs. Thirty-three percent of those we surveyed say they are planning a data cleansing project in the next 12 months. Other types of data management projects include:

  • Data integration
  • Data migration
  • Data preparation
  • Data enrichment
  • Data analytics

By providing clarity for those embarking on data management programs as well as tips for improving existing programs, we hope to enable organizations to tackle their major data priorities in the upcoming year. For more data management stats and trends, read the 2017 global data management benchmark report.

Download the report

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