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Turning data quality into a high-priority business initiative

Rachel Wheeler Archive

For organizations that rely heavily on banks of consumer data - ranging from retail companies that keep tabs on their customers to government offices that provide essential public services - there's a need for high-quality data. These groups need to stay in touch with many people at once, all without their collections of contact information becoming inaccurate or outdated.

Most often, companies consider this an IT concern. The thinking is that because high-tech workers are the ones managing all of a company's data, they should also be the ones to maintain quality standards. This might not be a fair way of thinking, though. There's a growing sentiment that fixing companies' data quality standards should be a company-wide pursuit, not merely a job for the IT department.

Creating a business context
The temptation when working with data is to dump all the responsibilities on the IT office, letting the technicians handle the nitty-gritty work. But that might not be the best way to go, according to the Sunday Telegraph. Amit Shah of Guidewire Software explains that other departments might be better informed about how to put data in the proper perspective.

"While IT is often tasked with driving data initiatives, it neither creates the data nor uses it in a business context," Shah explained. "IT should be responsible for storing the data and providing the mechanisms to get it safely into business intelligence and analytics applications. As only the business actually creates, uses and understands the data, it is crucial that it must have a significant ownership in the process of validating the data that will fuel the company."

Marketing, sales and customer service teams might have a better idea than IT about what exactly makes data important. These specialists have the proper perspective on how to keep data relevant to their everyday operations.

Changing the approach
This adjusted focus on data quality requires a lot of fundamental changes to a business. For example, everyone needs to have a shared focus on data stewardship. This should happen early on - even if only IT has technical "ownership" of a cluster of data, everyone should be willing to contribute opinions on how to maintain its quality.

Above all other goals, companies should strive to get everyone on the same page. If employees across all departments are willing to collaborate to meet their many goals, then success likely lies ahead for their data-driven plans.

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