Data quality, governance are challenges for procurement: research

Only 20 percent of organizations are implementing an improvement program

July 10, 2017
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CHICAGO—Despite having access to more information and analytics than ever before, poor data quality is crippling procurement performance, according to the First Annual Procurement Data Governance Survey, released by BravoSolution, a strategic procurement solution provider, and North Carolina State’s Supply Chain Resource Cooperative (SCRC).

This study is first in a series of research projects designed to uncover the current and future state of data governance within the procurement function and the role good governance plays in advanced analytics.

“The report highlights the importance of data quality and governance mechanisms that organizations can put in place to achieve value,” said Robert Handfield, executive director of SCRC at North Carolina State University. “The results of the First Annual Procurement Data Governance Survey emphasize that for organizations seeking to harness the power of analytics, investment in data governance is a foundational requirement for procurement.”

BravoSolution and SCRC surveyed 70 procurement leaders and found that for almost two-thirds of organizations, bad data quality is the primary cause for less than optimum procurement decisions. The research also showed that although poor data is a significant industry issue, only 20 percent of organizations are currently implementing an improvement program.

“Procurement is no exception to the big data movement. Advanced analytics is the key to unlocking procurement performance. They provide the only way to gain true strategic insights that create the business case for action and leads to supply initiatives that capture opportunities for reduced cost and increased value,” said Andrea Brody, chief marketing officer at BravoSolution. “Data should drive, not inhibit, confident decision-making. If procurement teams can’t rely on what the numbers show, it makes digital strategy and transformation virtually impossible.”

When asked to rank data quality priorities, 58 percent of respondents said accuracy was the biggest concern, followed by valid data (18 percent), complete data (11 percent), unique data (11 percent) and timely data (11 percent).