Key Findings of the 3rd Annual Supply Chain Data Quality and Data Governance Study

di Vishal Patel

As more procurement and supply chain processes become digitized, the importance of high quality, well managed data will skyrocket. With the rise of automation transitioning more operational heavy lifting into the realm of computers, data becomes the only viable mechanism for monitoring and improvement.

Data quality and governance therefore hold two-fold importance in this new digital supply chain world:

• The quality of the data driving analytics and business decision making determines the ultimate applicability and success of those decisions.
• The quality of the data resulting from digitized processes impacts leadership’s confidence in it and can be the difference between a strategically opportunistic judgement call and a dismissal of evidence that conditions are turning in such a way that renders previously laid plans irrelevant.

For the last three years, the Supply Chain Resource Cooperative (SCRC) at N. C. State University has conducted a Supply Chain Data Quality and Data Governance Study.

In the recently released 2019 report, there were a few key findings that offer particularly strong insight for leaders looking to strengthen their data quality and understand how they compare to other companies on the same journey.

Key finding #1: Data Quality is Improving

68% of the respondents in 2019 indicated that their data quality is either fair (40%) or good (28%). This is a significant movement from 2018, when 31% reported that their data was fair and 13% good, for a total of 44%.
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While this benchmark is moving in the right direction, it is notable that the percentage of respondents with good and fair data actually fell from 2017 to 2018, potentially indicating a learning curve with regard to the actual current state of data as well as the true standard of quality that needs to be met and upheld in order for it to be trusted and actionable.

Key finding #2: Data is Becoming More Actionable

In 2019, 32% of respondents report that they are able to use data once they locate it (another growing challenge as the volume of available data swells), up from 15% in 2018. The inverse of this is also notable, with 68% of respondents either saying their available data is not “clean” or actionable, or not responding to the question at all.
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The fact that over two-thirds of survey participants still say data is not usable is disconcerting, but it is a significant improvement of the 85% of respondents in the same position in 2018.

Key finding #3: Governance is a High Priority

The source of data quality is not necessarily the volume and rate with which new information becomes available. Instead, the issue appears to be more foundational than that.

When asked which areas of digital complexity pose the biggest problem, 60% of companies indicated “Poor master data quality, standardization, and governance”.
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While master data quality and standardization may be issues that predate a supply chain organization’s current focus, governance is well within their scope of responsibility. Companies can expect the emphasis on (and measurement of) governance to increase in the year ahead.

Just as the issue of data quality extends far beyond creating quality data for its own sake, the solution to the issues illuminated by this study extends to the far corners of the enterprise and beyond. This year’s respondents indicated that the top two business reasons for data quality issues are (1.) a lack of enterprise-wide standards and (2.) disconnected systems.

The solution therefore lies predominantly in how technology is applied to both support supply chain operations and track their progress. Having a cohesive, centralized approach to data management will reduce the fragmentation of systems and the data produced by them.

It will serve as the genesis of a fortuitous cycle: as data quality increases, so will leadership’s reliance upon it and the enterprise’s investment in it.