What is a key activity to maintain data accuracy in SCM analytics?

• A. Conduct random data validation
• B. Do nothing; data will self-correct
• C. Rely solely on manual spreadsheets
• D. Implement data governance and cleaning

Answer: (D)

Maintaining data accuracy in SCM analytics hinges on data governance plus data cleaning. Data governance establishes the rules, standards, and responsibilities for data across the supply chain—who can modify data, which definitions to apply, and how data quality will be measured. Data cleaning then enforces those standards by detecting and correcting errors, duplicates, missing values, and inconsistencies during data integration and processing. This combination creates a repeatable, scalable process for preserving data quality as data flows from multiple sources like ERP, WMS, and TMS, and over time, which is essential for reliable analytics and informed decision-making. Other approaches such as random validation, relying on spreadsheets, or doing nothing lack the ongoing policy, standardization, and automation needed to sustain accuracy.