Data governance in the manufacturing industry can be particularly challenging due to the complexity of the data used. Manufacturing processes across the value chain require structured and unstructured datasets from different sources in different formats and volumes. These distinct sources are often siloed systems not designed to share data. This creates organizational problems that can hinder effective data implementation. Moreover, sourcing multi-format data from multiple outlets introduces security and storage concerns for the manufacturing industry.
Collected data is only valuable if effectively used in decision-making and operational analysis. The quality of data collection and management directly affects any data-driven output's quality. Manual data entry, data silos, and collection from disparate data sources are all prevalent practices in the manufacturing industry that limit the quality, and thus the usability, of collected data. As such, companies must rectify these practices to ensure that their data is accurate, up-to-date, and complete.
As manufacturing relies increasingly on digital tools, companies face new concerns regarding malicious activities from external and internal actors. Organizations must prevent unauthorized access and manipulation of their data to protect sensitive information and intellectual property. However, if their data is not readily accessible, operations will suffer setbacks. Therefore, balancing data agility with data security is a top priority for this industry.
Determine who will be accountable for managing and maintaining the data. This can include roles like data stewards, owners, and custodians. It's essential to have clear roles and responsibilities defined for each of these roles to ensure accountability for data management.
Establish organizational policies and guidelines for data use, storage, and management. This includes data retention policies, data privacy policies, data access policies, and data security policies. It also includes policies related to data sharing with vendors, distributors, dealers, B2B or B2C commerce sites, and manufacturers’ reps. The policies may also include direct guidance on sources of truth for data related to finance, inventory, bills of material, engineering specifications, etc.
Develop a data classification scheme to identify the most critical data to the organization and assign appropriate levels of protection, access, and retention based on the classification.
Develop processes and procedures to ensure data quality, including data cleansing, data validation, and data reconciliation.
Define processes for exposing data from disparate sources into an enterprise data lake. The data lake, different from a data warehouse is a repository for storing and organizing data that becomes most valuable when combined with other sources or new business use cases. This includes identifying and cataloging data sources, defining data mapping rules, and establishing data staging, transformation, and loading procedures.
Establish a data governance committee to oversee the data governance program, provide guidance, and make decisions about data management policies and procedures.
Train employees on data governance policies and procedures, as well as the importance of data quality, security, and privacy.
Establish real-time, automated processes for monitoring data usage and quality. Traditional methods of periodic audits are essential to provide oversight; however, realizing the benefit of fast-moving data requires that anomalies and errors are discovered and remediated quickly.
Ensure the data governance program complies with relevant regulations and industry standards, such as GDPR, CCPA, HIPAA, and ISO 27001.
Storm Reply’s Data Governance Solutions are based on defining data management processes and practices tied to technologies that produce the highest quality, most secure data possible. The firm’s thorough understanding of the digital data landscape assures manufacturers that they get the most value from their data. Storm Reply has built data solutions for many of the world’s largest organizations and can help manufacturing companies reap the benefits of secure, well-managed data.
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