Describing data stewards as the “firefighters” of PLM (product lifecycle management) or other digital transformation initiatives might be overstating their role; nevertheless, they certainly play a crucial role in the success of such initiatives.
Driving successful PLM initiatives includes carefully managing interdependencies across solution design and customization, user education, data migration, technical platform integrations, process optimization, capability deployment, and user adoption. Critical success factors includes:
- Executive ”active” sponsorship to contribute to business transformation (as opposed to ”passive” engagement limited to vision definition).
- Clear business ownership (process and data) to drive improvement roadmap, change impact assessment, pragmatic implementation and transition from AS IS to TO BE solutions.
- Committed key users and data stewards (business-led) to contribute to data readiness, process verification and validation across the relevant personas, including clear management of technical and data interdependencies.
- Knowledgeable data custodians (technically-led) to drive how data models, data flows, and technical architecture come together in a cohesive ecosystem.
Data stewards are expected to be the gatekeepers of data quality control and process improvement
Data governance refers to the management and control of data within an organization. It involves establishing policies, processes, and procedures to ensure that data is accurate, consistent, secure, and used appropriately to support organizational goals and objectives.
Several definitions reinforce the importance of quality and traceable “data-driven decisions” enabled by data governance:
Data governance is the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.
Source: DAMA International
Data governance is the specification of decision rights and accountability framework to ensure the appropriate behavior in the valuation, creation, consumption, and control of data and analytics.
Source: Gartner
Data governance is the framework for managing data quality: a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.
Source: Data Governance Institute
Think of data governance as a set of rules and guidelines that govern how data is managed, accessed, and used throughout its lifecycle. It involves defining roles and responsibilities for data management, establishing standards for data quality and integrity, and implementing controls to protect sensitive information from unauthorized access or misuse. Overall, data governance is about establishing a framework for managing data effectively, ensuring its quality, integrity, and security, and maximizing its value to the organization. It helps organizations make informed decisions, improve operational efficiency, mitigate risks, and maintain regulatory compliance.
Data stewards and data custodians are the gatekeepers of quality control and process improvement
Data stewards and data custodians are both responsible for managing and ensuring the quality, security, and usability of data within an organization, but they have different roles and responsibilities.
Data stewards drive dow data is authored and consumed (in business terms = end-user perspective):
- Data stewards are typically business-focused roles responsible for defining and implementing data governance policies, standards, and procedures.
- They ensure that data meets business requirements, aligns with organizational goals, and complies with regulatory requirements.
- Data stewards often collaborate with business stakeholders to understand data needs, define data definitions and classifications, and establish data quality metrics.
- They play a key role in data governance by defining data ownership, access controls, and data usage policies.
- Data stewards are responsible for resolving data-related issues, driving business health insights, addressing data quality issues, and providing guidance on data management best practices.
Data custodians drive how data is managed / maintained (in technical terms = IT perspective)
- Data custodians are typically IT-focused roles responsible for implementing and managing technical aspects of data management, such as data model architecture, storage, security, access controls, and interfaces.
- They are responsible for implementing and maintaining data infrastructure, databases, and data management systems.
- Data custodians ensure that data is securely stored, backed up, and protected from unauthorized access, loss, or corruption.
- They implement data security measures, such as encryption, authentication, and access controls, to protect sensitive data from unauthorized access or breaches.
- Data custodians may also be responsible for data integration, data migration, and data archival processes.
Every PLM and other digital transformation initiatives require elements of firefighting towards successful deployment
As a matter of fact, these initiatives often encounter unforeseen challenges, resistance to change, vendor challenges, and technical issues that require immediate resolution to ensure smooth implementation and user acceptance. Whether addressing data quality issues, resolving technical glitches, providing user training, or adapting to evolving business needs, proactive firefighting efforts are crucial for overcoming obstacles and maintaining momentum towards achieving the desired outcomes of the initiative.
By effectively managing, and sometimes proactively anticipating, firefighting activities and leveraging lessons learned to refine processes and strategies, organizations can enhance their agility, resilience, and ultimately, the success of their PLM and digital transformation efforts. It implies connecting the relevant data sets and continuously driving for process improvement and effective business insights.
While data stewards and data custodians have distinct roles and responsibilities, they often collaborate closely to ensure that data is effectively managed, secured, and utilized to support organizational objectives. Effective communication and collaboration between data stewards and data custodians are essential for establishing robust data governance practices and ensuring the integrity and reliability of organizational data.
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