Data stewardship is the management and oversight of an organization’s data assets according to established data governance practices. Data lifecycle management is crucial in data stewardship programs, ensuring data quality, consistency, and accessibility across various roles to facilitate data-driven decision making. Selected business users ensure that the organization has high-quality data that is accessible to the right users at the right times for the right purposes.
While the data governance function focuses on the development of policies and standards for the management of data and information according to data management best practices, the data stewardship function implements these policies and ensures that the standards are followed at business unit and operational levels. Data stewardship focuses on the practical aspects of managing and implementing data policies. A data steward acts as a liaison between the IT department and their business unit in an organization, showing the link to the classic definition of the word “steward “: a person who is responsible for managing something on behalf of someone else.
Some organizations have created a formal full-time role “Data Steward” and assigned staff to various business domains to serve in that position. Other organizations have selected their data stewards from staff who remain in their current position (Claims Analyst, Lead Underwriter, Senior Financial Analyst, etc.) and given them the additional responsibilities of business data stewardship. Regardless of the approach used, data stewards implement the policies and standards created by the data governance organization, assess the level of quality for critical data in their assigned domain, create and enhance the business definitions for data in their domain, and serve as the resident expert for data-related issues in that area, effectively managing the organization’s data assets.
What is Data Stewardship?
Data stewardship is the practice of overseeing and managing an organization’s data assets to ensure they are accurate, complete, consistent, and secure throughout their lifecycle. It involves a set of roles, responsibilities, and processes designed to support the organizational strategy through a robust data governance program. Data stewardship encompasses various aspects of data management, including data quality, data security, data compliance, and data governance.
The primary objective of data stewardship is to ensure the quality and fitness for purpose of the organization’s data assets. This is critical for making informed business decisions and driving everyday activities. By implementing effective data stewardship practices, organizations can maintain high standards of data quality, ensuring that their data is reliable and valuable for operational and strategic purposes.
Data Steward Description
A data steward is a person who is responsible for the fitness of data and its context (content and metadata) of critical data elements in a specific domain for an organization. Data stewards use data quality tools to maintain data accuracy and adherence to standards.
A data steward should be a senior professional in the organization and in the subject area/domain who understands the organization’s business and has some education in data management concepts . The candidate should be able to recommend solutions to data challenges and achieve compromises that enhance the use and management of the organization’s data. Specific competencies include subject area knowledge, peer respect, data management knowledge (can be acquired through training ), analysis skills, and communication. Since many data domains cross organizational boundaries, good data stewards must possess superior teamwork skills and the ability to see past the confines of their specific unit needs to the enterprise’s requirements.
Data stewardship responsibilities encompass various data management activities beyond just governance tasks. These responsibilities include defining and communicating data standards, ensuring data quality, and collaborating with stakeholders. Effective data stewardship requires qualifications such as strong analytical skills, excellent communication, and a deep understanding of data management principles.
Although the accepted wisdom, and research by EWSolutions , indicates the best data stewards come from the business units, in many organizations the staff who know the data best originate in Information Technology departments. Some organizations start their data stewardship programs with IT-focused data stewards and train business unit staff members to assume the role; other organizations believe that starting the data steward function in the business areas is the best route. This is a cultural issue, and each organization must determine how it will approach data stewardship according to its culture while respecting the validity of the industry best practices and the need for sustainability of the data stewardship function.
Role of Data Governance in Data Stewardship
Some organizations believe that there is no need to establish a data governance function before or at the same time as the data stewardship initiative. This is contrary to industry best practices and has been shown to be a main reason for failure for many data stewardship programs. Data governance is the central component in enterprise data management. It is the practice that provides planning, oversight, and control over management of data and the use of data and data-related resources, development and implementation of policies and decision rights over the use of data.
Enterprise data governance initiatives are crucial in guiding data usage and security policies, ensuring effective communication between IT and business sectors, and facilitating risk management.
Data governance creates the policies and standards that data stewardship implements, and data governance oversees and guides the enforcement of the data stewardship activities. Without data governance, data stewardship would have no policies or standards to implement across the organization, each unit would develop and deploy its own ways of operation. This is a recipe for anarchy in the implementation of a data stewardship function, since the lack of the enterprise oversight provided by the data governance organization allows the data stewards to focus on their tactical responsibilities unhampered by the need to develop enterprise policies and standards and manage their enforcement.
Data Steward Responsibilities for Data Quality
Data stewards can have a variety of responsibilities, depending on the organization’s approach to enterprise data management and data governance. The most common responsibilities for data stewards usually include:
Data Management – Establish and maintain data quality and integrity through the following, in accordance with the policies and procedures laid out by the data governance management.
Data validation and profiling (in conjunction with data quality team)
Business rule conformance and data model validation
Data exception resolution
Data quality improvement projects – Collaborate with data professionals to ensure adherence to data standards and enhance the quality of business data.
Data quality metrics – Essential for maintaining accurate and consistent data within organizations.
Business Metadata Management – Serve as subject matter experts (SMEs) to answer metadata requests (access and interpretation) for business metadata from the data governance specialists and other requestors.
Data Definition Management – Develop, enhance, manage, and explain the business data definitions in the data steward’s domain.
Data Stakeholder and Owner Identification – Identify the stakeholder(s) and owner(s) of data management and the implementation of data-oriented policies by stakeholders.
Data Usage and Access Management – Oversee data access and ensure usage policies are understood and approved, in conjunction with other teams (e.g., data security, information architecture, etc.)
Data Policies Violation Management – Resolve violation of data governance policies and help teams across the enterprise take appropriate corrective action, document and communicate decisions to ensure that policies are followed in future.
Data Change Management – Manage changes to data definitions, usage, access, policies, and administration in compliance with Data Governance standards and practices.
Benefits of Data Stewardship
Data stewardship offers numerous benefits to organizations, enhancing various aspects of data management and governance. Some of the key benefits include:
Improved Data Quality : Data stewardship ensures that data is accurate, complete, and consistent, which is essential for making informed business decisions. High-quality data reduces errors and enhances the reliability of business insights.Increased Data Security : By ensuring that sensitive data is protected and accessed only by authorized personnel, data stewardship reduces the risk of data breaches and cyber-attacks, safeguarding the organization’s data assets.Better Data Governance : Data stewardship establishes policies and procedures for data management, ensuring that data is collected, stored, and used in accordance with regulatory requirements. This enhances the overall governance framework of the organization.Improved Data Integration : Data stewardship ensures that data is consistent and compatible across different systems and applications, enabling seamless data integration and data exchange. This facilitates better collaboration and data sharing across the organization.Enhanced Data Analytics : With high-quality data available for analysis, data stewardship enables organizations to gain valuable insights and make data-driven decisions. This can lead to improved operational efficiency and strategic planning.Improved Data Sharing : Data stewardship ensures that data is accessible and usable by authorized personnel, enabling collaboration and data sharing across different departments and teams. This fosters a data-driven culture within the organization.Improved Data Compliance : By ensuring that data is collected, stored, and used in accordance with regulatory requirements, data stewardship reduces the risk of non-compliance and associated penalties. This is crucial for maintaining the organization’s reputation and avoiding legal issues.
Challenges to Data Stewardship
Despite its numerous benefits, data stewardship faces several challenges that organizations must address to ensure its success. Some of the key challenges include:
Lack of Resources : Data stewardship requires significant resources, including personnel, technology, and budget. Organizations with limited resources may find it challenging to allocate the necessary support for effective data stewardship.Limited Expertise : Data stewardship requires specialized skills and expertise, which can be difficult to find and retain. Organizations need to invest in training and development to build a competent data stewardship team.Resistance to Change : Implementing data stewardship often requires changes to existing processes and procedures. This can be met with resistance from employees and stakeholders who are accustomed to the current ways of working.Insufficient Training : Ongoing training and education are essential to ensure that data stewards have the necessary skills and knowledge to perform their roles effectively. Without adequate training, data stewards may struggle to fulfill their responsibilities.Complexity of Data : Managing complex and diverse data sets can be challenging. Data stewardship involves overseeing various types of data, each with its own unique requirements and challenges.Evolving Regulatory Requirements : Data stewardship must keep pace with evolving regulatory requirements, which can be challenging and time-consuming. Organizations need to stay updated with the latest regulations to ensure compliance.
Overall, data stewardship is a critical component of an organization’s data management strategy. Despite the challenges, the benefits of implementing effective data stewardship practices far outweigh the difficulties. By addressing these challenges proactively, organizations can ensure the quality and integrity of their data assets, which is essential for making informed business decisions and driving everyday activities.
Critical Success Factors for Data Stewardship
There are many factors that influence the success or failure of a data stewardship initiative. Some of them include:
Lack of enterprise data management – Organizations that do not have an enterprise data management function that is responsible for coordinating the various data management disciplines (data governance, master data management, metadata management, data quality, enterprise data architecture, etc.) will not be able to provide guidance to a data stewardship effort on the implementation of these components. As a result, any efforts to improve the value of data based on better metadata, higher data quality, organized master data, etc., will be unsuccessful, based on numerous studies.
Lack of enterprise data governance – Data governance is the function that develops the organization’s policies and standards for data and oversees their implementation by data stewards. Without a functioning enterprise data governance program based on industry best practices, any data stewardship effort will be forced to create its own policies, develop its own standards and attempt to implement them without the authority that is granted to program led by experienced data governance professionals. A lack of enterprise data governance has been shown to be one of the major factors in data stewardship failures.
Corporate culture – A culture that does not embrace the enterprise nature of data stewardship can derail the effort before it starts. Many stewardship initiatives fail to gain the attention they need or the momentum they deserve because they do not have executive sponsorship or senior management support. Reduced funding for enterprise initiatives or a project-based funding model that does not fund any enterprise programs, concerns with resource allocation and capabilities, and a lack of connection to the business goals are some of the reasons there may be resistance to sponsorship for data stewardship (and data management in general). In many organizations, it is essential to have at least one advocate – preferably an executive with vision and organizational authority – to ensure that data stewardship has is a sustained program across the enterprise.
Lack of defined roles and responsibilities for data stewards – Organizations that simply assign data stewardship tasks to certain staff members without clearly defining the role and explaining the specific responsibilities of a data steward see poor results from those efforts, according to many researchers. Additionally, those companies that do not invest in training designed for data stewards (foundations of data management, concepts of data governance, task-focused training in data definitions and data quality activities) do not realize the sustained benefits from a data stewardship program that trained data stewards provide. Lack of measurements and metrics for data stewards’ success – Measurement is the clearest, simplest way to demonstrate the success of data stewardship. All activities of data stewards should be aligned with specific metrics and should be measured regularly. Example: “Claims data stewards will define all 30 critical data elements (from enterprise data model) by xx/xx/xxxxx. Data quality for the 10 most critical calculations (as defined by the Claims BI team) will be reduced by 10% within the calendar year due to the regular profiling performed by the Claims data stewards.”
In conclusion, the function of data stewardship is an essential component of any organization’s enterprise data management initiative, bringing a formal responsibility for ensuring high quality data is available through standard processes. This high-quality data will enable effective operations and decision making that can result in a competitive advantage, avoid errors that can trigger regulation violations, improve revenues, raise profits and reduce costs. Organizations of every size, in every industry, can benefit from the implementation of a data stewardship program as part of enterprise data governance within an enterprise data management initiative.
