Unlock Executive Buy-in for Data Stewardship

Executive Summary

This webinar emphasises the critical role of Data Stewardship in enhancing business performance and compliance. It highlights the necessity for executive engagement in fostering a culture of accountability and effective Data Governance. Howard Diesel addresses common challenges, such as passive resistance from business executives, and the importance of Data Management strategies in problem-solving. Additionally, the webinar covers essential topics such as Data Quality assessments, the impact of Data Stewardship on organisational compliance, and the integration of technical and business Data Management. Collectively, with these insights, Howard aims to equip leaders with the tools needed to drive impactful Data Stewardship initiatives within their organisations.

Webinar Details

Title: Unlock Executive Buy-in for Data Stewardship
Date: 26/06/2025
Presenter: Howard Diesel
Meetup Group: African Data Management Community Forum
Write-up Author: Howard Diesel

The Value of Data Stewardship in Business

Howard Diesel opens the webinar and shares his wish to conduct a poll aimed at gathering feedback regarding Data Executives. The poll’s objective is to highlight whether the attendees believe that their business executives truly understand the value of Data Stewardship. He notes that this question arose from a recent training session conducted with a customer.

Figure 1 Do your Business Execs truly understand the Value of Data Stewardship

The Need for Executive Engagement and Data Stewardship

In a recent engagement, Howard noted that it became evident that significant challenges stemmed from a lack of executive engagement and understanding of Data Stewardship issues. A heated meeting revealed that executives often dismissed problems presented by employees, advising them to bring solutions instead. Additionally, this attitude fostered passive resistance, as team members felt unsupported in addressing the stewardship challenges that often crossed political boundaries. Lastly, Howard shared an example of the present struggle for executive sponsorship, where an employee had been told to resolve issues independently without the necessary support from leadership.

Figure 2 Do your Business Execs truly understand the Value of Data Stewardship Results

Addressing Passive Resistance in Business Executives

During engagement initiatives, it is important to recognise and address passive resistance among business executives. Howard highlights that engagement can be assessed through participation levels; if executives are not actively involved, they may either be passively resisting or silently disagreeing with the initiatives. Additionally, Howard suggests that trust plays a crucial role in this dynamic and that change managers often undertake the responsibility of identifying resistance. They typically develop a resistance plan by analysing executive engagement quarterly, allowing for a structured approach to address and mitigate resistance effectively.

An attendee shared an example of an active executive who was previously driving engagement, but was replaced by someone less enthusiastic, which hindered progress despite initial training and awareness efforts. This emphasises the importance of moving beyond mere awareness to fostering desire and activation among staff, utilising the ProSci framework that involves commitment monitoring and trust-building. Additionally, successful implementation requires ensuring that communication is effective and that genuine commitment from all employees is achieved, as this is crucial for overcoming resistance and attaining program success.

Figure 3 Data Stewardship Context Setting

The Importance of Data Stewardship in Business

Data Stewardship programs often fail due to a lack of executive-level commitment, which subsequently undermines Data Governance. Effective Data Stewards, who are responsible for executing data-related tasks, cannot succeed without support from leadership. If executives do not actively engage and prioritise data initiatives, Data Stewards may feel disconnected and may not prioritise training or adequately fulfil their roles.

Howard highlighted a recent instance where the challenge of getting Data Stewards to attend training sessions reflected broader issues of commitment and support. To address these challenges, executives must take the lead in fostering a clear vision and collaboration between data and business operations, demonstrating the value of data initiatives to drive engagement and success.

Figure 4 Data Stewardship Context Setting

Figure 5 Why Data Stewardship Programs Fail

Figure 6 Why Data Stewardship Programs Fail pt.2

Figure 7 The Role of the Data Executive

Data Management and Its Impact on Organisational Performance

The “What’s in it for me” principle emphasises the challenge of demonstrating the impact of Data Stewardship in organisations. Data Stewards often struggle to convey the significance of data issues to executives, which can result in their concerns being dismissed as mere complaints. This disconnect leads to an ongoing problem where important insights fall through the cracks, and the message about the necessity of Data Management fails to reach decision-makers.

The absence of a dedicated Data Executive further complicates this issue. A potential solution lies in leveraging data effectively as a quantifiable asset, as illustrated by an example where departments share information through cumbersome PDF reports that require manual Data Extraction. This highlights the need for streamlined data communication to address existing challenges more efficiently.

This report outlines the current challenges associated with loan management and Data Extraction from PDFs, emphasising the importance of maintaining an issue log within the ITIL framework. The discussion highlights the need for a comprehensive approach that encompasses not only hardware management but also data assets, ensuring seamless integration of processes. Additionally, it emphasises the importance for executives to quickly assess the impact and quantify issues within their first 90 to 100 days in office, facilitating a better understanding and visualisation of real-world scenarios.

Figure 8 The Data Issue Log: Your Secret Weapon

Data Management for Effective Problem-Solving Strategies

The Data Issue Log on the dashboard highlights critical areas that need attention to avoid turning it into a passive tool and instead drive proactive behaviour. Currently, the three identified issues are costing the organisation approximately $603 per day, with the CFO’s scenario indicating the highest financial impact. It’s essential for executives to be aware of these issues and understand their implications in business terms; thus, quantifying the costs and transitioning from mere complaints to a focus on business impacts is vital. A sample data issue log is provided, detailing core issues and root causes, such as a lack of input validation and standardisation rules, to facilitate informed discussions and encourage executive involvement.

To effectively address business issues related to Data Management, it’s crucial to conduct a business impact assessment that highlights the estimated costs and engages executives, particularly the executive sponsor. This assessment should map data issues to relevant business processes, especially those that cross functional areas, to emphasise the collaborative support needed for resolution.

Communicating the implications in terms of cost, risk, and opportunity is essential, as is the role of Data Stewards in quantifying these impacts using established industry standards, such as the cost differences between good and bad records. Ultimately, understanding the escalating costs of unresolved data issues over time will help motivate business stakeholders to take action.

Figure 9 Data Issue Log

Figure 10 Data Issue Log Data Model

Figure 11 Data Issue Log Sample Data

Figure 12 The Business Impact Assessment

Data Quality Assessments and Cost Calculation in Business

Data Quality assessment is crucial for businesses, as demonstrated in an example involving Data Stewards managing 100,000 records. They estimated that approximately 10% of these records, or 10,000, were dirty. Consequently, the processing cost of managing these dirty records and the overall data handling amounted to an inflated total of $190,000, nearly double the expected $100,000. This disparity underscores the significant financial impact of poor Data Quality on organisations, as demonstrated by Gartner’s methodology for evaluating costs associated with data challenges within the economy.

The Impact of Data Stewardship on Compliance

To effectively leverage data, it is crucial to acknowledge the time investment required for data preparation and analysis. For instance, extracting and formatting data from a PDF can take approximately a week. Successful case studies demonstrate the impact of executive involvement in Data Governance, as seen in a pharmaceutical company that achieved a 30% reduction in compliance files and a broader program that resulted in a 60% reduction in compliance through training and stewardship initiatives.

Notably, tech innovators achieved a 70% decrease in faulty data entries by implementing a comprehensive Data Quality strategy that reduced errors from 15% to 3%. Additionally, the National Centre for Education Statistics illustrated the importance of defining clear stewardship roles among executives to enhance Data Management. Demonstrating the tangible benefits of engagement is crucial in persuading stakeholders to prioritise their involvement.

Figure 13 Mold Stud Case Study: Data Stewardship

Figure 14 Executive Involvement in Data Stewardship

Figure 15 The Playbook: Activating Executives

Data Stewardship and Accountability in Business

An extensive playbook has been developed to guide the activation of Data Stewardship programs, offering a step-by-step process that includes messaging and storytelling strategies for executives, as well as insights into quick wins and long-term value. Many organisations struggle with implementing effective Data Stewardship due to high turnover and the need for retraining, which often leads to setbacks in progress.

Key components of the playbook include assessing the necessity for Data Stewardship, evaluating the business impact, and managing data issues through effective logging practices. However, challenges remain, as inconsistencies in how data issues are reported across various IT and Data Management platforms make it difficult to gain a comprehensive understanding of the existing problems.

Data maturity assessments are enhanced through leveraging existing ITIL frameworks for hardware and software management. By integrating a taxonomy for data assets into ServiceNow, the team aimed to streamline data-related inquiries, directing them to a dedicated first-line data support instead of relying on an ineffective SharePoint log. This strategy would ensure consistency across systems, reports, and statistics while addressing the existing challenges faced by the organisation.

Figure 16 Executive Activation Playbook

Figure 17 Q&A and Interactive Discussion

Implementing Effective Data Governance with Executive Teams

To effectively communicate the necessity of a project to executives, it’s crucial to articulate the benefits they will gain from it clearly. This involves not only identifying the challenges faced, such as issues with personnel or quality, but also ensuring executives internalise the problems as their own. A transformation step is needed to shift from mere acknowledgement of the issues to genuine ownership of them.

Once this is established, monitoring the activation of resources and roles becomes vital. By formally recognising Data Stewards and allocating responsibilities within their departments, clarity emerges, as demonstrated when risks associated with various data assets are assigned to specific individuals, leading to greater engagement and understanding of the governance process.

Howard emphasised that engaging executives in the strategic allocation process is crucial, particularly in understanding how to delegate responsibilities to the appropriate team members effectively. This involves not only convincing leadership of the analysis’s importance but also monitoring the activation and maintaining a clear call to action. Additionally, Howard emphasised the importance of a well-structured playbook that aligns executives with the overall strategy. Lastly, attendees were encouraged to share their challenges related to engagement while maintaining confidentiality.

The Challenges of Technical and Business Data Stewardship

An attendee highlights the ongoing challenges faced in managing Data Stewardship, particularly the division between technical and business Data Stewards. Technical stewards from the IT department focus primarily on systems and applications, while business stewards prioritise product improvement, often neglecting their role in Data Management.

This disconnect leads to a reliance on dedicated Data Management and quality experts, with little proactive involvement from either group. Despite efforts to organise working groups that bring together Data Stewards and technical teams to address data issues, participation remains low due to competing priorities and a lack of understanding of the importance of their involvement in Data Stewardship.

Howard emphasises the importance of aligning issues with their priorities and processes to communicate effectively with stakeholders, ultimately leading to solutions that do not necessitate significant system changes. Additionally, an example was shared of a major Master Data problem, which was resolved through adjusted business processes rather than costly modifications to mainframe systems, demonstrating that operational changes can sometimes address complex issues. A session revealed passive resistance among financial heads regarding asset ownership, illustrating reluctance to embrace change due to fear of backlash.

Data Management and MetaData Management in Organisations

The importance of a data issue log as a valuable asset for managing Metadata was highlighted, particularly in relation to tagging and defining data changes. Howard emphasised the negative connotations associated with the term “steward,” which can discourage individuals from taking on data responsibilities. To address this, terminology was changed to “data SMEs” and “data sponsors,” resulting in a more positive reception.

Howard then touches on the overwhelming nature of the Data Steward role, with one individual expressing frustration over being inundated with issues, leading to a sense of being burdened. To better manage responsibilities, the group proposed identifying assets and creating a RACI matrix at the asset level to understand cross-departmental functions and streamline Data Management.

In many organisations, issues that span political and cross-unit boundaries require escalation to higher management. Typically, departments are designated for different aspects of customer creation, financial management, and insurance, necessitating collaboration across functions. Each stage requires a primary owner to make decisions about changes, supported by supplementary owners who are interested in their respective segments.

Effective Data Management is crucial, as those directly involved with customer interactions often struggle with poor Data Quality, hindering their success. Identifying individuals passionate about addressing these data issues and empowering them with the authority to drive change across departments is essential for improving outcomes.

Figure 18 Data Steward Roles

The Challenges of Data Stewardship in Business

Appointing individuals with a business background rather than solely technical expertise ensures a successful Data Steward. While technical skills can be beneficial, Data Stewards must quickly acquire subject matter expertise to effectively establish policies, procedures, and business rules, as they are critical to the understanding and application of data within the organisation. Additionally, effective collaboration between technical and business professionals is essential, as IT personnel may struggle to define business-related terms without that specific knowledge. Howard highlights the challenges of working in isolation and emphasises the importance of teamwork in preventing downstream complications.

Linking a portion of Key Performance Indicators (KPIs) to Data Management objectives enhances executive engagement in Data Quality initiatives. A CEO mandated that 5% of KPIs be tied to this effort, enabling leaders to motivate their teams by illustrating how easy it could be to achieve this goal. While getting executives on board may be straightforward, the challenge can lie with senior managers who were already entrenched in their roles as Subject Matter Experts (SMEs).

To overcome this, it was proposed that the additional 5% budget could fund junior assistants to support the Data Stewardship process, thereby alleviating some of the workload while driving Data Quality improvements. Despite initial resistance from executives who questioned the value of these KPIs, the initiative ultimately aimed to foster a culture of accountability and improvement in Data Management throughout the organisation.

The role of a Data Executive is crucial for effective Data Governance, requiring long-term commitment and strategic oversight. Engaging with Data Stewards to clarify their responsibilities and organising data assets by unit is essential. This process involves assessing how data assets impact departmental productivity and performance, identifying both technical and production stewards.

A comprehensive understanding of the value chain across multiple departments is necessary to evaluate the benefits of Data Management at the enterprise level. Thus, it distinguishes itself from domain-specific stewardship, which may focus on areas such as customers, loans, or project disbursements.

Data Governance and Data Issue Log Management

Building a convincing business case for a master data project highlights the significance of the data issue log impact. Howard notes a project that was initially rejected by the CEO, as they expressed scepticism about the value of master data. It took several months of collaboration with the data issue log to demonstrate its benefits successfully.

Howard then emphasised the value of integrating tools like Power BI for metrics and tracking within Data Governance efforts. Additionally, one participant shared their experience assisting a customer with Data Governance, noting the challenges faced when all responsibilities rested with the knowledge manager, which indicated a cultural issue within the organisation. Overall, the emphasis lay on structured Data Management and collaborative support.

Figure 19 Value Stream

Data Quality Policy and Data Management Issues

Howard addressed various Data Quality policy issues and identified the need for a more structured approach to logging and managing these issues. He noted that the current process lacks follow-through and relies heavily on email without clear closure or escalation paths. Additionally, a key suggestion was to empower individuals within the business to take ownership of their data, moving away from the reliance on the Knowledge Manager.

This cultural shift is necessary, and it’s important to maintain a balanced workload for Data Stewards to prevent them from feeling overwhelmed. Additionally, there’s an emphasis on championing tools that promote accountability for Data Quality. A link to additional resources was shared in the chat for those interested in engaging more deeply.