Sponsors and Use Cases

At the start of the data engineering journey, it is imperative to determine the biggest supporters of the initiative, along with what and how the initiative will be used by these supporters.

It is critical to identify the key sponsors of the initiative, regardless of organisation size. Some potential sponsors could include the organisation’s Chief Information Officer (CIO), who is responsible for making decisions relating to IT systems and policies, the Chief Data Officer (CDO), who helps make data governance decisions, and senior management, who provide guidance and direction. All of these stakeholders will need to be engaged at various levels to get the necessary buy-in and support to drive the data engineering initiative.

From our experience with past data engineering engagements, we have found that a RACI (Responsible, Accountable, Consulted, and Informed) matrix can help to provide clarity on how stakeholders engage with the working-level team to drive data engineering initiatives from various angles.

The RACI template could be used to identify the different user groups, understand their business goals, and identify the different roles that the CIO, CDO, and senior management could play in driving the initiative.

RACI is an acronym derived from the four key responsibilities most typically used: Responsible, Accountable, Consulted, and Informed. It is used for clarifying and defining roles and responsibilities in cross-functional or departmental projects and processes.

Through the example highlighted in the RACI template, we can determine that some significant duties of a project sponsor include:

• Define project directions, objectives, and scope
• Provide approval and funding for the initiative
• Review risk management through periodic reviews
• Ensure active participation from the various stakeholders
• Ensure adequate support and resources
• Resolve conflicts

Once sponsors have been identified, it is then imperative to determine the value that a use case can bring to the teams’ overall data engineering strategy. A use case often provides decision makers, stakeholders, and management a tool to determine the outcome of the data engineering initiative based on evidence and transparency. There must be a clear focus on the considerations, associated risks, and business value of a use case.

Examples of questions that can be used by teams to scope use cases include:

• What is the current business process that the initiative aims to resolve?
• What is the data engineering problem statement? / What will this data engineering initiative resolve within the organisation?
• How urgent is the initiative/what is the severity of the initiative against the organisation?
• Are there any potential solutions currently considered by the organisation?
• What data is currently available? What data is currently lacking?

Once these (and other) questions have been answered, the use case would be better scoped out. This use case could then be presented to sponsors to get their buy-in. Once support has been obtained, the use case could be integrated into the data engineering initiative. A properly thought-out use case with support from key sponsors will propel the data engineering initiative at an accelerated pace.