Every engineering company is awash in digital data. Instead of drowning in it, data stewards put it to use.
Many organizations are frustrated by the slow progress of their digital transformation. While there are many signs your digital transformation is in trouble, the most common is insufficient data quality.
Thankfully, there’s an easy way to improve the quality of your data: appoint a data steward. Here’s everything you need to know about this crucial role and how engineers can champion data stewards to improve data quality and accelerate digital transformation.
What is data stewardship?
Data stewardship is about managing an organization’s digital assets to provide engineers and other end users with high quality data that is quickly and consistently accessible.
Data stewards:
- Monitor the quality of data, often using automated data quality checks.
- Correct data deficiencies or manage those who make corrections.
- Collaborate with data scientists, business analysts and executives to translate data into actionable insights.
- Advocate for improved data quality among system owners.
- Identify opportunities to use data to advance the business plan and gain a competitive advantage.
- Champion efforts to move the organization toward a data-driven culture anchored in digital transformation.
- Educate end-users about available data, locations, structures and relationships.
- Explain the organization’s data quality standards to those who enter or acquire data.
- Enforce regulations on how data can be used.
- Champion information governance.
- Encourage the use of available data standards and structures for custom software development.
- Propose enhancements to the business rules that validate data entered into systems.
What is the value of data stewardship?
Effective data stewardship adds value to digital transformation by:
- Improving data quality and immediate data access for more reliable data-driven decision making.
- Reducing data cleanup effort before data analytics work can commence.
- Enabling faster and lower effort data analytics work.
- Producing more valuable and reliable data analytics results.
- Building more widespread awareness of data management best practices.
- Assuring that data-related security and privacy requirements are being met.
- Enabling compliance with data management and cybersecurity regulations.
- Supporting more effective implementation of data governance.
With digital transformation and data stewardship, engineers can apply the learning from one project to the next and avoid re-organizing and re-learning for every project.
What creates skepticism about the value of data stewardship?
Sometimes engineers and other professionals are skeptical when the CIO discusses data stewardship to improve data quality and data management. These are typical reactions:
- Our engineering data is good enough to run the business. What’s the problem?
- We noticed our data isn’t good enough for data analytics or digital transformation, but we can correct that in our engineering department without the CIO needing to fire up a gargantuan corporate initiative.
- The CIO is trying to increase their self-importance.
- I don’t see a business case for spending more money on our digital engineering data.
- Asking our client for resources to improve the engineering, procurement and construction (EPC) data won’t be well received.
This skepticism is short-sighted because:
- It’s challenging to sustain an ad hoc data quality improvement initiative. It’s better to formalize the data stewardship function.
- It’s not just about digital engineering data. Engineers also need data from other departments and disciplines for their work. A corporate data improvement initiative may be required.
- Engineering teams are the data stewards of engineering data and, therefore, should value its improvement.
- Providing quality data to the client ensures the client can operate, maintain and enhance whatever the engineers designed and built. Providing the client with that ability leads to recurring engineering business.
Why do we need data stewardship?
Many organizations face data issues that data stewardship can address. These issues include:
- Organizations have massive amounts of digital and unstructured data that aren’t well managed.
- The volume of data is exploding, and its value is being recognized.
- The absence of standard ways to store and access data.
- Different applications and divisions use different data standards.
- Inability to agree on what data is most important to the organization and should receive the most data management attention.
- Organizations need a way to establish authoritative data standards from among competing and conflicting standards.
- It’s unclear which of multiple internal data sources are authoritative.
- Data vendors operate with proprietary data standards, making integrating their data with internal data difficult.
- The processes employees should use to work together to correct data issues are unclear.
More formal data stewardship can reduce or eliminate the costs and risks associated with these issues.
Isn’t data stewardship part of the IT department’s role?
Too many managers believe that data stewardship and data management are the responsibility of the IT department. They have confidence in the IT department and see no need for further involvement.
To IT departments, data management means:
- Don’t lose any digital data through regular backups.
- Make sure digital data is recoverable in case of a disaster.
- Protect digital data against cybersecurity attacks.
- Paper-based documents and records are managed elsewhere.
IT’s view of their responsibility doesn’t include any aspect of data stewardship as defined above.
How can you implement data stewardship best practices?
Implementing these best practices enables data stewards to perform their roles successfully and build data value by supporting digital transformation.
Establish executive sponsorship for data stewardship
When senior executives publicly support data stewards, it provides necessary credibility and authority when they’re:
- Overseeing how data is managed and used.
- Encouraging more attention to correcting data errors.
- Guiding data analytics work.
- Recommending digital transformation to enhance the value of data.
Nurture a data-driven corporate culture
Data stewards advocate for data and promote the effective use of data throughout the organization. By encouraging engineers and others to include available data in every decision, they become prime drivers of a data-driven culture.
Make data stewards essential members of the data team
Data stewards are typically scattered throughout business units. When organizations make them full members of the data team, they work closely with their peers to:
- Share knowledge of locations, structure and contents of corporate data stores.
- Advance data management best practices, including digital transformation.
- Collaborate on policy and procedures.
- Communicate the organization’s data governance function.
Grasp data and business environments
Data stewards work between their team and the engineers and analysts that consume data. To be effective, they build a deep knowledge of data sources and the business unit they’re assigned to. With this knowledge, they can identify opportunities to enhance and apply data to achieve competitive advantage.
Set incentives for data stewards
To promote effective job performance, the chief data officer (CDO):
- Defines the roles and responsibilities of data stewards.
- Defines and tracks quantitative and qualitative key performance indicators (KPIs).
- Builds achievement of those KPIs into data stewards’ compensation.
Develop data stewardship skills
Encourage data stewards to develop their skills and view their roles more broadly. Have them create a personal, professional development plan that includes membership in professional associations, speaking, and development opportunities.
Form a data stewardship community
Organizations form a data stewardship community to help data stewards connect, communicate and share experiences. This community enables data stewards to collaborate on issues such as:
- Data standards.
- Details of various internal and external data sources.
- Data management policies.
- Business terminology.
- How best to empower end users in the available data and data analytics tools.
- Brainstorming opportunities to extract more value from the data, often through digital transformation.
- Sharing best practices.
Make data policies transparent
All policies that involve data should be clearly and transparently defined and described. Data stewards should communicate these policies to everyone inside and outside the organization. When revising or establishing new policies, data stewards should collaborate with team members to achieve consensus on new or updated policies.
When engineers lobby for more data stewardship and support data stewards, data quality and accessibility improve. Then, digital transformation advances and delivers benefits to engineers and the business plan more broadly.
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Yogi Schulz has over 40 years of Information Technology experience in various industries. He writes for IT World Canada and other trade publications. Yogi works extensively in the petroleum industry to select and implement financial, production revenue accounting, land & contracts, and geotechnical systems. He manages projects that arise from changes in business requirements, from the need to leverage technology opportunities and from mergers. His specialties include IT strategy, web strategy, and systems project management.
