«Don’t make it hard to understand for the business. Make it simple and clear.»

Get new perspectives on Data Governance with Valentina Niklasson from Volvo Penta as she talks about certain patterns, stages in the acceptance of Quality Management or Lean, that Data has to go through. Her rich experience in making Data Governance business-centric emerges, showcasing how you can get an organization engaged in Data.

Gain insights on the synergy between lean methodology and effective Data Management. We explore the application of the PDCA Deming circle in Data and discuss how common languages and methodologies bridge the gap between Data, IT and business. This convergence is not just theoretical; it's a practical pathway to tapping into customer insights, translating needs into strategies, and fostering a culture where continuous improvement reigns.

Finally, we delve into the human aspect of Data and Data Stewardship, emphasizing the importance of people over technology in cultivating a data-driven culture. By engaging the curious early and involving them in the development of business information models, we build ambassadors within the business, ready to champion change. Valentina and I talk about the dynamic role of Data Stewards and the approach to involving business personnel, ensuring the smooth adoption of new processes and strategies.

Here are my key takeaways:
Quality management as inspiration

• Data is still treated as an IT problem, but should really be treated as a business problem.
• We need to find a better way to communicate across data, IT and business.
• Use the same methodology wherever possible and try to reduce complexity in processes.
• Try to adapt to the ways of working in the business. Not creating own ways on digital, data or IT.
• You need to understand customer relations, end customers and the entire value chain to define needs correctly.
• Standardized ways of working can help to do right from start.
• Deming Cycle, PDCA, can be directly adopted to data. Think of data as the product you are building, that should have a certain quality standard.
• Don’t make it hard to understand for the business:
  • Using the same forms and approaches.
  • Business data driven process.
  • Let the business take part in the entire process.
• Lean Methodology should take a bigger place in data.
• A product management mindset makes data quality work easier.

Data Stewardship

•  You need to ensure owning the problem as well as the solution.
• High data quality is vital for data-driven organization. Someone needs to ensure this.
• Stewardship can have a negative connotation. 
• The technical demands on Data Stewards are really big today.
• Data Stewardship works if the Data Steward is part of a broader team.
• The role of Steward needs to be adjusted to the fast-speed reality.
• Data Stewards need to be able to solve problems, not only report to a central organization.
• Data Stewards should be approached in the business. You need that domain knowledge, yet they cannot perform the entire stewardship role.
• Most important to empower Data Stewards to start working and analyzing the challenges ahead.
• Don’t force Data Stewards to be technical data experts. That should be a supportive role in the Digital / data organization.
• If you build something new, engage Data Stewards from the beginning. 
• You cannot take responsibility for something you don’t understand.
• If you want to be sustainable in Data, you need to help the people in your organization to be part of the journey.
• It’s not only about hiring new competency, but engaging with the knowledge you have in your organization.