MetaDAMA - Data Management in the Nordics
This is DAMA Norway's podcast to create an arena for sharing experiences within Data Management, showcase competence and level of knowledge in this field in the Nordics, get in touch with professionals, spread the word about Data Management and not least promote the profession Data Management.
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Dette er DAMA Norge sin podcast for å skape en arena for deling av erfaringer med Data Management, vise frem kompetanse og kunnskapsnivå innen fagfeltet i Norden, komme i kontakt med fagpersoner, spre ordet om Data Management og ikke minst fremme profesjonen Data Management.
MetaDAMA - Data Management in the Nordics
3#17 - Håkan Edvinsson - Data Diplomacy, Enterprise Architecture and Data Governance (Eng)
"We don’t need Data Governance where we don’t have anything to fix."
How can Data Diplomacy transform an organization into a data-driven organization? This episode brings Håkan Edvinsson, a visionary in data management and governance, into the conversation, revealing the intricacies and impacts of Data Diplomacy in Nordic organizations. Håkan's journey from business data modeling in the 90s to robust governance practices today offers a treasure trove of insights. Together, we dissect the evolution of enterprise architecture and its role in business innovation.
Discover how data governance is not just about maintaining quality but is a dynamic force that propels organizations forward with each structural change. We discuss the concept of data design and how this approach is shaping the future of responsible data usage in companies like Volvo Penta and Gothenburg Energy. Our dialogue uncovers the importance of integrating governance into decision-making and planning, ensuring data is not just managed but used as a strategic asset for innovation.
The finale of our discussion broadens the horizon, touching upon artificial intelligence and its relationship with traditional data practices. We challenge the status quo, urging businesses to embrace a leaner governance model that aligns with Lean and Agile methodologies. Alongside this, we unravel the subtle yet crucial distinction between data and information, arguing for a proactive business ownership in data design and governance.
Here are my key takeaways:
- If you want an organization to last, someone has to define key terms.
- Data Governance and Data Quality should not be done reactively, but rather by design.
Enterprise Architecture
- Connecting the work of EA to certain project gates, is underpinning a reactiveness in EA.
- EA claims to be the master interpreter of business needs, yet EA artifacts are based on second hand knowledge.
- Architecture as well as Governance are supporting a development, not dictating it.
- EA is NOT the business designer, just an interpreter, a facilitator, that enables those with 1st hand knowledge.
- Don’t generalize away from business reality.
Data Diplomacy
- As long as you are working with operational data, you need to embrace business data design.
- You need to bridge Business with IT.
- The «gravity for change», mainly through external factors provide management attention.
- Use these external triggers to create more with less.
- Dont talk solutions and technology - too many opinions. Stick to the data.
- Focus on what data should look like. Base your work on the facts.
- Enable people to understand data, requires Data Governance to take a facilitator role, not an excellence role.
- «Being a hero once doesn’t mean you are lasting.» - you need to find a sustainable way of doing data work, beyond task based, checklist compliance.
- Establish a Data Governance network that represents the entire organization.
- A common language and established tacit knowledge can speed up processes.
- You need to be ready, prepared, and on the edge to ensure you are resilient to change.
- Integrate your data decisions into the management structure.
- Firefighting gets more credit then fire prevention.
- Traditional Data Governance is too focused on operational upkeep, laking a future outlook.
- Data Governance don’t rely have the means to state: What should it look like in tomorrows world?
- Entity Manager: taking charge of definition, label and structure of a certain data entity, of the data that we should have.
- A Facilitator works with these entity mangers in their respective area.
- Advice against top-down, classical Data Governance implementation.
