2#8 - Nina Walberg - The 6 principles for value creation through data (Eng)

MetaDAMA - Data Management in the Nordics

«Its not just about the use of data, but the use of data in a cross-functional setting.»

What a fantastic conversation with Nina Walberg. Nina has been with Oda since 2019 and has a background in Optimization and SCM from NTNU.

Oda strive to create a society where people have more space for life. Make life as hassle-free as possible. And to achievetis with help from data, Oda has created its 6 principles for how they create value with data.

Here are my key takeaways:

Business model and use of data

• Odas business model allows for a better and more cautious way of thinking sustainability. The quantum of products can be tailored to the actual need.
• Climate recipe: Oda provides data on the climate footprint to its customers, when ordering products.
• Use data to provide not just inspiration to your customers, but also help them to create a complete basket of groceries for the week, to avoid any additional trips to the super market.
• The use of data needs to be combined with all functions, also business functions. All should be part of the development process

6 Principles

• 6 principles recently updated, but originally created by the entire team in 2019.
• Oda believes in autonomous teams and that trust and responsibility is given to these team.

1. Domain knowledge and discipline expertise
   • 70% of Data and Insight people are embedded in cross-functional teams.
   • Data is connected across the company and across domains. So you can not work exclusively in an embedded model. You need some central functionality.
   • Data Maturity differs between domains. So really the embedded model depends on the circumstances and how Oda applies that.
   • Data Mesh has been an inspiration.
2. Distributed data ownership, shared data governance
   • Processes and parts of the product for Oda are developed by the domain teams. To federate the ownership is a natural move.
   • Domain boundaries need to be explicit. «Every model that we have in dbt is tagged with a team.»
   • Ownership of certain products is harder or sometimes not right to distribute. It can either be core products with no natural domain team to own, and that many are dependent on, or the core data platform itself.
   • Customer data first, but without proper product data you can’t live up to that
3. Data as a product
   • Make sure you don’t just deliver a product, but that it meets the customer need, not just the customer demand.
   • Consistency matters, structure matters, naming matters when it comes to data products.
4. Enablement over handovers
   • Enabling others to do what they should be able to do themselves.
   • Oda has established a segmentation model for five levels of self-service with different expectations to different user groups.
   • Self-service needs to be tailored to different roles, maturity, and needs of the internal users.
   • Data University, Data Hours and many other initiatives help to create a learning culture and improve data literacy.
5. Impact through exploration and experimentation
   • It is important to test and see how a solution actually provides value to the expectations.
   • This provides insights and information you can act on.
6. Proactive attitude towards privacy and data ethics
   • Data ethics needs to be incorporated and can’t be an afterthought.
   • Company values can and should be directly linked to the work with ethics.

This episode was recorded in September 2022. Click here if you what to know more.