#268 Adapting to and Adopting Product Thinking - Transforming Your Org for Sustainable Data Mesh - Interview w/ Iulia Varvara

Data Mesh Radio - A podcast by Data as a Product Podcast Network

Categories:

Please Rate and Review us on your podcast app of choice!Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereEpisode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding. Get in touch with Scott on LinkedIn if you want to chat data mesh.Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.Iulia's LinkedIn: https://www.linkedin.com/in/iuliavarvara/In this episode, Scott interviewed Iulia Varvara, Advisory Consultant in Digital and Organizational Transformation at Thoughtworks. To be clear, she was only representing her own views on the episode.Some key takeaways/thoughts from Iulia's point of view:If you are greatly changing your general approach to something - which data mesh does in many ways - you need to focus some amount on actual transformation. These approaches are not a switch you flip, it takes time and concerted effort to make lasting changes that work well.If an organization hasn't really broadly embraced product thinking, starting with data as a product/product thinking in data can act as a catalyst for other aspects of the business to embrace product thinking.You don't change the organizational mindset through words - you start using new ways of working that change people's mindset as they see the benefit of those ways of working. At the end of the day, talk is cheap.To do data mesh well and have it work for an organization, it's best to tailor to their existing ways of working. Yes, change is necessary but a revolution is far less likely to work than an evolution. How are teams working and where can we make smaller tweaks?Because you need to tailor your implementation to your own organization, any data mesh blueprint that will supposedly work for all organizations is likely to be snake oil at best.?Controversial?: The first two principles of data mesh - domain data ownership and data as a product - have the most impact on the organizational...