• How selecting the right architecture, oriented around loose coupling, can enable some technology functions to innovate quickly even though others need to change more slowly;
• Why trust is the product in banking, and how that drives data classification, data quality, security, privacy, and the regulatory environment; and,
• How both commercial and regulatory incentives drive  banks to innovate.

We both found Ken so interesting that as soon as the podcast recording was over we were looking forward to listening to it again.

We found Laurel both articulate and inspiring, and her message of empowering managers to become experts in their own data realms will resonate with organizations of all sizes and budgets. Listen for yourself!

Aaron talks about stages of organizational readiness, overcoming the inertia of existing culture and methods, and an agile approach to kickstarting internal data platforms. He shares inspiring stories of spectacular early stage client successes on their roads to data transformation. He also dives deep into ongoing business and academic efforts to develop voluntary data ethics standards, and, gives us an overview of the principles and structures Avanade is developing as part of its own internal data ethics initiative.

There's a lot of great information in this podcast that we think you'll enjoy as much as we do.

During the course of our conversation Ricardo focuses on the challenges of creating a data-first direct-to-consumer business on a startup budget, including data access and quality issues, building a minimum viable team, rapidly prototyping potential products, and how to build trust in data models.

Please join us to take a closer look at using data to transform a familiar marketplace from the perspective of a innovative startup founder.

• capacity planning,
• reducing waste by matching purchasing to predicted demand,
• overcoming information hoarding, silos, and data quality issues,
• making data accessible and trackable,
• reconciling data sets that originate from different sources,
• co-creating data solutions with end users to ensure adoption,
• the importance of domain knowledge as well as data literacy in both managing and visualizing clinical data,
• eliminating cultural biases in data capture and analysis and in patient experience,
• and the responsibilities that accompany data ownership.

Please join us for an episode that's as relevant to organizations outside of the realm of medicine as it is for healthcare providers.