There’s a lot at stake in the decisions that social workers have to make when they care for people — and Dr. Besa Bauta keeps this in mind when her teams are designing the data products that care providers use in the field.
As Chief Data Officer at MercyFirst, a New York-based social service nonprofit, Besa explains how her teams use design and design thinking to create useful decision support applications that lead to improved clinician-client interactions, health and well-being outcomes, and better decision making.
In addition to her work at MercyFirst, Besa currently serves as an adjunct assistant professor at New York University’s Silver School of Social Work where she teaches public health, social science theories and mental/behavioral health. On today’s episode, Besa and I talked about how MercyFirst’s focus on user experience improves its delivery of care and the challenges Besa and her team have encountered in driving adoption of new technology.
In total, we covered:
We're not a technology company, ...so, for us, it’s about finding the right partners that understand our use cases and who are also willing to work alongside us to actually develop something that our end-users — our physicians, for example — are able to use in their interaction with a patient. - Besa
No one wants to have a different type of application every other week, month, or year. We want to have a solution that grows with the organization. - Besa on the importance of creating a product that is sustainable over time
If we think about data as largely about providing decision support or decision intelligence, how do you measure that it's designed to do a good job? What's the KPI for choosing good KPIs? - Brian
Earlier on, engaging with the key stakeholders is really important. You're going to have important gatekeepers, who are going to say, ‘No, no, no,’ — the naysayers. I start with the naysayers first — the harder nuts to crack — and say, ‘How can this improve your process or your service?’ If I could win them over, the rest is cake. Well, almost. Not all the time. - Besa
Failure is how some orgs learn about just how much design matters. At some point, they realize that data science, engineering, and technical work doesn't count if no human will use that app, model, product, or dashboard when it rolls out. -Brian
Besa: It was a dud. [laugh].
Brian: —yeah, if it doesn’t get used, it doesn't matter
What my team has done is create workgroups with our vendors and others to sort of shift developmental timelines [...] and change what needs to go into development and production first—and then ensure there's a tiered approach to meet [everyone’s] needs because we work as a collective. It’s not just one healthcare organization: there are many health and social service organizations on the same boat. - Besa
It's really important to think about the human in the middle of this entire process. Sometimes products get developed without really thinking, ‘is this going to improve the way I do things? Is it going to improve anything?’ … The more personalized a product is,the better it is and the greater the adoption. - Besa
102 - CDO Spotlight: The Non-Technical Roles Data Science and Analytics Teams Need to Drive Adoption of Data Products w/ Iván Herrero Bartolomé
101 - Insights on Framing IOT Solutions as Data Products and Lessons Learned from Katy Pusch
100 - Why Your Data, AI, Product & Business Strategies Must Work Together (and Digital Transformation is The Wrong Framing) with Vin Vashishta
099 - Don’t Boil the Ocean: How to Generate Business Value Early With Your Data Products with Jon Cooke, CTO of Dataception
098 - Why Emilie Schario Wants You to Run Your Data Team Like a Product Team
097 - Why Regions Bank’s CDAO, Manav Misra, Implemented a Product-Oriented Approach to Designing Data Products
096 - Why Chad Sanderson, Head of Product for Convoy’s Data Platform, is a Champion of Data UX
095 - Increasing Adoption of Data Products Through Design Training: My Interview from TDWI Munich
094 - The Multi-Million Dollar Impact of Data Product Management and UX with Vijay Yadav of Merck
093 - Why Agile Alone Won’t Increase Adoption of Your Enterprise Data Products
092 - How to measure data product value from a UX and business lens (and how not to do it)
091 - How Brazil’s Biggest Fiber Company, Oi, Leverages Design To Create Useful Data Products with Sr. Exec. Design Manager, João Critis
090 - Michelle Carney’s Mission With MLUX: Bringing UX and Machine Learning Together
089 - Reader Questions Answered about Dashboard UX Design
088 - Doing UX Research for Data Products and The Magic of Qualitative User Feedback with Mike Oren, Head of Design Research at Klaviyo
087 - How Data Product Management and UX Integrate with Data Scientists at Albertsons Companies to Improve the Grocery Shopping Experience
086 - CED: My UX Framework for Designing Analytics Tools That Drive Decision Making
085 - Dr. William D. Báez on the Journey and ROI of Integrating UX Design into Machine Learning and Analytics Solutions
084 - The Messy Truth of Designing and Building a Successful Analytics SAAS Product featuring Jonathan Kay (CEO, Apptopia)
083 -Why Bob Goodman Thinks Product Management and Design Must Dance Together to Create “Experience Layers” for Data Products
Create your
podcast in
minutes
It is Free
Insight Story: Tech Trends Unpacked
Zero-Shot
Fast Forward by Tomorrow Unlocked: Tech past, tech future
Black Wolf Feed (Chapo Premium Feed Bootleg)
Bannon`s War Room