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
082 - What the 2021 $1M Squirrel AI Award Winner Wants You To Know About Designing Interpretable Machine Learning Solutions w/ Cynthia Rudin
081 - The Cultural and $ Benefits of Human-Centered AI in the Enterprise: Digging Into BCG/MIT Sloan’s AI Research w/ François Candelon
080 – How to Measure the Impact of Data Products…and Anything Else with Forecasting and Measurement Expert Doug Hubbard
079 - How Sisu’s CPO, Berit Hoffmann, Is Approaching the Design of Their Analytics Product…and the UX Mistakes She Won’t Make Again
078 - From Data to Product: What is Data Product Management and Why Do We Need It with Eric Weber
077 - Productizing Analytics for Performing Arts Organizations with AMS Analytics CPO Jordan Gross Richmond
076 - How Bedrock’s “Data by Design” Mantra Helps Them Build Human-Centered Solutions with Jesús Templado
075 - How CDW is Integrating Design Into Its Data Science and Analytics Teams with Prasad Vadlamani
074 - Why a Former Microsoft ML/AI Researcher Turned to Design to Create Intelligent Products from Messy Data with Abhay Agarwal, Founder of Polytopal
073 - Addressing the Functional and Emotional Needs of Users When Designing Data Products with Param Venkataraman
072 - How to Get Stakeholders to Reveal What They Really Need From a Data Product with Cindy Dishmey Montgomery
071 - The ROI of UX Research and How It Applies to Data Products with Bill Albert
070 - Fighting Fire with ML, the AI Incident Database, and Why Design Matters in AI-Driven Software with Sean McGregor
069 - The Role of Creativity and Product Thinking in Data Monetization with ‘Infonomics’ Author Doug Laney
068 - Why User Adoption of Enterprise Data Products Continues to Lag with International Institute for Analytics Executive VP Drew Smith
067 - Why Roche Diagnostics’ BI and Data Science Teams Are Adopting Human-Centered Design and UX featuring Omar Khawaja
066 - How Alison Magyari Used Design Thinking to Transform Eaton’s Business Analytics Approach to Creating Data Products
065 - Balancing Human Intuition and Machine Intelligence with Salesforce Director of Product Management Pavan Tumu
064 - How AI Shapes the Products of Startups in MIT’s “Tough Tech” Venture Fund, The Engine feat. General Partner, Reed Sturtevant
063 - Beyond Compliance: Designing Data Products With Data Privacy As a UX Benefit with The Data Diva (Debbie Reynolds)
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