I attended the February PDMA event hosted at Optum. The Minneapolis chapter had arranged both a tour of the Optum facility and a panel discussion on the intersection of Product Management, Product Development, and Data Analytics. The event started with a networking session while tours were conducted. The tour featured several customer showcase areas. The first was visiting a large digital analytics command room that was several stories tall and covered in monitors with real-time information showing a vast amount of healthcare related actives across the united states. This room could be used to monitor the outbreaks and spreading of disease and the activities of the healthcare providers. It allows Optum to actively support the healthcare system with early identification of trends and coordination of activities. We headed into a detailed analytics room that featured individual station with large interactive touch screens. Our tour guides took use through numerous analytics scenarios with real-time drill down into trends, treatments, and member services that were possible with the depth of data they have been able to integrate and create the capabilities to explore and interact with data. This section of the tour concluded in a large surround screen video experience around the future of healthcare.
The event continued with the panel discussion featuring 6 panelists ranging from corporate to consultants with various backgrounds in the product and analytics spaces. With an audience size around 100 people, they did some polling and it saw a split between attendees being more on the product side vs. pure data scientists. The panel also talked briefly about the 5 eras of product development that was broken out accordingly:
- Create a product in isolation and push it out through advertising
- Customer focus groups
- Lean / Design Thinking / Customer Discovery
- Data Science
- Now we need to integrate 3 & 4
It was highly stressed that many data projects fail and the root cause is the lack of defining what value you want to get out of the data up front. Meaning you have to define the questions you are trying to answer before getting lost in analysis. While data analysis can also discover anomalies and trends along the way, that should be secondary to understanding what you are trying to learn from it. The questions also help define the “right” data you want vs. getting overwhelmed with studying “all” the data. In the end, your looking for the problem that your product/service can solve, not the offering itself in the data.
I look forward to attending more events and more networking!
Learn more about PDMA (http://www.pdma.org/minnesota)