Case in point. I wrote a blog Medical Education, Biting the Hand that Pays back in April of 2016. I call it my ugly baby post. There was a diaspora from the newsletter, blog, and LinkedIn follower tallies. Many in the industry don't want anything to change. They dream up new ways to look at garbage data. Questions of validity, value, or applicability to practice at the point of care appear to be secondary to keeping the status quo. Another advantage to a diversified client portfolio? You can be honest and tease out the threads of possibility. If one stock tanks, you have other relationships to grow and bring value and expertise. This past week I was reminded that friendships are only as solid as the last round of collaborations and industry support. It is amusing because I don't live in that world anymore. Trust me, it isn't hand holding and singing Kumbaya in health economics, policy, or clinical medicine either but I honestly don't typically see the ruthless self-serving interactions. In fact, many people I hadn't seen in too long stopped by the lecture or grabbed me in the lounge to say hello. Continuing medical education isn't the "only as good as your last thing" industry. I did have one HEOR co-presenter approach me at a table of influential conference attendees and introduce herself to my companions as blah blah, PhD--as a dig at my lack of PhD. I do have a MSc where I studied population genetics and a Doctorate of Chiropractic where I treated patients. Not sure how the PhD took over the I Can Do This Better space but their grip is slipping as multiple perspectives are valued to drive the change we need in healthcare. My point here is we need to be less territorial. I will keep repeating my favorite definition of innovation. Innovation happens in the gaps between disciplines--not by navel gazing and self promotion. My friend and colleague describes his data role as "data adjacent". We all need to be shrinking the gaps between understanding our data and making meaningful leaps. He describes this as absorbing data insights and biostatistics from our conversations and collaborations. I have been thinking about the phrase for a few weeks. It resonates and describes outlier analyses and incremental understandings that can lead to important revelations. The ‘Adjacent Possible’ of Big Data: What Evolution Teaches About Insights GenerationThis is the time when the enterprise has to adjust its expectations and its analytics modus operandi. If pipeline problems exist, they need to be fixed. If quality problems exist, they need to be diagnosed (data source quality vs. data analysis quality). In addition, an adjacent possible approach to insights needs to be considered and adopted. The Systems Thinker sees opportunity in iterative approaches informed by a wider set of databases and analytic strategies. I think back to the aughts and my last bit of structured education in biostatistics. It was easily forgettable without context or a bigger question to explore. The process of data analysis is often fraught with silo’d context i.e. the analyst often does not have the full business context to understand the data or understand the motivation for a business driven question or understand the implications of their insights. Applying the theory of adjacent possible here implies that by introducing the idea of collaboration to the insights generation process by inviting and including team members who each might have a slice of the business context from their point of view can lead to higher valued conclusions and insights. Comments are closed.
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