A long time ago, Peter Norden would observe operations research does not exist independent of its application area. Success and impact requires strong core "analytics without borders" (AWB) and a strong working knowledge of the application area. Experience in the application of AWB in different application areas can be helpful. For example the OPcurve, commonly used in semiconductor, also applies in health care around MRI machines. However the person has to good domain knowledge in both. Additionally get published requires a network, one network doesn't recognize another.
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Ken Fordyce
director analytics without borders
Arkieva
Wilmington DE
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Original Message:
Sent: 11-06-2023 02:47
From: Richard Liu
Subject: Maximizing Impact: The Versatility of Analytics in Healthcare and Beyond
Hello All,
Recently, I came across a compelling blog titled 'Increased Use of Split-Liver Transplantation Can Relieve Organ Shortage and Bring More Equitable Outcomes for Patients' (Link to the blog). The authors, from Carnegie Mellon University, explore how split-liver transplants - where one donor liver is divided to save two lives - could address the shortage of livers for transplant and make access to transplants more fair.
This research struck a chord with me. In my business analytics studies, I've seen how powerful data can be in making decisions that can change lives. Like the researchers, I've also worked with models that can make a real-world impact. However, their work is tightly focused on healthcare, which is quite specialized compared to my broad experiences across various industries.
I'm curious about your views. How important do you think it is to apply analytics to one specific field versus a broader application? Does anyone here have experience in healthcare analytics and can share how it compares to other industries? Let's dive into how data analytics shapes different sectors.
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Richard Liu
UC Davis
San Francisco CA
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