I can possibly offer insight to this question:
> how did companies make decisions in the 1980s without real-time data analytics and yet survive even be effective?
With respect to insurance, this is the domain of actuaries. My cousin was an actuary for a life insurance company, and they have ways of modeling risk to allow them to determine policy premiums. When he was doing that work (prior to the rise in analytics as we know it today), they used various statistical models to do this modeling. I would guess that if we were to look more carefully at their techniques, we would classify them as some form of analytics. They just didn't call it "analytics" back then.
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-Irv Lustig
Optimization Principal
Princeton Consultants
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Original Message:
Sent: 05-10-2024 13:19
From: Alberto Aparicio
Subject: Data analytics use cases in insurance
In the 2024 Berkshire Hathaway annual meeting, Ajit Jain, director and vice chairman of insurance operations addressed GEICO's data analytics shortcomings. For all the experienced applied analysts out there, how did companies make decisions in the 1980s without real-time data analytics and yet survive even be effective? What daily reporting or modeling could be used during that time? And generally, for the rest of you, why is this investor concerned about analytics being a source of vulnerability at GEICO?
https://www.youtube.com/watch?v=IfX1z_pXmQM
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Alberto Aparicio
Data Analyst
Charitable Adult Rides & Services, Inc.
San Diego
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