Evolution to Systems Thinking from Model Thinking
summary
Describes how multiple data-science algorithms (predictive and optimization models) are integrated at Ola to solve a single business problem, arguing for evaluating the full system of models rather than optimizing individual models in isolation. Covers practical challenges in measuring and attributing the impact of interconnected algorithms and outlines strategies for handling those measurement and attribution issues.
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chapters (4)
- 0:00Start
- 1:36Data Science for Business-drivetrain approach
- 4:47Examples of Drive Train Approach
- 8:21Evolution to system thinking from model thinking
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