Optimizing Name Matching and Data Structure: Challenges and Opportunities

The meeting participants, referred to as "State Changers," discussed a problem presented by George. The problem involves matching names in a dataset for compliance purposes, but the dataset is messy and lacks a clear structure. The compliance lawyers are waiting for a definition of what constitutes a name match. The State Changers suggest using the ROC curve, which evaluates the trade-off between sensitivity and specificity in a test. They advise George to experiment with different techniques and improve the data quality. They also discuss the possibility of creating a product that integrates with existing CRMs and practice management systems via an API call. The State Changers recommend starting with experiments and gradually improving the solution based on feedback and more refined data. They emphasize the importance of translating expertise into a technical product and using no-code tools like Xano for non-specialized tasks. They also suggest considering existing services and APIs before building everything from scratch. Lastly, they discuss the deflationary nature of technology costs and recommend waiting for a smarter version of the solution before making a bigger investment.

(Source: Office Hours 8/25 )

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