GMAIST Automation ML SLDC

Problem

The Client’s GMAIST Team (Global Medical Affairs International) were using the Global Content Management and Approval (GCMA) system to manually manage the review and approval of material based on the various quality parameters. This consisted of 600-3800 transactions annually which was time consuming.

Solution

An ML model was created to assist GMAIST process that involved human judgment. It was aimed to examine the promotional claims and reference pairs and suggest if they corresponded or not. These suggestions were then provided to a GMAIST reviewer to accelerate their review of claim-reference pairs.

Impact

01

Improved consistency and quality

02

Reduced time spent by the GMAIST team on manual tasks enabling users to engage in higher value-add activities and more meaningful work.

03

aved up to 8K-32K hours over the period of 3 years, depending upon demand.

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