Manually allocating pursuit resources based on gut feel leads to wasted BD spend and missed high-probability wins. A custom automation workflow ingests signals from CRM (Salesforce), historical bid databases, and market intelligence to generate a dynamic win-probability score for each active opportunity. This score, derived from ML models evaluating client relationship depth, competitive intensity, and solution fit, directly informs a recommendation engine. The system automates the identification of which opportunities warrant executive sponsorship, additional proposal investment, or strategic pricing concessions, transforming business development from a reactive cost center to a proactive profit driver.




