Modernizing Targeting to Close the Field Execution Gap - with Damion Nero of Daiichi Sankyo

2026-06-10 · Source: The AI in Business Podcast · Field: Health & Wellbeing — Pharmaceuticals & Biotechnology, Artificial Intelligence & Machine Learning, Operations & Process Management · Depth: Intermediate, extended

Summary

Pharma commercial teams are struggling with a "field execution gap," where critical intelligence arrives too late to influence sales representative behavior. Damion Nero, Global Head of Statistics at Daiichi Sankyo, identifies fragmented data pipelines, rather than a lack of data, as the core structural issue. While dynamic targeting adoption in large pharma increased from 17% in 2023 to 25%, three-quarters of the industry still relies on outdated models. Successful AI adoption prioritizes routine, high-certainty use cases, which consistently deliver more commercial lift than ambitious automation. Organizations that excel often insource data processes or utilize specialized vendors to build integrated systems for rapid, curated information dissemination, aiming to augment human capabilities. One case study showed a 25% increase in rep productivity over 18 months by shifting to weekly targeting recommendations.

Key takeaway

For Directors of AI/ML or Operations Professionals in pharma aiming to close the field execution gap, prioritize integrating fragmented data pipelines to deliver timely intelligence. Focus AI investments on automating routine administrative tasks for field reps, freeing them to build essential HCP relationships. This approach, proven to boost rep productivity by 25% with weekly targeting, fosters organizational trust and yields greater commercial lift than chasing ambitious, unproven automation. Your strategy should augment human capabilities, not seek to replace them.

Key insights

Fragmented data pipelines, not data scarcity, cause pharma's commercial field execution gap, delaying actionable intelligence.

Principles

• Prioritize routine, high-certainty AI use cases.
• AI should augment human skills, not replace them.
• Underinvestment in data infrastructure creates delays.

Method

Build integrated data pipelines for ingestion, transformation, and operationalization to ensure timely intelligence delivery to field teams. Focus on curating data from multiple sources for customizable reports.

In practice

• Implement weekly targeting recommendations.
• Automate administrative tasks for reps.
• Develop in-house data dissemination processes.

Topics

• Pharma Commercial Operations
• Field Execution Gap
• AI Adoption Strategy
• Dynamic Targeting
• Data Pipeline Integration
• Sales Force Productivity

Best for: CTO, VP of Engineering/Data, Executive, Director of AI/ML, Consultant, Operations Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI in Business Podcast.