OneVision RetEx with Veeva

This video provides a demonstration of the OneVision Retail Execution (RetEx) module's integration with Veeva CRM, showcasing a streamlined workflow designed to optimize in-store product monitoring and inventory checks for field sales representatives. The core purpose is to illustrate how specialized computer vision technology can be seamlessly embedded within the pharmaceutical industry's leading commercial platform to enhance compliance and sales effectiveness at the point of sale. The demonstration focuses on efficiency, real-time data capture, and immediate analytical feedback, minimizing the administrative burden on field teams.

The workflow begins within Veeva CRM, where the user initiates the store check activity by tapping a link that directs them to the OneVision RetEx application. Upon landing, the user is presented with a list of products requiring monitoring. The critical step involves leveraging the device’s camera, which activates the OneVision hybrid engine. This engine utilizes advanced computer vision technology to recognize brands and products down to the single Stock Keeping Unit (SKU) level simply by analyzing a photograph of the shelf. A significant feature highlighted is the engine’s ability to perform this recognition in real-time, even when the device is in "airplane mode," eliminating reliance on constant internet connectivity—a crucial requirement for field operations in varying geographic locations.

Following the data capture, the system immediately processes the visual information and provides the user with real-time analytics directly within the store check window. These immediate insights offer an overview of the point of sale, specifically detailing the "share of facings" and "share of shelf" for the monitored products, allowing the representative to compare their findings against established market share data. This instant feedback loop empowers the field team to make tactical decisions and adjustments while still on-site. For deeper strategic analysis, headquarters staff access in-depth Tableau analytics available through the OneVision web application, enabling comprehensive trend analysis and performance tracking across multiple points of sale. Finally, the collected data is synchronized back into Veeva CRM, populating the inventory monitoring section. This ensures that Veeva remains the central system of record, providing the representative with a complete, updated data set to continue their subsequent activities at that specific point of sale.

Key Takeaways:

• Seamless Veeva CRM Orchestration: The video demonstrates Veeva CRM’s role as the primary platform for initiating and concluding field activities, proving that specialized tools can be effectively integrated to extend Veeva’s functionality without disrupting the core user experience or data governance structure.

• Offline AI Execution is Critical: The ability of the OneVision hybrid engine to perform real-time SKU recognition in "airplane mode" (offline) is a vital capability for life sciences field teams, ensuring data capture and operational continuity even in areas with poor or non-existent cellular connectivity.

• Computer Vision for Compliance and Inventory: Utilizing computer vision to monitor "share of facings" and "share of shelf" automates the auditing process, ensuring planogram compliance and accurate inventory data capture, which is essential for optimizing commercial supply chain and promotional spend.

• Real-Time Analytical Feedback Loop: Providing immediate analytics to the field representative—such as comparing observed shelf share against market share—transforms the representative from a data collector into a strategic decision-maker, enabling instant course correction and maximizing the impact of the store visit.

• Data Engineering for BI Integration: The reliance on "in-depth Tableau analytics" for headquarters staff emphasizes the necessity of robust data engineering pipelines capable of integrating high-volume, unstructured visual data (from the recognition engine) with structured CRM data for comprehensive business intelligence reporting.

• Focus on Commercial Operations Metrics: The specific metrics highlighted ("share of facings," "share of shelf") are core indicators for commercial success in retail environments, demonstrating a direct link between the technology and key performance indicators for pharmaceutical consumer health or medical device sales.

• Extending Veeva Investment: This integration model serves as a blueprint for IntuitionLabs.ai clients seeking to maximize their existing Veeva investment by integrating specialized, AI-powered modules that address niche commercial challenges, rather than relying solely on standard Veeva functionality.

• Bidirectional Data Synchronization: The final step of synchronizing the captured store check data back into the Veeva CRM inventory monitoring section ensures data integrity and provides a unified view of commercial execution, eliminating data silos between specialized field tools and the enterprise CRM.

• Hybrid Engine Methodology: The concept of a "hybrid engine" suggests a combination of local processing (for offline recognition) and cloud processing (for deeper analytics and synchronization), offering a balanced approach to performance, data security, and regulatory compliance.

Tools/Resources Mentioned:

• Veeva CRM
• OneVision RetEx (Retail Execution module)
• OneVision Hybrid Engine (Computer Vision/Recognition Technology)
• Tableau (for in-depth web application analytics)

Key Concepts:

• Retail Execution (RetEx): The process of ensuring that products are correctly displayed, priced, and stocked at the point of sale, often involving field audits and compliance checks.
• Share of Facings/Share of Shelf: Key commercial metrics measuring the amount of physical shelf space a product occupies relative to its competitors, directly impacting visibility and sales.
• SKU (Stock Keeping Unit): A specific, identifiable product item used for inventory tracking and management.
• Computer Vision: An AI technology used here to enable machines to "see" and interpret visual data (photos of shelves) to automatically identify and count products.