Dairy Victory Platform: A novel benchmarking platform to empower economic decisions on dairy farms

Abstract

In the face of diminishing economic margins, dairy farmers globally are compelled to maintain economic competitiveness. Benchmarking emerges as a strategic tool to establish new, achievable improvement objectives that balance ambition with practicality. This typically requires integrating diverse data sources, such as feed, milk production, diet, and market prices. However, many farms lack essential cow-level data like daily milk output and milk income over feed cost (IOFC), which hampers economic performance visibility and informed decision making. To address this challenge, we introduce Dairy Victory Platform (DVP), a novel cloud-based benchmarking platform designed to simplify complex analyses. The DVP uniquely calculates zootechnical and economic key performance indicators (KPI) at the cow and herd levels and benchmarks these against a dynamically selected cohort of farms, facilitating comparisons across various farm sizes, and milk production levels. The primary objective of this paper is to demonstrate the utility of DVP as a decision-making tool in supporting farmers and consultants with both operational and strategic decisions. It emphasizes leveraging benchmarking information to enhance decision-making processes, thereby highlighting the significant value that DVP brings to farmers, consultants, and dairy farm stakeholders. Our study analyzed data from 712 farms from December 2023, focusing on several KPI, such as milk production, milk quality, feed efficiency, and IOFC using DHI records. This approach showcases DVP's ability to use minimal data inputs for detailed analysis, leveraging peer performance to set desirable and achievable goals. We present a case study demonstrating how the DVP platform can guide dairy farms using anonymized peer data. This approach enables users to potentially improve their IOFC by up to 35%. Our findings highlight the potential of DVP as a powerful tool for generating insightful analyses, simulations, and recommendations, primarily from test-day data, but also integrated with market and estimated data. This supports more strategic decision-making in dairy management, including automatic goal-setting based on peer performance.