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P.PSH.1238 - Demonstrating the value of an end to end feedback system for the beef supply chain

Improving labour efficiency reduces the overhead cost structure of a beef business.

Project start date: 06 February 2020
Project end date: 29 May 2022
Publication date: 02 May 2024
Project status: Completed
Livestock species: Grain-fed Cattle, Grass-fed Cattle
Relevant regions: National
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Summary

The purpose of this project is to pilot an end-to-end feedback system in a vertically integrated beef supply chain using processing intelligence for data capture and predictive analytics. The pilot demonstrates how individual animal data made available through the supply chain as well as ISC’s data platform and applications (such as Livestock Data Link) can be extracted and analysed to provide feedback and insights to the various stakeholders in the beef supply chain. It shows how this information can be used for decision support to improve the overall outcomes of the beef supply chain.

Objectives

The overall objective was to provide supply and demand visibility across the supply chain through the development of decision support that achieves 'the right animal for the right market at the right time'. Fundamental to this process was the identification of individual animal data from breeding, backgrounding, feed lotting, and processing required to provide the necessary insights to achieve the objective.

Additional objectives included the identification of gaps in existing capabilities and capacities in data capture and management. Design and development of a cloud based (open access) system that accommodates diverse data sources and formats. Provision of a use case in establishing and improving the Red Meat Integrity System through valuable learnings of key programs (i.e., ISC data platform, LDL and eNVD) integrating with a solution provider system (Hitachi) and a supply chain system (ACC-ACBU).

Identification of the value of industry data and the opportunities of integration with ISC’s data platform. Evaluation of the outcomes of the on-farm pilot data management system and extrapolation across the supply chain. Provision of a clear journey map to digital agriculture transformation for each participant in the red meat supply chain.

Key findings

• Integration of the various systems from farm to processing is achievable at an individual animal level.
• The insights produced from this integration can improve the overall yield, efficiency and ultimately profitability across an integrated beef supply chain.
• The co-created framework for end-to-end feedback across the beef supply chain was operationalised through an IT artifact which proved that a combination of low code user interface development and appropriate use of public cloud infrastructure provides an effective platform for widespread deployment of a Connected Beef Supply Chain Control Tower.

Benefits to industry

• A Connected Beef Supply Chain Tower (Beef SCCT) can be provided to small, medium, and large businesses cost effectively.
• The ability to multi-tenant an overall Beef SCCT i.e., the core solution is designed and containerised in such a manner that a single instance of the solution may serve multiple customers provides the opportunity for a peak body such as MLA or Integrity Systems Company to provide this service to their stakeholders.
• The deeper insights provided by the Beef SCCT not only benefit those businesses with integrated beef supply chains they also benefit the individual supply chain partners who run standalone businesses e.g., breeding, or backgrounding farms, feedlots, or processing plants.

MLA action

The capability exists to expand the Beef SCCT as it provides the framework for extending environmental solutions.

Future research

• The Beef SCCT project has focused on conventional meat quality feedback data as provided via the ISC Livestock Data Link system. Opportunities exist to extend the research to include the new objective carcase measurement technologies that have been developed by MLA. The connection of this data to the data collected during the life cycle of an animal will provide significant insights into contributing factors from genetics to practices and procedures that contribute to high yield and quality.
• The capability exists to expand the Beef SCCT to include simulation and digital twining.
• The core architecture of the Beef SCCT provides the framework for extending the solution to facilitate the identification and measurement of Scope 3 Green House Gas Emissions as defined by the GHG Protocol and Emissions Reduction Fund.

More information

Project manager: Dean Gutzke
Contact email: reports@mla.com.au
Primary researcher: Hitachi Consulting Australia