P.PSH.1300 - Digitalisation Pilot of Operational & Supply chain Data Management
While many agree that full traceability minimises the impact of livestock issues, advancements in blockchain and AI systems are likely to unlock further analytics and decision-making support in the future.
| Project start date: | 19 April 2021 |
| Project end date: | 30 September 2022 |
| Publication date: | 23 April 2024 |
| Project status: | Completed |
| Livestock species: | Grain-fed Cattle, Grass-fed Cattle |
| Relevant regions: | National |
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Summary
The agricultural industry involves production supply chains which spans across a vast network of on-farm and off-farm activities that involve multiple parties and organisations. When it comes to the collection and management of agricultural production data, significant gaps are common, however when data does exist, it is often fragmented and disparate.
Without ways to address these data management gaps, producers and downstream food and beverage processors resort to intuition when managing their own production activities and associated data sets. Consolidating data and bridging these gaps has the dual effect of providing producers and supply chain participants with a complete and comprehensive knowledgebase to achieve detailed operational insights, and secondly it facilities with improved transparency, traceability, and provenance of end-products for customers within local and global markets.
AxisTech together with the participation of Stone Axe Pastoral Company aimed to unlock their data and identify opportunities for analysis using a complete and unbroken set of data records from product code right back to animal genetics and lifecycle.
Objectives
Our key objective was to demonstrate the AxisStream data management platform that integrates data from a range of installed devices and software at Stone Axe’s properties. This data was consolidated into the platform where data is completely owned and controlled by Stone Axe with the aim to achieve unimpaired and comprehensive operational insights for the producer and supply chain participants into their operations using this data.
This project included several key activities listed below which formed the project deliverables:
• ingestion of off-farm data
• ingestion of on-farm data
• scoping study: industrial blockchain – Ripe
• scoping study: meat processors
• scoping study: data sharing
Key findings
Collaboration between all parties along the supply chain is challenging, especially when it comes to technology and innovation. The willingness to participate, establish trust and communicate clear benefits for participation are all crucial factors for projects such as this to be successful.
Digitisation process and management: this is the building block for data transformation, standardisation and making it accessible for sending streamlined data along the supply chain.
This also enables and supports data flows and feedback loops with other external systems thus, establishing the interoperability and reuse of data.
On-farm and off-farm data synchronisation: having a synced database into Stockbook would be highly beneficial for Stone Axe’s business processes and streamlining data flows.
Meat processors: Elevated levels of concern regarding privacy around technological solutions for operational and production management and a reluctance to engage with Ag-tech providers.
Data sharing:
• Trust: It is essential to establish trust between supply chain parties to procure complete participation in digitisation and supply chain projects.
• Time: Onboarding of participants takes time thus, this time must be available in order to commit with engagement in projects.
Benefits to industry
• Time savings: by reducing the time required for document/data collection, standardisation, and aggregation and collation of data sets for ongoing reporting requirements.
• Cost savings: decreased labour costs related to time savings above, in addition to reducing and improving production input costs. For example, by analysing historical and current operational data (e.g., fertiliser, treatments, and livestock feed; cost, intake, wastage etc.) combined with, weather forecasts and trends, producers can improve their feed budgets, inventories, treatments, and application rates to reduce production input costs and wastage.
• Genetic improvements: the evaluation of breeding performance and meat processor data, would lead to improved genetic selection and breeding plans resulting in superior consumer end-products, expanded market access and increase their overall profitability.
• Increased productivity: from genetic improvements and time savings above. Time saved can then be allocated towards enterprise expansion, development and refining on-farm processes.
• Sustainability, GHG, ESG, Natural Capital reporting: Value can be derived from increased efficiency, traceability, the ability to analyse product safety, quality, and sustainability with verifiable data.
MLA action
Create increased awareness from red meat livestock case studies that embrace a digital culture.
Future research
Future research opportunities from this project include:
• develop a widget tool for Stockbook within the AxisStream platform
• investigate the reluctance of supply chain participants to engage in collaborative and integrated supply chain solution studies.
Data planning and collection can be a large undertaking for any business, especially when having to access data from disparate sources and for a range of locations. It is essential that adequate resources and hours allocated to achieve this task is committed to by businesses completing any data project such as this.
More information
| Project manager: | John McGuren |
| Contact email: | reports@mla.com.au |
| Primary researcher: | AxisTech Pty Ltd |
