Supply chain data sources audit

Summary

In 2016, Meat & Livestock Australia (MLA) launched the Digital Value Chain Strategy (DVCS). The DVCS vision is for the red meat value chain to be utilising the world’s best digital technology by 2025. To enable this vision, the DVCS seeks to connect the red meat industry through shared industry datasets.

The purpose of this project was to engage with value chain participants to identify what data generators (products, platforms and services) are used within each node of the entire red meat value chain.

This project involved undertaking a deep dive into and exploring what data they generate; where this is stored; the challenges and gaps that they experience working with data; and how data can be used to address industry challenges.

Objectives

The object of this project was to provide a comprehensive review of:

• relevant data producers, i.e. the products, platforms and services in use by each node in the Red Meat Digital Value Chain
• how the relevant data generated is currently stored and used
• the volume, quality and velocity of relevant data
• gaps in the data and opportunities for enrichment
• priority data access requirements for each node (for example producers want access to carcass data etc)
• each node’s concerns and blockers regarding the sharing of data with other nodes in the supply chain including a comprehensive risk analysis and mitigation strategy for each blocker
• common (i.e industry wide) challenges and blockers.

Key findings

• A wealth of data is already shared but it is not seamless, transparent and consistent.
• Data volume, velocity, veracity (quality) and variety create challenges that need to be carefully managed and not all of the challenges will be solved by a data platform.
• Concerns and blockers exist across industry segments. Eleven blockers and concerns were expressed by different segments in the red meat value chain.
• Five key themes were universal across the red meat industry:

1. Willingness to share data is limited to certain situations and for certain purposes. There were concerns across all segments regarding open data sources being freely available. However, industry is open to data sharing for a specific issue or opportunity.
2. Data ownership and reuse rights are unclear and cause concern across the industry. Industry indicated that data ownership and the assignment of data rights and standards regarding the reuse of data are critically important.
3. Sharing data helps create trusted relationships. The stronger the relationship and regularly interactions between parties, the more likely operational data was shared in addition to transactional and performance data.
4. Few contracts for the sale of livestock address the sharing of data. A scan of contracts across a range of red meat processors revealed that few specifically addressed the issue of data ownership, data reuse, access and privacy.
5. The capability and capacity to make use of big data is unevenly distributed. Different value chain segments have varied skill and competency in making use of large volumes of data to drive decision making.

• Lastly, the project recommended twelve industry requirements that needed to be considered before advancing an industry data platform.

Benefits to industry

The key driver of the DVCS being to realise an estimated increase in red meat industry gross value of $2.9 billion per annum from digital technology adoption across the value chain. To enable this vision to be realised the DVCS seeks to connect the red meat industry through shared industry datasets.

MLA action

Based on the findings and recommendations that came out of the project, a follow-up project was completed to review current ISC data sets and identify the data opportunities that ISC should be prioritising.

In addition, the project findings will be used to inform the principles governing data use and sharing (to be formulated into an implementation guide). Lastly, the project will assist with pulling together a formal data catalogue and determining where MLA targets future efforts in connecting datasets.

Future research

Potential future areas of work to explore:

• interoperability of key systems
• digital literacy program for red meat industry participants to prepare them to optimise value from an industry data platform
• understanding data requirements of international supply chain partners
• ndertaking phase 2 of the supply chain data to extend into other input providers and red meat industry actors (ie. government bodies, veterinarians, breed organisations, etc).