Using data to back decisions along the entire supply chain

One of the world’s largest cattle supply chains, Australian Country Choice (ACC) is increasingly relying on data-driven decisions.

ACC recently developed its data capture, integration and reporting systems, connecting every segment of the value chain to transform how it makes decisions across 1.75 million hectares of land, three feedlots and a Brisbane processing facility.

Maintaining oversight of the entire value chain has given ACC management a clearer picture of the impact, profitability and efficiency of their investment in technology.

Here’s a snapshot of how they’ve linked data capture, input and analysis from farm to processing facility, and ultimately, to market.

Adopting new technologies

ACC partnered with MLA’s Co-Innovation program to employ specialist staff to enhance digital capability and employee engagement in a project to improve data integration across its farms, processing plant and markets. Collectively they called these roles the ‘data lab’.

This was not simply a ‘set and forget’ process – rather, it required ongoing monitoring to overcome the challenges ACC faced to maintain quality data across all sectors of the business.

These challenges included:

• connectivity issues which delayed data replication
• manual data syncing which disrupted day-to-day operations
• limited technical support for on-the-spot resolution
• making sure staff understood the benefits to them and the company.

A solution was to implement automated systems across ACC’s businesses, to provide timely and meaningful information.

1. On-farm

ACC now uses semi-automatic crush side data collection as part of day-to-day farm operations to collect critical cattle data, including:

• breed
• weight
• dentition
• sex
• Bos indicus content
• pregnancy status
• body condition score.

With this information, up-to-date dashboards are generated on various profit drivers – including fertility, average daily gain (ADG) and feedback on genetic traits.

ACC Agribusiness Analyst, Lauren Evans said an important part of integrating new technologies was to train all staff in using the reporting software.

“We created a ‘leading from behind’ culture, which made sure operational teams provided input in all stages of the project – this promoted engagement and buy in, ensuring a smooth transition into this new data collection process,” Lauren said.

Collecting production data over several years has allowed the business to understand the importance of several key traits and their contribution to individual animal performance and value. Collecting data has help improve management decisions across the business and contributed to:

• shortened calving window
• improved calf survival
• improved predictions of when cattle will reach feedlot entry weight, to inform processing schedules
• improved stocking rate and turnoff decisions
• successful registration of a beef cattle herd management carbon project, as well as improved understanding of individual methane emissions.

Lessons learned:

• Provide training and support for staff as they implement changes, so the whole team works together to build a system which has the least amount of disruption and maintains data integrity.
• Collect as much data as necessary to create a complete picture of individual animal performance.

2. Processing

ACC Processing Analyst, Lewis Habraken, said the processing facility component of the project focused on using data to create daily snapshots of profitability and ‘whole of life’ animal performance.

This was done using:

• Digital infrastructure: Hot carcase scanning to predict lean meat yield, eating quality and marble score supporting the goal of sorting carcases for boning prior to entering the chiller.
• Automated reporting: Improved monitoring and traceability of out-of-spec carcases, to identify the cause of non-compliance and link to factors such as vendor, breed or operational and transport activities.
• Whole of life reporting: The ability to quickly identify high- and low-performing cattle and carcases so the business can develop strategies to remove low-performing cattle earlier in the production process.

“This reporting has allowed us to better understand individual animal performance. It’s generated more complete datasets on cattle which can be taken back to the producer so they can identify where changes can be made on-farm, to improve productivity and profitability,” Lewis said.

Lessons learned:

• Small changes in daily efficiency gains can add up to significant annual dollar-value savings for the business.
• Without detailed data, opportunities for improvement are not always obvious.
• Access to quality data is critical to help build better cost/benefit calculations for capital-expenditure decisions.

3. Market

ACC now draws on the data and insights generated on-farm and in the processing plant to fine-tune its strategy of marketing its beef products.

During this project, a forecasting tool and carcase utilisation model was developed to manage sales and other commitments in advance. This means ACC’s beef products can be more proactively managed to minimise unnecessary expenses, and sales to new customers can be optimised.

Chris Lutton, Market Analyst, said development of these systems has improved understanding on how ACC can optimise production.

“Along with new carcase utilisation models, we’ve been able to use our sales data to inform decision-making at all steps of the business. Feedback and demand-planning at the farm gate will help determine cattle that producers breed, keep, feed and buy to support their business goals,” Chris said.

Lessons learned:

• Full supply chain data shows the true profitability of the business, gate to plate.
• Forecasting and utilisation tools help prioritise markets and product development opportunities.
• Data can help identify and remove low-performing cattle earlier, creating an opportunity to increase business efficiency.

Lessons learned for wider industry

Linking data from farm to processing facility to market has supported better insights about the impact of practices and processes across the supply chain to drive improved decision making.

For ACC, this data works to optimise performance drivers through the supply chain to ensure the business remains sustainable, and produces high-quality, consistent products every time.

Merrick Studders, ACC's Chief Commercial Officer, said the insights from this project can be applied to other businesses in the red meat industry.

“For others looking to improve capacity in their own business, this project has demonstrated how data can be collected, integrated and analysed efficiently, and used to make more-informed decisions across the supply chain.”

He said key areas all red meat business operators could focus on to capture efficiencies from data include:

• using individual cattle data to measure overall emissions intensity
• improving animal fertility and performance, to reduce emissions intensity
• aligning product with consumer expectations
• lowering production costs through greater efficiencies
• the ability to demonstrate animal welfare and wellbeing practices
• combining data from other tools – such as satellite imagery and predictive modelling for pasture biomass, rainfall and feed availability – to link livestock production data with environmental production data.

Data has allowed ACC to improve production, and these focused roles and processes have been a critical part of the journey.