Top 3 data types collected by Australian livestock producers


There are vast amounts of data produced by Australian Livestock enterprises.

Here are the top 3 data types they collect and how they store it on farm.

Back in 2017, our data provider, KG2, was engaged to conduct a survey on behalf of the CSIRO and Agricultural Research Development Corporations using our farmer database.

This study was designed to benchmark Australian farmer’s needs, perceived risks and expectations regarding the digitalisation of agricultural and farm data (Jakku et al, 2017).

This was known as the “Precision to Decision “or P2D project, and KG2 spoke to 1000 Australian farmers about their thoughts and approach to farm data collection and use.

One of our last blogs talked about the top 3 data types Australian crop farmers collected, which you can read here.

In this blog, we’re going to talk about the 693 livestock producers who participated in the study, and the 91% who said they collected at least one type of farm data (Jakku et al, 2017).

1.  Financial data

Financial data had the highest collection rate amongst livestock producers at 79% (Jakku et al, 2017).

This data type was also the most collected amongst crop producers (Jakku et al, 2017), highlighting the importance of financial visibility and record keeping for managing enterprise operations, especially against the backdrop of market dynamics and increasing input prices.

But how useful is this data?

Livestock producers rated financial data as the most useful with an average score of 4.5 out of 5 (Jakku et al, 2017).

But how is this data stored?

68% of livestock producers stored financial data electronically on farm, followed by 21% storing it on paper on farm (Jakku et al, 2017).

Interestingly, pork producers had the highest rate of financial farm data collection compared to other livestock industries, however, this was with a sample of 15 (Jakku et al, 2017).

Farmer market research amongst individual livestock industry types would provide more robust insights regarding specific needs and perspectives towards to farm data use.

2.    Veterinary medicine records

Veterinary medicine record data had the second highest collection rate at 63%(Jakku et al, 2017).

Animal health, traceability and biosecurity are extremely important aspects of livestock production, so keeping track of medical data for animals is crucial in terms of productivity, market access and financial stability.

But how useful is this data?

Veterinary medicine record data received an average usefulness rating of 3.7 out of 5 (Jakku et al, 2017).

This data type plays a crucial role in demonstrating industry compliance and managing herd health, but it is also largely a requirement of livestock producers to collect such data in order to engage with key stakeholders for processing and transport.

But how is this data stored? 

65% of livestock producers stored this data type on farm on paper, whilst only 31% stored such data electronically on farm. (Jakku et al, 2017).

Digital veterinary medicine records can be viewed as more efficient when it comes to storing and transferring animal health information, which is to the benefit of farmers and stakeholders throughout livestock supply chains.

The problem with any digitised system in Agribusiness or rural Australia however, is that lack of technology, infrastructure or connectivity will create bottlenecks in the process.

3.    Animal breeding data

The third highest data collection rate was for animal breeding data at 57% (Jakku et al, 2017).

Tracking of breeding on farm and therefore genetics is important for livestock producers as it plays a large role in enhancing key livestock traits, be that wool production or feed conversion efficiency.

But how useful is this data?

Animal breed data received an average usefulness rating of 4.2 out of 5 (Jakku et al, 2017).

Pure bred and cross bred animals maximise different traits which may be highly prized in some markets but irrelevant in others.

Therefore, keeping track of breeding is crucial for farmers who aim to produce animals and meat products of certain specifications for key markets.

But how is this data stored?

53% stored animal breeding data on farm on paper, whereas 42% stored this data electronically on farm (Jakku et al, 2017).

While paper is the preferred storage method, electronic storage of such information does bring many benefits, particularly when it comes to benchmarking and tracking animal performance over time.

Having an electronic version of breeding records would be useful to keep track of not just what animal breeds are being maintained or crossed, but what the calving or lambing rate for certain animals are as well.

This combined with other data such as kill sheet information from a processor or feed intake and growth rate can provide a rich picture regarding animal performance.

The future of farm data in the livestock industry

The are many opportunities for data to be used in the Australian livestock industry.

Farm data can provide greater visibility for producers on the enterprise level whilst also enhancing traceability and biosecurity efforts on the national level.

Farmers are busy people, so the incentive to collect, store, manage and use data is largely influenced by the ease of such processes, financial cost and the benefit received.

A more recent study into the use of data throughout the Australian livestock industry could provide crucial insight in relation to changes since 2017. The KG2 farmer database is used by numerous agribusiness stakeholders for market research purposes, contributing the understanding and development of the Australian agricultural industry.

With the technological advancements occurring in the agribusiness space, it is paramount that farmer perception and use of data is understood, alongside the barriers they face in utilising data insights.

See the full P2D report here

Interested in learning more about engaging farmers using Agricultural Media? Get in touch to find out how the Allegiant Media team can help you target farmers with maximum efficiency and minimum waste on your next campaign.

This article was originally published on on February 24, 2021.

Source: Jakku, Emma; Zhang, Airong; Llewellyn, Rick. Producer survey to identify accelerating precision agriculture to decision agriculture (P2D) needs and issues. Final Report. Brisbane: CSIRO and Cotton Research and Development Corporation; 2017.