You would assume that those who appreciate something, would be more likely to use or adopt it. In the case of farm data, you would normally expect younger farmers to value data more…But is this actually the case?
Farm data, AgTech and Internet of Things (IoT) are terms that have all become associated with sustainable agriculture and modern agribusiness.
Technological advancements in the industry have placed increasing pressure on farmers to “digitise” and contribute granular insights to various platforms and service providers, all in the hope of improved efficiency and greater yields.
Despite the advancements and pressure, there are still numerous barriers to AgTech adoption and farm data collection.
Financial constraints and connectivity issues will undoubtedly stifle the proliferation of new technology, but what about psychological barriers? What about psychological influences over perceptions of farm data? How does this influence farmer perception and valuing of data insights?
Psychological barriers and perceived value of farm data
A farmer’s perspective and opinion towards technology and approaches to management will largely dictate their willingness to test and change.
An interesting analysis of farmer appreciation of the value of data can be found in the 2017 “Precision to Decision “or P2D project.
KG2 was engaged to conduct this study with 1000 Australian farmers on behalf of the CSIRO and Agricultural Research Development Corporations using our farmer database. The 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).
The study also analysed farmers appreciation for the value of data via hierarchical multiple regression, for both broadacre cropping industries and broadacre livestock industries (Jakku et al, 2017).
The following outlines some interesting findings from the analysis.
Broadacre cropping industries
For the broadacre cropping industry, the model indicated that maximising production as important, knowledge of telecommunications options and greater total number of data types collected “predicted greater data appreciation” (Jakku et al, 2017).
Interestingly, those with low levels of knowledge appreciated the value of data when they had collected more types of data (Jakku et al, 2017).
Broadacre livestock industries
In the broadacre livestock industry, poorer technical support for agricultural technologies, greater knowledge of telecommunication options and greater total number of data types collected were found to significantly predict greater data appreciation (Jakku et al, 2017).
Interestingly, those with higher levels of knowledge appreciated the value of data more “even when they had not collected as many data types” (Jakku et al, 2017).
Age and education
For both broadacre cropping and broadacre livestock industries, an association between education and data appreciation was found when only demographic variables were considered in the model (Jakku et al, 2017).
Adding more variables to the model however then revealed age as only significantly associated with data appreciation in broadacre livestock industries, i.e younger farmer appreciated the value of data more than those older than them (Jakku et al, 2017).
So what does this mean for the Australian agricultural industry?
Some key takeaways from these findings include not only the role of age over opinions toward data, but also experience and understanding.
Agricultural market research using our farmer database has consistently revealed underlying psychological influences over farmers decisions and opinions. This is revealed not only in our Five Faces of Australian Agriculture segmentation model, but also in cross sectional market research studies for clients via qualitative insights.
When it comes to understanding how much Australian producers value farm data, there is always a contextual backdrop to their experience. Understanding this backdrop then reveals influences over farmer’s willingness to try new technologies, data collection methods and software applications.
Engaging farmers, exposing them to data driven technologies and building their understanding will be key in driving greater awareness and adoption of farm data tools.
These tools when combined with greater rural connectivity can help to improve the efficiency and performance of Australian agriculture, providing enhanced visibility over enterprise operations and the industry as a whole.
See the full P2D report and regression analysis here
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. http://hdl.handle.net/102.100.100/87458?index=1