SAS® Analytics help to support more productive and profitable agri-business in Ireland
Ireland's national agriculture and food development authority uses analytics...
Employing 1,300 staff at 80 locations, and with an annual budget of more than €170 million, Teagasc is Ireland's agriculture and food development body. Providing integrated research and development, advisory and training services, the semi-state authority's mission is to support science-based innovation in the agri-food sector and broader bioeconomy to improve profitability, competitiveness and sustainability.
Research to drive that innovation is a key activity - and has been supported by SAS® Analytics for 15 years. Indeed, 40 percent of Teagasc's budget is devoted to research, with the remainder divided equally between advisory and education services. The results of this essential work inform legislation and government policy and improve operations on farms and in other agribusinesses to make the sector more productive and competitive in general.
Supporting profitable growth
"Agriculture is still a very important part of the Irish economy, and we're dedicated to supporting the industry through research, advice and education," says Dr. Jim Grant, Statistician in Teagasc's Research Support Team. "The fundamental aim of our research is to help improve productivity – and SAS has been the statistical tool of choice in Teagasc for a long time."
With 150 scientists, 70 specialists and 160 technicians providing research services from seven dedicated centres, Grant says the ideal process sees a research project being completed followed by "technology transfer" to farmers and other clients via Teagasc's advisory service, with educational support helping to ensure organisations can implement changes in the most effective ways. In the Irish Gaelic language, Teagasc means instruction.
The research undertaken is varied, ranging from highly applied work that takes a problem-solving approach – for example, working closely with mushroom producers to solve specific production problems – to more fundamental academic research: for example, genetics in dairying and sheep farming.
Grant's role is to help Teagasc researchers by providing more advanced analytical inputs. "The biggest challenge I face, in broad terms, is the wide range of areas I have to cover," he continues. "One of the most important things, for me, is to have tools and procedures I can assimilate quickly and with which I can work with ease. I need to respond to requests quickly, and in areas that I've not necessarily covered before."
SAS has supported Teagasc's work for around 15 years, and is currently used by 50 people. "As far as I'm concerned, SAS provides the best possible solution for my work," Grant says. With other statistical tools available at Teagasc, Grant adds, "When other packages let me down, I find that I can turn to SAS and it will take up the slack."
Shaping agricultural practices
In terms of his day-to-day activity, Grant says, "Researchers contact me when they realise they've left their comfort zone in statistics." His input is then largely based around experimental design or survey work. "We supply the more advanced capabilities that Teagasc researchers often need, and I primarily work with mixed models. SAS is extremely flexible in this area, in terms of supporting my work."
Recent analyses have covered environmental work looking at the impact on de-nitrification of adding materials to water wells, with a resulting paper published in the Ecological Engineering journal. In other examples, Grant's analyses have involved extracting information beyond standard approaches in groundwater and surface water movement research, plus the systematic design of forestry trials.
Grant operates in a dynamic and varied environment – which demands high levels of flexibility allied with power in analytics. "A large part of what happens in our research programs is fairly straightforward, in terms of design and analysis," he says. "But when more complex issues crop up, we get involved. I'm typically working across a wide range of areas at the same time, so I need that flexibility, and a tool with which I'm not only familiar but also makes a lot of procedures available, so I can use it quickly."
Results from SAS analyses have a direct impact on policy, and on farming and agri-food practices in the field. "The information we produce goes up the line into legislation and down the line into improving operations on farms." Grant says. "Various other important areas are also dependent on our results – for instance, administering certain grant schemes, such as in forestry.
"SAS gives me the ability to implement what I believe is needed in my analysis. I can look at a problem, decide what should be done, then find the right tool to deal with it. SAS is our preferred solution, and enables me to work quickly and effectively."
Grant says he also benefits from the SAS Support website and the examples, case histories, conference papers and documentation it provides. "That's all very useful when I have a particular problem to fix." He adds, "I always aim to provide added value in my work, going beyond a researcher's original query. Often I come across something interesting, perhaps an area the researcher hadn't noticed. Being able to programme in SAS, to simulate things, is very convenient and helps with that. SAS is very good at supporting our work – it's the de facto standard in Teagasc and has been for a long time. It's very flexible, offers a wide range of procedures, and is well supported."
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Faster and more effective analysis, helping the Research Support Team deliver new results and insights covering diverse research programmes; real-life outcomes include influencing agricultural and other legislation and improving operations on farms, having a positive impact on the sector's productivity, profitability and sustainability.
“The biggest challenge is the range of areas I have to cover. Our research is focused on helping improve productivity, and SAS has been our preferred solution for a long time. I can look at a problem, decide what to do, and then deal with it.”
Dr Jim Grant
Statistician, Research Support Team