1. Building the evidence and rigour – combining science and experience Bill Ryan

2. Outcome we want Development of technologies and innovations that, when implemented, makes the system more productive Science and agribusiness contribute to this process – but they are different

3. Science Understanding of the foundations and principles that underpin production Development of new technologies and management systems for primary industry Typically involves a reductionist approach and is not time bound

4. Science Needs to be peer reviewed Need to maintain our standards and capability We need to do the best science that we can for a range of reasons Strong Scientific rigour is an important part of the process

5. Agribusiness Technical aspects Financial management Labour and staff matters Logistics Other drivers for the business Involves all aspects of the business

6. Agribusiness Technical matter are only part of the complexity Can play a role in innovation – the “D” in all parts It is time bound and decisions have to be made Has its own rigour – if you don’t make money you don’t stay in business Deals with all the complexity of the business

7. Address three aspects that impact the pathway of technology development and adoption Information and data Innovation in implementing technology Other drivers for the business Explore how the two components interact

8. Underpins the foundation of all aspects of the business Often viewed differently by science and agribusiness Science aims to get the best possible data May not always be required Information and data

9. Analyse a given site in any year Only right 68% of the time Analyse with additional years and relevant sites increases the accuracy by 40% (MET analysis) Statisticians view MET analysis as superior Growers want individual site data – they do their own analysis National Variety testing Neither position is right or wrong – just different

10. Early weaning example Experiment at Flora Valley By year two had fed about 250 small calves Challenged by management for a diet to early wean 100,000 cows Making decisions on incomplete data Result was an additional 20,000 calves

11. Agribusiness often makes sound commercial decisions on limited data Data and information often viewed differently by science and agribusiness If working together need to understand and appreciate the differences Conclusions

12. Some innovation in research phase Often much more in the implementation or “D” phase Implementing early weaning on a whole station basis – implementing some of my own research  Required significant investment  Convince management and staff that it was feasible and would increase productivity Innovation in implementing technologies

13. First year  2 staff members  Cost of $3.27 / kg of gain By Year three  0.5 staff members  Cost of $0.56 / kg of gain Branding percentage increased 10% Unexpected benefits  Simplified management system on the station  Animals educated to feeding systems Innovation during implementation

14. No progress unless all involved are committed to the change Much more innovation during the implementation phase than the research phase  Example in soil amelioration work today More progress during this phase – often drives new research Fostering innovation  Real challenge for RDCs Key lessons

15. Key driver – making a profit Once this is consistently achieved other drivers can be many and varied Impacted by personal situations Examples  Schooling  Finishing harvest by Christmas Other drivers for the business

16. Impact of speed on harvesting efficiency Recent work by Kondinin Group

17. At 6 km/hr cover 7.7 ha/hr with 29 tonne throughput – high level of efficiency At 8 km/hr cover 10.3 ha/hr with 40 tonne throughput – greatly reduced efficiency  8% of all grain entering header is thrown out the back  Loss of 270 kg /ha or $80/ha Interaction of harvesting speed and crop density While not logical decisions are legitimate

18. To maximise impact of research and maximise innovation  All sectors must work together in partnership  They bring different but complementary skills to the table  While science may have the best possible numbers if the customer is not involved you won’t make any progress Where does this leave us