Building the evidence and rigour – combining science and

experience

Bill Ryan

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

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

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

Agribusiness

Technical aspects

Financial management

Labour and staff matters

Logistics

Other drivers for the business

Involves all aspects of the business

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

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

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

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

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

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

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 researchRequired significant investmentConvince management and staff that it was

feasible and would increase productivity

Innovation in implementing technologies

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

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

Key driver – making a profit

Once this is consistently achieved other drivers can be many and varied

Impacted by personal situations

ExamplesSchoolingFinishing harvest by Christmas

Other drivers for the business

Impact of speed on harvesting efficiency

Recent work by Kondinin Group

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 efficiency8% of all grain entering header is thrown

out the backLoss of 270 kg /ha or $80/ha

Interaction of harvesting speed and crop density

While not logical decisions are legitimate

To maximise impact of research and maximise innovationAll sectors must work together in

partnershipThey bring different but complementary

skills to the tableWhile science may have the best

possible numbers if the customer is not involved you won’t make any progress

Where does this leave us