Unlocking the value of data that currently exists and is accessible by MLA across the red meat industry value chain
Location: Any of the MLA offices in North Sydney NSW, Armidale NSW or Brisbane QLD
Duration: 5 months
- Ability to problem solve and synthesize complex issues in the fields of computer science, data science and any knowledge of agricultural systems
- Economic modelling using Microsoft Excel, Microsoft Access, or equivalent software program
- Report writing in Microsoft Word
MLA is leading the development of a Digital Value Chain strategy with industry to enable the seamless capture, integration and interpretation of the vast and increasing range of data that’s being generated through new and existing technology in the red meat industry.
Maximising information exchange will ensure the red meat industry produces what their markets need more sustainably and profitably. Improved communication will also increase the capacity of all industry players to embrace new technology – and the use of meaningful data in their own business. But to achieve this MLA needs collaboration across industry and with the world’s best innovation companies.
Producers, processors, logistics companies, retailers and consumers are faced daily with a plethora of concepts and solutions that all fit within the auspices of a digital strategy. The feedback to MLA from stakeholders across the industry is they don’t know:
- what is real
- how it can be used
- is it of value to them
- which options to choose
- how do I use it within my business
- who owns the data
- what do I do with the data and do I need new analytical skills, and
- will I be better off or is this just a passing fad?
This project will focus on conducting background research to address the questions above. There already exists a huge amount of information in our industry and a key outcome will be to identify all the data, who owns it and where it can add value.
Current data sources include: Eating quality, Carcase compliance, Livestock movements and location history, Animal health information & Genetics
Research to be conducted
- Identify the core datasets, along with Master Data & Quality strategies to bring those datasets together for analysis.
- Identify any missing attributes that may need to be added to the datasets to achieve the project outcomes.
- Develop innovative models and analytics that demonstrate how the datasets can create additional value that does not currently exist.
The expected outcome of this research would be a feasibility report that would outline the potential value propositions for different users to access the industry data. While the project would need to identify the barriers to linking the data, the benefits would need to be analysed in isolation of these challenges.
The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.
It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 50% of their time on-site with the industry partner. The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
To participate in the AMSI Intern program, all applicants must satisfy the following criteria:
- Be a PhD or Masters student currently enrolled at an AMSI member institution.
- PhD or Masters by Research candidature must be confirmed.
- Applicants must have the written approval of their Principal Supervisor to undertake the internship. This approval must be submitted at the time of application.
- Internships are also subject to any requirements stipulated by the student’s and the academic mentor’s university.
4 June 2017
INT – 0317