Advanced Livestock Marketing Analytics and Market Reporting for Cattle and Sheep
Location: Sydney CBD, NSW
Duration: 4 months
Proposed start date: ASAP
Keywords: .Net, C#, SQL, Microsoft BI, and Azure, Mathematical Modelling, Data Science, Computer Science
AuctionsPlus is Australia’s online marketplace for livestock. Established in 1986, well before the internet and on-farm computers in Australia. AuctionsPlus has become the largest and most trusted marketplace for livestock over the past 3 years. Livestock are sold by description with photos and videos in online weekly sales where buyers compete for stock from all over Australia. All stock must be assessed (judged) by an accredited assessor that has been licensed by AuctionsPlus and they objectively measure the livestock.
Stock sold across Australia are subject to different environmental factors and price fluctuations. Historically most stock have been sold in a physical auction where a small number of buyers attend the auction and compete for the animals via an auction system. By introducing the online marketplace we now see 300+ buyers at each sale with animals travelling across the whole of Australia.
The business has experienced rapid growth over the past 3 years and now facilitates the exchange of over $770 million worth of livestock each year – approximately 450,000 cattle and 2.75 million sheep. One of the challenges AuctionPlus faces is that they have a huge amount of structured data and have not established a way to deliver insights and market intel to users and the broader market. They have approximately 52,000 unique people visiting the website each month – www.auctionsplus.com.au and would like to be able to deliver to them better market indicators that are personalised to their regions and stock types. There are also no live market indicators that cover the entire supply chain that producers can use to assist in determining the true value of their livestock. See article on BeefCentral describing lack of transparency on pricing – http://www.beefcentral.com/news/mick-keogh-explains-accc-beef-and-cattle-market-study-findings/.
AuctionPlus believe that there is an opportunity to utilise their dataset alongside other available datasets to provide better insights into the livestock market reporting. They are seeking assistance in getting control of, cleansing, storing and analysing data for valuable insights. They also want to look at the data in different ways and learn how they could use it in the future to deliver insights to customers. This requires fresh eyes and an understanding of how to pull personalised insights from the dataset.
They use Azure and Microsoft BI as hosts and are interested at looking at new tools and technologies to bring into the business and store data so they can then learn how to derive valuable information and useful feedback to the customer for a better more focussed experience. This could include subscription models or ways in which to provide snapshots of personalised data to individuals.
Research to be Conducted
Research would focus on:
• Investigate existing regional market data for livestock on price and other value add features across stock categories and regions
• Build a prototype live livestock analytics model that delivers insights on the market in a real-time environment that can predict the impact of marketing decisions.
• Collate the AuctionsPlus data with industry data to provide insights/price discovery across alternative sales channels
• Assist/provide insights that drive farmers to put realistic price reserves on their stock
We are looking for a PhD student with the following skills:
• .Net, C#, SQL, Microsoft BI, and Azure
• Mathematical Modelling, Data Science, Computer Science
Identify what are the actual market drivers in livestock sales by anaylsing a huge amount of current stored data to generate better more timely and accurate insights into livestock market reporting. As an organisation AuctionsPlus needs to establish how they can cleanse the data, warehouse the data in a way that it is accessible to industry, compare the various sales channels and identify insights that can assist in better decisions for the entire supply chain.
AuctionsPlus also see an opportunity to set the example to a conservative industry. By sharing data across the supply chain they hope to strengthen the entire industry and provide feedback to producers around how they can improve their products – value adding to their production.
Potentially a live modelling tool could be developed from prototype that can be used by internal and external customers to assist in better understanding market drivers. Developing a prototype live livestock analytics model that delivers insights on the market in a real-time environment that can predict the impact of marketing decisions would position AuctionsPlus as a true market leader in livestock sales. Additionally it would dramatically improve customer experiences, provide a more effective use of data and potentially cost savings to the business through greater understanding of variables and market efficiencies.
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 80% 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 APR.Intern program, all applicants must satisfy the following criteria:
• Be a PhD student currently enrolled at an Australian university
• PhD 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
29 April 2018
INT – 0407