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Greenleaf Value chain scenario modelling

Project start date: 27 February 2015
Project end date: 20 June 2016
Publication date: 01 June 2016
Project status: Completed
Livestock species: Sheep, Goat, Lamb, Grassfed cattle, Grainfed cattle
Relevant regions: National
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This project is the first research stage in the development of decision support tools that will help companies manage the increasing complexity of product differentiation required to meet new and changing market demands for red-meat supply chains. Current data available for making decisions for supply chain value is not being utilised. Furthermore, MLA have identified a strong desire to support the Australian Red Meat industry by developing capability around objective measurements, supported by digital systems to improve red-meat industry productivity through better alignment of inputs to consumer needs.

Objective measurement data will more accurately describe livestock value and enable reward for higher value carcases. However, decisions made in carcase fabrication are required to achieve the most profitable mix of cuts and to sustain premiums. Combining these decisions on the supply and demand ends of a supply chain gives a myriad of possible pathways with significant differences in profit. Decision support tools are needed to support existing processes and the need will increase as objective measurements are developed.

This project confirmed most companies do not have the capability to manage these decisions on an ongoing commercial basis although a number recognise the need to develop this capability within their businesses in some form.

14 companies including producers, butcher shops, processors, value adders and retailers engaged in the project across beef and lamb supply chains and recognised the importance of these types of tools to their businesses in the immediate term. Six of these companies expressed a strong desire to develop and implement commercial versions of the prototypes within the next 12 months.

Live animal, carcase, primal, retail scan data and commodity pricing data were used in the modelling development.

Collaboration with 3 software companies during development of optimisation modelling prototypes demonstrated that profit maximisation models can be developed that increase supply chain value. Improved decision making in one retail supply chain example demonstrated a 45% increase in weekly profit as a result of improved cut breakdown and sales uplift.

Nine decision support modules listed below were demonstrated to add value through improved use of data. The four marked with asterix were proven in trial optimisation modules.

  • Category management*
  • Sales optimization*
  • Disassembly optimisation module*
  • Product development module
  • MSA product packaging module*
  • Livestock supply module
  • Livestock sourcing/pricing module
  • Supply Chain optimisation module
  • Global strategic positioning module

More information

Project manager: Joshua Whelan
Primary researcher: Greenleaf Enterprises Pty Limited