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Supply Chain Network Optimisation by GRA for Electronic Maintenance and Repair Agency

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GRA , a leading supply chain consultancy and logistics management company in Australia offered their supply chain network optimisation services to an electronic maintenance and repair agency.

While requesting a review of their current maintenance, storage and distribution network, the client sought GRA’s advice on identifying opportunities to reduce whole of life support costs, increase network capacity, improve customer service delivery and assess infrastructure requirements.

Key challenges: 

  • To optimise a network fragmented by autonomous business units with mutually exclusive budgets and no ‘end-to-end’ performance management
  • To maintain support to obsolescent and obsolete electronic equipment at reduced total network cost 
  • To increase network capacity for the support of new electronic equipment at reduced total network cost


A project was commissioned to identify the network capacity and cost reduction opportunities across people, process and systems. 


This phase of the project involved interviews with staff, manufacturers and service providers to gauge the balance between process and practice as well as the culture of the industry sector players.


The process phase involved analysis of support plans, service agreements and contracts within and between business units as well as the broader industry community.

Additionally, future delivery models for maintenance, storage and distribution were identified.  


The system phase involved data extraction and analysis of corporate maintenance, storage and distribution data as well as merging of the data to form a network perspective.

Performance was assessed with an end-to-end review of the supply chain while technology was evaluated to identify obsolete systems as well as new system requirements.

Key findings:

  • Visibility of end-to-end network performance highlighted the need to:
    • Change from a linear network to a multi-echelon network with a potential reduction in Time to Make Serviceable of 55%
    • Remove repetition of maintenance effort by moving configuration and diagnostic data with the equipment, enabling a potential reduction in average Actual Repair Time per repair of 21% for Medium Grade Repair and 12% for Heavy Grade Repair
    • Reduce network support to obsolescent/obsolete equipment by reducing the asset liability to match actual demand for the asset
    • Enable cost savings in business units of the network to offset increased costs in other business units where the net benefit is optimised  
  • Infrastructure for new technology equipment will require less volume per item but have greater complexity

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