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Agillence optimization engines sit on our web-based proprietary infrastructure.  The architecture allows rapid deployment of the optimization solutions, via 'Software as a Service" agreement . 


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ASCD (Agillence Supply Chain Designer)


ASCD is a supply chain design tool, especially powerful where your business requires multi-stop shipments.  It optimizes simultaneously multi-stop route territory (outbound from warehouses) and upper echelon supply chain together.





ASCD is a tool to design supply chain network optimizing several cost factors while respecting various constraints such as capacities.  A simple example, but challenging as shown in the picture above, is to trade off inbound costs, warehousing/inventory carrying costs at DC's and outbound costs where outbound involves multi-stop routes with delivery frequency requirements.  To have an implementable solution, it is essential to model multi-stop delivery cost accurately considering delivery frequency requirements.


The following questions can be answered by ASCD:


    • How many facilities do I need and where?
    • Where do I put new facilities and what should be their sizes?
    • How do I rationalize combined supply chain networks?
    • How robust is my supply chain under various assumptions?
    • What's the impact of higher or lower customer service?
    • Where should I package my products?
    • Do I need one layer or two layer distribution?
    • Which customers should be served by which DC?
    • Which customers should be served by which route?
    • Which suppliers should I work with?


The picture below is an output example of ASCD that optimizes a large service part distribution network.




Key Features

  • Multi-stop and delivery frequency modeling for lower echelon
  • Unlimited echelon, lateral or reverse flow
  • Unlimited cost breaks (unlimited piecewise linear cost)
  • Complex process relationship within a facility
  • Separate modeling of warehousing costs and inventory carrying costs
  • Easy baselining
  • Concurrent optimization of multiple scenarios