LLamasoft and CLX Logistics announce agreement to offer European truckload and global ocean and parcel data to LLamasoft customers

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LLamasoft, the supply chain design software solutions provider, and CLX Logistics, a global provider of comprehensive logistics management, technology, and supply chain consulting services, announced an agreement to offer European truckload, global ocean and global parcel data to LLamasoft customers for use in strategic supply chain design.

CLX Logistics has offered a dedicated transportation benchmark service for more than 10 years. During this time, the number of companies using the service has grown substantially. Today, the CLX Logistics Benchmark database contains in excess of EUR 4.1 billion contracted transportation expenditures (no spot market) with detailed data on a full range of global, pan-European and domestic routes and a variety of transport modes. CLX Logistics rate benchmarking service will now be available to LLamasoft customers through a referral agreement.

The partnership will provide LLamasoft customers with an additional resource from which to draw valuable global reference data for use in supply chain modelling. "The growing number of companies participating in our benchmarking proves the added value that our accurate and reliable apple-to-apple comparison brings," said Marc Huijgen, CLX Logistics European VP. "We have seen companies that considered their processes to be best-of-breed, saving double-digit percentages after deploying our benchmark data in their procurement strategy. Hence we are excited to team up with the leading supply chain design software company LLamasoft to jointly help both our clients make better supply chain decisions."

"Making CLX rate benchmarking service available to our customers is part of our continuing effort to help fill in missing model data—thus removing one of the biggest obstacles to successful supply chain design initiatives," said LLamasoft president and CEO Donald Hicks. "Highly sought-after European truckload data will enable a higher level of data accuracy in modeling to help support critical supply chain decision-making."

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