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Enriched data drives
improved carrier
selection
Request a Demo

Intelligent metrics drive
carrier selections

  • Each shipper can, at the line of business level, use weighted parameters to drive carrier service selection
  • The system allows factoring in virtual KPIs
  • The service selection can be de-correlated from the carrier SLA when it has benefits
  • Carrier selection rules change dynamically and can be manually moderated

Delivery options
cost / time based

  • The system continuously builds customer specific KPIs that are used for carrier selection
  • Any metric can be used to influence carrier service selection such as Green House Gases
  • All selection parameters are self-managed online by each shipper
  • The shipper's organisation is pictured in the overall SRM concept so that all mechanisms are managed from a single place and deployed across the organisation

Customer wants
to know what is going
on with the order

  • All customer interactions are performed on the shipper's platform
  • Providing consolidated information at order level
  • Carrier tracking is merged with internal tracking information to build a customer friendly view of events
  • Predictive mechanisms allow picturing the entire order delivery sequence
  • Tracking view that limits the level of details provided, configured to meet the target audience requirements / understanding

Customer is proactively
informed of any issues

  • Anomalies tracking is generated by the SRM platform through carrier information and external events
  • In the event of a major deviation from predictive sequence, the system will automatically switch to an alternative carrier service
  • The predictive nature of SRM allows identifying anomalies at any step of the shipment sequence
  • SRM records information about all the deliveries for learning purposes, including anomalies that resulted in successful deliveries

All shipment delivery
information is recorded

  • The actual delivery recorded through a Pod or IoD is not the end of the process
  • All events recorded during the order lifecycle are used to fuel the SRM system automation
  • Quality metrics as well as Green House Gas emissions are recorded for customer specific reporting purposes
  • All KPIs can be used to influence carrier selection automatically
  • A full set of dashboards allow monitoring trends and deviations on cost or quality metrics
  • Carrier invoices are collected and reconciled with booking / manifest data to help with auditing

Data Model constantly
learns from real life
events

  • All delivery information is collected to build a knowledge based
  • T2 maintains an AI knowledge based to provide tracking event prediction
  • All information (internal, external) can be merged into custom KPIs that are stored and managed at the Line of Business level

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