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Beer Bottles

Food and Beverage

Better schedules create the space for greater flexibility 

For food and beverage distributors, excellent products are only part of the value they bring to their customers. Many distinguish themselves on the basis of customer service. But challenges in last-mile deliveries can impact on-time performance and undermine a fleet’s ability to meet their customer service goals.

Successful food and beverage delivery fleets must:

  • Maximise fleet utilisation and Minimize fleet miles

  • Consistently meet customer time-window commitments and minimise customer refusals

  • Accommodate both planned and on-demand orders

Automated Scheduling and coordinated asset sharing to maximise utilisation and coverage

flowOS is designed to optimise the core of a scheduled bus operator's business - the schedule - to ensure that fleets can move quickly to allocate and reallocate charge slots in response to changes on the network.

Prospective's cloud-based Automated Scheduling software enables EV operators to meet both customer service and fleet efficiency goals. For some for the world's biggest operators, Prospective's next-generation scheduling system is proven to deliver:

  • Increased vehicle utilisation

  • Increased customer satisfaction 

  • Reduced fleet miles per passenger served

  • A customer portal that enables passengers to see accurate, predicted charge point occupancy

  • Machine learning capabilities that continuously monitor all available data to optimise asset performance over time.

  • Integration with third applications and TMS systems

With flowOS you can:

  • Automate the generation and continuous adjustment of timetables and itineraries that maximise availability and resource utilisation

  • Provide a single source across supplier networks to aid multi fleet, multi utility coordination and asset orchestration

  • Generate different scenarios quickly based on different service frequencies, punctuality and headway targets.

  • Update fleet plans based on charge status

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