IFS schedules field service appointments. But delivery routing is a different problem higher stop density, stricter time windows, capacity constraints. Locate2u provides the delivery-specific route optimisation that IFS lacks.
IFS is known for its field service management capabilities scheduling technicians for service appointments based on skills, availability, and territory. But field service scheduling and delivery route optimisation solve fundamentally different problems.
A field service technician visits 5-8 locations per day with 1-2 hour service windows. A delivery driver visits 30-80 locations with 15-minute time windows and a vehicle that must not exceed its weight capacity at any point during the route. IFS's scheduling engine handles the first scenario well but is not designed for the second. Locate2u adds the delivery-specific route optimisation that sequences high-density stop lists for minimum drive time while tracking capacity constraints at every point in the route.
Scheduling 6 service calls across a city is computationally simple there are only 720 possible sequences. Optimising 45 delivery stops involves over 10^56 possible sequences. Delivery route optimisation requires a fundamentally different algorithm that can handle this combinatorial complexity while still returning results in under 60 seconds.
Service technicians carry tools, not cargo. Delivery drivers carry goods that consume vehicle weight and volume capacity at every stop. A delivery route optimiser must track how much capacity remains after each delivery and ensure the truck never exceeds limits. IFS service scheduling does not model this constraint type.
Service appointments typically have 2-4 hour windows. Delivery time windows are often 30-60 minutes. Optimising 45 stops where each has a tight time window requires an engine that can simultaneously satisfy dozens of overlapping constraints while minimising total travel a problem IFS scheduling was not built to solve.
In field service, the technician's on-site labour is the primary cost. In delivery, drive time between stops is the primary cost. Delivery optimisation must minimise travel distance above all else, while service scheduling prioritises skill match and availability. Different cost functions require different optimisation approaches.
Locate2u pulls delivery orders from IFS Cloud via REST APIs. Customer addresses, delivery time windows, item weights, and special handling requirements are imported automatically without manual export.
The AI engine sequences 30-80+ stops per vehicle for minimum drive time. It enforces tight time windows, tracks vehicle capacity at every stop, and accounts for traffic patterns handling the complexity that service scheduling cannot.
Drivers follow optimised routes on the mobile app with turn-by-turn navigation. Delivery confirmations, timestamps, and proof of delivery sync back to IFS order records automatically.
Handles the combinatorial complexity of 30-80+ stop routes that service scheduling cannot. Returns optimised sequences in under 60 seconds regardless of stop count.
Optimises around 30-60 minute delivery windows that are far tighter than service appointment slots. Every stop is sequenced to arrive within its window while minimising total fleet drive time.
Tracks vehicle weight and volume at every point in the route, not just at departure. Ensures no vehicle exceeds limits even on mixed delivery-and-pickup runs where load changes at each stop.
When new deliveries arrive mid-day or stops are cancelled, routes re-optimise instantly. The high stop density of delivery routes makes re-sequencing especially impactful a single insertion can affect 20+ subsequent stops.
Optimises across your delivery fleet simultaneously. Assigns orders to vehicles based on capacity and route efficiency, not just territory which is how IFS typically assigns service calls.
Fine-tune optimised routes by dragging stops between drivers or reordering the sequence. Capacity gauges and time window indicators update in real time so dispatchers can see the impact of every change.
Reduction in total delivery fleet driving time
Fuel cost savings from optimised sequencing
On-time delivery rate with tight window constraints
Additional stops per driver per day