Optimize for Field Service Engineers & Technicians

Companies often assign jobs based on geographical boundaries or patches when dealing with field service engineers who operate within pre-defined postcode areas, usually close to their home or base address.

These postcode areas act as "hard borders," meaning that jobs within a specific postcode are typically assigned to the engineer responsible for that area, regardless of the circumstances.

However, this approach can be inefficient due to real-world factors like distance, traffic, and the sequence of jobs.

Why Optimize Algorithms Provide More Efficient Plans

1. Dynamic Route Optimization:

Optimize AI algorithms consider various factors beyond postcode boundaries, such as traffic data, the current location of engineers, the sequence of their existing jobs, and the overall travel distance. By analysing these factors, the algorithm can create a more efficient plan that reduces travel time, mileage, costs, and slashes emissions.

2. Minimising Unnecessary Travel:

Instead of rigidly adhering to postcode borders, the Optimize algorithms can recognise when an engineer from a neighboring postcode is closer to a new job based on their current location and job sequence. This flexibility allows the company to assign jobs in a way that minimises unnecessary travel, leading to cost savings and lower emissions.

3. Real-Time Adaptability:

If an engineer finishes a job near the border of their postcode, and a new job is added just across the boundary in a neighboring area, the algorithm can quickly adapt to assign the job to the closer engineer, rather than the one traditionally responsible for that postcode.

Real-World Example

Imagine two engineers, 👩🔧 Alice and 👨🔧 Bob, who cover neighboring postcode areas A and B, respectively.

Scenario:

👩🔧Alice is finishing a job at the edge of postcode area A, near the border with area B. 👨🔧Bob, who covers area B, is currently working on a job far from the border within his area.

New Job: A new job comes up within 👩🔧Alice's designated area A, but it's actually closer to 👨🔧Bob's current location because he's finishing a job near the boundary.

If the company strictly adheres to postcode borders, 👩🔧Alice would be assigned the new job, leading to unnecessary travel time, higher fuel costs, increased emissions and reduced productivity.

Optimized Solution: The Optimize algorithm recognises that 👨🔧Bob, despite being assigned to area B, is closer to the new job and assigns it to him instead.

This reduces the overall travel distance, saves fuel, cuts costs, and emissions while enhancing productivity, leaving more time to carry out further jobs without any increase in base costs.

Case Study:

One of our standout success stories is with Enterprise Flex-E-Rent . By integrating Optimize with their field management software, Enterprise experienced significant improvements in efficiency and customer satisfaction.

Key Outcomes:

• 13% Mileage reduction
• 6% Reduction in routes
• 12% Reduction on Time
• 7% Increase in engineer utilisation

Conclusion

In this way, while postcode areas act as useful guidelines for organising field service operations, they should not be seen as absolute barriers. Optimize algorithms can provide a more flexible, data-driven approach that considers real-world factors, leading to more efficient job assignments, reduced operational costs, and a smaller environmental footprint.

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