Demonstration case 03 - service scheduling

Synthetic field-service scenario

Who should go to which job?

A service company has 12 interventions across four zones and four technicians with different skills. Every individual assignment may look acceptable, but a good schedule must consider the whole working day.

Synthetic demonstration based on a realistic business problem. It does not represent a project for a specific client.
See the schedule
12 interventionsSame working day
4 techniciansDifferent skills
4 zonesSynthetic grid

Baseline - manual assignment

Every assignment respects skills, but geography creates unnecessary travel.

In the manual assignment T1 receives J1, J10 and J7; T2 receives J4, J9 and J11; T3 receives J3, J6 and J8; T4 receives J5, J2 and J12. Using the best ordering inside those already assigned jobs, total depot-to-depot travel is about 137.5 km.

137.5 kmtotal route
about 4 h 35 min drivingat 30 km/h equivalent speed

The issue is not whether a technician can perform one job. The issue is how one assignment affects the rest of the system.

Manual assignmentD123456789101112T1T2T3T4

What does the model consider?

Assignment and routing are treated as one decision.

The model considers required skills, location, technician availability, intervention duration and total travel across all technicians at the same time.

01

Objective

Reduce unnecessary total travel while completing every intervention.

02

Constraints

Every job goes to a technician with the required skill and each intervention is completed once.

03

Variables

Which technician receives each job and in what sequence the jobs are visited.

04

Priority

Optimize the whole schedule, not just the nearest next job.

View skills, locations and manual assignments

Every intervention lasts 90 minutes. Technicians start and end at the central depot. The synthetic coordinate grid is interpreted as kilometres and travel time uses an equivalent speed of 30 km/h.

Technician skills

TechnicianSkills
T1Electrical / Mechanical / General
T2Electrical / HVAC / General
T3Mechanical / HVAC / General
T4Electrical / Mechanical / HVAC / General

Jobs and synthetic coordinates

JobCoordinateRequired skill
J1(-5, 4)Electrical
J2(-6, 5)General
J3(-4, 6)Mechanical
J4(5, 4)Electrical
J5(6, 5)General
J6(4, 6)HVAC
J7(5, -4)Mechanical
J8(6, -5)General
J9(4, -6)HVAC
J10(-5, -4)Electrical
J11(-6, -5)General
J12(-4, -6)Mechanical

Before and after

Grouping compatible jobs by zone nearly halves total travel.

One feasible optimized solution assigns the north-west zone to T1, north-east to T2, south-east to T3 and south-west to T4. Every job remains with a qualified technician.

BEFORE - manual assignmentManual assignmentD123456789101112T1T2T3T4
T1 J1 - J10 - J7T2 J4 - J9 - J11T3 J3 - J6 - J8T4 J5 - J2 - J12
137.5 kmabout 4 h 35 min
AFTER - optimized assignmentOptimized assignmentD123456789101112T1T2T3T4
T1 J1 - J2 - J3T2 J4 - J5 - J6T3 J7 - J8 - J9T4 J10 - J11 - J12
69.1 kmabout 2 h 18 min
Decision delta

We did not add people. We changed the system schedule.

The same technicians and the same interventions require much less total travel when skills and geography are optimized together.

Baseline137.5 km / about 4 h 35 min

Manual assignments send technicians across distant zones.

Spacelytics69.1 km / about 2 h 18 min

Compatible jobs are grouped by zone and required skills.

Delta-68.5 km / -49.8%

About 2 h 17 min less total driving time.

What-if / scenario analysis

The schedule must react when the day changes.

A good assignment for one job is not the same as a good system-wide schedule. Changing one condition can alter several later assignments.

Re-optimization

One technician is unavailable

The model checks skills again and reallocates work across the remaining qualified technicians.

Check real reserve

An urgent intervention appears

The model can identify where time and skill reserve exists without breaking the rest of the plan.

Fewer valid candidates

A job requires two skills

The allowed technician set narrows and the whole schedule is evaluated again.

XAIOR - explaining the result

Why is the nearest technician not always the best choice?

The model does not optimize one intervention in isolation.

First, the model checks whether the technician has the required skill. Geographic proximity by itself is not enough.

When several technicians are qualified, the model considers how each assignment affects their later jobs and total team travel.

In this scenario, grouping compatible interventions by zone reduces the synthetic route from about 137.5 km to 69.1 km.

The saved time may become reserve for an urgent job, lower lateness risk or more completed work, but no financial saving is claimed without real labor and mileage costs.

The nearest technician is not always the best technician for the whole schedule.

Analytical resultXAIORExplainabilityHuman decision

From demonstration to a real problem

What if these were your data?

In a real project, jobs, locations, work calendars and skill matrices can come from CRM, ERP, a field-service system or Excel. The synthetic coordinate grid would be replaced by your operational geography.

How much time do your people spend between jobs?
Which skills constrain the schedule most?
What happens when an urgent intervention appears?
Does the planner optimize the whole day or solve one request at a time?
Describe the problem you are trying to solve