Intelligent Scheduling Assistant
An interactive decision-support tool that replaced paper maps and best-guess dispatch with data-driven engineer scheduling, minimising travel time through intelligent routing following specific business rules.
Key Results
The Challenge
Dispatchers relied on paper maps, personal experience, and best guesses to assign engineers to jobs while on the phone with policyholders. Scheduling quality depended entirely on individual knowledge, new staff took months to become effective, and the process couldn't scale as the engineer pool grew.
The Solution
We built a read-only, web-based decision-support tool that ingests live data from BigChange to visualise engineer availability and location, then recommends the most efficient engineer for each job based on proximity, return-home corridors, and capacity constraints.
Key Capabilities
Live Data Ingestion from BigChange
Pulls engineer rosters, home addresses, current bookings, and availability gaps directly from the BigChange API. Schedule data is fetched on demand with a manual refresh option, ensuring dispatchers always work with current information.
Proximity & Corridor Recommendation Engine
Ranks engineers by static distance to the job, identifies return-to-home corridors to minimise wasted travel, and filters by capacity constraints such as 4-hour or 8-hour slot availability. Engineers outside the corridor are still shown but visually flagged.
Map-Based Dispatcher Dashboard
A web interface designed for rapid decision-making on a live call. Dispatchers enter a job postcode and duration, receive a ranked list of engineers with drive times, and see everything plotted on an interactive map — including home locations, assigned jobs, and corridor paths.
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