Resource Planning System for HWRCs
For HWRC Operations
Running a HWRC network is hard. Demand shifts by day, season, site and waste stream, yet day-to-day decisions are still made manually with limited data to support them. Recycling rates, carbon targets, service levels and operating costs all compete for priority with no system to balance them. The result is inefficient transport, under-utilised vehicles and resources in the wrong place at the wrong time, driving up cost and carbon whilst impacting service delivery.
Our AI-enabled platform tracks your operations, monitors activity and service levels, predicts demand and models the optimal transport plan – providing you with the tools to transform performance and achieve your sustainability goals.

The Problem
HWRCs & Resource Planning – An Impossible Balancing Act.

How PIN works
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Digitise

- Tracking devices with a 10-year battery life, fitted to your skips and vehicles by our expert team. Quickly and efficiently.
- Every HWRC site digitally mapped. Individual containers matched to bays and waste streams.
- Every location, journey, site visit and job automatically captured. No manual input.
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Analyse

- PIN's AI-powered software oversees your operation in real time.
- Monitoring every job, every container, service outages and site closures.
- Measuring transport productivity, utilisation and container availability.
- Uncovering the trends, identifying the inefficiencies and improvement opportunities to transform how you run your operations.
TRANSFORM
AI-enabled demand forecasting predicts demand by site, day and waste stream. Factoring in seasonality, weather and public holidays. The transport planner models the optimal vehicle and driver schedule to meet demand, balancing capacity across the network, whilst improving service levels, reducing carbon and transport costs.
Optimise transport & resources

Lower costs

Improve service delivery

Increase operational efficiency

Manage assets & containers

Achieve sustainability goals

See our AI-powered Software in Action
A walkthrough using real-world examples, so you can see exactly how PIN would revolutionise the way you work.
Angus Council Case Study
We have been working with Angus Council since 2022, and have worked closely with them to build this for the industry.
Analysis revealed seasonal patterns, day-of-week rhythms, and a structural mismatch between flexing demand and a flat year-round transport capacity.
These insights became the foundation of a new AI-driven planning model – one that forecasts daily service demand, recommends the vehicle capacity needed to meet it, and learns continuously over time. When tested against real operations, it didn’t just suggest efficiencies were possible. It mapped the path.
Modelling six optimisation scenarios, 1m+ options, efficiencies of up to 30% and £150,000 cost savings.
A Resource Planning System purpose-built for HWRCs, designed to help any local authority or operator plan smarter, run leaner, and respond faster.

Get in touch, let’s talk.
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