Solutions
Analytics, forecasting and reporting
The savings pay for the system. The evidence is what makes it permanent.
Once containers have been reporting for a few months, the fill history answers questions no waste collection operation could previously answer: which bins are genuinely used, which have been over-served for years, which are redundant, what a collection actually costs, and whether a specific container was emptied on a specific day.
The savings pay for the system. The evidence is what makes it hard to remove.
What the data answers
Complaint and enquiry evidence
Every reading and every confirmed lift is timestamped. When a resident or a councillor says a container has not been emptied for a fortnight, you check rather than guess, and reply the same day with a record instead of an apology.
Demand heat mapping
Fill curves per container, per week, per season. Which locations are busy, which are quiet, and which have a pattern nobody in the office would have predicted — Stralsund found some bins virtually empty while others filled far faster than expected.
Bin estate rationalisation
Bin estates grow by accretion and are almost never reviewed. With precise locations and months of fill data you can identify overlapping and under-used containers and remove them on evidence — which is exactly what Vejle began doing.
Mileage and carbon reporting
Kilometres avoided, lifts avoided, fuel not burned. Vejle's programme targets 5.5 tonnes of CO₂ saved a year and a 30% travel reduction; Stralsund cut weekly mileage by 54%. These are numbers a climate report can use.
Contract and budget evidence
Lift counts per container per period, against contracted frequency. Whether you are commissioning or delivering the service, this is the number the next negotiation turns on — and currently almost nobody has it.
Service performance
Threshold breaches, time from flag to lift, missed collections, sensor health. Ordinary operational KPIs, but measured rather than reported.
The second-order win
Removing bins you never needed
Most bin estates are the accumulated residue of individual decisions. A complaint came in, a bin was added, and nobody ever went back to ask whether it was justified. Multiply that by twenty years and you have containers standing thirty metres apart, each collected on the same fixed frequency, each costing a lift.
Fill history settles it. If two containers in sight of each other both sit at 30% between visits, one of them is unnecessary, and removing it is a permanent saving — a lift, a sensor, a maintenance liability and a graffiti target gone. Because the decision rests on months of measured data rather than an officer's impression, it survives the inevitable objection.
Vejle began exactly this exercise once it had accurate location and fill-level history, trimming overlaps and reducing the number of bins without compromising the service residents actually experience.
Questions the data answers
- Utilisation
- What fill level does each container actually reach between visits?
- Frequency fit
- How many of last month's lifts went to containers under 50%?
- Overlap
- Which containers within 100 m of each other are both under-used?
- Seasonality
- How does demand at this location differ between February and August?
- Cost per lift
- What does a collection at this container cost, including the drive to reach it?
- Service proof
- Was container 4471 emptied on 14 August, and at what time?
- Carbon
- How many kilometres and tonnes of CO₂ has the change avoided this year?
Access and integration
Your data, in your systems
Reporting is available in the platform, but nobody wants a twelfth dashboard to log into. Everything is exportable and accessible through an open API, so fill history and lift records can feed the systems your organisation already uses for performance reporting and financial analysis.
- Open API for fill readings, lift confirmations, container registers and sensor health.
- Full export at any time, in standard formats, throughout the contract rather than only at the end of it.
- Feeds your BI tools — Power BI, Tableau or whatever your performance team already runs.
- Push to existing route systems where crews should keep the in-cab interface they know.
- UK-hosted, with the processing detail your information governance team will ask for.
Questions
Data and reporting questions
How long before the data is useful?
Live fill levels are useful immediately — you can see which containers are full today from the first week. Pattern analysis needs longer: about four weeks before weekly rhythms are clear, and a full year before you can characterise seasonality properly. Fanø had a measurable 20% reduction in emptyings within two months, so the operational payoff arrives well before the analytical one.
Can we use this data to answer FOI requests and councillor enquiries?
Yes, and several authorities value it as highly as the cost saving. Every reading and confirmed lift is timestamped, so service history for any container over any period is a query rather than an investigation. Vejle's department head specifically cites being able to respond quickly to elected members fielding resident questions — and being able to show that unnecessary journeys are not being made, which is a political point as much as an operational one.
Does the reporting cover carbon and mileage?
Yes. Kilometres travelled, lifts performed and lifts avoided are all recorded, which is the basis for a fuel and CO₂ calculation against your fleet's emissions factors. Vejle's programme targets a 5.5 tonne annual CO₂ reduction alongside a 30% travel reduction; Stralsund measured weekly mileage falling from 1,677 km to 779 km. These figures are defensible in a climate report because they rest on counted journeys rather than modelled assumptions.
Who owns the data and where is it held?
You do. It is hosted in the United Kingdom, exportable in full at any time, and available through an open API. Fill-level readings are measurements of council or estate assets rather than personal data, so the data protection position is normally straightforward — but we will support your DPIA and provide the processing detail your information governance team needs. If you end the contract, your history leaves with you.
Next step
See what your own bin data would say
A 90-day pilot on one round tells you exactly how much of your current collection effort is going to bins that were not full. No commitment beyond the pilot, and you keep the data.