Estimate the saving on your own numbers.
Truck rolls are the most directly quantifiable cost smoc.cloud removes. Put your fleet size, your read-failure rate and your own cost per field visit in — the maths is yours, not ours. Truck rolls are only one of several quantifiable returns — talk to us about the others, and about where smoc.cloud adds value from day one.
A neighbourhood goes dark — smoc.cloud resolves most of it remotely before anyone drives out.
Dozens of meters drop off the network at 00:00. smoc.cloud detects the cluster, exhausts every remote diagnostic and remote fix first, and only sends a crew to the devices that genuinely need one — all before the contact centre opens at 08:00.
47 meters across 3 substations stop responding simultaneously.
smoc.cloud correlates the cluster and opens a priority triage case. No van is dispatched yet.
Remote diagnostics — last-gasp events, comms logs and connector health — separate 39 meters with a backhaul problem from 8 with genuine loss of supply.
Remote actions: session re-establish, on-demand re-read and modem reset bring 39 meters back with zero site visits.
Only the 8 confirmed supply failures escalate to a single planned field job, with device list, location and diagnostic history attached.
Crew restores supply on one visit. Case auto-closes with a full audit trail.
Outcome: 39 of 47 meters recovered remotely, one truck roll instead of a street-by-street sweep, zero customer complaints, and a complete audit trail proving the SLA was met — automatically.
At the cost per field visit in the estimator below, sending a crew to all 47 meters would cost £3,995. SMOC resolves 39 of them remotely, leaving £680 of visits actually needed — a saving of £3,315 — 83% of the cost — on this one incident. Input your own numbers below to get a clearer view for your situation.
Size your own avoided field cost
Set the four sliders to match your estate: how many metering devices you operate, how many of them suffer read or comms failures each year, what a field visit really costs you fully loaded, and how many of those visits early detection and remote resolution should remove. The panel on the right updates instantly, and every figure further down this page — including the use cases — recalculates on the same numbers.
- Devices affected per year
- 25,000
- Field visits avoided
- 10,000
Indicative estimate only, based on the assumptions you enter. It excludes billing-estimate corrections, SLA penalties and complaint handling — which is where the rest of the case usually sits.
How the saving scales with your estate
Same assumptions as the calculator above — a read-failure rate, a share of failures resolved remotely and a cost per field visit. Select an estate size to load it into the calculator.
- Avoided cost per 1,000 devices / year
- £850
- Selected estate
- 1,000,000 devices
- Annual avoided field cost
- £850,000
What smoc.cloud is used for, day to day.
Each use case below carries its own share of the avoided field visits from the calculator above — change any slider and every figure here recalculates on your numbers.
Lifting read rates without sending vans
Electricity distribution
Mixed PLC and cellular meters across several vendors
AMI operations and field planning
- Missing reads are found days later, after billing windows have already closed.
- Head-end systems disagree on which device actually failed.
- Field visits are raised for faults that were never at the meter.
- Meter, network and head-end events are normalised into one ordered timeline per device.
- Correlation separates comms faults from device faults before a job is raised.
- Remote re-reads and re-registrations are attempted first, automatically.
- Fewer field visits raised for comms-only faults.
- Read failures detected the same day rather than at billing.
- Read rate reported per district against regulatory thresholds.
10,000 visits avoided × 60% attributed here = 6,000 visits × £85 per visit. Move the calculator sliders above and this figure updates with your own assumptions — 40% of failed reads are currently assumed resolvable without a field visit.
- Devices in estate
- 1,000,000
- Read-failure rate
- 2.5%
- Visits avoided (all use cases)
- 10,000
- Attributed to comms-fault triage
- 60%
- Visits avoided here
- 6,000
- Cost per field visit
- £85
Replacing battery devices on condition, not age
Gas and water
Battery-powered devices on LoRaWAN and NB-IoT
Asset management and capital planning
- Battery telemetry is inconsistent across device makers and networks.
- Replacement campaigns are planned by device age rather than device condition.
- Silent devices are only noticed once reads are already missing.
- Battery and communications signals are normalised into a single device-health model.
- Predictive scoring flags devices trending towards failure.
- Replacement lists are grouped geographically for efficient routing.
- Healthy devices stay in the field; failing ones are caught first.
- Replacement spend follows condition instead of the calendar.
- Read-rate exposure is visible before it becomes a penalty.
10,000 visits avoided × 25% attributed here = 2,500 visits × £85 per visit. Move the calculator sliders above and this figure updates with your own assumptions — 40% of failed reads are currently assumed resolvable without a field visit.
- Devices in estate
- 1,000,000
- Read-failure rate
- 2.5%
- Visits avoided (all use cases)
- 10,000
- Attributed to condition-based replacement
- 25%
- Visits avoided here
- 2,500
- Cost per field visit
- £85
Running several utilities from one operations centre
System integrators and managed service providers
Multiple client utilities, multiple head-end systems
Service delivery and SLA reporting
- Each client utility brings its own head-end, conventions and reporting format.
- Evidence for SLA reviews is assembled by hand from separate systems.
- Client data must be provably separated at every layer.
- One vendor-neutral information model covers every client estate.
- Tenant isolation is enforced through identity, authorisation and data partitioning.
- SLA and exception reporting is generated per tenant from the same audit trail.
- New client estates onboarded without a new toolchain.
- SLA evidence produced from records rather than spreadsheets.
- One operations team covering many utilities.
10,000 visits avoided × 15% attributed here = 1,500 visits × £85 per visit. Move the calculator sliders above and this figure updates with your own assumptions — 40% of failed reads are currently assumed resolvable without a field visit.
- Devices in estate
- 1,000,000
- Read-failure rate
- 2.5%
- Visits avoided (all use cases)
- 10,000
- Attributed to shared multi-tenant operations
- 15%
- Visits avoided here
- 1,500
- Cost per field visit
- £85
See your estate in smoc.cloud.
A demo walks through your utility types, your vendors and your compliance obligations — not a generic slide deck.