£10,239 Wasted!

In an empty school that didn't know it was still on.

| LOCATION: A Northern England Secondary School, Lancashire

Client

Secondary School, NW UK

Industry

Education / Public Sector

Data Monitored

Electricity · 15-min intervals

Waste Identified

£10,239 / 9 months

Data confidence

EnergyLens metering achieved 99.98% data completeness across the reporting period (4 missing intervals from 233,208 kWh of captured data). Evidence-grade from day one.

100% GDPR-compliant by design

The Nightmare

The school's energy bill kept arriving. The school kept paying it. Nobody knew how much of it was for an empty building running in the dark.

The legacy BMS was a black box. Schedules hadn't been properly audited in years. When sustainability reporting season came around, the Facilities Manager and Sustainability Director were left chasing spreadsheets and estimates - not evidence. Audit prep was weeks of pain, and the outputs still didn't hold up to scrutiny.

Meanwhile, the meters kept ticking. Plant was starting 1 hour 45 minutes before the first pupil arrived. Heating ran 3 hours 15 minutes after the last one left. Weekends weren't locked down. And nobody could prove any of it - because the data wasn't being captured, analysed, or acted on.

The Result:

18.1% of total electricity spend was pure waste. Not inefficiency. Waste. And it was invisible.

In Their Words

"We knew energy was being wasted. We just couldn't prove it, quantify it, or explain it to anyone who held the budget. EnergyLens gave us the first evidence pack that actually stood up. The schedule corrections alone will pay for the system — and we've got data we can take to governors, auditors, and grant panels."

Facilities Manager

Northern England Secondary School

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The DIREK Fix

DIREK connected EnergyLens directly to the school's existing meter infrastructure — no BMS replacement, no rip-and-replace, no capital project. Fifteen-minute interval data fed straight into D-XPERT™, achieving 99.98% data completeness from day one.

No guesswork. No estimates. Decision-grade recommendations built on metered reality. D-XPERT pinpointed exactly what was running, when it shouldn't be, and what it was costing. Then it built a costed, measurable corrective plan:

Here's what the data exposed, and what DIREK told them to do about it:

1. Schedule drift exposed

Start-up at 06:30 vs target 08:15 - plant running 1h45m before it needed to

2. Shut-down overrun confirmed

Systems running to 18:15 vs target 15:00 - an extra 3h15m of avoidable cost every weekday

3. Weekend operation flagged

Baseline demand above the expected floor, indicating plant running without occupancy

4. Peak demand clustering identified

Top 1% demand intervals at 154.5 kW, due to plant starts; sequencing fix suggested.

5. SAS score established as a live KPI

current 82/100 vs 90+ target, with a 30-day recovery plan.

6. Audit-ready evidence pack generated

Findings based on metered data, ready for Ofsted, DfE, or grants.

The 30-day recovery plan didn't ask for capital spend. It asked for BMS schedule corrections, timer checks, and a shutdown protocol. Jobs that take days. Savings that last years.