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Consumption is invisible until somebody draws it.

Electricity is obscure, intangible and invisible to almost everyone who pays for it. Drawn properly, it becomes something a facilities manager can read at a glance — and most of what is wrong with a building shows up as a shape long before it shows up as a number.

The load profile

Patterns line up with what actually happens in the building — the shift starting, the chillers cutting in, the cleaners at ten at night. Anomalies announce themselves.

Coloured by tariff period, it answers a second question: not just how much energy is being consumed, but when.

Half-hourly demand profile by time-of-use periodHalf-hourly real power in megawatts, drawn as bars coloured by Megaflex time-of-use period — off-peak, standard and peak — with apparent power in megavolt-amperes overlaid as a line. Demand peaks at 85.2 megawatts. Maximum apparent power of 90.7 megavolt-amperes occurs at a power factor of 0.94. Every figure is listed in the Energy Analysis table beneath the graph.0255075100MW / MVAWed 24Thu 25Fri 26Sat 27Sun 28Mon 29Tue 3012:0012:0012:0012:0012:0012:0012:00
Peak demand (MW)Standard demand (MW)Off-peak demand (MW)Apparent power (MVA)9 intervals flagged suspect
Total energy
9,738 MWh
Maximum demand
85.2 MW
Maximum apparent power
90.7 MVA
Date of maximum demand
24 Jun, 08:30
Power factor at MD
0.94
Load factor
68 %
Eight days of half-hourly data from a single metering point. Account anonymised.

A month you can read in one look.

A profile shows you one day well and a month badly. The heat map puts the day across and the time of day down, so a habit and a one-off look completely different.

Trading hours draw themselves. So does the shift that starts an hour early on a Friday, the plant left running over a long weekend, and — unmistakably — the days the power was not there at all.

Consumption heat map for June 2026One month of half-hourly demand for a commercial account. Each column is a day, each row a half hour of the day, and darker cells are higher demand, peaking at 37 kilowatts. Reading down a column gives one day's shape; reading across a row shows how the same half hour changes through the month.00:0006:0012:0018:00Time of day151015202530Day of month — June 2026
Lower Higher — to 37 kW
A commercial restaurant account. One month, every half hour, one cell each. Account anonymised.

Some of what runs overnight has to. The rest is habit.

Baseload is what a site draws outside trading hours, and plenty of it is doing real work — refrigeration holding stock, security and emergency lighting, servers, pumps, frost protection. None of that is waste.

But it sits alongside the air conditioning nobody switched off, the plant that starts three hours before anyone arrives, and the lighting circuit that has been on since 2019. The useful question is not what the building costs when it is closed — it is how much of that is unnecessary.

MOL tracks the overnight floor against a target and shows the gap. Because it runs every hour the building is shut, a small reduction repeats several thousand times a year, which is what makes it the most reliably recoverable line in an energy budget.

Six ways to look at the same data

Load profile

The half-hourly shape of consumption. Almost always the first thing anyone opens, and the one view where a leak, an overnight load or a failed power-factor correction announces itself.

Heat map

A month in one picture — day across, time of day down. Shows what a profile cannot: whether last Tuesday was unusual, or whether every Tuesday looks like that.

Baseload analysis

The overnight floor, tracked against a target. Separating the load that has to run from the load that merely does is the most reliably recoverable line in an energy budget.

Period comparison

Month against month, in graph and table, for an account or a group of them.

Consumption comparison

Two sites over the same period, or one site over two periods — which is how you find out whether an energy-saving intervention actually did anything.

Daily and 3D analysis

A month drawn as thirty small daily profiles, and the same data as an intensity surface across day and hour.

Every one of them is built on the same validated interval data, so two views of a site never disagree with each other — and none of them disagrees with the invoice.

The rest of MOL

Meter data managementDashboardsTariff & billingVirtual metersPrepaymentEngineering diagnosticsAPI

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