Traditional energy reporting depends heavily on performance ratios and percentage deviations. Performance ratios include such things as kWh per square metre per annum for buildings, litres per kilometre for vehicles and, in industrial contexts, specific energy ratios (kWh per unit of throughput). Unfortunately ratios and percentages don’t tell the full story because they neglect the scale of consumption. A small percentage loss related to a large energy user could cost more than a large percentage on a small one; while a small building with a very high energy intensity could offer much less scope for saving than a large building with only moderately poor performance.

I’m reminded of my first day as an energy manager at London Borough of Lambeth. My departmental director asked me which of his buildings I would be looking at first, and the only thing I could think of to say was ‘the biggest energy users’. With hindsight I should really have said ‘the ones with the biggest opportunities for reduction’ but at that time I would have had no idea how to work out which those were. Now I know, and the process is this: first, for each building, establish from published sources what its yardstick energy intensity (per square metre) is for fuel and electricity separately. Then multiply this number by the floor area. This gives the yardstick energy consumption, in annual kWh, for each utility in each building. The difference between actual and yardstick kWh is the amount of energy that the building would save if able to operate at yardstick energy intensities. I call this the ‘performance deficit’ and if you price up your individual performance deficits and rank them in descending cash value order, you have a prioritised hit list for your estate.

The concept extends beyond buildings to encompass processes and vehicles. True the necessary yardstick energy intensities won’t be available as published figures but there are other ways to get at them, including benchmarking against similar objects. An example from my own experience is provided by a transport fleet with a few dozen cars and just a handful of delivery vehicles. Each car had a manufacturer’s fuel economy figure which could be expressed in litres per kilometre. Multiplying each by the annual distance travelled gave me a table of achievable annual litres and thus the ‘excess’ litres when compared with actual purchases. Meanwhile for the heavy commercial vehicles (of which there were only four, doing very similar duties) I calculated the actual litres-per-kilometre and used the best as the yardstick for the rest, again in order to establish an opportunity ranking and to evaluate the value of savings that each should yield.

The general lesson is this: don’t try to rank opportunities using ratios and percentages. Always try to work with absolute quantities and costs.

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