To most people ‘baseline’ energy consumption means the actual quantity of energy that was used over a certain reference period. Quite often, annual figures are used and subsequent annual consumption is then gauged against this yardstick (ideally with adjustments to account for the influence of the weather or other factors). There is a subtly better way, however.

Best practice in energy monitoring and targeting starts with finding the formula that relates consumption to one or more relevant driving factors (weather, product output, *etc*). Once you have such a formula you can estimate expected consumption over any interval you choose, giving you the ability to check that the quantities used over a week (say) were reasonable given the prevailing conditions.

As time goes by, energy-saving measures may be introduced. When that happens the related expected-consumption formulae need to be revised to reflect the new achievable performance. In that way any subsequent loss or inefficiency shows up properly because we can feed current driving-factor figures into the current formula to work out how much we *should* have used. But we can also feed the same numbers into the *original* formula to work out how much we *would* have used in the absence of our energy-saving measures. That original formula is called the historical baseline formula: it enables us to evaluate progress at any interval in a way that automatically adjusts for changes in the influencing factors. Thinking in terms of baseline *formulae* is therefore far superior to using baseline *quantities.*