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OK, so it’s really important to understand how much energy

you’re consuming …

… and the where, when and why you are consuming it. I know, I’m preaching to the converted here but bear with me.

The more detailed that information the better and using half-hourly profile data helps to fill in the “when” and possibly the “where” details.

BUT while this is all ‘best practice’ it doesn’t really to answer the biggest energy question of all “WHY” am I using energy?

To do this, “how much” and “when” are not enough – we need to mix it up a little, by combining your energy consumption data with your key operational metrics you can bring a whole new perspective to your energy consumption.

The easiest way to illustrate the value of this is to use a few examples.

In retail, one key operational metric is “foot fall” – the number of people being served by a store or specific location within a shopping centre. There’s a whole science behind counting customers and “steering” them to a desired location/store, but for the sake of this discussion let’s just focus on energy.

By combining foot fall with energy consumption, it is possible to understand, in real-time how much energy is required to serve a customer i.e. “energy per customer”.

As a retailer energy per customer, is far more useful – you can instantly compare all your stores with a simple yet meaningful metric, helping to focus on where to invest your time and effort.

Now if you add in the time element you can see how the “energy per customer” varies throughout the day.

In manufacturing on the other hand it’s all about getting products out the door, so by combining your manufacturing output figures you can quickly see how much energy goes into each product manufactured, instantly seeing how this gets effected by a different shift, tool changeovers, downtime etc.

Perhaps if you’re managing a commercial estate “energy per square meter” is more appropriate? You’re operational metrics might be different, but you get my point, by combining energy information with operational metrics you can gain new perspectives on your energy data.

So as you can see, whatever the environment you operate in by mixing it up a little bit you can figure out WHY you use as much energy as you do. If you can do that, then you can start to figure out what changes to make to reduce you costs.

Just a different way to look at your energy use…what do you think?