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Natural Capital: How Do You Go about Accounting for It?

mattison, richard, trucostThere are many reasons why companies would want to account for their natural capital impacts. I’ll come to those later, but first I want to answer the question of how do you actually go about it?

There are two versions of this answer; a technical one (a long answer beyond the scope of this article – but if you want the detail, I’d be pleased to provide it) and a shorter one. I’ll start with the shorter one by describing how we helped PUMA and Parent Company Kering to publish the world’s first Environmental Profit & Loss statement in 2011, since if you are interested in this topic you are likely to be aware of it.

First – here is a view of the top line output.

Fig 1: PUMA Environmental Profit and Loss Account

PUMA Environmental Profit and Loss Account

 

So how did we go about creating the EP&L? First we had to measure PUMA’s operational and supply chain impacts, back to raw materials, in traditional sustainability metrics (tonnes of GHG emissions, waste disposal and air pollution, cubic meters of water consumption, and hectares of land use). The problem is we live in a fully globalised market and supply chains are often extremely complex. Consequently, it is currently near impossible to gather data from the entire supply chain in a timely manner.

As an environmentally conscious manufacturer, PUMA had already addressed its operational impacts and had been promoting the reporting of environmental performance data with strategic suppliers for some time.

This provided a great starting point. But which other suppliers, or suppliers of suppliers, did we need to engage with to measure material environmental impacts across PUMA’s supply chain? A common question for any company taking the first steps in managing its supply chain impacts.

The key to unlock this problem is provided by Environmentally Extended Input Output (EEIO) modeling, an economic technique that identifies the interdependencies of different branches of an economy – the development of which won Wassily Leontief the 1973 Nobel Prize in Economics.

EEIO modelling identified ‘hotspots’ of environmental impact across PUMA’s supply chain tiers around which we were able to pinpoint high impact suppliers for engagement.  It also provided baseline data for lower impact areas of the supply chain. Following our engagement with PUMA’s high impact suppliers, we combined these data with PUMA’s previously collected data to improve the modelled baseline and deliver a complete environmental footprint across PUMA’s operations and supply chain.

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