STEP ONE: ENTER YOUR DATA
The first step requires data
The more data you include the better. However, the model has been designed by experienced environmental management consultants who have enjoyed many years of overcoming the challenges of incomplete data sets, so although pristine data sets are most welcome, we have adapted to cope with less than perfect data.
The basic data requirements are energy use and in order to calculate an intensity ratio, the total meter square coverage of buildings, number of full-time employees and or turnover. This can be entered over a time period of your choice and as either a total for the company or ideally as a total per facility. The same is true of all other data such as water usage, waste tonnage, business and freight travel, paper usage, IT procurement, catering costs; the list is endless. The tool combines simplicity with an exhaustive reporting structure enabling a comprehensive carbon footprint.
STEP TWO: CALCULATE YOUR CARBON USAGE
The second step calculates your scope 1, 2, and 3 carbon emissions to create your carbon footprint. Our calculation methodology applies average data international carbon factors publicly available from governments and environmental bodies, and supplier specific factors from life cycle assessment analyses and meta-analyses obtained from peer-reviewed scientific studies. UK government conversion factors are used in compliance with the Open Government Licence for public sector information. See an example report is here.
The methodology is fully compliant with the Greenhouse Gas (GHG) Protocol Corporate Accounting and Reporting
STEP THREE: COMPARE YOUR FOOTPRINT
The third step is the benchmarking Once you have collected and entered your data, the model uses a bespoke database containing Scopes 1 and 2 (and some scope 3) emissions data, collected by our partner Compare Your Footprint throughout their many years of environmental consultancy, along with publicly reported emissions data from annual reports and purchased from databases of quoted companies. All this data is anonymised.