Calculate

The spend total sits next to the emissions total, on the same filters. Reading the two together is what makes an intensity figure possible, and it is the first check on whether a baseline covers the spend a team thought it covered.

A filter isolates the organisations that hold product data, and the emission factor method marker shows where a product carbon footprint was used instead of a spend based figure. Product data is the closest method to the real thing, so those rows are the strongest part of a baseline.

A count of the organisations in the current view, moving with the filters. It answers the question that follows any total: how many organisations produced it, and is that the number the team expected to be measuring. Where the count comes in lower than expected, entity matching is the first place to look.

EcoVadis is available as a column and as a filter, so a rating a team already relies on sits beside the emissions figure rather than in a separate portal. Organisations can be narrowed to those holding a rating, or to those without one.

One table, one row per organisation. Each row carries the DitchCarbon score, the industry benchmark for that score, region, total spend, embodied emissions, the emission factor method used, target status and whether the organisation disclosed to CDP. Sort on any column to put the organisations that matter at the top.

Load a vendor list and the spend against it. DitchCarbon returns a total in kgCO2e for the whole portfolio, and says underneath which basis produced it, organisation emission factors where an organisation has published them. Numbers you can defend within 2 weeks, without asking a single organisation for anything.

Projects separate one set of organisations and spend from another inside the same account. A division, a legal entity, a reporting year or a consultancy's individual client each gets its own project, and any figure can be read for one project or across all of them.

Eleven filters, combinable: year, project, region, industry, emission factor method, whether product data exists, CDP status, EcoVadis rating, target status, where a target came from, and organisation status. The headline figures move with the filter, so a filtered view is a whole answer rather than a filtered list.

Identifiers, not name matching. An organisation can be added or matched on DUNS, LEI or ISIN, with website domain, email, HQ region and industry as supporting signals. Parent and subsidiary relationships are resolved as well, so a figure attaches to the entity you buy from rather than the group above it.

Each row carries its own method marker: organisation data where the organisation published its own emissions, product data from a published product carbon footprint, activity data from what was actually consumed, or industry data where nothing better exists. Filter the table on the method to isolate the rows resting on a sector average.

Two numbers on every row. The DitchCarbon score for the organisation, and the benchmark score for its industry. A score of 42 against a benchmark of 74 is an organisation well behind its peers, and a score of 98 against 97 is one already at the front. The gap is the signal.

Yes. Every standard column can be shown or hidden, and custom fields can be added for the attributes a team already tracks, for example contract owner, tier or renewable electricity share. Custom fields appear in the table next to the emissions columns rather than in a separate system.

Every figure on the page narrows to a single reporting year, a single project, or both. One part of the business can be read against the whole without exporting anything, and the filter carries across every card and chart on the page rather than resetting per component.

Every line in the baseline records the method used to calculate it. The breakdown groups those methods into organisation, industry, product and activity data, and shows each as a share of the total. Data quality becomes a proportion you can point at, rather than a claim you have to make.

One toggle answers it. Switch the headline emissions figure to industry emission factors only, then switch back to organisation emission factors where they exist. The difference between the two numbers is how much of your baseline rests on what organisations actually published, rather than on a sector average.