Data Review explained

Our Data Review feature helps you to understand how your Purchased Goods and Services emissions are being calculated by Unravel Carbon’s data engine.

Our Data Review tools also allow you to correct unmatched (e.g. incomprehensible or non-english) items. Correcting issues by completing data review tasks will allow you to improve your emissions data quality over time.

Understanding your data match quality

How Unravel Carbon’s engine works

Before we explain how we measure data match quality, it helps to understand how the Unravel Carbon engine works. When you upload data to the platform our engine will use the information available to determine how to use the item in your emissions inventory. The image below shows how the engine does this:

We use data match types to describe how the item is being used to calculate your emissions. Read on to learn more about each one.

Data match types and data match quality

There are four data match types  in the Unravel Carbon engine which are used to measure your data match quality:

1. Unmatched - These data points have not been matched to an emissions factor by our engine, and so are not included in your emissions estimate. This might be because the item description is incomprehensible or not in English.
2. Spend matched - These data points have been matched to a spend-based emissions factor by our engine, meaning total emissions are calculated based on the amount spent on the item or service.
3. Item matched - These data points have been matched to an item-specific emissions factor by our engine, meaning emissions are calculated based on activity data (e.g. quantity or weight of items, distance travelled, fuel consumed). Item-specific emission factors include material-based, supplier-specific, or location-specific emission factors, and global industry averages. This is the best match type as it provides the most specific and granular emissions data.
4. Excluded - These data points have been excluded as there are no material emissions associated with them. This includes items like salaries, taxes, fees, and refunds.

The data match quality chart provides a breakdown of your data points by data match type. The percentage of rows matched shows the proportion of your uploaded data that has been matched to an emissions factor for the selected time period and business facilities. Excluded items are not included in this percentage. You can increase your data match quality by completing the data review tasks to match these items with an emissions factor.

Increasing your data match quality