Analysing and reporting data

When reporting against carbon data, it is important to decide on a reporting metric and to report publicly before the data is collected and processed.

In order to make this reporting transferable and therefore comparable with other departments and even other countries, it is essential to be clear and open about methodologies around recording and calculating reporting metrics and and to make the underlying data available for analysis by others.

This can lead to an element of data cleanup. For instance, if a contract has no end date, the SPP value of it cannot be calculated. If two departments use different methodologies to calculate SPP metrics, these will need to be reconciled to enable direct comparisons and from there, a top level overview of SPP across the public sector.

Reporting data

Data reports can take many forms, depending on the use case of the audience. A Minister or Secretary might require a written report, whereas a time-poor department heads might only want e-mail alerts, while analysts and report writers might want a dashboard or even a spreadsheet. Regardless, with good, clean, accessible data, all these use cases can be met.

Internal analysis

In governments around the world there is an appetite to use and analyse sustainable procurement data alongside other datasets to identify correlations. Examples include regional data, regulatory data (school or care home assessments), tax data, grant data. This can help test hypotheses around whether or not sustainable procurements compromise on or improve other outcomes. Moreover, such analyses allow for departments to identify points of potential intervention.

External analysis

As Covid-19 showed, public facing toolsets and dashboards are of immense value. This is because these tools allow the public to understand not only problems around emerging crises but outcomes relating to data. Public facing dashboards allow public users, be they civil society, private sector analysts or concerned citizens the ability to interact with the data and understand the data.

Whether or not to publish openly

Internal publishing such as for policy outcome measurement can rely on sensitive datasets that might be confidential, for instance codes around taxation. These concerns are typically related to edge cases which can be redacted (e.g. personal identifiers such as social security numbers) or overestimated. By way of example, whether or not spend data was published openly would have little effect on invoicing fraud, especially as fraudsters have other ways of obtaining this information. However, the benefits of publishing spend data outweigh these risks.

This is because open publishing demonstrates to citizens, funders such as international banks and development banks where the problems lie to better target funding and investment for SPP and wider development beyond. Without licensing or usage constraints, the public and private sector can also take, use, and adapt the data to better suit their needs. Civil society can use the data to hold buyers to account, to ensure that these buyers are living up to their promises and targets around sustainable procurement.

For governments too, there are benefits. Publishing the data openly allows government departments to get around complicated data sharing agreements and allow government analysts to just dive into the data. For broader government, open publication helps foster transparency and therefore trust in the government.

The art of the possible

Source: https://vpt.lrv.lt/lt/svieslente

Source: https://spendnetwork.com/carbon/