In 2020, I attended the World Economic Forum in Davos and the Enterprise Applications of the R Language (EARL) conference; at both events, I spoke about the planetary emergency and how using data to predict biodiversity loss can help guide us into more sustainable future. Both events generated interest and inquiries from the commercial and non-profit sectors. Over a number of international events since then, the commercial need for robust, scientific data on biodiversity impacts—along with the ability to project change into the future—has only become more obvious.

In response to this need, the Natural History Museum has supported the Biodiversity Futures Lab (of which I am Co-Lead) to further pursue commercial opportunities. The main aim is impact; we want to help companies make more sustainable choices. Any funds raised go back into the NHM.

I have developed a Reproducible Analytical Pipeline in R to produce robust data on biodiversity indicators, particularly the Biodiversity Intactness Index. This pipeline allows us to respond more quickly to data requests, while ensuring reproducibility. I also lead on the improvements in statistical methodology and data enhancements.

We have also been engaging with the Task Force for Nature Related Financial Disclosure and others.