WHO CARES - ABOUT WHAT
PUBLIC INTEREST IN UNSDG TOPICS
Materiality analysis is a process used to ensure that organisations are focusing on issues that have a direct or indirect impact on an organisation’s ability to create, preserve or erode economic, environmental and social value for itself, its stakeholders and society at large. A pioneering approach involves using ‘big data’ from internet search query records to determine the saliency of different sustainability issues, across different countries, and over time. Based on millions of Google searches, public interest in 64 different sustainability issues has been mapped across eight countries. The data are then analysed and trend lines are fitted using the statistical functions in Tableau. Based on aggregate search data, per capita search data, and trends in searches over time, we are able to both establish the importance of different sustainability issues across different cultural contexts, and also forecast future salient topics for organisations to address. This information can be a powerful aid in setting organisational sustainability strategies, and tailoring sustainability reporting to public concerns. This page presents different search query studies of materiality.
Who Cares - About What?
Materiality Assessment using Search Traffic for Key Sustainability Issues
* NOTE: This page presents a limited version of the results presented as a demonstration of capability. Information on different countries and KPIs is available upon request.
Despite sustainability being a global concept, not every country places the same level of importance on the same issues. The visualisations below illustrate the level of interest different issues have within different countries, and how this interest changes over time.
The first visualisation shows the average monthly volume of Google searches for key words over the past year for, 64 different sustainability issues. The data are based on over 70 million individual Google searches across seven countries. The visualisation reveals the level of interest and engagement people have with these sustainability issues. It needs to be emphasised that the countries differ dramatically in the size of their population. However, further analysis of the 10 most searched for issues for each country revealed that, of the 64 issues, only 22 issues found across all the seven top 10 lists. Fifteen of the issues appeared in more than one countries top 10 list. There was therefore, a large degree of commonality in which issues were considered important across the countries, with some issues appearing in all the countries top 10 list.
SEARCH VOLUME ON KPI'S ACROSS COUNTRIES
PER-CAPITA SEARCH VOLUME ON KPI'S
In addition to looking at absolute search volumes, it is also important to consider trends in searches for different issues over time. Trends in 15 issues that were found to be common to more than one countries top 10 issues are analysed across the past 14 years in the second visualisation.
Interest in different sustainability issues rises and falls over time, and throughout the year. The trend lines illustrate the general direction of trends in each issue, within each country over the past 14 years. Unlike the previous visualisation, here search traffic is normalised between 0 and 100. The 100 point represents the highest relative level of search traffic the issue has received over the 14 years. Different lines on the visualisation should only be compared in terms of trends, as the vertical axis does not use absolute numbers. For example a score of 50 for searches for 'Climate change' in India could represent a vastly different total number of searches than a score of 50 for searches for 'Climate change' in New Zealand. However, it can be said that in both cases, searches for 'Climate change' were only half as high, relative to all other searches, as they were at another point in time in both countries.
The data are drawn from Google Trends. Rather than relying on search terms, the visualisation employs search ‘topics’. ‘Topics’ utilise Google Knowledge Graph, which pulls together related search terms under a common topic, for example, the topic ‘Human rights’ will include searches for similar phrases such as ‘Human liberty’ and also equivalent terms searched for in a different languages, such as ‘derechos humanos’ (Spanish for human rights). This ensures that the visualisation better covers general engagement or interest in a topic without the limitations of using a single search term.