Understanding the characteristics of high growth companies using non-traditional data sources


A new study into high growth companies by the Office for National Statistics (ONS) Data Science Campus has used web content read by Glass AI to understand the characteristics that may lead to high performance.

Research into the characteristics of high growth companies to date has tended to use traditional datasets and methods. “Non-traditional data” in this context broadly refers to data initially collected for a purpose other than statistics, research or administration. For example, data collected about a company from the web.

For this study, Glass shared web content from a random sample of 30,000 UK active companies. Active companies were determined by tracking changes to the web site within a couple of months prior to the delivery. The data included company descriptions, sector classifications, other company mentions, news articles, job adverts and people biographies.

The analysis from the ONS confirmed existing research that it’s difficult to predict high growth firms. However, the analysis of the web content showed that the use of certain key terms and being well networked with other companies are features associated with high growth firms — and given further data these insights could be developed further to help tailor targeting and policy to help businesses that could potentially be high growth.

Read the full report here.