Telling impactful stories with data
Companies House, the UK's registrar of companies for HM Government, wanted to dive into their wealth of data to create a series of blogs which would tell engaging and insightful stories about UK business today.
In collaboration with Data Design Studios, experts in data story-telling and visualisation, we started to sift through the 4.4million companies in the data set to draw out the most compelling narratives.
By applying data science techniques to the data, we were able uncover a number of interesting story angles that Data Design Studios brought to life through their visualisations for Companies House.
"Vuzo were indispensable at helping us get a handle on the data and draw out the narratives we needed to deliver on the brief - they helped us identify proverbial story needles in a very large data haystack. We couldn't have done it without them."
Data Design Studios
What's in a Name?
We wanted to understand how certain words had increased or decreased over time by calculating the share of words in company names per year.
SIC Code Synergies
SIC codes are used as a tool to organise the number of UK companies. We thought it would be interesting to investigate their correlations with one another as well as over time to identify changes in the types of businesses being incorporated.
For real estate, unsurprisingly, 2008 was a pivotal moment but we found the subsequent annual rise of SIC property pairings following the financial crisis interesting.
Since some companies have more than one SIC code, we built a network of relationships between SIC codes and analysed how the share of each SIC code paring varies over time.
The changing face of Beauty
We started to see interesting patterns emerge when looking at the rise and fall of the use of certain words in business names over time. Beauty, alongside a long list of others stuck out.
All great things start with ABC
We wanted to investigate whether the "Yellow Pages" effect had impacted how organisations chose to name their companies, our analysis demonstrated that not all letters were created equally
We calculated the share of companies founded each year using each letter of the alphabet. We looked at how these varied over time. To provide a benchmark, we used a dictionary list to calculate the expected share of each letter.