Visualizing Company Visit Scores From the Bank of England

Economic data is commonly expressed in aggregate. Consumption and investment behaviors are summed up as Gross Domestic Product, prices of a basket of goods are analyzed to provide an aggregate Consumer Price Index, and Unemployment and tax records are analyzed to provide unemployment rates. Economic concepts are broken out by industry, geography, or other criteria, but economic classifications are still presented in a "top-down" fashion.

Huge strides have been made in the field of data analysis. Techniques for dealing with large data sets have emerged, and "big data" has become a trendy buzzword. Fields which previously relied on intuition are being revolutionized by this new availability of meaningful data.

Economics is a mature field. Econometrics is essentially what data science was before the term data science existed. The theory behind the aggregation of the economy is well developed, and these numbers have been accepted by the business and academic community. New data sources are available, but markets still move on official data releases.

New advances are being made in collecting economic data. Companies like Premise are working to aggregate price level data from the ground up in developing countries, while MIT's Billion Prices Project is collecting this same data by scraping the web.

These still remain two separate worlds however. Economic data was aggregated in the first place because the sort of data collection we have today never existed, and was always meant to be an approximation of the behaviour of the economy.

Change needs to occur on both sides of the divide, and the Bank of England's release of granular survey data can illustrate how this can be bridged. I created this visualization to help move back and forth intelligently between detailed survey data and broad economic concepts, and I hope this can be used to inspire more collaborative innovation between these two fields.

Start by choosing an economic concept below you'd like to visualize.