Logging on to the Emsi UK website this morning may have been a little disorientating for a few moments. The header has been replaced by the strapline Insight connecting the education, economic development and employment sectors. There are now three portals connecting to these three sectors. And the cool little dancing bar chart won’t have escaped your attention.
But beyond this refresh, we wanted to draw your attention to something we have added that we are sure you will find exciting: Emsi Labs. What is this?
Our innovation team are constantly coming up with ideas of how we can use our data, sometimes in conjunction with other datasets, to answer questions and provide solutions for organisations in the education, economic development and employment sectors. Sometimes these ideas end up leading down a rabbit hole. Sometimes they simply end up on the cutting room floor. But quite often they end up forming the basis of a solution to a problem that the organisations we are partnering with are trying to solve.
Emsi Labs, which can be found on the Resources dropdown, is basically an interactive testing ground for these ideas. Our hope is that by throwing them out into the public sphere and asking for feedback, we can more quickly see which concepts are destined for the rabbit hole, which are for the cutting floor, and which are worth pursuing towards a finished product. Think of it as an area of experimentation: we get to throw our very rough and ready ideas out to you; you get the opportunity to go and have some fun playing around with the data; and we both end up with a better sense of which concepts can provide the solutions that will help you achieve your organisation’s goals.
We currently have three prototypes on Emsi Labs:
- Brexit jobs — Shows the link between jobs and earnings, and how an area voted in last year’s referendum
- Peer areas for industry structure — Allows you to see which local authorities are most similar in terms of their industrial mix
- T-level specialisation in LEP regions — Uses the Location Quotient (LQ) statistical measurement to identify which T-Level routes have the highest relative specialisation for every LEP region in the country
So do feel free to go and have a play around with these prototypes, and do be sure to leave your comments so that we can get to know what you think of each idea, how you might use the data, and whether we’re on to something.