What does a T-Rex have to do with data science?
Realise recently finished a really interesting project for LNER involving T-Rexes, and it reminded me of a conversation I had a few years ago. A new C-suite level individual joined our client, and we had a quick introduction call with them to run through who we are and how we can support them with their business challenges. At the end of the call, they sighed with relief and said that they were surprised to have understood everything we spoke about. It turns out, they had been dreading the call because they’ve found that calls with analysts are usually very hard to follow.
But what does this have to do with LNER or T-Rexes for that matter?
For our recent project with the rail operator, we worked on their Carbon Saving Departures Board - a new initiative designed to demystify ‘carbon jargon’ and help passengers make more sustainable travel choices this summer. The key was conveying complex methodologies and outcomes to the everyday train passenger in a way that they could truly understand and connect with.
The project involved data analytics, as well as robust logic, to compare the emissions that passengers save travelling by train with LNER from London King’s Cross on a typical day (as opposed to car and plane) to something easily recognisable. The overarching aim of the work was to simplify the science and help each passenger understand the positive impact that they were making in a tangible way.
The end result needed to be easily digestible for the general public on a split-flap board displayed in London King’s Cross station. It could not be a detailed algorithm, nor a complex value with lots of symbols that people might not have seen since they studied GCSE maths, but more of a fun, accessible way of describing the output. In other words, we had to tell the data story in the most engaging way.
So, what do T-Rexes have in common with data science? Well, about 140 T-Rexes equate to the 839k kg of CO₂ you would have saved on a typical day this summer if you travelled from London King’s Cross Station with LNER instead of by car or plane*.
Data science doesn’t have to be rocket science. If you have any business challenges (or any issues with T-Rexes!) that you would like to discuss with our team of friendly and down-to-earth analysts, please reach out to me at below.
The project involved data analytics, as well as robust logic, to compare the emissions that passengers save travelling by train with LNER from London King’s Cross on a typical day (as opposed to car and plane) to something easily recognisable. The overarching aim of the work was to simplify the science and help each passenger understand the positive impact that they were making in a tangible way.
The end result needed to be easily digestible for the general public on a split-flap board displayed in London King’s Cross station. It could not be a detailed algorithm, nor a complex value with lots of symbols that people might not have seen since they studied GCSE maths, but more of a fun, accessible way of describing the output. In other words, we had to tell the data story in the most engaging way.
So, what do T-Rexes have in common with data science? Well, about 140 T-Rexes equate to the 839k kg of CO₂ you would have saved on a typical day this summer if you travelled from London King’s Cross Station with LNER instead of by car or plane*.
Data science doesn’t have to be rocket science. If you have any business challenges (or any issues with T-Rexes!) that you would like to discuss with our team of friendly and down-to-earth analysts, please reach out to me at below.
*Based on one day summary data / compared to car & plane / emissions avoided / full and part journeys included.