The graduate programme at Jaguar Land Rover has been running for the last three years and last year won the DataIQ Best Development Programme award. Analytics strategy and transformation leader Asheeka Hyde puts the success of the programme down to three things. They are: the immediate return on investment, the strength of the group and the time and the continuous development of the programme.
“The graduates immediately started to produce value for the business, working on really important projects. We had a really diverse range of candidates and the programme was structured with this in mind and we spend quite a bit of time developing it,” she said.
With the 14 graduates in the first cohort Hyde quite sensibly assessed their skills before letting them loose on real world projects. She found that they weren’t familiar with some of the tools and processes used in the team. “It felt unfair to put directly to work, trying to deliver and learn at the same time, without having any training up front,” said Hyde.
The first three weeks introduces the graduates to the basics of descriptive, then diagnostic analytics. They are then given an understanding of data gathering, data cleansing, diagnosis and presentation, data visualisation with Tableau, data quality and preparing data for modelling.
In week four the grads move on to modelling, statistics and learning about common initial algorithms, as well as the tool RapidMiner. In week five they are introduced to data science and the basics of machine learning. The final week is dedicated to a hackathon in which they are set a project on the Monday and have to present on the Friday.
The programme aims to teach them soft skills such as presentation, teamwork, storytelling and stakeholder management. Those weeks are broken down into half a day of introductions, two days of training, two days of project work and a half a day of presentations.
To support the new employees throughout the programme, there is a buddy scheme set up so that each graduate is paired with another graduate from the previous year. Furthermore, in the agile team, each graduate has a performance line manager, as well as somebody who is only slightly senior to them and is responsible for helping them with their project goals. “So each person has three people they can talk to at any given time. They are also very close to each other having been with each other for six weeks,” said Hyde.
After the six weeks of training, the graduates will still have a development day every fortnight. On that day the first year grads are expected to explore and start understanding different areas with mandatory rotation between the specialisms. The second year grads dedicate themselves to one of three chosen specialisms. They are: data science, data engineering and analytics development which is also sometimes known as business analytics.
“The mandatory rotation is to give them a foundation in each area, so even if you were a data scientist, you need to know how to converse with the data engineer and the analytics developer,” Hyde said.
JLR was commended for the equal gender split of its first cohort, but Hyde is concerned that the men were outnumbered women among the applicants. Also in the following year, the there were three girls and five boys and the most recent cohort of six graduates who were recruited in January for next year’s programme return an equal gender split once more.
Hyde said: “There is more to do on that. We’re having conversations about that with HR because diversity is important to the team.”