Family folklore has it that, aged two, I used to arrange my building blocks into symmetrical patterns in their tray, every day a different pattern. Ten years later I discovered logic puzzle books which, strangely, I consumed as light relief from homework.
From my earliest days, I’ve been drawn to finding patterns, and problem-solving, and so it was that I developed an affinity for maths and went on to study it to MSc level. My first proper job was to model the movement of air traffic through UK airspace. The technique used would now be referred to as a form of data science, but this was analytics before the term analytics, let alone data science, became commonplace.
Over the following 20 years, my career took me through organisations including easyJet, Tesco, Sky and TUI, and through roles within traditional analytics, BI, data management, research, campaign operations and web analytics.
As I’ve progressed, I’ve found a passion not just for data but also for people development, consumer psychology and for driving strategic change. Never one for a career plan, my approach has been to follow what I enjoy, and to keep learning, which seems to be a good formula for success.
One of them has to be creating a new consumer needs segmentation for TUI. At the point of launch, the project - a truly collaborative effort between research and analytics - had already been a year in the making. However, the hard yards of selling it into the broader organisation had only just begun.
My team and I spent many weeks road-showing the new segments and bringing them to life for our stakeholders. Our efforts paid off when they were placed at the heart of the new corporate strategy and selected by the group business to underpin their consumer strategy.
My father is an electrical engineer by training. Having transcended his working-class upbringing to attend university, and, eventually, reach director level within his own career, he’s shown me the value of hard work. He’s also taught me that we’re only ever as good as the people that support us.
Professionally, more or less. I moved to Collinson this year as it was time to move on and stretch myself. I had imagined moving to a larger organisation, such as those I’d worked for previously, but I’m actually very pleased to be part of a smaller, family-owned company where the impact of my actions are more apparent and it’s easier to see how everything joins up. Being a part of the travel experiences leadership team provides a great opportunity to see across the different business areas and work with them to really embed data and analytics into their decision-making.
I think we’ve now moved beyond peak hype for data science as a discipline and are increasingly accepting that we need to start with the data. Data governance and data ops are the new buzzwords as analysis is only as good as the available data.
I see a rebalancing of the need for traditional analysis vs data science as organisations become increasingly aware of the need for a mix of skills and competencies. Finally, businesses will take a more realistic view of their data’s potential and the broader cultural integration that needs to be in place to maximise this.
I believe there remains an untapped opportunity for many organisations to use their customer data, combined with a knowledge of behavioural economics, to provide a genuinely personalised yet authentic customer experience. However, beyond this, as society moves into what some may call a post-truth era, instead of using data to obfuscate and influence, I wonder if it’s now time to use it objectively to inform, through bolder and clearer communication of the absolute facts. Perhaps, it’s time to become a little more data literate as a society and explore how data and analytics as a community could facilitate this?
There is a view, with data, that bigger is better and that we should be looking to gather any and all data that we can get our hands on and get analysing. I believe that it’s more sustainable to create a meaningful data-set from the outset that will not only save analysts time downstream but also provide greater visibility and accountability from a data governance perspective. This pushes a level of responsibility onto the owners of the source systems, that hasn’t always been there, to know the data that they’re generating and consider their place in the value chain.