I started out as an analyst almost by chance. It was a lower profile sector at the time and I was barely aware that it existed until I happened upon a job description that looked interesting. But it quickly became clear that I’d found my niche. I spent five years in analytics at The Co-op Bank before moving to dunnhumby. It was the perfect time to be at a fast-growing company at the forefront of a fast-growing industry. I spent ten years there, with my assignments spanning retail, CPG, the fuel industry and adtech, and including a two-year stint in Asia. The experiences I had and the people that I met while there continue to play a major role in my career today. As such, when I arrived at Cardlytics in 2016, I was pleased to find many of the same ingredients that made dunnhumby great - a fast-growing company full of enthusiastic, talented people and an incredible data asset that would be the envy of any analyst.
Going to live in Shanghai and working with retailers across Asia was an incredible experience. The culture differences were huge and the language barrier often a significant obstacle, but it was great to see many of the data and analytical techniques and principles that we’d applied successfully at home work equally well in a completely different environment.
Invest time in developing a thorough understanding of the organisation and sector that you work in. Successful use of data depends at least as much on asking the right question and communicating the answer effectively as it does on using the best tools and techniques.The two big events on the horizon at the start of the year were PSD2 and GDPR. After a huge amount of talk and activity in the build-up, the scale of impact since their respective enforcement dates has been relatively limited. This was, perhaps, always the most likely outcome in the short-term. Nevertheless, the opportunities for innovation afforded by both remain, particularly with regards to consumer data portability.
While the industry as a whole will continue to grow and progress, there will necessarily be some winners and losers along the way. The plethora of supporting technology companies that have exploded in recent years will have to start to consolidate. Some data science teams that have so far been given freedom to experiment by forward-thinking organisations will come under increasing pressure to prove their work has a positive return, especially if the economy worsens. Ultimately, this should be healthy in identifying where genuine value lies, but it will become more important than ever to communicate that value effectively.
I take a very open-minded view on requirements for specific existing skills - the right person can pick those up along the way - and focus instead on problem-solving ability, proven appetite for learning and enthusiasm for the role. For those already on the team, I believe the key is making time and space for them to continue to experiment and learn - not always easy to do, but critical for growth and retention of our best people.
Much of the highest profile data-derived activity has ultimately had the purpose of “selling more stuff”, which has contributed in part to the associated negative publicity. In the near future, data will drive revolutions in areas such as healthcare, transportation and communication that will transform the perception of its role.Data and analytics technology/service provider