From an early age I wanted to work in software development, and I fell into data and analytics before my career had really started; I was lucky enough to be one of the first to study cloud-based big data and analytics systems at university.
From there, I was set on applying the emerging techniques that I had come across and saw AN&Y Media as an ideal place to do that. They were a team of analysts and traders who operated in the fast-paced arena of programmatic ad-trading and analytics: effectively an arms race; there was no better place to cut my teeth building data products.
I later moved to MailOnline’s programmatic team, taking on several roles focused on maximising the operation’s data commercially. I helped to develop MailOnline’s principal data insights suite and integrated datasets across the DMG Media group. In a slightly odd twist, I was asked to use my knowledge developed extracting data for commercial gain to form MailOnline’s stance on GDPR; protecting consumers and publishers from data exploitation.
Recently, I’ve been building the core data team at Global; a company transitioning into an ad-tech powerhouse. In 2019, we reshaped the team, its focus and the technology stack as we deliver against ambitious 2020 plans.
At MailOnline, we searched extensively for tools that could power our commercial proposition, eventually deciding to develop something in-house. At the time, data management platforms were immature but by extracting granular data, we could recognise consumer patterns that maximised assets and told stories back to clients.
The product suite really did catapult us ahead of the market and for several years we watched as competitors released products with the same functionality as our original. Looking back, we really did have a great team with a perfect blend of market knowledge, innovative thinking and technical freedom to put theory into practice.
I’m fortunate to have received great advice over the years. From John Goulding’s drive and finger-on-the-pulse product innovation to Kevin Beatty’s consumer-first approach; there are many inspirational people - the challenge is doing justice to their advice. For instance, in sport, I’ve always taken inspiration from the way managers instill team values, build confidence and momentum.
2019 was far from expected for me: it’s not often that you’re involved in merging four companies to become one of the largest players in a new media vertical; and all in a matter of months. That said, Global’s ambitions were one of the main driving forces behind me joining the team.
It’s easy to overlook the value of good data warehousing. We’ve brought software engineering best practices to data engineering and focused on developing a platform and team to accelerate us into 2020. This has been essential, as Global’s ambition and focus on data analytics show little sign of slowing down.
I’m excited about how data analysis tools and techniques can be democratised within an organisation. We’re seeing more and more data cataloging and data lineage systems and I think this will be an area for growth within 2020. Companies have built swathes of data-sets within data lakes and data warehouses, but it requires analysts from across the business to really take advantage of this. Creating citizen analysts and developing communities where analysts can share identified patterns between them should be the goal for many organisations.
It’s a fantastic time for data and analytics - the discipline is maturing and being recognised as a real accelerator to business. There’s both the opportunity for new products, services and commercial collaboration, but also to challenge or re-enforce existing processes. If companies are willing to risk enabling their data scientists to question the status-quo, I believe there are huge gains to be made.
Naturally, with opportunity comes responsibility – which is easily forgotten. Consumers’ perception of what’s happening with their data is just as important as what is actually happening, and we’ve seen what can happen when that trust is eroded.
I think one of the biggest challenges is when applied well, data and analytics becomes second nature for basing business decisions. As a result, it’s often easy to overlook the complexity of the work that supported these decisions. Retrospectives and reflecting on which techniques and processes are effective is difficult, particularly in a fast-paced environment where the next challenge is always around the corner, but it’s essential. It’s even harder to enforce this when teams are succeeding, but complacency guarantees mistakes and competitors will be ready to take advantage.