I’ve been involved in data and analytics for most of my career, in both the UK and the US. In 2000, I co-founded one of the world’s first web analytics firms, helping to shape the industry in its infancy, and pioneering techniques in digital media and marketing analytics.
In 2006, I joined Microsoft in Seattle and ran a series of data and analytics initiatives for its advertising network, the Bing search engine, and the global marketing organisation. My time at Microsoft really helped me to understand that delivering value from data in a large organisation doesn’t just require good data and good technology, but also the ability to build trust across an organisation and listen to stakeholders’ needs and concerns. It also taught me that data needs to serve the business, not the other way around.
Since 2019, I’ve been back in the UK in the role of chief data officer for Publicis Spine, a data-focused unit of Publicis Groupe that has been charged with creating a core data platform and service capability for the entire organisation. It’s been fascinating to learn about the complexity of both Publicis Groupe’s own business and that of its clients, and to see how far along many of them are in placing data at the heart of their own businesses.
I have had many significant achievements over my career in terms of driving business value through data, but the moments I’m most proud of are those when I’ve been able to help individuals – from junior members of my team, to senior VP stakeholders – understand something new, either about themselves, or the business they run, or our customers.
Those “Aha” moments are deeply satisfying to bring about, and are as much about listening and empathising with the other person and what they’re trying to achieve as they are about producing some amazing finding or insight.
I am very inspired by the work that Satya Nadella has done as CEO of Microsoft. As well as being a very data-driven leader, he has created enormous positive cultural change at the company in a relatively short space of time, helping Microsoft to be a kinder and more inclusive organisation.
After the Cambridge Analytica scandal of 2018, I was fearful that 2019 may bring an even bigger data scandal, which would have further weakened the public’s trust in companies that gather and use large amounts of information. Fortunately, this did not happen, though the UK’s Information Commissioner’s Office did propose some pretty hefty fines to British Airways and Marriott International for data breaches.
On a personal note, Publicis made a much more aggressive push into data – buying Epsilon for almost $4 billion – than I expected, underlining the group’s commitment to this space (and also its sense of urgency to deliver a differentiated value proposition around data to its clients).
2020 will see the continued democratisation of data science and the demystification of the profession, which should reduce some of the hiring pressure in the industry, though may leave many newly minted (but inexperienced) data scientists struggling to find work.
This will coincide with a period of disillusionment around “AI” systems, with greater scrutiny applied to investments in this area. Together these developments should be broadly positive for the industry, with better-defined use cases driving more reasonable levels of investment in more productive areas, which will help to improve the perception around the value of data and analytics.
Data, and the intelligent automation that depends on it, offers the prospect for people to focus on the more creative and interesting parts of their jobs, as the repetitious parts are automated. Ultimately this will be good for individuals, businesses and society, but it will require some adjustment – and the transition will not be comfortable or easy for everyone.
The impact of data and AI is a bit like the impact of electrification in the early 20th century – whole industries and careers will be changed beyond recognition, in ways that are difficult to predict. It may be a bumpy ride, but I am excited to see how it plays out.
The biggest challenges I see with clients and data are cultural. Many organisations have invested significantly over the last few years in building large scale data platforms but have not invested in instilling a culture of measurable accountability in their employees.
The effect of this has been to create a lot of numbers on dashboards, but not a lot of data-driven decision-making. Companies need to embrace an open, experimentation-driven mindset, supported by a clear sense of purpose and an underlying ethical framework. Unfortunately, these cultural changes are much harder to implement than even the most complex data platform project.