Having graduated with a degree in geography and GIS, I’ve had a lifetime in the world of data and analytics – from setting up an analytics consulting business (Claritas) in the early 90s to running data and analytics teams for some of the UK’s biggest brands (including Orange and Sky TV).
I joined O2 (Telefonica) in 2002 to run part of the consumer P&L and, after five years, I took over responsibility for data and analytics as general manager for business intelligence. In 2013, I joined the executive team of News UK as chief data officer and then moved to be Sainsbury’s first group CDO in 2016. In September of 2018, I decided to step away from big corporates and joined Pepper Group – a global financial services business that operates medium sized businesses across 12 geographies. As group CDO, I’m responsible for driving the adoption of analytics and machine learning within each of our global businesses. I am also a non-executive director of Global Data, an AIM listed business information company.
There are two things that I’m proud of; firstly, being appointed as one of the first board-level CDOs in the UK, proving that data does have a role at the executive level in corporate businesses. Secondly, I have led (and am still leading) significant data-orientated transformation programmes across a variety of different industries that have delivered substantial business value.
Without being glib, my current boss, Mike Culhane. As co-founder and group CEO of Pepper he has clearly demonstrated his business acumen and ability to establish and scale a financial services business. But his most impressive quality is the tone he sets to lead the business; there is a real family-feel, a highly entrepreneurial but supportive culture and complete empowerment to get on and do the job you have been employed to do.
The beauty of working for a smaller, private equity-backed business is that change is constant, so what I thought I would be doing at the start of 2019, turned out to be just a small part of what I actually ended up spending my time on. Aside from creating a data and analytics code of ethics, I’ve spent a lot of time working in Asia looking at M&A opportunities. I’ve also helped establish a new Pepper business in India and have been learning a lot about financial services technology platforms. The thread that links all of this together is understanding how data and technology can be used to create and grow lending and servicing businesses.
A year ago I thought that the focus for 2019 would be how data can be used ethically – putting the customer in the spotlight and making sure that unintended bias and misuse of data was a thing of the past, but it’s clear that this debate has not moved on as fast as maybe needed.
Hopefully 2020 will be the year that regulation or control of some description comes into effect that enables data consumers to first understand how they and their suppliers are using data and secondly to govern how organisations can and cannot use their data without unintended bias or consequence.
I also think that there will be a geographic shift in where analytics innovation happens. Having spent a lot of time in Asia this year, it is clear that while India, for example, was often seen as a cost-based offshore opportunity, actually tech and data innovation is widespread and more often than not, especially in the fintech world, India is setting the agenda. That’s exciting, given the breadth and depth of talent there.
If you believe that any job can be done or done better with the application of data, you must believe that machine learning and artificial intelligence can have a profoundly positive impact on business, the economy and society. Whether it is through the applications in digital biology (faster diagnosis, better care programmes), safety (predictive maintenance, robotic maintenance) or bringing financial services to the 60% of the Earth’s population that is un- or under-banked, the opportunities are endless.
The single biggest challenge we face at Pepper is, without doubt, the challenge around international data standards. As governments around the globe start to wake up to the value and power of data, legislation is being created at a phenomenal pace. Unfortunately, no two countries are the same, which means it is impossible to set a standard operating model which can be used across geographies. This covers everything from data sovereignty, attitudes to public cloud, specific financial services regulation and so on.