I’ve worked my entire career in data. I’d love to claim I had the foresight straight out of university that data was going to change the world over the subsequent couple of decades, but, if I’m honest, I was randomly assigned a project at the end of my graduate training at IBM and it happened to be building MI reports. But from that start, I quickly realised how important data was to the future of business (and that one day data would become sexy!)
Since then I have built two market-leading data businesses from scratch. Back in 2010, I left IBM with my business partner Jon Summers to start Ernst & Young’s (EY) Financial Services Data Advisory Practice, growing it to over 140 people in four years. And again in 2014, when Jon and I left EY with colleagues to co-found Mudano. Today we’ve built Mudano into the leading financial services data consulting business in the UK.
When you start a business, you’re a big driver for its culture, achievements and ambition. My proudest moment was when I realised the business had grown beyond the co-founders’ initial ambition and progressed well beyond our personal capabilities.
The things that make me most proud are when we develop solutions that solve problems people didn’t even realise were solvable; whether that be predicting issues in multi-billion pound change portfolios, generating tens of millions of new revenue through machine learning-led propensity models or changing organisations’ complete understanding of their own business through customer journey visualisation.
I love how fast technology is changing the art of the possible in data. I am constantly inspired by our technical specialists at Mudano, our scientists and engineers, for their relentless passion for staying at the cutting edge, not only in technology but focusing on the business opportunities that unlocks.
2019 saw a continued mindset shift around data within the financial services sector. It has been great to see the changing expectations across the business of what can (and must) be achieved with data and machine learning to drive real business value.
We moved from applied machine learning being vanity projects in 2018, to innovation and delivery projects in 2019. This means we start 2020 with a much stronger drive to realise the value of data in machine learning in all types of change projects
The democratisation of data will mean data becomes more open, enabling data-led decision making for more people at all levels across organisations. Coupled with more accessible data visualisation and prepackaged machine learning models, this will further democratise not just data, but also the ability to generate insights.
Data ethics has rightly become a topic of discussion for the industry. The impact on fairness and inherent bias of moving more decision making to machines must be addressed to ensure leaps in technology drive the right type of societal progress.
The next few years will see the continued progression to commoditised AI in all aspects of our lives. I believe there is a huge opportunity for this to drive a future of humans augmented by AI, rather than just the automation and removal of human jobs.
The robots are coming, but hopefully we will find a way for them to help us all do more, not just have them take our jobs. A society underpinned by AI will be able to accelerate its potential like never before.
Probably the greatest technological challenge faced by clients isn’t a technological one, it is a cultural one. The need for organisations to embrace data culture in order to derive the greatest value from it cannot be understated.
By and large, we are still rooted in 20th-century management practices built on top of 19th-century management principles and the gap between technology, data and the organisation must be addressed in order to claim the opportunity that data affords us.