My career started on the Barclays graduate programme. My career advanced quickly under senior executive guidance through retail, business corporate and global banking where I specialised in building analytical models to guide business decisions, for example, econometric models. I loved every minute of it. I was given the opportunity to work in many highly-visible data and analytics projects. Amid the early days of the financial crisis, I was asked by RBS to play a pivotal role in its turnaround. Given the uncertainties of the times, I was given a lot of advice against making the move, but my heart told me that I’d regret not at least trying to help turnaround the critical situation at RBS. So, I left Barclays and I set-up and ran the first data and analytics function in RBS’s corporate and institutional bank. Over four years, I had a great time delivering a data and analytics transformation roadmap with an amazing team. The concept of big data was just starting and I played a role in helping the bank and wider market understand how it could help us. My success saw me become the first chief analytics officer within any bank in the UK. I left RBS to then gain experience in the start-up market, principally working with ex-US intelligence and defence agency experts in data and analytics to learn about the bleeding-edge. I self-funded myself for one year at this time, which allowed me to meet many amazing people and complete some innovative projects. Having data and analytics experience in start-up, but also business expansion (Barclays) and turnaround (RBS) meant that I had quite unique experience to offer, so I made a planned move into consulting with Atos, leading its UK and Ireland data, analytics and AI business. This role was highly rewarding - I worked with an amazing team and portfolio of clients in an organisation that was a top-tier digital services provider. Moving to IBM has been eye-opening. As the clear market leader for consulting and systems integration services, it literally owns the track record for innovation and disruption. This is why I joined. The culture in IBM is essentially to dedicate our team to client success, innovation and be responsible for driving change in a positive way. I look forward to all the new challenges and learning to come as a proud IBMer .
I am the formal coach for some amazing data people. This ranges from leading heads of analytics to undergraduates from universities. It is extremely humbling and rewarding when anyone contacts me to be their performance coach.
Work hard, work smart, be patient and invest in your communication skills.Personally, I did not expect to change company, but the opportunity to join IBM was unmissable. From a market standpoint, the growth rate didn’t surprise me, nor the things people are now doing with data. The only big thing that surprised me was the ROI on AI platforms. I recently was told by a client that the £500,000 investment has quickly generated over £40 million of new revenue.
I see many organisations reorganising their data and analytics operations because they haven’t had the success due to various internal issues. Or quite the opposite - many have been successful and now want to expand into new use cases. With all this in mind, I predict that next year the growth rate will beat market expectations of circa 30-plus %.
IBM invests a huge amount in the attraction and development of talent and skills. We had over 80 highly-talented graduates join us in data, analytics, AI and cognitive in the UK in 2018, which is amazing. We relentlessly focus on personal up-skilling. We make sure every employee has to do a minimum of 40 hours of skills development training every year and this is supported by a skills academy, learning journeys and many other investments, such as our partnership with Coursera. The results are extremely positive with IBM placed number one as the leader for open source, for example, with our Apache Foundation contribution. Nobody else even comes close. We are prolific in our contributions of open source code on GitHub. So, investment in talent and skills clearly pays off and is critical to both our and the market’s overall success.
Although we are not there yet, cognitive business models really excite me. This is where a business can seamlessly engage with its customers. To do this, though, requires all the data, analytics and cognitive applications to be joined up. Nobody has perfected this, though some banks in Asia are quite advanced. Being a cognitive business is not about having a bot. It’s about how we augment human expertise to unlock new intelligence from vast quantities of data and to develop deep, predictive insights at scale. Have you ever had a conversation with a bot that covered the weather, your upcoming family holiday and then reasoning with you on the most fair and appropriate level of insurance cover? You’d say, “no”, but in the next ten years we’ll be there - and a lot more.Business and professional services inc. recruitment