My data journey started in the mid-90s at what is now IBM Cognos during a pivotal point in the BI revolution. I then worked as an interim across different businesses and vertical sectors in BI, integration, IT consolidation, architecture and ultimately management roles. This period also placed me in numerous data remediation transformations in the run-up to the “Y2K problem”. My first group experience came at Royal Mail pre-privatisation on a breath-taking transformation against a backdrop of declining mail revenues. This seeded an ability to translate complex board-level business challenges into multi-year people, process and technology roadmaps and executable delivery programmes. At TELUS, I delivered large scale IT transformations during periods of M&A, divestiture and group consolidation. At Zurich UK, I established its first chief data office and digital innovation lab at a time when establishing analytics and data science capabilities became of board-room interest. My time leading data, analytics and CIO advisory at Capgemini Financial Services followed by numerous portfolio roles across Deloitte, HSBC, BKL, the home of British computing Bletchley Park and, currently, Centrica has honed an ability to present complex ideas in a simple manner and take this through to delivery and ultimately business value.
I enjoyed my role in the TELUS transformation across its Canadian businesses, I was successful at Royal Mail Group establishing a supply-chain visibility vision and integration platform. At Zurich UK I was able to implement its first data strategy through rapid innovative application deliveries and at Capgemini my work developing financial service data apprenticeships was rewarding. I have attained British Computer Society Fellowship, a Computer Weekly Rising Star award, multiple Information Age UK Data 50 rankings and, most recently in 2018, an Information Age TechLeaders award for my interim IT leadership across a portfolio of corporate and SME clients.
Never stop reading, learning and applying new approaches to recurring daily challenges. Stay in full-stack coding as long as possible while continually developing core competencies in data, integration, analytics, AI and data science approaches. Become a rounded business professional rather than a pure-play technologist. Walk in the shoes of the businesses, functions and people you are supporting before helping them improve through technology transformation. Diversify your professional experience early in your career and avoid specialism where possible. Consider automation and machines as advocates rather than competitors and embrace opportunities for collaboration, creativity and complex change at their periphery.
I don’t think any year turns out exactly the way we expect it to in advance. Technology and market change are accelerating at an increasing pace and so each year we are confronted with ever more complex issues and tighter targets around cost, revenue and risk. The perpetual hype associated with AI, digital, analytics, blockchain, IoT and data science in my opinion, convolutes an organisation’s ability to focus on pragmatic execution, plus regulatory change usually lags behind technology change which presents its own series of problems. I expected AI to become more mainstream, tangible and deliverable in 2018.
In the year of Brexit, I think there will be a renewed focus on operational efficiency, customer-centricity and operational data exploitation on the front-foot of the data agenda with GDPR, consent, privacy and integration constraints on the back-foot to be balanced accordingly. At Centrica, I expect an increasingly competitive market driving a need to develop highly-personalised digital customer interactions across channels. This could drive the wider operational adoption of AI, cloud, unstructured, streaming, machine learning and analytics putting the customer and their connected home at the heart of everything we do.
I have encountered this challenge in every role throughout my career - some people have great data skills and some people have great business skills, but few have a healthy balance of both. Modern data practitioners need to be a collaborative blend of technical and business change skills who can converse in the common language of business. During my time at Capgemini and TELUS respectively, we developed these multi-faceted skills through government apprenticeships and key university partnerships. Centrica itself has developed an innovative agile model that brings diverse skillsets together across our projects, the innovation hub and business functions.
I have been extremely impressed with the emergence of natural language processing supported by analytics and data science at the back-end. At Centrica, we have a chatbot called Wilbur supporting both front-office and back-office interactions which has tangibly improved customer experience and underlying employee service workloads.