Conor McGovern, vice-president of analytics and AI, Capgemini Invent
Describe your career to date
I have spent more than 25 years in data and analytics consulting. My first role as an analyst at Deloitte was to assist with programme management for a global consumer goods brand. When not taking minutes in meetings, I started helping another team simulating flows through the distribution centre we were programme managing the build for. Fortunately, there was more value in me focusing on the analytics, freeing me from programme management duties and setting me on my career path.
Starting in 2003, I focused on marketing analytics, building data and analytics teams and products to meet the growing demands of the CMO. The appeal was both the fundamental lack of data-driven marketing accountability (research then showed only 11% of marketing directors could demonstrate return on their marketing investment) and the challenge of deriving insight and foresight from a tangle of client and third-party data. In 2007, I moved to head Accenture’s Marketing Sciences team in the UK, rising to lead the global marketing analytics function and working with some of the world’s largest brands.
In March 2020, I took on a new challenge to lead Capgemini Invent’s analytics and AI practice in the UK. I consider these last three years a career highlight. The team has more than doubled to well over 200 data and analytics consulting experts. In 2021, I took on an additional global role leading a new group within Invent called Enterprise Data & Analytics, which has grown to over 2,000 practitioners today. The real highlights though are achieving this growth while preserving our unique, collaborative culture and being part of the business and societal benefit we deliver.
What key skills or attributes do you consider have contributed to your success in this role?
The first attribute is championing collaboration - whether that’s within and across my teams, with wider Invent and broader Capgemini or building trusted, collaborative relationships with our clients. Second is a personal passion for continuous learning, keeping on top of what’s new in our amazing field and the application of new developments for our clients.
What level of data maturity do you typically encounter across your client base and what tends to hold this back?
Our clients genuinely span the full gamut of analytical maturity. We have the honour of working with many of the world’s recognised data-leaders in their industry. This requires us in Capgemini Invent to be at the top of our game, bringing fresh, innovative, sometimes experimental ideas to our clients.
We also work with a wide array of clients who are earlier in their data and analytics transformation journey. Here there are opportunities to rapidly accelerate progress, learning from the pitfalls others have experienced.
On what holds back advancing an organisation’s analytical maturity, there is no one single, simple factor. There can be challenges around foundational data enablers necessary for building data-powered enterprises such as infrastructure, governance, and operations. This may require additional focus on data quality, modernising data infrastructure or operationalising data and analytics through data and MLOps.
There can be challenges around data activation - the use of data in end-to-end business processes to secure business outcomes i.e., transforming data and insights into actions at scale. This may require better alignment of data and analytics strategy with business strategy, building users trust in corporate data and insights, fostering a data-powered culture or establishing centres of excellence to support business teams.
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