The pathway
How you actually get there, here
How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.
- 1
VP, Regional Operations Intelligence (from a large enterprise)
3-5 years as a VPSkills to master
- Scaling regional strategies to global impact, managing multi-region teams, influencing C-suite peers, and developing a deep understanding of enterprise-level financial levers.
You're ready to move on when
- Successfully led a major regional operational transformation programme using data, delivering significant P&L impact.
- Built and retained a high-performing regional BI leadership team.
- Consistently provided strategic insights that influenced regional executive decisions beyond just operations.
- Demonstrated ability to navigate complex organisational politics and build consensus across diverse functions.
- 2
Chief Data Officer (CDO) or Chief Analytics Officer (CAO) (from a smaller/mid-sized company)
5-7 years as a CDO/CAOSkills to master
- Adapting enterprise data strategy to specific operational contexts, managing the unique challenges of global operations data, and leading a function within a larger C-suite structure rather than owning the entire data remit.
You're ready to move on when
- Successfully built and led a company-wide data/analytics function from the ground up.
- Demonstrated strong commercial acumen and ability to tie data initiatives directly to business value.
- Proven ability to influence a Board and executive team on data strategy and investment.
- Developed a robust understanding of data governance and compliance at an enterprise level.
- 3
VP of Operations (with strong BI/Analytics focus)
5-8 years as a VP of OperationsSkills to master
- Deepening expertise in data architecture and advanced analytics, transitioning from a primary operations role to a dedicated intelligence leadership role, and building a global BI talent pipeline.
You're ready to move on when
- Consistently used data and analytics to drive significant improvements in operational efficiency and cost reduction.
- Championed the adoption of new BI tools and methodologies within their operations function.
- Built strong partnerships with existing BI/IT teams, demonstrating a clear understanding of data infrastructure.
- Demonstrated a passion for data and a vision for its transformative power beyond their immediate operational remit.