Centre of Enablement Manager - Data/Analytics & AI in Watford

Centre of Enablement/Excellence (CoE) Manager is accountable for the end-to-end operational leadership of the Data, Analytics & AI Centre of Enablement within Group. The role ensures that the CoE operates effectively as the central governing and enablement function, driving standardisation, prioritisation, adoption, and value realisation of data and AI initiatives across the organisation. Operating within a lean, high-authority, low-touch Target Operating Model, the CoE Manager does not directly deliver use cases but ensures:

• Demand is effectively triaged and prioritised
• Delivery teams are aligned and supported
• Value is clearly defined, tracked, and realised
• Adoption is driven across the business

Key responsibilities:

1. Team Leadership & Governance - Lead and develop the CoE Management and Data & AI Governance teams. Define clear roles, ways of working, and performance expectations. Ensure alignment with enterprise Data, Analytics & AI operating model and governance frameworks.
2. CoE Performance & Operations - Own the day-to-day operational effectiveness of the CoE. Establish and manage KPIs covering demand pipeline, delivery flow, and value realisation. Ensure consistent processes across intake, prioritisation, approval, and oversight.
3. Demand Management - Lead the demand intake and triage process. Ensure a structured prioritisation framework that balances cost vs effort, business value, and strategic alignment. Manage and maintain a transparent pipeline of work. Coordinate resource allocation across internal teams and external partners.
4. Benefits Realisation & Value Tracking - Define frameworks for measuring ROI and business impact of Data & AI initiatives. Ensure all requests have a clearly defined value case prior to approval. Conduct post-implementation reviews and value audits. Maintain and report a centralised view of realised benefits across the portfolio.
5. Communications & Engagement - Promote the CoE and its services across Group. Own a Communication & Engagement strategy including roadshows, showcases, and webinars. Own the CoE digital presence (SharePoint, knowledge base, FAQs, guidance materials). Gather and report user feedback and satisfaction metrics.
6. Workforce Training & Upskilling - Partner with Learning & Development to define Data & AI capability frameworks and develop structured training pathways aligned to business roles. Support the creation of learning content with internal teams and external partners. Enable workforce uplift in data literacy, AI adoption, and tooling.
7. Change Management & Adoption - Monitor adoption of Data & AI solutions across the organisation. Identify barriers to adoption and define remediation actions. Partner with Change Managers to embed adoption into delivery lifecycle. Track adoption KPIs (usage, engagement, behavioural change).
8. Innovation & Community - Foster a culture of innovation across Group. Establish and lead a Data & AI Innovation Hub, including Hackathons and other relevant events. Facilitate structured intake of innovative Use Cases and Proof-of-Concepts (PoCs). Ensure successful PoCs are transitioned into formal delivery pipelines.
9. Policies & Procedures - Own Data, Analytics & AI policies, standards, and procedures. Ensure alignment with governance, risk, security, and compliance frameworks. Coordinate updates, approvals, and communication to stakeholders.

Skills & Experience

Essential - Proven experience leading a Centre of Excellence / Centre of Enablement function. Experience in Data, Analytics, AI, or digital transformation environments. Demonstrated ability to manage demand pipelines and prioritisation frameworks. Strong stakeholder engagement across business and technology functions. Experience in benefits realisation and value tracking.

Desirable - Experience working with System Integrators or external delivery partners. Knowledge of AI governance, risk, and ethical frameworks. Experience with enterprise-scale change management and adoption strategies. Familiarity with Data & AI tooling ecosystems.