R and DA Automation Lead

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JOB DESCRIPTION

 

R&DA Automation Lead

Automation | Innovation | Standardisation | Process Efficiency

 

Role purpose

Lead the R&DA automation, innovation and standardisation agenda by identifying, prioritising and delivering scalable solutions that reduce manual effort, simplify processes, improve quality and controls, accelerate reporting cycles and strengthen the stakeholder experience.

 

R&DA Automation Lead

• Function  - Reporting & Data Analytics (R&DA)
• Focus  - Automation, innovation, standardisation and process efficiency
• Role type - Transformation, solution delivery and change leadership

 

The opportunity

The R&DA Automation Lead will shape and execute a function-wide agenda for automation, innovation, standardisation and process efficiency across reporting, analytics and related finance processes. The role will connect business priorities with technology capabilities, convert opportunities into governed delivery plans and ensure that solutions deliver measurable and sustainable outcomes.

The role is intentionally broad and is not tied to a single programme. It covers the full improvement lifecycle, from opportunity discovery and process simplification through solution design, testing, deployment, adoption and benefits realisation.

 

Primary objectives

• Reduce manual and non-value-adding work through automation and AI-enabled solutions.
• Establish common process, data, reporting, documentation and control standards before technology is applied.
• Build a prioritised, transparent and value-led automation pipeline.
• Improve turnaround time, accuracy, consistency, controls and scalability.
• Encourage experimentation, reuse and responsible adoption of emerging capabilities.
• Create sustainable ownership through documentation, training, support models and continuous improvement.

 

Key responsibilities

Automation, standardisation and portfolio leadership

• Define and maintain the R&DA automation, innovation, standardisation and process-efficiency roadmap.
• Translate business and transformation priorities into a sequenced portfolio of initiatives.
• Establish intake, assessment and prioritisation criteria covering value, feasibility, complexity, risk, control impact and scalability.
• Balance quick wins with strategic, reusable capabilities and longer-term platform opportunities.
• Maintain visibility of pipeline, delivery status, dependencies, decisions, benefits and next-wave opportunities.

Opportunity discovery and process efficiency

• Lead discovery sessions with process owners, report owners, SMEs, technology teams and stakeholders.
• Build fact-based baselines covering volumes, effort, cycle time, frequency, manual touchpoints, exceptions, rework, quality issues and controls.
• Map current processes and identify bottlenecks, duplication, low-value activities and unnecessary hand-offs.
• Challenge processes constructively and simplify, standardise or rationalise them before automating.
• Identify opportunities for report consolidation, decommissioning, self-service, re-platforming and improved operating models.

Standardisation and scalable operating practices

• Define and maintain common standards for processes, report structures, naming conventions, templates, business rules, controls, documentation and repositories.
• Identify variations across teams and regions, distinguish justified local requirements from avoidable complexity and drive alignment to agreed standards.
• Create reusable process patterns, automation components, parameter libraries, validation rules, exception categories and support artefacts.
• Establish design and readiness checkpoints so initiatives enter build only when inputs, ownership and standards are sufficiently complete.
• Track adoption of agreed standards and address non-compliance, duplication or unnecessary customisation through governance and stakeholder engagement.

Innovation and AI enablement

• Identify practical use cases where AI, advanced analytics, automation or workflow capabilities can enhance reporting, insights, efficiency and decision support.
• Facilitate ideation, proof-of-concept activity and controlled pilots with clear hypotheses and success measures.
• Promote responsible experimentation, reuse of proven patterns and evidence-based scale-up decisions.
• Monitor emerging capabilities and translate relevant developments into practical R&DA opportunities.
• Build an innovation culture through showcases, communities, reusable assets and knowledge sharing.

Solution design and delivery

• Convert approved opportunities into clear business requirements, process designs, acceptance criteria, delivery plans and ownership models.
• Partner with business, enablement, data and technology teams to assess feasibility and define scalable solutions.
• Address source access, service accounts, environments, licences, security, privacy, compliance, integration, monitoring and support needs.
• Guide solution build and configuration while maintaining traceability to business outcomes and control requirements.
• Ensure standard design patterns, documentation and governance are applied across initiatives.

Testing, deployment and operational readiness

• Oversee unit, system, integration, performance, exception and user-acceptance testing as appropriate.
• Ensure automated outputs are compared with approved baselines and that defects are tracked to closure.
• Confirm deployment readiness, rollback considerations, runbooks, monitoring, alerts, access and support arrangements.
• Lead pilot, go-live, stabilisation and handover activities.
• Embed operational controls, ownership, service expectations and escalation routes.

Benefits, controls and continuous improvement

• Define baselines and measures for effort reduction, cycle time, quality, control effectiveness, adoption and stakeholder experience.
• Track forecast and realised benefits and secure appropriate business acceptance.
• Monitor solution performance, exceptions, failures and root causes after implementation.
• Maintain an enhancement and continuous-improvement backlog.
• Ensure automation does not weaken required controls, data protection, audit evidence or accountability.

Stakeholder, change and capability leadership

• Act as a trusted advisor who explains technical choices in clear business language.
• Build alignment across Global, Regional, R&DA, Finance, process-owner, enablement and technology stakeholders.
• Manage resistance to standardisation, rationalisation, role changes and new ways of working.
• Develop training, knowledge-transfer and adoption plans for users and support teams.
• Coach team members and improve techno-functional capability across process, data, automation and innovation disciplines.
• Escalate constraints early with impact, options, recommendation, owner and required decision date.

 

End-to-end delivery lifecycle

Stage & Lead accountability

• Discover - Understand demand, stakeholders, process, data, pain points, controls and baseline performance.
• Simplify - Remove unnecessary steps, standardise inputs and outputs, rationalise reports and clarify ownership.
• Prioritise - Assess value, feasibility, complexity, risk, reuse potential and strategic fit.
• Design - Define future-state process, requirements, solution approach, controls, support and success criteria.
• Build and validate - Develop or configure the solution; complete technical, business and control testing.
• Deploy and adopt - Pilot, release, train, communicate, stabilise and transfer ownership.
• Realise value - Measure outcomes against baseline and obtain stakeholder acceptance.
• Improve and scale - Resolve recurring issues, enhance the solution, reuse patterns and extend successful capabilities.

 

Key deliverables

• R&DA automation and innovation strategy, roadmap and prioritised pipeline.
• Opportunity intake, assessment and prioritisation framework.
• Process inventories, AS-IS maps, baselines, pain-point assessments and an agreed standardisation backlog.
• Business cases and benefits estimates for selected initiatives.
• Future-state process designs, requirements and acceptance criteria.
• Technical feasibility assessments and solution design inputs.
• Delivery plans, RAID logs, decision logs and leadership reporting.
• Test plans, evidence, defect logs and sign-offs.
• Deployment, change, training, runbook and support documentation.
• Benefits-realisation dashboard and continuous-improvement backlog.
• Standard process models, templates, naming conventions, control frameworks, reusable solution patterns and knowledge assets.

 

Experience and qualifications

Essential

• Relevant experience in reporting and data analytics, finance transformation, process improvement, automation, innovation or technology delivery.
• Proven experience leading initiatives from discovery and design through testing, deployment, adoption and benefits realisation.
• Strong understanding of process mapping, data flows, business rules, controls, exception handling and operational support.
• Experience translating business opportunities into structured requirements, roadmaps and executable delivery plans.
• Strong stakeholder management, facilitation, governance, problem-solving and executive communication skills.
• Ability to manage multiple initiatives, dependencies and priorities in a global or multi-stakeholder environment.

 

Preferred

• Experience with RPA, workflow automation, analytics platforms, AI-enabled solutions, low-code tools, Python or comparable automation approaches.
• Knowledge of Lean, Six Sigma, agile delivery, project management, product management or change management practices.
• Experience with access/security reviews, service accounts, development environments, testing disciplines and production support.
• Experience creating reusable capabilities and scaling solutions across teams, processes or geographies.

 

Core capabilities

Capability area & Expected capability

• Strategic - Roadmap development; portfolio prioritisation; value framing; operating-model alignment
• Process & standardisation - Discovery; process mapping; simplification; standardisation; rationalisation; common templates; controls
• Technology  - Automation and AI use-case assessment; requirements; integration; monitoring; support readiness
• Delivery - Planning; governance; testing; deployment; adoption; benefits realisation
• Leadership - Stakeholder influence; decision facilitation; team coaching; clear executive communication

 

Measures of success

• A transparent and prioritised pipeline aligned to R&DA and Finance priorities.
• Improvement initiatives delivered to agreed scope, quality, control and readiness standards.
• Reduced manual effort and process complexity, with measurable improvement in speed, quality or control.
• Business adoption and operational ownership established before closure.
• Benefits evidenced against agreed baselines and accepted by relevant stakeholders.
• Agreed process, reporting, documentation and control standards adopted across appropriate processes, teams and regions.
• Risks, dependencies and decisions surfaced early through reliable, decision-oriented reporting.
• A stronger culture of innovation, experimentation, continuous improvement and techno-functional learning.

 

Leadership attributes

• Outcome-focused and accountable
• Curious, innovative and commercially aware
• Structured, analytical and data-led
• Technically credible without losing business context
• Comfortable challenging complexity and established ways of working
• Collaborative across business and technology teams
• Clear, concise and influential communicator
• Committed to responsible innovation, quality, controls and sustainable change

 

Important note

• This document is a generic role profile for an R&DA Automation Lead. Final reporting line, grade, location, employment terms, mandatory qualifications and HR language should be confirmed through the applicable talent and resourcing process before publication or recruitment use.

 

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