BUSINESS PERFORMANCE & ANALYTICS LEAD at CIC Insurance Group

Job Description

About the Role

Reporting to the Director, Special Projects, the role holder will provide reliable, timely and actionable performance intelligence that supports transformation initiatives and management decision-making, with particular responsibility for sales activity, pipeline, productivity, performance measurement, forecasting, dashboards and performance analytics. The role will establish the data, measurement and analytical architecture required to understand performance, identify emerging issues, guide management intervention and determine whether transformation initiatives are delivering measurable results.

Key Responsibilities:

1. Performance Measurement and Data Governance

• Establish performance baselines against which transformation initiatives and business performance can be measured.
• Define appropriate lead and lag indicators for key performance areas.
• Develop performance-measurement frameworks aligned to strategic and transformation objectives.
• Establish standard definitions, calculation methodologies and data sources for key sales and business KPIs.
• Promote consistency, accuracy and integrity of performance data across the Group.
• Identify data-quality issues and work with relevant stakeholders to resolve them.
• Monitor performance trends and highlight emerging risks, opportunities and areas requiring management attention.

2. Sales Activity & Performance Dashboard

Working closely with Business Excellence and IT/Digital, lead the business requirements and performance logic for the Sales Activity & Performance Dashboard, covering, as relevant:

• Sales performance by team and branch.
• Sales performance by product.
• Individual sales productivity.
• Customer visits and engagements.
• Sales activity levels.
• Pipeline volumes and movement.
• Pipeline quality.
• Conversion rates.
• Forecasts and forecast accuracy.
• Performance against target.
• Performance against prior year.
• Productivity comparisons and leaderboards.
• Performance gaps and recovery plans.
• Ensure that dashboards provide actionable management information rather than simply presenting data.
• Establish appropriate refresh frequencies, definitions and controls for critical performance information.

3. Performance Analytics and Business Insight

• Analyse performance data to identify trends, relationships, anomalies and underlying drivers.
• Investigate differences in performance across branches, teams, products and sales channels.
• Analyse the relationship between sales activities and commercial outcomes.
• Identify where opportunities are being lost or delayed within the sales pipeline.
• Analyse product growth and decline and identify relevant performance drivers.
• Identify teams, branches or processes exhibiting material productivity gaps.
• Distinguish structural performance issues from temporary or isolated variances.
• Translate analytical findings into clear management insights and practical recommendations.
• Challenge assumptions and proposed interventions using objective evidence.

4. Forecasting and Performance Risk

• Develop and continuously improve sales forecasting methodologies.
• Monitor forecast accuracy and identify sources of forecast variance.
• Conduct trend, variance and scenario analysis.
• Identify emerging risks to target achievement.
• Highlight material performance risks and opportunities to management.
• Provide forward-looking analysis to support timely management intervention and corrective action.

5. Transformation Benefits Realization

• Establish a measurement approach for each major transformation initiative.
• Define the appropriate baseline, intervention, target, actual result and benefit measure.
• Track whether expected operational and commercial benefits are being realised.
• Quantify and document measurable improvements attributable to transformation interventions, where the data permits.
• Distinguish between activity completion and actual business impact.
• Provide evidence-based reporting on transformation outcomes to the Director, management and relevant governance forums.

Key Deliverables / Success Measures

• Group sales-performance baseline.
• Standard definitions and methodologies for key performance indicators.
• Sales Activity & Performance Dashboard.
• Daily, weekly and monthly performance reporting, as required.
• Pipeline, productivity and conversion analytics.
• Sales forecasting methodology/model and accuracy monitoring.
• Performance variance and risk reports.
• Transformation benefits-realisation framework.
• Executive-level performance insights and recommendations.
• Improved data consistency and confidence in management information.
• Clear evidence of the performance impact of major transformation initiatives.

Who We’re Looking For

Essential Knowledge/Skills and Experience Required:

Essential

• Bachelor’s degree in Statistics, Mathematics, Actuarial Science, Economics, Finance, Business Analytics, Data Analytics, Computer Science, Engineering or a related discipline.
• 5–8 years’ relevant experience in business intelligence, performance analytics, management information, commercial analytics, data analysis or business performance management.
• Advanced Excel capability.
• Strong practical experience with Power BI or an equivalent business-intelligence platform.
• Strong analytical, communication and executive-presentation capabilities.

Desirable

• Master’s degree in Business Analytics, Data Analytics, Economics, Finance, MBA or a related field.
• Power BI certification.
• SQL or other data-querying capability.
• Python or R capability.
• Experience in sales or commercial analytics.
• Experience working with CRM systems and sales data.
• Experience designing and implementing executive dashboards.

Critical Competencies

• Strong analytical and critical thinking.
• Excellent data interpretation and quantitative reasoning.
• Strong business and commercial acumen.
• Advanced Excel and Power BI capability.
• Ability to translate complex data into clear business insight.
• Strong understanding of data quality, definitions and measurement integrity.
• Strong problem-solving and investigative capability.
• Excellent data storytelling and presentation skills.
• Ability to communicate analytical findings to non-technical stakeholders.
• Confidence to challenge management assumptions using evidence.
• Curiosity and intellectual rigour.
• Strong commercial orientation and focus on business impact.