Senior People Data Analyst

1.

People Data and Insights Strategy

• Ensure that the people analytics strategy is closely aligned with the overall business objectives.

• Gather and integrate data from various sources such as HR systems, employee surveys, and performance metrics.

• Identify key performance indicators (KPIs) that are relevant to the organisation's goals.

• Use historical data to predict future trends and outcomes

• Translate data insights into actionable recommendations that help stakeholders implement strategies to improve workforce outcomes.

• Developing storytelling techniques to engage and inspire end users to act

• Serve as a subject matter expert on data, insights and trends

2.

Stakeholder Collaboration:

• Partner with HR, business leaders, and cross-functional teams to understand their data and insight needs and deliver data-driven solutions.

• Work closely with the senior employee engagement manager to define data led employee engagement initiatives and strategies

• Present findings and recommendations in a clear, concise manner that resonates with both technical and non-technical audiences.

• Act as a trusted advisor on how to use data to drive workforce strategies and decisions.

3.

Metrics Development and Monitoring:

• Define and monitor key performance indicators (KPIs) related to workforce performance, engagement, and productivity.

• Establish benchmarks and track progress against workforce goals and industry standards.

• Continuously enhance metrics and reporting frameworks to reflect evolving business needs.

4.

Data Analysis and Insights:

• Analyse workforce data to uncover trends, patterns, and insights that inform HR and organisational strategies.

• Perform root cause analyses to address workforce challenges, such as turnover, absenteeism, or engagement.

• Develop and deliver dashboards, reports, and presentations that provide clear, actionable insights for HR leaders and stakeholders.

2.

Predictive and Advanced Analytics:

• Build predictive models to forecast workforce trends and help anticipate challenges in areas like turnover, hiring, and talent mobility.

• Leverage advanced analytics techniques, such as regression analysis, clustering, and machine learning, to solve complex people-related questions.

• Continuously refine models based on feedback and evolving organisational needs.

4.

Storytelling:

• Craft a compelling storyline that guides the audience through the data, providing context and highlighting key insights.

• Craft insights that amplify that value of data, insights and foster a culture of data centric decisions

• Ensure the data is accurate, relevant, and well-understood.

High-quality data forms the foundation of your story.

• Use impactful visual elements like charts, graphs, and diagrams to make the data more accessible and engaging.

• Tailor the delivery of your data story to meet the needs and understanding level of your audience.

• Focus on ...