We are looking for a Graduate Planning & Data Analyst to join us in Leicester.
Main duties and responsibilities
Data capture & integrity management
- Source data collection: Responsible for the daily collection of raw operational data from the production floor, including machine uptime, labor hours, and output volumes.
- Data auditing: Perform regular “sanity checks” and audits on captured data to ensure absolute accuracy before it is used for planning or reporting.
- Inventory tracking: Capture and maintain real-time data regarding raw materials, work-in-progress (WIP), and finished goods to prevent shortages and excess.
Dashboard development & visualisation
- Performance visualisation: Build, update, and maintain functional dashboards (using Excel or Power BI) that track key metrics.
- Stakeholder reporting: Prepare clear visual reports for production meetings, helping stakeholders quickly identify trends and operational bottlenecks.
- Automation of reporting: Streamline existing manual reporting processes to ensure data is updated with minimal delay.
Capacity & resource planning support
- Production scheduling support: Work closely with the Master Production Scheduler (MPS) to align daily production schedules with available labor and machine capacity.
- Scenario modelling: Help simulate “what-if” scenarios (e.g., the impact of a machine breakdown or an urgent order) to help the team pivot quickly.
- Resource allocation: Monitor resource constraints and provide data-backed recommendations on how to best distribute personnel and equipment to meet targets.
Daily operational problem solving
- Bottleneck identification: Use data captured from the floor to pinpoint specific areas where production is slowing down and propose immediate solutions.
- Cross-functional collaboration: Act as the “data bridge” between the planning office and the production floor, ensuring communication is based on accurate facts.
AI & automation
- Process mapping: Document current manual planning workflows to identify candidates for AI-driven automation.
- Continuous learning: Proactively up-skill in AI tools and frameworks to transition traditional planning into “intelligent” planning.
AI integration
- Lead and assist in the deployment of intelligent AI agents designed to automate routine data entry and predictive scheduling.
- Train internal stakeholders to use AI agents and provide support in challenges and issues.
Essential and desirable skills
Essential skills
- Education: A recently completed Bachelor’s/ master’s degree in supply chain management, Industrial Engineering, Business Analytics, or a related quantitative field.
- Advanced data manipulation: High proficiency in Microsoft Excel, including the use of advanced formulas (XLOOKUP, Index/Match), PivotTables, and Power Query for data cleansing.
- AI & automation interest: Familiarity with the concept of AI agents and how they can be applied to supply chain efficiency.
- Data visualisation: Proven ability to build and manage functional dashboards (Excel or Power BI) that translate raw data into clear operational insights.
- Data accuracy & auditing: A meticulous approach to data capture, with the ability to identify discrepancies and ensure high integrity in inventory and production records.
- Analytical thinking: Strong competency in capacity planning and resource management logic (balancing labor, machinery, and time constraints).
- Collaborative problem-solving: Ability to work effectively on a fast-paced production floor and communicate clearly with the Master Production Scheduler and other stakeholders.
- Innate curiosity: A proactive “investigative” mindset with a strong desire to understand the root causes of operational challenges.
Desirable skills
- Programming foundations: Basic knowledge of Python or SQL, or a demonstrated interest in learning these to automate manual data tasks.
- Process mapping: Experience in documenting workflows and identifying “friction points” that are suitable for automation.
- Inventory modelling: Previous exposure to inventory optimisation techniques (e.g., Safety Stock calculations or EOQ modelling) during academic projects or internships.
- Lean/Six Sigma: Foundational understanding of Lean manufacturing principles to help minimise waste in the production area.
Qualifications or relevant work experience
Recently completed Bachelor’s/ Master’s degree (or equivalent) in one of the following:
- Supply Chain Management / Logistics
- Industrial or Systems Engineering
- Business Analytics / Data Science
Desirable experience
- Internship/ experience: Any previous experience, internship or placement within a manufacturing, production, or logistics environment.
- Programming: Basic exposure to SQL or Python, specifically for the purpose of automating repetitive data tasks.
- Production floor familiarity: Comfort working in a “boots-on-the-ground” production environment and interacting directly with shop-floo
