Master Thesis Segmentation and Planning
- 🇸🇪 Sweden
- On-site
- 11 hours ago
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About this opportunity:
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Effective supply-chain planning requires balancing customer service, inventory, capacity, responsiveness, operational effort, and cost. The appropriate planning methodology depends on factors such as demand variability and predictability, product lifecycle, supply and manufacturing lead times, bill-of-material complexity, supply constraints, customer service requirements, inventory value, demand volume, replenishment frequency, decoupling points, product characteristics, and the degree of planning detail required. The suitability of a methodology may also vary across planning horizons and supply-chain tiers.
Using one methodology universally can create unnecessary complexity, excessive manual work, poor responsiveness, or inappropriate inventory levels. Conversely, applying an overly simple method to a critical or highly constrained product can increase shortages, expedite costs, and delivery-performance risks. A structured segmentation framework is therefore needed to determine which planning methodology is most appropriate for each product, location, supply-chain segment, or product-location combination.
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The framework should be business-outcome-oriented. Methodology selection should be evaluated not only through planning performance, but also through its impact on inventory turnover, delivery precision, supply-chain cost, planner workload, resilience, capacity utilization, and the effort required to maintain planning data and rules.
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What you will do:
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The thesis will investigate how products and supply-chain segments can be systematically classified and assigned to appropriate supply-chain planning methodologies. The study should develop a conceptual and practically applicable framework for determining:
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• Which segmentation dimensions and criteria should be used to distinguish products and supply-chain environments to select appropriate planning methodologies, such as supply network planning, reorder-point planning, MRP, DDMRP, finite-capacity planning, or hybrid approaches
• Which performance metrics should be used to govern and evaluate whether a selected methodology delivers the expected business outcomes
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The research may combine a literature review with empirical analysis of supply-chain, inventory, demand, and planning data. Relevant methods may include segmentation analysis, clustering, decision trees, multicriteria decision analysis, optimization, simulation, cost-benefit analysis, and interviews with supply-chain and planning stakeholders. The final framework should support fact-based decisions on where to standardize, automate, differentiate, simplify, or change planning methodologies.
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The skills you bring:
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- Suitable background: Supply Chain Management, Industrial Engineering, Operations Research, Data Science, Business Analytics, Economics, or a related field
- Knowledge of inventory management, demand planning, MRP, DDMRP, forecasting, optimization, simulation, and data analysis is advantageous.
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Why join Ericsson?At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
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What happens once you apply?Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
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Primary country and city: Sweden (SE) || Stockholm
Req ID:Â 793188Â Â
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Master Thesis Segmentation and Planning · Ericsson