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Product and Portfolio complexity often drive significant indirect costs in manufacturing and product development organisations. With increasing cost pressure and competition, the reduction of complexity becomes a pivotal element for cost management in many industries.

This thesis project explores the different dimensions of complexity from a cost and value perspective and suggests a methodology how to consider the financial aspects of complexity in product development project decisions. A business case model shall be developed to assess the potential costs of increased complexity vs the investments and potential product cost and function trade-offs for complexity reduction.

Complexity reduction is part of Husqvarna’s 2030 strategy, and this thesis will be used to develop the analytical framework to ensure that all relevant parameters are considered when taking complexity reduction decisions. The study will be done for the Husqvarna Construction Division (HCD).

Objectives:
 

Define and identify different complexity dimensions and drivers:

• Map out sources of complexity in product design, manufacturing processes, and supply chain.
• Explore what parameters influence the cost / value analys of complexity (i.e. is / how the cost / benefit of reduced complexity impacted by the production volume / technical complexity /value proposition to the customer)
• Identify measurable factors such as variant proliferation, tooling changes, and engineering effort and suggest KPIs to measure complexity in the organization
• Align on what dimensions are most relevant for HCD and what could be neglected to make the model more simple
   

Quantify Cost Impact:

• Develop a framework to calculate the cost implications of complexity across the division:
• Direct costs (materials, tooling, assembly, possibility to negotiate with suppliers)
• Indirect costs (engineering hours, compliance, inventory, quality assurance, IT, marketing)
• Lifecycle costs (maintenance, data management, spare parts)

Propose a Business Case Model:

• Create a calculation model that compares:
• Current complexity costs
• Potential savings from modularization and common components, late variant
• Create a model that can evaluate if a complexity reduction case is economic feasible or not (e.g. is it worth to develop one machine that can be used on all markets instead of specialized machines per market that often come with cheaper specifications).

Expected Deliverables:

• Complexity Cost Driver Map: A structured analysis of where complexity adds cost. Ideally assessing a fixed standard cost per item and transaction/function it passes through (could be on a ABC basis, differentiating high runners, regular items and slow-moving items)  
• Benchmark: Examples of how other companies and industries are working with complexity reduction and cost estimations
• Calculation Framework: A practical model for decision-making on modular investments.

Candidate Profile:
 

Background:
Master’s student in Supply Chain Management, Mechanical Engineering, or Business & Technology.

Skills:

• Strong analytical and modeling capabilities.
• Interest in manufacturing systems and product development.
• Familiarity with cost analysis and business case development.

Tools:
Excel, Power BI, or similar for data modeling; basic knowledge of ERP/MRP systems is a plus.

Why Join?

Work on a real-world challenge with direct impact on product strategy and profitability. Collaborate with cross-functional teams in engineering, operations, and finance. Gain experience in strategic decision-making tools for global manufacturing organizations.