## 4 Key Outcomes and Discussion
### Enablers and Barriers in the Implementation of Mass Customization  
The effectiveness of MC strategies depends on the interaction between facilitating factors and implementation constraints. The following overview consolidates these two perspectives to provide a balanced understanding.  
Enablers of MC
* Product modularity and platform strategies: modular product architectures and shared platforms support the creation of product variants without excessive complexity. These design strategies enable flexibility and scale economies.
* Advanced manufacturing technologies: technologies such as additive manufacturing, flexible manufacturing systems (FMS), reconfigurable manufacturing systems (RMS), and CPS enable agile production of customized products with minimal downtime and reconfiguration costs.
* Customer integration tools: co-design platforms, web configurators, and recommender systems facilitate active customer participation, helping translate individual preferences into feasible product configurations.
* Postponement and process modularity: delayed product differentiation (DPD) and modular production lines allow final customization to occur at later production stages, reducing inventory and operational uncertainty.
* Supply chain reconfigurability: agile supply chains enabled by real-time data exchange and collaborative planning allow rapid adaptation to customer orders and enhance service levels.
* Sustainability-oriented design: modular design and localized production reduce environmental impact. MC aligns well with circular economy principles by enabling repairaability, reuse, and resource optimization.
* Barriers to MC
* High initial costs and investment risks: developing modular architectures, acquiring new manufacturing technologies, and integrating ICT systems often require significant capital and organizational transformation.
* Data and IT integration challenges: many companies struggle with poor interoperability between systems, fragmented customer data, and cybersecurity concerns. These issues limit the capacity to automate and personalize effectively.
* Organizational complexity and resistance: MC demands cross-functional integration and cultural change, which may be resisted by staff and management. Legacy processes and siloed departments can obstruct implementation.
* Customer-related constraints: despite technological tools, many customers find customization processes confusing or time consuming. Poorly designed interfaces can reduce engagement and lead to suboptimal configurations.  
* Rigid supply chains: traditional supply chains may not accommodate high-variety, low-volume production. Without flexibility in procurement, manufacturing, and distribution, the benefits of MC are diluted.
* Lack of standardized evaluation metrics: the absence of commonly accepted KPIs makes it difficult to assess MC success consistently across industries or compare alternative approaches.  
Despite their enabling role, several I4.0 technologies face significant implementation challenges. AI-based systems require large, high-quality datasets and may raise concerns about transparency, explainability, and bias. IoT devices introduce new cybersecurity and data privacy vulnerabilities, while CPS and advanced analytics involve substantial infrastructure investment and skilled personnel. These limitations may hinder adoption, especially among SMEs or in environments with legacy systems. Moreover, the integration of these technologies often requires deep organizational change and cross-functional coordination, which can create resistance or inertia within firms.