In today’s competitive and innovation-focused marketplace, product design goes beyond aesthetics and functionality; it significantly influences time to market, customer satisfaction and profitability. As customer expectations change and product lifecycles become shorter, design and engineering teams need to work efficiently, collaborate across different locations and adapt quickly to shifts in demand. Nevertheless, many organizations still depend on traditional on-prem systems that struggle to meet contemporary requirements.
These traditional systems often suffer from common challenges like
Data silos and lack of integration
Challenge: Legacy systems often operate in isolation, making it difficult to share data across departments such as R&D, manufacturing, sales and logistics.
Example: A tire manufacturer’s R&D team develops a new tread design; however, the legacy Product Management System (PMS) does not integrate with the Enterprise Resource Planning (ERP) or Customer Relationship Management (CRM) systems. As a result, marketing and sales teams remain unaware of the new product’s specifications or launch timeline.
Limited Support for Modern Technologies
Challenge: Legacy systems cannot often support technologies such as the IoT, AI, ML or cloud-based analytics. These technologies are essential for predictive maintenance, quality control and demand forecasting.
Example: A company aims to use IoT sensors to monitor tire performance in real time and provide that data for product development. However, the legacy product management system (PMS) cannot ingest or process this data, which limits innovation.
Poor user experience and manual processes
Challenge: Older systems often have outdated interfaces and require manual data entry, increasing the risk of errors and slowing down workflows.
Example: Engineers must manually input test results from tire durability tests into spreadsheets, then re-enter them into the PMS. This wastes time and introduces errors that affect product quality tracking.
Inflexibility and high maintenance costs
Challenge: Customizing or upgrading legacy systems is expensive and time-consuming, making it hard to adapt to market changes or regulatory updates.
Example: When new environmental regulations require detailed tracking of raw materials, the legacy PMS cannot be easily updated to capture this information, forcing the company to depend on external tools or manual tracking.
Inadequate Product Lifecycle Management (PLM)
Challenge: Legacy systems often lack end-to-end visibility into the product lifecycle from concept to retirement.
Example: A tire model that underperforms in certain climates continues to be sold in those regions because the PMS doesn’t provide lifecycle performance analytics or customer feedback integration.
Security and compliance risks
Challenge: Older systems may not meet modern cybersecurity standards or compliance requirements (e.g., GDPR, ISO 9001).
Example: A data breach exposes sensitive product design files because the legacy PMS lacks encryption and access control features.
Modernizing product design is essential to address common challenges and evolving customer expectations, such as improved fuel efficiency, sustainability, cost-effectiveness and the specific requirements of electric vehicles (EVs) like lower rolling resistance and higher load capacity. This process goes beyond mere technical upgrades; it is a strategic enabler of digital transformation. Many leading tire manufacturers are beginning to modernize their product designs using cloud technologies, primarily for the following reasons:
Global collaboration at scale
Cloud-native platforms enable seamless, real-time collaboration among globally dispersed design teams, suppliers and partners. Engineers can co-develop, review and simulate designs without the latency or data silos associated with on-prem infrastructure.
Elastic compute and storage
Product design applications, especially CAD, PLM and CAE tools, are resource-intensive. The cloud provides unlimited compute power and storage, allowing companies to run high-fidelity simulations and render jobs without investing in expensive on-site hardware.
Business agility and speed to market
Cloud platforms empower teams to rapidly prototype, test and iterate on designs, helping companies respond to changing market demands and customer feedback faster than ever before. Infrastructure as Code (IaC) and automation tools accelerate provisioning, scaling and deployment.
Reduced costs and operational overhead
By consolidating and modernizing design tools on the cloud, organizations can drastically reduce the cost of hardware maintenance, software licensing and manual administrative tasks. Subscription-based models also improve cost predictability and align spending with actual usage.
Security, resilience and compliance
Leading cloud providers offer built-in security features such as data encryption, identity access management and continuous monitoring. Combined with disaster recovery and backup services, this ensures the integrity and availability of critical design data even in adverse conditions.
Support for emerging technologies
The cloud is the ideal foundation for integrating AI/ML, digital twins, IoT and generative design into the product development lifecycle. With access to advanced analytics and machine learning services, engineering teams can derive deeper insights, optimize performance and drive innovation.
Modernizing design workflows with the cloud solves today’s infrastructure challenges. It also paves the way for future-ready engineering that is fast, intelligent and resilient.
Through the example below, HCLtech has tried to showcase how a global manufacturing leader modernized its entire product design and engineering ecosystem using AWS cloud technologies and the remarkable outcomes they achieved in agility, performance and resilience.
A global tire manufacturer adopted a cloud-first approach to modernizing its design workflows in partnership with AWS and the cloud transformation team at HCLTech.
Key steps included:
- Assessment and planning: Workshops were conducted to understand current business processes, integrations and infrastructure.
- Cloud hosting evaluation: Multiple deployment models, including SaaS and IaaS, were considered to meet flexibility and performance needs.
- Architecture modernization: A robust, scalable and cost-efficient architecture was deployed using Infrastructure as Code.
- Data and application migration: Design applications and databases were migrated using services like AWS DataSync and modernized for PaaS compatibility.
Key areas of transformation
- CAD and PLM on the AWS Cloud: Critical product design and lifecycle management applications were moved to cloud-based environments, enabling remote access, collaboration and automation.
- High-Performance Computing (HPC): Simulation and job processing tasks were migrated to AWS cloud HPC environments to improve performance and scalability.
- Monitoring and governance: Centralized monitoring, alerting and analytics were implemented to ensure smooth operations and track usage.
- Security and resilience: Leveraging VDI solutions and cloud-native security tools significantly enhanced data protection and compliance.
Business impact
The transformation yielded measurable improvements across several key dimensions:
- Speed: Design and simulation processes were accelerated by integrating tools and data on a single platform.
- Cost efficiency: Application modernization reduced maintenance costs and freed up resources for innovation.
- Security: Cloud-hosted infrastructure and encryption best practices ensured secure access and data integrity.
- Performance: System responsiveness improved by over 20%, with infrastructure costs reduced by up to 25%.
- Resilience: Disaster recovery and high availability setups enhanced business continuity and reduced risk during outages.
What’s next? The roadmap forward
AWS Cloud transformation is not a one-time event. It’s an ongoing journey. Future priorities include:
- Consolidating legacy applications into a unified cloud-hosted PLM platform.
- Scaling containerized design applications for rapid deployment across geographies.
- Exploring AI-driven design automation and predictive analytics.
- Launching pilots in areas like quality control, requirement management and manufacturing optimization.
Conclusion
This journey shows the potential of cloud computing to enhance engineering and product design. By adopting modern cloud technologies, organizations can achieve greater agility, security and innovation, better positioning themselves for success in the digital era.
For more information, please write to us at: AWSEBU2@hcltech.com
