Overcoming heavy equipment design challenges in today’s rapidly evolving market

By Hendrik Lange

Today’s heavy equipment manufacturers face unprecedented pressures in a rapidly evolving marketplace. From increasing product complexity to increasing demand for customization and stringent regulatory requirements, manufacturers of construction, mining, agricultural and material handling equipment must navigate a challenging landscape while maintaining profitability and innovation. In the podcast below, Chad Jackson of Lifecycle Insights and Jagannathan TC from Siemens Digital Industries Software reveal critical insights into how manufacturers can accelerate their equipment design processes to stay competitive.

The conversation explores innovative solutions that can help manufacturers streamline their development cycles while meeting the demanding requirements of their customers. As the industry keeps evolving, understanding these challenges and implementing the right strategies becomes essential for long-term success.

High-mix, low-volume product offerings present unique challenges

Heavy equipment manufacturers operate under a high-mix, low-volume business model, which creates significant challenges for design teams and results in increased pressure on product development cycles. Unlike high-volume consumer products, heavy equipment manufacturers invest substantial effort in design and engineering for relatively small production runs, resulting in lower profit margins per unit.

This business model is compounded by several key factors that complicate development cycles and increase costs. First, electrification and digitalization of modern heavy equipment requires the integration of multiple distinct systems, like mechanical, electrical, electronics and software. Each of these systems must work seamlessly together, creating a multidisciplinary challenge that many organizations struggle to manage effectively.

Second, regulatory requirements continue to intensify across global markets, with governments implementing stricter standards for energy efficiency, emissions and safety. These requirements add layers of complexity to the design process and require extensive testing and validation before products can reach the market.

Finally, the utilitarian nature of heavy equipment demands extensive customization to meet specific functional requirements. Unlike consumer products where aesthetics and comfort play a significant role, heavy equipment often must be customized to specific customer applications and designed for durability and reliability in harsh operating environments.

The benefits of integrated, multidisciplinary equipment design environments

Many heavy equipment manufacturers have grown through decades of organic expansion and strategic acquisitions, resulting in organizations with multiple brands, tools, and processes. This fragmented reality creates significant inefficiencies, including manual work, data duplication, extensive search times and non-value-added activities throughout the design process.

The challenge becomes more pronounced when different departments within these organizations work in isolation, using disparate systems and point solutions, focusing on their own priorities rather than on the common goal. This siloed approach leads to endless design iterations, communication breakdowns and costly delays in bringing products to market.

To address these challenges, successful manufacturers are adopting integrated, multidisciplinary equipment design environments that operate on shared data models and unified product development platforms. This approach enables faster iteration cycles, reduces redundant work, and allows teams to frontload critical decision points in the development process. By catching issues early in the design phase, organizations can avoid the exponentially higher costs of addressing problems later in the product lifecycle.

The ideal solutions focus on both horizontal integration—bringing multiple disciplines together to work simultaneously rather than sequentially—and vertical integration throughout the entire product lifecycle from initial design through manufacturing and into field operations. This comprehensive approach creates a digital thread that maintains data consistency and visibility across all stakeholders throughout the development process.

Managing customization and configuration complexity

The heavy equipment industry heavily relies on two distinct business models: configure-to-order (CTO) and engineer-to-order (ETO) approaches. Configure-to-order scenarios involve core products like excavators or tractors that can be customized with various attachments and accessories to meet specific customer requirements. This approach requires sophisticated configuration management systems that can handle extensive product variations while maintaining development efficiency.

For designing configure-to-order products, success depends on establishing validated configurations at the product planning stage, ensuring that design teams focus their efforts on proven, market-ready combinations only. This approach emphasizes platform strategies that maximize component reuse and commonality across product lines, reducing development costs and improving efficiency.

Engineer-to-order scenarios present even greater complexity, as manufacturers must create completely custom solutions for specific customer requirements. This process involves two critical phases: winning the initial bid and executing the project once awarded. Both phases require sophisticated automation tools and robust rules engines that can quickly generate accurate bids while ensuring technical feasibility.

Leading organizations have achieved remarkable results through advanced automation in their ETO processes, with some companies reporting up to 80% reduction in bid lead times and doubling their capacity to respond to opportunities with the same team size. Design automation capabilities have enabled some manufacturers to reduce engineering effort by up to 90%, freeing valuable talent to focus on innovation and more complex challenges.

The role of artificial intelligence and future technologies

As the industry evolves, artificial intelligence and machine learning technologies are transforming heavy equipment design processes. However, successful implementation requires focusing on specific use cases and measurable outcomes rather than following technology trends.

Current AI applications include adaptive user interfaces that accelerate designer productivity and reduce learning curves for new team members. Advanced design platforms now feature AI-driven chatbots and agents for rapid information retrieval and generative design capabilities that create initial concepts based on specified requirements and constraints.

The foundation for successful AI implementation lies in integrated, automated systems that collect and learn from operational data. Organizations with robust digital platforms are better positioned to leverage AI capabilities while protecting intellectual property through secure data management.

Future AI developments will focus on “technology with a purpose”—solutions delivering measurable business value through improved efficiency, reduced costs, and enhanced innovation capabilities.

Maintaining competitiveness and profitability

Accelerated heavy equipment design requires a comprehensive approach that addresses technology, process, and organizational challenges simultaneously. Manufacturers must focus on four key criteria when selecting platforms:

Ease of deployment
Ease of learning
Scalability
Open architecture for system integration

A digital transformation begins by integrating design environments enabling multidisciplinary collaboration and maintaining data consistency throughout the product lifecycle. This foundation supports both horizontal integration between engineering disciplines and vertical integration across development stages.

The heavy equipment industry faces a critical juncture where accelerated new product introduction (NPI) of innovative designs is essential for maintaining competitiveness and profitability. Organizations investing in integrated platforms, streamlined equipment design processes and emerging technologies will thrive in an increasingly demanding marketplace while continuing to innovate and serve customers effectively.

About the speakers

Jagannathan TC has been in the industrial software business now for over 16 years, after spending over 7 years at the beginning of his career in the automotive industry. As part of Siemens, Jagannathan has been in several roles in sales and sales management covering enterprise accounts, mid-market, SMB with a strong focus on Automotive, Industrial Machinery & Heavy Equipment industries. Today, Jagannathan is Director-Sales for Core Industries in DISW-India. He holds a full-time MBA in Strategic Marketing, Strategy & Leadership and an Automobile Engineering degree.

Chad Jackson is the Chief Analyst and CEO of Lifecycle Insights. He leads the company’s research and thought leadership programs, attends and speaks at industry events, and reviews emerging technology solutions. Chad’s thirty-year career has focused on improving executives’ ability to reap value from technology-led engineering initiatives during the industry’s transition to smart, connected products.