Unlocking Innovation: 5 Reasons Why Engineers Need Service Data for Designing Complex Products

As an engineer focused on designing new, innovative products, you face the persistent challenge of accessing accurate, relevant, and contextualized data from the various domains where your products are used. This lack of visibility can hinder informed decision-making and collaboration, leading to inefficiency. Despite technological advancements like IoT, AR, AI, and machine learning, the issue isn't data availability. Instead, the challenge is accessing and utilizing the right data effectively. One example is data from service interactions, which often remains underutilized, leading to missed opportunities for innovation and optimization. Bridging this gap requires establishing a digital thread to better integrate engineering, production, and service operations, facilitating the seamless flow of information across the product lifecycle.

CIMdata recently published a research report on this topic, which can be read here: Connecting Services to Engineering - CIMdata Commentary Report

A key aspect of establishing a digital thread is the integration of engineering and service data through comprehensive Bills of Material (BOMs), facilitating better planning, execution, and insights across functions. By linking physical assets to virtual representations, organizations can enhance predictive maintenance, resource planning, and customer experiences.

5 reasons why engineering teams need to understand service data

The following list illustrates just some of the value of gaining access to and understanding service data, as part of the design process.

1. Enhance product reliability: Accessing service data provides insights into real-world product performance, enabling engineers to design more reliable and durable products that withstand long-term use.
2. Optimize maintenance processes: By understanding how products are serviced in the field, engineers can design for easier maintenance and service technicians can better plan to bring the right parts to every field service engagement, reducing downtime and improving overall operational efficiency.
3. Drive continuous improvement: Service data reveals areas for enhancement based on actual usage and maintenance patterns, allowing engineers to iteratively improve product designs for better performance and customer satisfaction.
4. Facilitate predictive maintenance: Leveraging service data enables engineers to implement predictive maintenance strategies, proactively addressing potential issues before they escalate, thus extending product lifespan and reducing lifecycle costs.
5. Foster customer-centric design: Incorporating service insights into the design process ensures that products meet customer needs throughout their lifecycle, enhancing user experience and fostering long-term customer loyalty.

Few would argue the above benefits have no value – the challenge is how to gain access in a meaningful way. The most common challenge in today’s digital age is too much data, not enough. What can be done to address this issue?

Making sense of the data

One approach that can help overcome this challenge is to embrace an asset-centric data collection and assessment strategy. This is an option that is now possible, which can be achieved by establishing a closed-loop digital thread.

As explained in a recent CIMdata research report, “This entails creating an asset system of record used within a comprehensive asset work execution and management process. This type of approach should include the eBOM, mBOM, and sBOM information linked to the asset hierarchy and system of record, which can then be used to enable the following capabilities.”

The report continues with an explanation of the other suggested steps to complete this process. Access the report here.

The result is data-driven insights across the product lifecycle. These can be leveraged to improve asset quality and performance while supporting new business models, such as outcome-based services.

The solution

PTC's Service Lifecycle Management (SLM) solution is one way to achieve these objectives. By standardizing how data is collected from product design through production and service delivery, organizations can optimize asset performance, enhance customer value, and drive business outcomes through a holistic approach that integrates digital and physical realms.

When service data is integrated into the design and innovation process, engineers can create complex, discrete products that not only meet performance requirements but also excel in reliability, maintainability, and customer satisfaction. Embracing a holistic approach that bridges engineering and service operations empowers engineers to drive innovation and deliver exceptional products that stand the test of time.