The importance of building an enterprise digital thread

An enterprise digital thread can help overcome the challenges around accessing accurate product data.

With the increasing complexity of today’s interconnected products and services comes the challenge of accessing accurate product data across various domains, industries, and corporate functions. Disconnected processes and systems hinder organizations' ability to be agile, respond to change, ensure operational excellence, and maintain strong customer intimacy. To address these challenges and enable innovation and refinement, organizations can leverage the power of an enterprise digital thread.

The concept of a digital thread involves interlinking all the data related to a product throughout its life cycle, both within and outside the enterprise. This includes data generated by different entities within the organization and its extended ecosystem, from the initial concept to deployment and even to the end of the product's life. By implementing a digital thread, organizations can achieve seamless flow and visibility of information, ensuring that accurate and contextual product data is available for timely and informed decision making. Digital threads serve as the foundation for digital twins, which are real-time virtual representations of objects, processes, and systems.

Why now is the time for enterprise digital threads

Product leaders face multiple data challenges throughout the product development process.

These challenges include:

Data silos: As different functions work on building products, large volumes of disconnected data are generated. This lack of data and process orchestration makes it difficult to ensure seamless connectivity of product data as it moves from the engineering phase to the maintenance phase.

Increasing complexity: With products becoming smarter and more connected, the lines between hardware, software, and mechanical components are blurring. This complexity, combined with heterogeneous data types and formats, leads to data integrity issues and product data complexity.

Data traceability: Due to process and data disconnects, tracing an accurate product configuration from engineering through service and maintenance becomes complex. This lack of visibility into key performance indicators (KPIs) across different enterprise functions hinders impact analysis, evaluation of product upgrades, and quick response to changes.

Diversified data semantics and ontologies: Achieving data interoperability is challenging when there are numerous industry standards to adhere to. Ensuring data interoperability across vendor platforms becomes increasingly difficult as the number of standards grows.

Fragmented IT landscape and data sources: Legacy mainframe systems have transitioned to open architecture systems and microservices-driven cloud components. However, the IT landscape remains fragmented, hindering the seamless flow of product data across the life cycle.

Mergers, acquisitions, and divestitures: M&As and divestitures introduce new complexities to data processes and IT landscapes. Varying levels of data quality and ownership make it challenging to establish connected data views.

Understanding digital threads

A digital thread intertwines product, life cycle, functions, and ecosystem data.

Products go through different states as they mature: requirements, engineering, manufacturing and delivery, and service maintenance. Throughout these states, various enterprise functions collaborate and generate product data aligned with defined process frameworks. A digital thread interconnects all these product data entities, creating an enterprise digital thread that spans key functions and the extended enterprise. This traceability of product data enables data continuity and supports various business scenarios throughout the product life cycle.

The four key characteristics of a digital thread

To facilitate implementation and drive positive outcomes, enterprise digital threads should exhibit four key traits:

1. Model-based: Models represent the graphical, mathematical, or physical representation of a concept, structure, or system. High-fidelity models provide information-rich parameters, enabling integration, analysis, and simulation across different stages of the product life cycle.

2. Interoperable: A digital thread should facilitate seamless interoperability between various systems, tools, and platforms. It should support standardized data formats, protocols, and interfaces to ensure the exchange and integration of information across different domains and stakeholders.

3. Connected: The digital thread connects data, processes, and systems across the entire product life cycle, enabling end-to-end visibility and traceability. It eliminates data silos and enables real-time access to accurate and up-to-date information, fostering collaboration and informed decision making.

4. Contextual: Contextual information provides a deeper understanding of product data and its relationship to specific processes, events, or conditions. Contextualization enables stakeholders to analyze and interpret data in the right context, enhancing its value and enabling effective decision making.

By embodying these characteristics, a digital thread empowers organizations to leverage the full potential of their product data, drive innovation, improve operational efficiency, and enhance customer experiences. It creates a cohesive and integrated digital ecosystem that supports the entire product life cycle and enables organizations to adapt to evolving market demands.

Unlocking value

Digital thread implementations can yield business value while streamlining the complex processes of realizing products.

By establishing seamless connectivity and data flow across the product life cycle, organizations can achieve the following outcomes:

Improved time to market: Digital threads enable faster product development cycles by facilitating collaboration, reducing rework, and enabling concurrent engineering. By eliminating data silos and streamlining information exchange, organizations can accelerate product innovation and reduce time-consuming manual processes.

Enhanced product quality: With comprehensive visibility into the product data across its life cycle, organizations can identify and address quality issues early on. By leveraging insights from the digital thread, they can optimize design, manufacturing, and service processes, leading to improved product quality and customer satisfaction.

Increased operational efficiency: A digital thread eliminates redundant data entry and manual handovers between different departments and systems. It enables automated workflows, real-time data updates, and streamlined processes, reducing errors, minimizing delays, and improving overall operational efficiency.

Effective decision making: The digital thread provides a holistic view of product information and its relationships, enabling stakeholders to make data-driven decisions. With access to accurate and up-to-date information, organizations can assess the impact of proposed changes, evaluate alternatives, and respond quickly to market demands.

Enhanced customer experiences: By leveraging insights from the digital thread, organizations can better understand customer needs and preferences. They can tailor products and services to meet specific requirements, deliver personalized experiences, and establish long-lasting customer relationships.

The approach for achieving best outcomes

The enterprise digital thread journey delivers functional, integration, and digital capabilities incrementally and continuously.

TCS has defined a roadmap that can be tailored and synchronized with an organization's current technology plans. The main objective is to leverage ongoing and past investments made in developing capabilities to maximize business value by carefully infusing the required capabilities into the roadmap for enterprise digital thread.

The roadmap focuses on four key aspects:

Business scenarios: The reference roadmap is divided into four outcome-based scenarios, which cover the entire life cycle of a product from concept to a performing asset: rapid development, agile engineering, accelerated launch, and optimizing performance.

Functional capabilities: The business and IT systems that manage the product lifecycle (PLM) and product data (PDM); enable multidomain product development; integrate the manufacturing process and supply chain; and integrate the asset and service life cycles.

Enterprise integration: A resilient and scalable integration capability built on a service-based orchestration layer using technologies such as microservices, knowledge graph navigation, and data streaming. The more such integrations rely on industry-standard semantics for the interoperability and exchange of data, the more resilient and extensible they can be.

Analytics and insights: A data aggregation and data science layer powered by AI/ML to bring intelligence to the evolution of products, track their metrics, and provide insights that are descriptive, preventive, predictive, and prescriptive in nature. As a result, insights can be made actionable, and decisions can be better informed. 

By following this roadmap, organizations can embark on a structured and strategic journey towards establishing an enterprise digital thread, realizing its benefits, and driving sustainable competitive advantage in today's fast-paced and data-intensive business landscape.

Where to start

Begin with one approach that makes sense for your company, incorporating others as you advance.

Develop a business case: Clearly link the problem-solution-value statements, focusing particularly on measurements.

Prioritize: Align current initiatives; in particular, augment the PLM transformation journey with the four digital thread characteristics.   

Make the cultural shift from engineering to lifecycle: Shift to model-centric, enterprise connectivity, insights-driven and closed-loop actions.

Add value: Deploy digital threads and digital twins together for long-term sustainability and to adapt to changing business models.

And along your journey to an enterprise digital thread, aim for these mile markers:

• Identify digital thread scenario-based pilots.

• Establish governance and ownership of heterogenous data, formats and interoperability. 

• Ensure convergence of digital thread pilots with current transformation programs.

• Ensure long-term governance and planning for a sustainable digital thread.

Wrapping up

To achieve their life cycle objectives, manufacturers must blend digital capabilities with core functions.

Data standards and ontologies need strong governance to achieve true data interoperability. As data cut across enterprise functions, ownership and accountability become critical to manage. Cloud-based deployments go beyond infrastructure and operational benefits and help companies achieve key business outcomes.

The convergence of digital thread and digital twins yields a strong business value by achieving faster time to market, improved service excellence, and other tangible benefits.