Weaving a Digital Fabric

Past attempts to monitor, assess or mitigate supply chains through data modeling have traditionally been limited by the scope of data capture. Previous models might only map a few strands of global shipping paths, leaving out the steps along the way, often handled by other stakeholders utilizing their own data collection platforms. Because important variables were often missing, insights from data analysis were clouded by uncertainty.

Digital fabric initiatives, by contrast, endeavor to build a far more comprehensive view of supply chains, interweaving massive volumes of real-time transactions. This effort results in higher-resolution detail from such technologies as RFID tags and IoT sensor data, but also broadens data capture by stitching multiple network databases together — even those operated by different enterprises.  

While building a digital fabric architecture for relevant supply chains represents an extensive multi-year effort to establish the infrastructure, the potential benefits of a comprehensive voluble data model may have a powerful, game-changing impact on how global supply chains are orchestrated, with unprecedented capabilities for all parties involved.

This success guide explores the challenges and potential business implications of a wide-scale digital fabric initiative. Offered as a case study, the ongoing efforts at Molex — one of the world’s largest electronic interconnect providers — illustrate a proven strategy for implementation, validating specific initiatives taken to achieve the manufacturer’s long-term goals for optimized inventory management, reduced lead times and enhanced agility across thousands of global threads.

For electronics companies exploring a buildout of digital fabric for supply chain orchestration, it is important to understand the technologies involved and the potential challenges and barriers to implementation.

While data collection, analytics and automation inside an enterprise can be instigated by a single directive of an executive, weaving together digital fabric requires navigating the interests of both internal and external stakeholders. Integrating diverse systems, applications and data sources across the supply chain and facilitating real-time data exchange requires a round-table conversation among stakeholders, including suppliers, manufacturers, distributors and retailers. As efforts at integrated platforms scale and evolve, third-party logistics (3PL), fourth-party logistics (4PL) and transport carriers may also play important roles in data-sharing arrangements.

The first hurdle is human, with each party taking actions to ensure transparent and trustworthy data exchange. Agreements must be made to share datasets, implement sufficient hardware connectivity at the many nodes across a network and, in the longer term, coordinate with future automated actions that may be created through the platform. This involves close collaboration and frequent communication among supply chain partners throughout the project.

The second preliminary challenge is technical. Diverse platforms may measure data differently, using varying languages and computing formats, or calculate key indicators in their own unique way. Aligning data across organizations requires an extensive process of evaluating the quality, reliability and interoperability of inputs, which is a necessary part of any initiative.

New tools in artificial intelligence (AI) and machine learning (ML) can help normalize the variance in data attributes inside an integrated platform, translating data collection from one operator to correspond with metrics from another. Automated data management may also aid in calculating the degree of uncertainty of data model insights in a “risk-adjusted” approach.

Once architecture for an integrated platform is designed and populated, the work of digital fabric implementation can move on to address a wide variety of supply chain improvement goals. Advanced analytics tools leverage this consolidated data to generate actionable insights, predict demand patterns, identify potential risks and optimize resource allocation.

The end game is to select the best automated toolkit for each enterprise and incorporate it into day-to-day business practices, establishing seamless collaboration and communication among supply chain partners. This real-time use of supply chain data across many locations integrates into a Business Digital Operating Model (BDOM), which is critical to institutionalizing the digital fabric. This organizational improvement is achieved through establishing secure messaging platforms, collaborative planning tools, shared dashboards or other custom applications.

When Molex began developing a digital fabric framework to enhance its industry-leading end-to-end (E2E) digital supply chain capabilities, it first needed to establish a comprehensive list of necessary capabilities. In planning, it was clear the company’s supply chain orchestration vision would not be realized without addressing proper linkage and visibility around the following capabilities, systems and platforms:

• Demand/supply planning and real-time scenario planning
• Strategic supplier performance scorecard
• End-to-end logistics visibility
• Enterprise-wide procurement intelligence platform
• Supplier collaboration network
• Global trade compliance automation
• Network modeling and process mining
• NPD/RFQ decision-making from design to sourcing to manufacturing

Implementation of this complex undertaking requires thoughtful strategy. By collaborating across the various teams involved in supply chain orchestration, a four-pronged strategy was developed to address all the key functions and teams needed for integration. These pillar focus areas emerged as talent, operating models, software and most importantly, data—which is regarded as the fuel for AI-driven insights.  

The Molex supply chain orchestration initiative and digital fabric enhancements represent improvements that are already helping customers maximize real-time responsiveness as market conditions shift. After data is captured and a patchwork of networks stitched together into a single model, the final step is to distribute the insights to decision-makers across the network. Both suppliers and internal departments can rely on real-time assessments of conditions, as well as future projections, to optimize their operations.

Getting digital fabric insights onto the dashboards of the personnel who can make best use of them involves software integration into the existing BDOM system. A similar strategy may be implemented to software infrastructure at each of the external stakeholders of the platform.

A carefully crafted BDOM can help organizations deploy and scale advanced model capabilities in ways that deliver mutual benefit. Updated business processes and new operating models are equally important for successful implementation. Operating models can be thought of as institutionalizing the new capabilities for end users.

Overall, a well-designed integration of digital fabric platforms leveraging BDOMs can provide enormous value. Organizations can now anticipate, adapt and mitigate in the face of supply chain situations that were previously opaque and uncertain.

By setting sights on both a comprehensive cross-organization data platform and a transformation of processes through BDOM tools, Molex is taking a more agile and responsive approach to supply chains that unlocks new opportunities, drives future growth and generates long-term competitive advantages.

Digital supply chain orchestration is a cornerstone of the Molex strategy for achieving operational excellence and delivering superior value to customers and stakeholders. The company’s investment in digital fabric development reflects its commitment to leveraging technology to drive innovation, efficiency and agility. As Molex continues to refine and expand its digital capabilities, it sets a new standard for supply chain management in the digital age.