Supply Chain Data Sharing for Greater Visibility in 2024: An Essential Strategic Imperative

In today‘s complex global business environment, data is the fuel powering supply chain optimization and resilience. However, for many organizations, unlocking the multitude of benefits offered by open and integrated data remains an elusive goal fraught with barriers. This article delves into the growing importance of cross-enterprise supply chain data sharing, explores key challenges, and provides strategic guidance on how leaders can embark on the data sharing journey for enhanced visibility and performance.

The Critical Need for Enhanced Visibility Through Data Sharing

Supply chain visibility refers to the ability to track products, inventory, and shipments as they move through an extended supply chain network. Comprehensive visibility enables proactive risk management, informed decision making, and supply-demand synchronization.

According to Gartner, the global market for supply chain visibility solutions is estimated to reach $9.3 billion by 2026, underlining the growing strategic importance of visibility capabilities for modern supply chains.

However, as Deloitte notes, most companies still operate with very limited visibility, especially beyond their tier 1 partners. This lack of end-to-end transparency leaves supply chains vulnerable to disruptions.

The key to achieving true visibility lies in tearing down data silos within and across organizations and embracing open information sharing. As per MIT‘s Center for Transportation and Logistics, companies that engage in supply chain data sharing observe improved forecast accuracy by up to 85%.

This chart demonstrates the revenue benefits of supply chain data integration through comprehensive visibility, underscoring why it is a strategic priority.

Let us explore some of the key ways in which open data sharing confers supply chain advantages:

• Enhanced resilience – By gaining visibility into emerging supply or demand changes through data sharing, companies can proactively mitigate risks and pivot swiftly when disruptions occur.
• Improved forecasting – Integrated data from across the value chain enhances predictive abilities, ensuring optimal inventory and production planning.
• Informed decision making – Real-time data exchange with all nodes enables faster and more contextual decisions aligned to actual ground realities.
• Greater agility – End-to-end transparency and insights allow companies to rapidly adapt to evolving market dynamics and customer needs.
• Operational efficiency – Data benchmarks help identify inefficiencies and improvement opportunities across the supply chain network.
• Superior customer service – Data sharing provides complete order visibility and enables dynamic rerouting or reprioritization in case of exceptions.
• Sustainability – Data exchange helps measure and optimize carbon footprint through enhanced supply chain mapping.

The business case for supply chain visibility through cross-enterprise data sharing is stronger than ever in 2024 as macro factors create volatility. It is an urgent strategic imperative that cannot be ignored.

Navigating Key Barriers to Data Sharing

However, the road to open and seamless data sharing is paved with very real obstacles that cause many digital transformation efforts to falter.

Top challenges highlighted in this chart range from technical hurdles like data silos and integration problems to softer barriers like internal resistance. Let us examine some key issues:

Data Silos

Siloed data is a perennial problem plaguing supply chain visibility. Information confined within internal departments or shared only upon request hinders end-to-end transparency. Companies meticulously safeguard data, failing to recognize its exponential value when combined across the ecosystem.

A Capgemini study found that 63% of businesses admit to having data silos, underlining the widespread nature of this challenge.

Integration Difficulties

Disparate partner IT systems and limited interoperability hinder real-time data connectivity across the supply chain. ERPs, WMS, TMS often run on different technology stacks. APIs enable some system connectivity but can be complex to implement at scale across the value chain.

As per Forbes, nearly 50% of businesses struggle with integrating supply chain data between solutions and partners.

Privacy and Security Concerns

Apprehension around data privacy and potential misuse makes companies reticent about openly sharing information. There are valid concerns considering sensitive data like sourcing details, production volumes, and lead times.

In a survey by TraceLink, 63% of supply chain leaders highlighted data security as a key barrier to participation in data sharing programs.

Internal Resistance

A lack of executive sponsorship and change management issues also impede adoption of open data exchange. Employees accustomed to proprietary data ownership often resist moves towards reciprocal sharing across organization boundaries.

As per McKinsey, two-thirds of digital transformation efforts fall short, frequently due to cultural challenges and lack of leadership commitment.

Best Practices for Enabling Seamless Supply Chain Data Sharing

Transitioning to a model of open real-time data exchange with partners requires concerted strategies focused on people, process and technology.

Based on analysis of success patterns, this framework outlines some leading practices:

Foster a Collaborative Culture

Cultural realignment and executive buy-in are foundations. Leaders must adopt a mindset where data is shared freely to drive collective success rather than hoarded as a competitive asset.

A study by AIAG emphasizes that a collaborative culture is 3X more important for supply chain excellence than any software application.

Change management and aligning employee KPIs to data sharing goals are critical to secure internal adoption. Companies like Apple, Amazon and Unilever have succeeded in fostering a culture oriented toward mutual growth through information sharing.

Invest in Robust Data Integration

Breaking down enterprise silos is vital but not enough – seamless data connectivity must extend across the entire value chain. Leverage integration platforms like AWS IoT Core, Azure Digital Twins and One Network to enable interoperability between diverse partner systems.

APIs allow simpler cross-system data sharing. Industrial data exchange standards like OCF unified modeling also hold promise. Start small by focusing on critical tier 1 suppliers before scaling data connectivity further.

Ensure Strong Data Security

Address valid data privacy and protection concerns upfront through robust cybersecurity protocols. Implement access controls, anomaly detection, encryption and data anonymization leveraging solutions like Protegrity.

Be transparent about security policies and offer partners visibility into data handling processes. Consider blockchain-based approaches to enable greater traceability across the ecosystem.

Adopt Standards and Governance

Lack of standards is a major impediment to effective data sharing, so it is vital to enforce consistency in data formats (JSON, XML), semantics, meta-models and quality.

A strong data governance framework provides the needed oversight. Leverage MDM, cataloguing and profiling tools to ensure fitness of shared data. Enable self-service access to distributed data via governed hubs.

Prioritize Actionable Insights

The goal of supply chain data sharing is to drive better decision making through sharper insights. Leverage AI-powered analytics tools to contextualize integrated data, identify optimization opportunities and enable predictive modeling for capacity planning, forecasting and risk management.

Select the Right Technology Platform

Choose an intelligent data sharing platform like Elemica or Nulogy that aligns to your needs for ease of adoption across the partner network. Ensure support for integration, analytics, and data governance on a single, scalable platform.

Technology and implementation partners with domain expertise are invaluable allies on the data sharing journey. Visionary leaders across industries are already harnessing platforms and partnerships to unlock the power of supply chain data sharing and gain unprecedented visibility.

Real-World Success Stories

Let us examine a few examples of organizations from diverse sectors that have reaped immense value by embracing open supply chain data integration:

Intel faced chronic semiconductor supply shortages. By sharing inventory, capacity and demand data with ecosystem partners, it gained collective visibility into constraints and orchestrated prioritization decisions faster through integrated analytics.

PepsiCo connected its downstream data to retailer systems for real-time visibility into POS and inventory at over 200,000 stores, facilitating superior demand sensing and agile supply planning.

Airbus leveraged an integrated supplier portal called Skywise to exchange technical data across its aviation parts ecosystem, improving quality and availability.

These examples validate that cross-enterprise data sharing is a winning strategy with substantial payoffs if adopted methodically.

Key Takeaways and Path Forward

As supply chains grow more complex, leaders cannot afford to navigate disruptions with blinders on. Comprehensive visibility enabled through extensive data sharing across the value chain is now an absolute imperative.

However, pragmatism is equally vital. Organizations must acknowledge impediments and address legitimate concerns through robust change management, security and governance protocols. The technology landscape offers more tools than ever before to smooth the data sharing journey.

Supply chain excellence in 2024 and beyond hinges on breaking silos and fostering seamless flows of information. Leaders must make strategic investments in platforms, partnerships and skills focused on unlocking the power of integrated data.

The time for action is now. Those who transform their linear chains into dynamic data-sharing ecosystems will gain enviable visibility and resilience to navigate uncertainties. The opportunity is tremendous for organizations to leverage collective data capital and mutually thrive through collaboration.