Data is crucial in supply chain management (SCM) as it increases visibility, transparency, and resilience. However, despite its importance, sharing data within supply chains remains a challenging task.
By addressing supply chain data sharing barriers with technology adoption, standardization, and cultural alignment, businesses can implement successful strategies and drive supply chain innovation.
Check out technical, organizational, legal and regulatory, and cultural barriers to effective supply chain data sharing with their solutions and best practices.
What are supply chain data sharing barriers?
The importance of sharing data in supply chains has been particularly underscored in the post-pandemic business environment. COVID-19 significantly disrupted global supply chains, and the after-effects continue to ripple through industries even in 2023.
Companies realized that without a higher level of supply chain resilience and visibility into their partner’s operations, and a shared understanding of critical data, their ability to respond to crises and rapidly changing market conditions is severely hampered.
Efficient data sharing is essential for supply chain management, but several challenges may undermine its effectiveness. Below are the key barriers categorized into technical, organizational, legal and regulatory, and cultural challenges.
Technical barriers
1. Technology integration
Diverse technological infrastructures may pose significant integration challenges. For instance, a retailer may use one system for inventory management while its supplier uses another, which can complicate real-time data sharing. These misalignments lead to inefficiencies, delayed decision-making, and increased operational costs.
Here are possible solutions to these challenges:
- Leverage low-code/no-code platforms to create interoperable solutions that can bridge technological gaps.
- Address legacy system challenges by upgrading infrastructure and adopting interoperable tools.
2. Data standardization
With multiple entities involved, the data can be presented in various formats and structures, creating problems in assimilation and analysis. The lack of data standardization, in terms of data quality and formats, is a substantial impediment to effective data sharing.
To manage this standardization issue:
- Adopt industry-wide frameworks such as Electronic Data Interchange (EDI) or GS1 standards.
- Align on common data quality metrics and reporting standards for smoother interoperability.
Organizational barriers
3. Data silos
One of the significant barriers to sharing data in your supply chain is the existence of data silos. A data silo happens when data is isolated and hoarded within different departments or organizations, making it inaccessible to others who could potentially benefit from it.
Any organization can end up with data silos without a strategic plan for data management. For instance, a manufacturer may not share its production plans with its distributor, leading to overproduction or shortages.
Here are solutions to mitigate it:
- Implement integrated ERP systems to enable cross-departmental data visibility.
- Establish cross-functional teams and KPIs that encourage data sharing across the supply chain.
4. Organizational culture
In supply chain management, an organization’s culture is a significant determinant of how readily data sharing is adopted. If a company’s culture doesn’t endorse openness and collaboration, data-sharing initiatives may be met with resistance.
Employees could view sharing data with other entities in the supply chain as risky, fearing that it might expose vulnerabilities or dilute their unique contribution.
Below are the solutions:
- Drive cultural change through leadership buy-in and training programs.
- Incentivize collaboration and showcase the collective benefits of data sharing.
Legal and regulatory barriers
5. Data privacy and security concerns
Businesses often hesitate to share data due to concerns over data privacy and potential misuse. This becomes even more relevant given the increasingly strict data protection laws and the rising incidents of cyber threats. Another reason is that companies do not wish to disclose their internal operations and share data related to their carbon emissions, labor management practices, sourcing of raw materials, and more.
Check out possible solutions to data privacy and security concerns:
- Leverage blockchain technology for secure and transparent data sharing.
- Implement encryption and multi-layered security protocols.
- Develop transparent agreements, such as NDAs, to build trust among stakeholders.
Cultural barriers
6. Organizational resistance to change
Cultural inertia and fear of transparency within organizations often damage data sharing. Resistance may be causes by concerns about exposing internal processes or perceived risks in collaboration.
Here are solutions to mitigate organizational resistance to change:
- Promote cross-company workshops and open dialogue about the benefits of collaboration.
- Showcase success stories of collaborative supply chains that thrive on data sharing.
What are supply chain data sharing best practices?
To increase efficiency and foster collaboration, organizations can adopt the following strategies to share data effectively and securely within the supply chain network:
1. Adopt a collaborative mindset
Collaborate with suppliers beyond the tier 2 network. Consider a global company that finds that its different teams—purchasing, logistics, warehouse, and sales—are functioning in silos.
The purchasing team has valuable data about vendor performance and delivery times that the logistics team could use to better plan transportation routes and schedules.
Similarly, the sales team has insights into customer buying patterns and seasonal trends that can aid the warehouse team in efficiently managing inventory.
Recognizing the potential benefits of collaboration, the SCM team adopts a shared mindset. They implement an integrated SCM system that enables each team to access and utilize data from the others.
The outcome is a cohesive relationship where all teams can make informed decisions based on shared data. This results in improved overall supply chain performance with:
- Improved forecasting
- Optimized inventory levels
- More efficient transportation schedules
- Better service to their customers.
2. Ensure data security
Take the case of a logistics and supply chain management company. They handle sensitive data like vendor details, transportation routes, and delivery schedules. To protect this information, the company implements multi-factor authentication for system access and encrypts data both at rest and in transit. They also anonymize the data to further safeguard confidentiality.
Additionally, the company is transparent about its data security practices, sharing updates with its different stakeholders and partners. This transparency helps build trust, ensuring a reputation for secure supply chain operations.
3. Establish clear data-sharing agreements
Consider a group of companies in a supply chain network sharing data for improved operational efficiency. To ensure all members understand their data-sharing roles and responsibilities, they establish a detailed data-sharing agreement.
The agreement outlines what data should be shared, how, and who can access it. It also stipulates data usage, protection guidelines, and penalties for data misuse. This clear agreement promotes a harmonious and productive relationship among the network members, fostering trust and mutual growth.
What is supply chain information sharing?
Supply chain information sharing is the collaborative exchange of data among various stakeholders within the supply chain industry to enhance supply chain performance, resilience, and efficiency. It involves sharing supply chain data across supply chain networks, including freight logistics optimization, to address supply chain disruptions and build a more resilient supply chain.
By sharing data, supply chain managers can improve information exchange, reduce costs, and support businesses in making competitive advantages. This process leverages technology such as artificial intelligence and information technology to improve accuracy and efficiency in goods movement chains.
Initiatives like the Freight Logistics Optimization Works Flow, supported by public and private sector entities like the White House and companies such as Land O Lakes, Georgia Ports Authority, and international conferences like the one in Long Beach, aim to establish foundational freight digital infrastructure and promote open data sharing among different stakeholders.
The sharing of accurate information across the supply chain, from raw materials to end-to-end logistics, not only reduces costs but also mitigates carbon emissions, contributing to a more sustainable supply chain ecosystem.
Moreover, by participating in pilot programs and adopting digital transformation strategies, companies can unlock additional benefits and realize the true value of supply chain information sharing, gaining a competitive edge in the global marketplace.
What does data sharing mean for supply chains?
Data sharing in the supply chain refers to the process where different entities involved in the supply chain, such as manufacturers, distributors, retailers, and logistics providers, exchange information.
This information can encompass a wide array of data points, such as:
- Inventory levels
- Demand forecasts
- Sales data
- Production plans
- Delivery schedules and more.
Sharing this data can lead to enhanced transparency, greater operational efficiency, and improved decision-making across the supply chain.
What data can be shared to enhance the supply chain?
Sharing data related to real-time inventory levels, transportation schedules, and demand forecasts can significantly improve the overall supply chain. This information exchange supports better decision-making across supply chain networks, enhances supply chain resilience, and enables more efficient freight logistics optimization.
By sharing accurate data, supply chain stakeholders can mitigate disruptions, reduce costs, and improve the efficiency of goods movement chains. Additionally, access to timely data facilitates proactive measures to address supply chain issues, ultimately supporting businesses in gaining competitive advantages and reducing carbon emissions.
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