Deep Dive

Failure to share complete, accurate, or timely data with suppliers can create significant problems throughout the supply chain, leading to a lack of visibility and transparency. This in turn may result in inaccurate demand forecasting and inventory management, often manifesting as the bullwhip effect, which causes excess stock or costly shortages. Consequently, operational inefficiencies like production delays and suboptimal logistics drive up costs. This can erode trust and collaboration with suppliers.

Ultimately, poor data sharing increases risks, reduces resilience, inflates costs through expedited shipping and lost sales and makes performance measurement difficult. This leaves the supply chain vulnerable and less competitive.

Benefits of AI-enabled data sharing with suppliers

Sharing data with suppliers can bring numerous benefits to a supply chain, leading to improved efficiency, reduced costs, enhanced resilience, and stronger relationships.

Improved Visibility and Transparency

• Real-time Insights: Sharing data like inventory levels, demand forecasts, sales data, and production plans gives suppliers real-time visibility into the supply chain's needs. This allows them to adjust their own operations proactively.
• End-to-End Tracking: Enhanced transparency enables tracking of products from raw materials to the end consumer, helping identify bottlenecks, quality issues, and potential disruptions.
• Enhanced Supplier Inventory Availability: Enable suppliers to leverage the latest data to predict future needs more accurately and optimize stock availability and improve responsiveness to plan changes.
• Reduced Bullwhip Effect: By sharing accurate demand data, the "bullwhip effect" (where small demand fluctuations amplify up the supply chain, leading to excess inventory and costs) can be significantly mitigated.
• Optimized Inventory Levels: Suppliers can better plan their production and inventory based on actual demand, reducing the need for safety stock and minimizing holding costs for everyone in the chain.

Increased Operational Efficiency

• Smoother Production: Suppliers can align their production schedules with the supply chain's needs, leading to more efficient manufacturing processes and reduced lead times.
• Efficient Transportation: Sharing delivery schedules and transportation data allows for better planning of routes and schedules, optimizing logistics and reducing transportation costs.
• Reduced Waste: Better forecasting and inventory management contribute to less waste due to obsolescence or overproduction.

Stronger Supplier Relationships and Collaboration

• Trust and Accountability: Open data sharing builds trust and fosters a collaborative environment. When suppliers see that honesty and transparency are rewarded, they are more likely to communicate problems directly and work towards solutions.
• Joint Problem Solving: With shared information, both parties can collaboratively identify and address issues, leading to quicker resolutions and continuous improvement.
• Co-Innovation: Understanding market trends and customer insights together can lead to co-creation of innovative solutions and products.

Better Risk Management and Resilience

• Early Detection of Disruptions: Real-time data allows for early detection of potential risks, such as sourcing delays or quality issues, enabling proactive measures to mitigate them.
• Swift Response to Changes: Timely information exchange enables rapid adjustments to changing market conditions or unexpected events, enhancing the supply chain's adaptability and resilience.
• Compliance: Data sharing helps ensure compliance with regulations related to sourcing, labor practices, and environmental impact.

Cost Reduction

• Lower Inventory Costs: As mentioned, optimized inventory levels reduce carrying costs.
• Reduced Expedited Shipping: Better planning minimizes the need for costly expedited shipments.
• Fewer Stockouts: Preventing stockouts means fewer lost sales and customer dissatisfaction.
• Improved Negotiating Power: Data on supplier performance can lead to better negotiation terms.

Improved Customer Service

• Higher Product Availability: Efficient supply chains with less disruption mean products are more consistently available for customers.
• Faster Deliveries: Optimized logistics contribute to quicker and more reliable delivery times.

In essence, sharing data transforms the supply chain from a series of independent transactions into an integrated, collaborative ecosystem, benefiting all participants.

Implementation & Enhancement

Selecting A Solution

When building out and utilizing automated supplier information exchange solutions, it is important to consider:

• Data quality & latency: real-time integration, master-data governance, streaming ETL – requirements to ensuring data is up-to-date.
• Change management: upskilling suppliers in their usage – test solutions with lower-risk suppliers, before switching focus to rolling out with the largest, high-impact suppliers in your supply chain, whose downstream impact is likely to be the greatest.
• Cybersecurity: ensure the system supports granular permissions and access controls consistent with your business requirements, and any partner access (e.g. via portals) is similarly secure.
• Ongoing maintenance costs: does the solution run in the cloud, or must it be hosted internally/on-premises and maintained manually?
• Open-source: is the information exchange software solution open-source, or is there a risk of platform/vendor lock-in?
• Incremental adoption: can the Automated Sharing With Suppliers solution be used to target specific suppliers initially to prove its value and deliver quick wins before broader roll-out?

HASH is an open-source platform capable of integrating information from any source, both structured and unstructured. This allows it to act independently as an Automated Sharing With Suppliers solution, or integrate with existing ones, to provide higher-quality, more up-to-date, and more extensive supply chain visibility. HASH was built from the ground-up to utilize AI, deeply integrating both traditional machine learning and new generative AI. To find out more about our platform, visit hash.ai or contact us to learn more about how our technology and services can support your supply chain.

Roadmap To Value

A typical Automated Sharing With Suppliers built on HASH looks like:

1. Baseline & cleanse data – connect key ERPs, supplier portals and specify any unstructured data sources of interest.
2. Launch sharing layer – real-time, secure data sharing
3. Pilot with key suppliers – prove value with reduced scope of suppliers
4. Expand to all suppliers – make system available to all suppliers
5. Continuously learn – reinforce models with new data; driving a culture of decision-intelligence through an "OODA loop".