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What Data Gives You Complete Supply Chain Visibility?

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Written by
in10 Content Team
Published on
February 21, 2024

Achieving complete supply chain visibility is a complex goal that depends on various factors, including the size of the company, the complexity of its supply chain, and the specific industry in which it operates. Not to mention whatever other facets of data make up the insights an individual customer needs. However, the required data can be substantial as it encompasses multiple supply chain layers. Here are critical types of data and metrics that are crucial for attaining comprehensive supply chain visibility:

Real-Time Tracking Data: This includes GPS/cellular/LoraWan tracking of shipments and assets, enabling companies to know the exact location and condition of their goods in transit. It's about more than just the volume of data but having timely and accurate data.

Inventory Levels: Detailed information on inventory across all locations, including warehouses and in-transit goods. This requires integrating data from various sources to ensure accuracy and timeliness.

Supplier Performance Metrics: Data on supplier reliability, quality, lead times, and compliance. This involves collecting and analyzing data from every supplier to monitor performance and mitigate risks.

Demand Forecasting Data: Historical sales data, market trends, and predictive analytics are vital for understanding future demand and planning accordingly.

Transportation and Logistics Data: Information on shipping routes, carrier performance, costs, and delivery times. This also includes insights from external factors affecting transportation, such as weather conditions and geopolitical events.

Customer Order and Service Data: Detailed records of customer orders, delivery status, returns, and service inquiries to ensure customer satisfaction and proactively resolve issues.

Risk Management Data: Information on potential supply chain risks, including geopolitical risks, natural disasters, and market fluctuations. This requires a wide range of data sources to identify and mitigate risks effectively.

Regulatory Compliance Data: Data ensuring that all products and processes comply with local, national, and international regulations, which is crucial for avoiding fines and ensuring smooth operations.

All data needs are quantitative and qualitative, requiring sophisticated analytics tools and technologies like AI and machine learning to interpret and act on the data effectively. Integration of this data across systems and platforms through technologies like IoT, blockchain, and cloud-based supply chain management solutions is crucial for real-time visibility and decision-making.

Given this data's vast and varied nature, it's clear that the "amount" of data is less about a specific volume and more about the depth, breadth, and quality of data collected and analyzed. Implementing a comprehensive data strategy that addresses these areas is essential for logistics companies aiming to achieve complete supply chain visibility.

Incorporating a wide range of data sources is crucial for enhancing supply chain visibility and making informed decisions. Beyond the traditional sources mentioned earlier, several other data streams and innovative companies like Bitvore can provide valuable insights. Bitvore, known for its AI-driven analysis and predictive analytics, offers unique perspectives by analyzing unstructured data from news, press releases, financial reports, and more. It gives companies a competitive edge by identifying trends, risks, and opportunities that might not be visible through conventional data sources. Here are some additional data sources and how they can be helpful:

Social Media and Online Sentiment Analysis: Tracking social media can provide real-time insights into consumer trends, brand perception, and potential disruptions or issues with products or services. Tools that analyze sentiment can help anticipate changes in demand or identify areas of concern before they escalate.

Economic Indicators and Market Data: This includes inflation rates, employment rates, consumer spending data, and other macroeconomic indicators affecting supply and demand. Market data specific to your industry can also provide insights into trends, risks, and opportunities.

Insights: Some companies provide AI-powered insights by analyzing vast amounts of unstructured data. This can include news about geopolitical events, the financial health of suppliers and customers, industry trends, and regulatory changes. These insights can help anticipate risks and opportunities, monitor the health of key partners, and stay ahead of industry trends.

IoT Sensor Data: Beyond location tracking, IoT sensors can provide data on temperature, humidity, and other conditions that might affect the quality of goods in transit, which is especially important in cold chain logistics.

Blockchain Data: Blockchain can offer transparent and immutable records of transactions, certifications, and product provenance, which is helpful for ensuring compliance, authenticity, and quality across the supply chain.

Third-party Logistics (3PL) and Carrier Data: Integrating data from 3PLs and carriers can provide deeper insights into transportation efficiency, costs, and reliability, enabling better logistics planning and carrier performance evaluation.

Customer Feedback and Support Tickets: Analyzing data from customer feedback and support tickets can provide insights into product quality, delivery performance, and customer service issues, allowing for rapid response and continuous improvement.

Environmental and Sustainability Data: As companies increasingly prioritize sustainability, data on carbon footprints, resource usage, and environmental impact of supply chain activities become crucial for making informed decisions that align with sustainability goals.

Integrating these diverse data sources requires robust data management and analytics capabilities. Advanced analytics, AI, and machine learning can help synthesize these varied data streams into actionable insights, enabling logistics companies to anticipate changes, optimize operations, and make strategic decisions based on comprehensive visibility into their supply chains and the broader market landscape.