By Paul R Salmon FCILT, FSCM
In today’s volatile, interconnected world, supply chains face unprecedented challenges—disruptions from pandemics, geopolitical tensions, extreme weather, and rapidly shifting consumer demands. Organisations everywhere are asking: how can we make our supply chains more resilient, agile, and cost-effective?
The answer increasingly lies in data. Data is not just an operational enabler; it’s a strategic asset. But not all data is created equal. Certain critical data elements form the backbone of supply chain success. Clean, complete, and actionable, these 10 data types empower organisations to anticipate disruption, respond rapidly, and optimise performance.
📦 1. Item Master Data: The Foundation of Everything
At the core of every supply chain lies item master data—unique identifiers (SKUs, part numbers), descriptions, weights, dimensions, and units of measure. This is the DNA of supply chain operations.
Why It Matters: Errors here cascade throughout procurement, warehousing, transportation, and billing. A single duplicate SKU can result in overstocking or stockouts.
Example: A global retailer discovered that 15% of its SKUs were duplicated or incorrectly classified, leading to £12M in unnecessary inventory. By cleaning and standardising its item master data, it reduced warehouse space by 20% and improved fulfilment speed.
📊 2. Inventory Levels (Real-Time): Seeing What You Have
You can’t manage what you can’t see. Real-time visibility of stock across warehouses, stores, supplier sites, and goods-in-transit is essential.
Why It Matters: Without accurate inventory data, organisations either hold too much stock (tying up cash) or too little (risking stockouts).
Example: During the pandemic, businesses with live inventory dashboards—like Zara—could adjust production and redeploy stock to meet shifting demand, while rivals were left with stranded goods.
🤝 3. Supplier Data: Know Your Network
Supplier data includes contact details, capabilities, lead times, financial health, certifications, and risk ratings.
Why It Matters: Supplier insight supports diversification strategies and proactive risk management.
Example: Toyota, scarred by supply chain shocks from the 2011 tsunami, now maps tier-1 and tier-2 suppliers in detail. This visibility allows them to spot vulnerabilities and switch suppliers faster than competitors.
🧱 4. Bill of Materials (BOM): Seeing Below the Surface
A BOM lists all components and raw materials needed to make a finished product. It provides multi-tier visibility into supply networks.
Why It Matters: Without it, organisations are blind to upstream risks (e.g., a tier-2 supplier dependent on a single source of cobalt).
Example: Apple uses BOM visibility to monitor critical materials like rare earth metals, ensuring diversification before geopolitical constraints bite.
📈 5. Demand Forecasts: Anticipate, Don’t React
Good forecasts combine historical data, market trends, and external signals (e.g., weather, social media sentiment).
Why It Matters: Accurate forecasts avoid the bullwhip effect, enabling leaner inventories and better production planning.
Example: Procter & Gamble leveraged AI-powered demand forecasting to maintain 95% on-shelf availability during volatile pandemic demand swings for cleaning products.
🚚 6. Transportation & Logistics Data: Track and Trace
Live tracking of shipments, carrier performance, and estimated delivery times supports dynamic logistics.
Why It Matters: Enables rerouting during disruption and proactive communication with customers.
Example: Maersk’s global container tracking platform allows customers to monitor shipments in real time and mitigate delays caused by port congestion.
🕒 7. Lead Times (Planned vs Actual): Know the Real Picture
Lead time data captures how long it takes to source, produce, and deliver goods.
Why It Matters: Without it, businesses cannot create accurate schedules or respond to delays effectively.
Example: A UK electronics manufacturer cut production delays by 30% by analysing lead time variances and working with suppliers to smooth them out.
🛒 8. Customer Order Data: Fulfilment Starts Here
Customer order data includes volumes, SKUs, delivery locations, and service-level agreements (SLAs).
Why It Matters: Drives picking, packing, and shipping operations. Clean order data enables accurate, on-time fulfilment.
Example: Amazon’s order management system uses granular customer data to dynamically route orders to the closest fulfilment centre, speeding up delivery and cutting transport costs.
💷 9. Financial Data (Cost-to-Serve): Balance Cost and Service
Cost-to-serve data captures procurement costs, logistics costs, and margins across products and customers.
Why It Matters: Helps businesses identify loss-making activities and make trade-offs between cost and service.
Example: A food distributor identified that 20% of its SKUs accounted for 80% of delivery costs. Armed with this insight, it rationalised SKUs and optimised routes, saving £2.5M annually.
🌱 10. Compliance & ESG Data: Building Sustainable Supply Chains
Environmental, Social, and Governance (ESG) data includes carbon footprints, ethical sourcing compliance, and supplier certifications.
Why It Matters: Consumers and regulators are increasingly demanding supply chain transparency.
Example: Unilever uses sustainability data to assess supplier performance, ensuring its products meet ethical and environmental standards.
🚀 The Strategic Imperative
These 10 data elements don’t just support day-to-day operations—they are the levers of resilience, efficiency, and competitive advantage. Clean, integrated, and accessible, they:
✅ Reduce costs through leaner inventories and optimised logistics.
✅ Enhance agility to respond faster to disruptions.
✅ Enable collaboration across partners and ecosystems.
In today’s world, businesses that treat data as a strategic asset—not just an operational necessity—will lead the next generation of supply chain innovation.
“In modern supply chains, data isn’t just information. It’s infrastructure.”
📝 Next Steps: A Data Health Check
How healthy is your supply chain data? Are your item masters clean? Do you have live inventory visibility? Are you confident in your supplier and lead time data?
The strongest supply chains of tomorrow will belong to those investing in data quality, governance, and analytics today.
