How supply chain analytics tools drive smarter 3PL decision-making

Running a 3PL with multi-warehouse operations, you know peak seasons bring relentless pressure. You have to manage a large influx of inbound shipments and orders, and also make sure they’re fulfilled on time.

Supply chain analytics tools change this equation. These AI-powered tools pull data insights from across your fulfillment system, so you can get real-time insights for data-driven decision-making.

Let’s explore what supply chain analytics tools are and how they optimize supply chain management.

What supply chain analytics tools are and why 3PLs rely on them

Supply chain analytics tools consolidate data from disparate systems into one unified view. This includes data from warehouse management systems (WMS), enterprise resource planning, ecommerce platforms, and even carrier APIs. These tools enable 3PLs and warehouse managers to make informed decisions for the fulfillment process.

These tools track a wide range of supply chain data in real time, including but not limited to:

• Inbound shipments: Order volumes, ETAs, carrier tracking, dock scheduling, and receipt discrepancies
• Inventory management: Quantities by SKU, location, and warehouse, plus aging stock and cycle counts
• Order cycle times: End-to-end metrics from order receipt through picking, packing, and shipping
• Labor metrics: Picks/lines per hour, travel distance, idle time, error rates, and shift productivity
• Carrier performance: On-time delivery rates, transit times by lane, damage incidents, and cost per shipment

For professionals in high-volume, multi-node fulfillment, this unification allows warehouse managers to anticipate visibility gaps and prevent stockouts or excess inventory during order surges.

The core types of analytics: Descriptive, diagnostic, predictive, and prescriptive

Supply chain analytics is divided into four primary categories, each addressing the “what,” “why,” “what if,” and “what now” of operations.

Descriptive analytics

Descriptive analytics provides the “what happened” foundation. It reveals patterns by summarizing historical data and setting baselines for trends. Descriptive analytics can help warehouse managers track daily inbound volumes, the number of picks per hour by zone, and stock movement frequency.

Diagnostic analytics

Diagnostic analytics digs into the “why,” uncovering root causes of problems and correlating patterns. It helps you diagnose issues before they worsen. With diagnostic analytics, warehouse managers can link delays to specific suppliers, understand slotting mismatches, and identify shipping carrier failures.

Predictive analytics

Predictive analytics forecasts “what might happen.” It uses AI to project trends and uncover emerging problems, empowering warehouse managers to anticipate disruptions early. Warehouse managers leverage predictive analytics to forecast shipment delays from vendor history, staffing needs during volume spikes, stockouts based on sales velocity, and capacity crunches from order backlogs.

Prescriptive analytics

Prescriptive analytics delivers the “what to do,” recommending precise actions to address and prevent issues. As a 3PL or warehouse manager, you can use these analytics to get guidance on supplier rerouting, path optimizations, slotting changes, carrier swaps, and more.

Together, these four types of supply chain analytics enable 3PLs to proactively detect issues and implement effective solutions.

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Using analytics to optimize routing, inventory placement, and cost control

3PLs and warehouse managers constantly make accurate decisions in short time spans: where to route orders, how to place inventory, and how to control costs. Modern warehouse management software delivers specialized capabilities for all these functions.

SAP Integrated Business Planning (IBP) is one of the best supply chain analytics tools for inventory management. It analyzes picker travel and SKU characteristics to recommend ideal locations. 3PLs can predict pick location depletion from real-time demand signals, preventing stockouts by scheduling bulk-to-pick transfers days ahead.

Kinaxis RapidResponse provides velocity mapping with dynamic SKU movement heatmaps. Moreover, Tableau and Microsoft Power BI offer exceptional reporting and anomaly visualization, so you can identify replenishment gaps on time.

Analytics for labor planning and productivity improvement

With supply chain analytics, you can manage your labor more efficiently. For instance, if you want to create precise workforce schedules, you can leverage historical order patterns and seasonal trends data to perform demand forecasting. This way, you can align your headcount to projected volumes and reduce overtime while maintaining service levels.

Many efficient supply chain analytics tools also come with picker performance features, automation ROI dashboards, and SLA compliance reports. These features empower 3PLs to plan labor and optimize productivity.

Whenever your labor productivity dips, you can leverage analytics to pinpoint the root cause and deploy targeted fixes.

Real-time dashboards enabling faster, more accurate decision-making

You can’t afford yesterday’s data in fast-moving 3PLs, and modern supply chain tools keep warehouse managers updated on the latest warehouse technology trends. Real-time dashboards are one such technological advancement. They provide live updates on your fulfillment operations, empowering you to act on the latest information.

These dashboards display order backlogs, processing speeds, inventory alerts, and automation status. Logiwa IO delivers this through tight integrations, giving full supply chain visibility.

The platform instantly notifies warehouse managers and 3PLs of carrier issues or bottlenecks. This enables them to make immediate operational corrections. Logiwa IO combines AI-driven WMS with powerful reporting to streamline your growth.

Ready to make smarter decisions? Explore Logiwa’s logistics software today.

FAQs about supply chain analytics