AI-Powered Supply Chain Management & Analytics Software - Live Product Demo
In this demo, you will see how supply chain teams use analytics to:
- End-to-End Supply Chain Visibility:
✔ Unified view across demand, inventory, and execution
✔ Early bottleneck detection - Inventory Optimization:
✔ Reduce excess inventory
✔ Detect demand–supply gaps earlier by SKU and location
✔ Improve forecast accuracy and reduce stockouts - Cost Reduction:
✔ Lower carrying and expediting costs
✔ Align planning with real capacity constraints
✔ Improve service levels without increasing inventory - Spare Parts & Asset Performance Management:
✔ Ensure availability of critical spares with lower working capital exposure
✔ Eliminate excess and unplanned spare parts across locations
✔ Reduce asset downtime by aligning MRO inventory with maintenance demand
Who This Demo Is Best For
- Supply chain leaders managing volatility and constraints
- Inventory & S&OP teams struggling with stockouts or excess
- Operations leaders facing recurring bottlenecks
- Maintenance & spare parts teams reducing downtime
Trusted by Global Operations Teams Across
Military and Defense | Retail and Supermarkets | Food & Beverages | Ports | Heavy Industry (Rail, Transportation & Logistics, Manufacturing, Cement and Building Materials, Automotive)
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Client Testimonials
What Our Customers Say
“AI makes it faster, cheaper and easier to break data silos. With ThroughPut’s robust supply chain model, we leverage real-time simulations to discover critical root causes and accelerate sustainable, holistic revenue growth decisions across all business units.”
Why do most supply chains still struggle despite having dashboards, reports, and ERP data?
Most supply chain systems today are designed to report performance, not to diagnose operational constraints.
Dashboards and ERP reports typically describe what happened — inventory levels, service metrics, delays, or production output. However, they rarely explain why performance is changing or which operational constraint is truly limiting throughput.
In complex supply chains, multiple variables interact across demand, inventory, production, and logistics. A stockout, for example, may appear to be a demand forecasting issue, but the real constraint could be capacity limits, replenishment delays, or inventory positioning across locations.
Without diagnostic analytics, teams often respond to the loudest signal rather than the most critical constraint, leading to reactive decisions, firefighting, and misallocated improvement efforts.
ThroughPut’s AI-powered operational diagnostics analyzes operational data across the entire supply chain to identify the true root causes of performance loss. Instead of simply reporting metrics, the platform helps teams determine where constraints exist, why they occur, and where intervention will create the greatest operational and financial impact.
Why do dashboards show metrics but fail to explain the root cause of supply chain problems?
Most dashboards are designed to monitor performance, not to diagnose the underlying causes of performance loss.
They typically aggregate operational data into KPIs such as inventory levels, service rates, forecast accuracy, or production output. While these metrics help teams observe what is happening across the supply chain, they rarely reveal which constraint is actually driving the result.
In complex operations, performance outcomes are shaped by interactions across demand variability, inventory positioning, production capacity, and logistics execution. A dashboard may show declining service levels or rising inventory, but it cannot determine whether the issue originates from capacity constraints, replenishment timing, planning policies, or demand volatility.
Without diagnostic analytics, teams often interpret symptoms rather than causes, leading to reactive decisions and repeated operational disruptions.
ThroughPut’s AI-powered operational diagnostics addresses this gap by analyzing supply chain data across functions to identify where constraints exist, why they occur, and which intervention will produce the greatest improvement in throughput, service levels, and working capital efficiency.
Why is it so difficult to identify the real bottleneck slowing down our operations?
In most operations, performance issues do not originate from a single visible problem. They emerge from interactions across demand variability, inventory policies, production capacity, and logistics execution. Because these elements influence each other, the true constraint is often hidden behind multiple symptoms.
Traditional tools such as ERP systems and reporting dashboards focus on tracking activity and performance metrics. While they can highlight delays, rising inventory, or declining service levels, they rarely determine which constraint is actually limiting throughput.
As a result, teams often respond to the most visible signal rather than the most critical one. A production delay may appear to be a scheduling issue, while the underlying constraint could be inventory positioning, supplier variability, or capacity imbalances elsewhere in the network. Without diagnostic analysis, improvement efforts frequently target symptoms instead of root causes.
ThroughPut’s AI-powered operational diagnostics analyzes operational data across demand, inventory, production, and logistics to identify where the true constraint exists and how it affects overall system performance. By pinpointing the bottleneck and quantifying its impact, teams can focus improvement efforts on the interventions that deliver the greatest gains in throughput, service levels, and working capital efficiency.
Why is it difficult to align crop production, storage capacity, and market demand in agriculture supply chains?
Agricultural supply chains are influenced by seasonal production cycles, demand volatility, and infrastructure constraints. Crop production decisions are often made months in advance, while market demand, weather conditions, and yield levels can change rapidly.
At the same time, storage capacity, processing facilities, and transportation networks may not be able to adjust quickly to these fluctuations. This often leads to surpluses in some regions and shortages in others, increasing waste and operational inefficiencies.
ThroughPut’s AI-powered analytics helps identify where supply, storage, and demand are misaligned, enabling teams to make better decisions that reduce waste and improve supply chain stability.