Demand Forecasting
Hierarchical ML forecasting from company level to individual SKU, with probabilistic demand ranges.
SLICE is a decision intelligence platform for manufacturing and industrial supply chains. It transforms demand signals, inventory data, and supply chain events into operational forecasting, optimisation, and risk intelligence — enabling supply chain teams to make faster, better-informed decisions across the full supply chain network.
Modern supply chains face compounding complexity: demand volatility, supplier risk, logistics disruption, and inventory pressure across globally distributed networks. SLICE provides the analytical foundation to navigate this complexity with data-driven confidence.
Hierarchical ML forecasting from company level to individual SKU, with probabilistic demand ranges.
Dynamic safety stock, service level management, and multi-echelon replenishment planning.
Supplier disruption monitoring, logistics delay prediction, and scenario planning analytics.
End-to-end visibility across the supply chain network for operational planning and risk management.
Typical clients: Manufacturers • Retailers • Consumer goods companies • Industrial distributors
SLICE combines demand intelligence, inventory science, and supply chain risk analytics in a single integrated platform.
Demand forecasting engine with hierarchical ML models, SKU-level prediction, probabilistic demand ranges, and intermittent demand handling for complex product portfolios.
Inventory optimisation module supporting safety stock calculation, service level management, multi-echelon planning, and dynamic replenishment policy design across the supply network.
Supply chain risk analytics — monitoring supplier performance, predicting logistics delays, tracking demand volatility, and enabling scenario planning for disruption events.
From Demand Signal → Forecast → Optimisation → Risk Intelligence
SLICE Forecast delivers accurate, actionable demand predictions at every level of the product and channel hierarchy.
Generate consistent forecasts from total company level down to individual SKU and location combinations. Reconciliation across the hierarchy ensures planning decisions are coherent at every level of the organisation.
Machine learning models trained at SKU level capture item-specific seasonality, promotions, and demand patterns. Cover thousands of SKUs simultaneously with automated model selection and performance tracking.
Produce demand distributions, not just point estimates. Quantify forecast uncertainty to support risk-informed inventory decisions, service level optimisation, and procurement buffer calculations.
Specialist models for slow-moving and intermittent demand items — including Croston's method and neural extensions — where conventional time series approaches break down. Accurate forecasting for the long tail of the product portfolio.
SLICE Optimise translates demand forecasts into inventory policies that balance service levels, working capital, and supply chain complexity.
Calculate optimal safety stock levels by SKU and location based on demand variability, lead time uncertainty, and service level targets. Reduce excess inventory while protecting fill rates across the network.
Set and track service level targets by product category, customer segment, or channel. Dynamically adjust inventory policies to achieve agreed service levels as demand patterns and supply conditions change.
Optimise inventory positioning across multi-tier distribution networks — from central warehouses through regional distribution centres to final destinations. Coordinate inventory policies across echelons to reduce total system stock while maintaining service performance.
Automate replenishment recommendations that respond to current demand signals, stock levels, and supplier lead times. Dynamic policies update as conditions change, replacing static reorder points with data-driven replenishment triggers.
Quantify the working capital implications of different inventory policies and service level targets. Support finance and supply chain teams in making informed trade-offs between inventory investment and customer service performance.
Identify slow-moving, excess, and at-risk inventory before it becomes a write-off. Flag items for review and support markdown and redistribution decisions with data-driven analytics.
SLICE Risk monitors the supply chain network for disruption signals and equips planning teams with the scenario intelligence to respond before events escalate.
Track supplier performance metrics, lead time variability, and delivery reliability across the supply base. Identify at-risk suppliers before disruptions materialise and prioritise mitigation actions by supply chain impact.
Predict inbound and outbound logistics delays using shipment tracking data, carrier performance history, and external signals. Proactively adjust replenishment plans when delivery risks are detected ahead of arrival.
Monitor demand volatility at SKU and category level. Detect unusual demand spikes, channel shifts, and structural demand changes that require supply chain response — and quantify the inventory and production implications.
Model the supply chain impact of disruption scenarios — supplier failures, logistics bottlenecks, demand shocks, or production constraints. Evaluate alternative sourcing and inventory strategies before committing resources.
This leads to:
SLICE becomes the decision intelligence layer for supply chain planning and operations.
See how SLICE transforms supply chain data into demand forecasts, inventory optimisation, and risk intelligence for manufacturing and industrial operations.
See SLICE in action and discuss your requirements with our team.