Can AI demand forecasting handle highly volatile or seasonal demand?

Yes. AI excels at detecting complex seasonality patterns, trend shifts, and external influences (weather, holidays, promotions) that traditional methods miss. However, extreme volatility (e.g., pandemic demand shocks) requires continuous model retraining. We teach adaptive forecasting and scenario planning.

How do we get supplier data for AI risk monitoring if suppliers won't share it?

AI can use publicly available data (financial filings, news, trade data, shipping records) plus your own supplier performance history. We teach data collection strategies, external data sources, and privacy-preserving approaches when suppliers are reluctant to share proprietary information.

Will planners resist AI forecasts, preferring their manual judgment and overrides?

Change management is critical. We teach collaborative forecasting where AI provides baseline, and planners contribute market intelligence and override for exceptions. Most planners embrace AI once they see accuracy gains and time freed from spreadsheet work.

Can AI integrate with our ERP system (SAP, Oracle, local platform)?

Most AI planning platforms integrate with major ERP vendors via APIs or data exports. Integration complexity varies by system age and customisation. We cover technical requirements, middleware options, and IT coordination strategies during training.

Training Solutions

FLOW-PLAN

Cohort-basedSubsidy eligible

AI Supply Chain & Demand Planning

Supply chain teams can deploy AI to forecast demand with 85-95% accuracy, optimise inventory to reduce working capital by 20-30%, monitor supplier risks proactively, and optimise logistics routes — improving service levels to 95-98% while cutting costs by 15-25%.

Equip supply chain, procurement, and planning teams with AI tools for demand forecasting, inventory optimisation, supplier risk management, and logistics planning. Built for supply chain directors and operations planners in manufacturing and distribution managing complex multi-tier supplier networks across Southeast Asia.

Duration3-4 days

InvestmentUSD $20,000 - $35,000

Best forSupply chain directors, demand planners, procurement managers, and logistics coordinators facing forecast accuracy below 80%, excess inventory, or frequent stockouts

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THE CHALLENGE

Sound familiar?

“

Our demand forecast is only 65% accurate — we're either overproducing (excess inventory) or underproducing (lost sales).

“

We hold 90 days of safety stock because we can't predict which components will be delayed by suppliers.

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Supply disruptions hit us by surprise — we don't know a critical supplier is in trouble until shipments stop arriving.

“

Planning across 500+ SKUs and 200+ suppliers is chaotic; AI could optimise the entire network instead of manual spreadsheets.

“

Transportation costs are 15-20% higher than competitors because our routing and consolidation are suboptimal.

“

We're experiencing bullwhip effect — small demand changes cascade into massive supply chain swings and inventory imbalances.

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OUTCOMES

What you'll achieve

Problems you'll solve

Demand forecasting accuracy at 60-75%, causing inventory imbalances and lost sales
Safety stock levels excessive (80-120 days), tying up $5M-$20M in working capital
Supply disruptions detected reactively, causing production delays and expedited freight costs
Multi-echelon inventory planning managed manually, resulting in 25-40% excess inventory
Transportation costs 15-25% above optimal due to suboptimal routing and load consolidation
Bullwhip effect amplifying demand variability across supply chain tiers, causing instability

Value you'll gain

Forecast Accuracy: Improve demand forecast from 65-75% to 85-95% using AI pattern recognition and external signals
Inventory Reduction: Cut working capital by 20-30% through AI-optimised safety stock and reorder points
Cost Avoidance: Prevent $500K-$2M annual supply disruption costs through AI early warning and supplier monitoring
Logistics Optimisation: Reduce transportation costs by 15-25% using AI route planning and load optimisation
Service Level: Increase on-time delivery from 85-90% to 95-98% through AI supply-demand balancing
Planning Efficiency: Free planning teams from 40-60% of manual forecasting and spreadsheet work using AI automation

OUR PROCESS

How we deliver results

Step 1

Supply Chain Assessment

We analyse your demand planning processes, inventory levels, supplier performance, logistics networks, and ERP/planning systems to identify AI optimisation opportunities.

Step 2

Planning Curriculum Customisation

We tailor the training to your supply chain complexity (SKU count, supplier tiers, geographic spread), planning challenges (forecast accuracy, inventory, logistics), and ERP platform.

Step 3

Hands-On AI Supply Chain Training

Your planning, procurement, and logistics teams gain practical experience with AI demand forecasting, inventory optimisation, supplier risk monitoring, and route planning across 3-4 days of workshops.

Step 4

Use Case Development

Teams design 3-5 AI supply chain use cases (e.g., AI demand forecasting for top SKUs, supplier risk scoring, logistics optimisation) tailored to your network and strategic priorities.

Step 5

Implementation & Integration

We provide 90-day support including AI model training on your demand data, ERP integration, supplier data onboarding, and continuous improvement frameworks for sustained planning excellence.

What you'll receive

Customised AI supply chain training programme (3-4 days)
5 training modules with hands-on labs and planning case studies
3-5 AI supply chain use cases with implementation roadmaps and ROI analysis
ERP integration frameworks and data governance guidelines
Supply chain performance dashboards tracking forecast accuracy, inventory, and service levels
Supplier risk monitoring and logistics optimisation templates
90-day post-training support and implementation guidance

Best for

Supply chain directors, demand planners, procurement managers, and logistics coordinators facing forecast accuracy below 80%, excess inventory, or frequent stockouts

IS THIS RIGHT FOR YOU?

Finding the right fit

This is ideal for you if...

Supply chain teams with forecast accuracy below 80% causing inventory imbalances
Organizations holding excess inventory (80-120 days) tying up working capital
Procurement teams facing frequent supply disruptions without early warning
Logistics managers with transportation costs 15-25% above optimal
Supply chain directors preparing to deploy AI planning and optimisation tools

Consider another option if...

Small businesses with simple supply chains (<50 SKUs, <20 suppliers) where AI may not be cost-effective
Organizations without historical demand data or ERP systems
Teams expecting AI to eliminate all forecast error and supply risk (AI improves, not perfects, planning)

See yourself in the list above?

Let's Talk

CURRICULUM

What you'll learn

2 days total

Introduction to AI in supply chain management, machine learning for forecasting, optimisation algorithms, and integration with ERP/planning systems.

What you'll be able to do

Explain how AI transforms supply chain planning from reactive to predictive and prescriptive
Identify high-impact AI use cases across demand planning, inventory, procurement, and logistics
Assess data requirements for AI supply chain models (sales history, supplier data, external signals)
Navigate technical requirements for integrating AI with ERP and planning platforms (SAP, Oracle, local systems)
Evaluate AI supply chain vendor capabilities and ROI expectations