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KI, die Ihre Lieferkette in Echtzeit überwacht, Störungen vorhersagt und Maßnahmen empfiehlt – damit Sie reagieren können, bevor Kunden die Auswirkungen spüren.

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The problem

Supply disruptions discovered after the fact

  • Disruptions discovered after the fact

    Stock-outs, supplier delays and logistics failures surface when customers complain — not when they can still be prevented.

  • Demand forecasting built on intuition

    Planning relies on historical averages and manual adjustments. Demand signals from external events are ignored until it's too late.

  • No single view across the chain

    Supplier data, inventory data and logistics data live in different systems. A connected picture requires manual consolidation every time.

  • Recommendations nobody acts on

    Insights arrive too late or without clear owners. Planners revert to spreadsheets because nothing connects to execution.

So funktioniert es

Sense disruption early—replan with scenarios, not panic

Schritt 1

Connect the network

Suppliers, lanes, inventory, and orders are modeled as a living graph with lead times and alternates.

Schritt 2

Run scenarios

Demand shocks, port delays, and commodity moves simulate service, cost, and carbon impacts.

Schritt 3

Orchestrate response

Recommended buys, expedites, and customer communications are drafted for planners to approve.

Planning horizons and safety stock rules stay under human control.

Erkennen Sie Störungen, bevor sie Sie sehen.

Leistungsumfang

What you get when you run this with Thinkia

A governed layer across data, workflows, and handoffs—so teams ship safely and scale with metrics.

Real-time supply chain monitoring

Unified view across suppliers, inventory and logistics in a single intelligence layer.

Disruption prediction

Detects early warning signals from external data (weather, geopolitics, supplier news) and internal patterns.

Demand forecasting

AI-enhanced forecasts that incorporate external signals beyond historical sales data.

Supplier risk scoring

Continuous assessment of supplier reliability, concentration risk and financial health indicators.

Automated reorder recommendations

Triggers procurement actions based on stock levels, lead times and forecast demand.

Scenario simulation

Models the impact of disruption scenarios on cost, availability and delivery commitments.

Unterstützt von Thinkia Synapse

Ergebnisse

What changes when this runs in production

Results vary by supply chain complexity, supplier data availability and integration maturity.

–65%

Earlier detection and response to supply chain events

+25%

Improvement in demand forecast accuracy vs. statistical baseline

–45%

Reduction in out-of-stock events with AI-driven reorder triggers

So arbeiten wir

From spreadsheet planning to sensing and scenarios your planners trust

Network map

Week 1–2

Nodes, lead times, and constraints are documented; critical paths and single sources are flagged.

Demand & risk signals

Week 3–5

Forecasts, POS, weather, and supplier events are fused with clear confidence bands.

S&OP pilot

Week 6–9

One product family runs integrated planning; stockouts and excess are tracked vs baseline.

Network scale

Week 10+

More SKUs, regions, and tiers; scenario playbooks feed exec and continuity planning.

ERP and planning tool fragmentation sets integration cost; waves follow planning horizons.

Loslegen

Ready to scope this for your context?

We start with a focused session—no commitment—to map constraints and a sensible path.

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