Supply Chain Workflow - magicplatforms/ai-workflows GitHub Wiki

1. AI in Demand & Supply-Chain Planning

sequenceDiagram
    participant DP as Demand Planner
    participant AI_DF as AI Demand Forecast Engine
    participant SP as Supply Planner
    participant AI_IO as AI Inventory Optimizer
    participant SCM as Supply-Chain Manager

    DP->>AI_DF: Send historical & external data
    AI_DF-->>DP: Baseline demand forecast
    AI_DF-->>SP: Push demand signal
    SP->>AI_IO: Ask for safety-stock targets
    AI_IO-->>SP: Dynamic inventory parameters
    SP-->>SCM: Draft supply plan
    SCM-->>SP: Approve / request scenarios
    SP->>AI_DF: Run what-if simulations
    AI_DF-->>SP: Scenario outcomes
    SP-->>SCM: Final plan for execution
  1. Data hand-off: DP uploads history, POS, weather, promos to AI_DF.
  2. Baseline forecast: AI_DF returns a cleansed forecast for DP review.
  3. Signal to supply: AI_DF passes the demand profile to SP.
  4. Inventory sizing: SP asks AI_IO for safety-stock & reorder points.
  5. Parameter output: AI_IO supplies optimized buffer settings.
  6. Plan draft: SP compiles a supply plan and shares it with SCM.
  7. Manager review: SCM approves or requests alternative scenarios.
  8. Scenario modeling: SP triggers what-if runs in AI_DF.
  9. Scenario results: AI_DF ranks responses (cost, service, carbon).
  10. Plan lock-in: SP submits the preferred scenario; SCM signs off.

2. AI in Logistics & Transportation

sequenceDiagram
    participant TP as Transportation Planner
    participant AI_RO as AI Route Optimizer
    participant CT as Control Tower
    participant Driver as Fleet Driver
    participant Cust as Customer

    TP->>AI_RO: Upload daily orders & constraints
    AI_RO-->>TP: Optimized delivery routes
    AI_RO-->>CT: Real-time ETA feed
    CT-->>Driver: Dispatch route instructions
    Driver-->>CT: GPS location & status
    AI_RO-->>CT: Predict delay alerts
    CT-->>TP: Exception flag
    TP->>AI_RO: Request route re-plan
    AI_RO-->>Driver: Updated turn-by-turn route
    CT-->>Cust: Proactive arrival update
  1. Load-in: TP supplies shipments, time windows, truck specs to AI_RO.
  2. Route plan: AI_RO returns lowest-cost, on-time route set.
  3. Visibility push: AI_RO streams live ETA to CT dashboards.
  4. Dispatch: CT transmits route to each Driver’s device.
  5. Telematics loop: Drivers feed GPS/status back to CT.
  6. Predictive alerts: AI_RO spots delays, notifies CT.
  7. Exception flag: CT escalates to TP for decision.
  8. Re-plan: TP asks AI_RO to reroute or mode-shift.
  9. New route: AI_RO sends updated instructions to Driver.
  10. Customer care: CT auto-updates Cust with revised ETA.

3. AI in Sourcing & Procurement

sequenceDiagram
    participant Emp as Employee Requester
    participant Bot as AI Guided-Buying Assistant
    participant P2P as Procure-to-Pay System
    participant CM as Category Manager
    participant AI_SA as AI Spend/Risk Analytics
    participant Sup as Supplier

    Emp->>Bot: Need item / service
    Bot-->>Emp: Recommend preferred option
    Emp-->>Bot: Confirm selection
    Bot->>P2P: Auto-create requisition
    P2P-->>CM: Approval workflow
    CM->>AI_SA: Benchmark price & risk
    AI_SA-->>CM: Analytics dashboard
    CM-->>P2P: Approve / edit request
    P2P-->>Sup: Issue purchase order
    Sup-->>P2P: Order confirmation
    AI_SA-->>CM: Continuous spend insight
  1. Self-service start: Emp states need in plain language.
  2. Guided buying: Bot returns a compliant option with price & lead-time.
  3. User confirm: Emp accepts or tweaks selection.
  4. Requisition draft: Bot creates a PR in P2P with coding/approvals.
  5. Routing: P2P sends request to CM for sign-off.
  6. Decision support: CM queries AI_SA for benchmarks and risk flags.
  7. Insight delivery: AI_SA highlights maverick spend, price variance, ESG risk.
  8. Approve / modify: CM okays or redirects to another supplier.
  9. PO issue: P2P converts PR into a Purchase Order and sends to Sup.
  10. Confirmation & ongoing analytics: Sup confirms; AI_SA keeps CM updated on spend and supplier performance.

These bullet lists display cleanly in GitHub Wikis, avoiding pipe-character conflicts while keeping every step explicit.