All Workflows
📊
Supply Planning

Demand Forecasting & MRP

Turn demand signals into purchase orders automatically — before shortages happen, not after.

40%
Fewer emergency POs
proactive procurement
25%
Inventory reduction
lean safety stock
98%
Forecast accuracy
AI-enhanced models
2 hrs
Daily planning cycle
vs 2-day manual runs
Overview

Why this workflow matters

For manufacturers, procurement and production planning are inseparable. When demand forecasting is disconnected from purchasing, the result is chronic shortages, excessive safety stock, emergency airfreight, and missed production schedules. Proconomy's Demand Forecasting and MRP workflow bridges the gap between what will be needed, what is already on order, and what needs to be procured — enabling procurement teams to act proactively rather than reactively. AI-driven forecast agents continuously analyse sales orders, production schedules, and historical consumption to generate purchase recommendations before stockouts occur.

Key Capabilities

  • Multi-level BOM explosion with scrap factors
  • AI demand forecast agent with 18-month rolling window
  • Suggested requisition engine with urgency ranking
  • Order bank visibility vs production schedule
  • Safety stock optimisation per part classification
  • Shortage early warning system
Process Flow

Step-by-step: how it works

Every step is designed to eliminate manual effort, reduce errors, and give your team real-time visibility at every stage of the process.

📡01

Demand Signal Capture

Sales orders, production schedules, and historical consumption data are aggregated into a unified demand picture.

Continuous / Daily

What happens

  • Pulls from confirmed sales orders, blanket order call-offs, and MPS
  • Historical consumption patterns weighted by seasonality and trends
  • New product introductions (NPI) handled separately with NPI forecast curves
  • Customer-specific demand signals tracked per product line

Roles involved

Production PlannerSales / Demand Planning
🤖AI Action

AI Demand Forecast Agent analyses rolling 18-month consumption history combined with current order book to generate statistically validated forecasts.

🔩02

BOM Explosion

The finished goods forecast is exploded through the Bill of Materials to derive component-level requirements at each sub-assembly level.

Automated

What happens

  • Multi-level BOM explosion down to raw material level
  • Scrap and yield factors applied per component and process
  • Alternate components resolved via Approved Manufacturer List (AML)
  • Phantom assemblies and co-products handled correctly

Roles involved

Production PlannerEngineering
🔎03

Inventory & On-Order Check

Current stock levels, goods in transit, and open purchase orders are netted against gross requirements to calculate true net demand.

Automated

What happens

  • Live inventory position per plant and storage location
  • Open PO quantities and expected delivery dates factored in
  • Safety stock rules applied per part classification (A/B/C)
  • Minimum order quantities and pack sizes respected

Roles involved

Production PlannerWarehouse Operator
💡04

Suggested Requisitions Generated

The system generates a prioritised list of suggested purchase requisitions — grouped by supplier, category, and urgency.

Automated

What happens

  • Suggested requisitions show: part, quantity, required date, suggested supplier
  • Urgency classification: Critical / High / Normal based on days-of-cover
  • Grouped by buyer responsibility and supplier for efficient processing
  • Blanket order call-offs separated from spot buys

Roles involved

Production Planner
🤖AI Action

AI ranks suggested requisitions by supply risk, flagging components with long lead times or single-source dependency.

05

Buyer Review & Release

Buyers review the suggested requisitions, adjust quantities if needed, and release them into the procurement workflow.

30–60 minutes daily

What happens

  • Buyers can accept, modify, or reject each suggested line
  • Override reasons captured for planning accuracy improvement
  • Bulk release for routine replenishment
  • Automatic escalation for critical parts approaching shortage

Roles involved

BuyerProcurement Manager
🤖AI Action

AI highlights lines where the suggested quantity deviates significantly from the buyer's historical release patterns.

📅06

Order Bank Management

All open and scheduled purchase orders are tracked against confirmed delivery dates — giving production planners full visibility of supply status.

Continuous

What happens

  • Order bank view shows all open POs vs required dates
  • Delivery date confirmations tracked from suppliers
  • Expedite alerts for POs at risk of missing production requirements
  • Supplier acknowledgement of POs tracked automatically

Roles involved

Production PlannerBuyer
🤖AI Action

AI Demand Forecast Agent monitors delivery confirmations and flags potential shortages 5–10 days before they impact production.

Team Roles

Who's involved in this workflow

Proconomy gives every stakeholder the right view, the right tools, and the right level of access — so no one is a bottleneck and nothing falls through the cracks.

🏭

Production Planner

  • Review and approve suggested requisitions
  • Maintain BOM accuracy
  • Manage production schedule changes
  • Escalate critical shortage situations
🛒

Buyer

  • Review and release suggested orders
  • Manage supplier call-offs
  • Expedite late deliveries
  • Negotiate blanket order terms
📊

Procurement Manager

  • Monitor order bank health
  • Set safety stock policies
  • Approve exceptions above threshold
  • Review forecast accuracy metrics
📦

Warehouse Operator

  • Confirm physical stock positions
  • Report damaged or rejected stock
  • Update cycle count results
Business Impact

What your organisation gains

These are not theoretical benefits — they are outcomes that procurement teams experience within the first quarter of deploying this workflow on Proconomy.

🚨
40% reduction
Emergency POs

Proactive demand signals mean procurement acts weeks ahead of shortages — not hours before a line stoppage.

📉
25% reduction
Inventory Levels

Precise net requirements calculation eliminates over-ordering while maintaining service levels — reducing working capital tied up in stock.

24× faster
Planning Speed

What took 2 days of manual MRP runs and spreadsheet work now completes in under 2 hours — automatically, every day.

🎯
+98%
Forecast Accuracy

AI models incorporating seasonality, trends, and real-time demand signals consistently outperform manual spreadsheet forecasts.

Applicable industries

🚗
Automotive

Multi-level BOM explosion across direct and indirect materials

💻
Consumer Electronics

Short lifecycle NPI demand planning and EOL transition management

⚙️
Industrial Equipment

Long lead time capital components and MRO management

🏥
Medical Devices

Regulated supply chain with validated forecast models

Semiconductor (OSAT)

Wafer-start driven material planning — substrate and bonding wire requirements exploded automatically

Explore more workflows

View all →
📊

See demand planning in action

See how Proconomy transforms this workflow for your procurement team — live, with your own scenarios.