6 real-life Business Process Automation examples in Industrial, Manufacturing and Engineering

6 real-life Business Process Automation examples in Industrial, Manufacturing and Engineering

Automation in industrial, manufacturing and engineering sectors are tightly coupled to physical production, plant uptime, quality control, and supplier coordination.

The manufacturing examples show that even administrative processes like invoice correction or SOP creation have outsized operational impact when they reduce bottlenecks, improve standardisation, and keep engineering, finance, and shop-floor teams aligned around throughput, safety, and cost.

Business function

Industry

Nestlé and Demand Forecasting

Nestlé S.A utilizes AI-driven analytics and machine learning to refine demand forecasting and inventory management, allowing for precise stock planning and real-time logistics tracking to minimize waste and ensure product availability.

Use Case
Improving Demand Forecasting Accuracy and Inventory Optimisation
Tools
Coupa
Input
Historical sales data, seasonal trends, consumer behaviour data, and container arrival predictions
Process
AI analyzes multi-variable inputs to generate statistical demand forecasts while predicting container arrival times at destination ports to mitigate external disruptions
Output
More accurate stock planning, fewer stockouts, and reduced overproduction
Outcome
Streamlined supply chain workflows and optimized inventory levels
Food and Beverage Manufacturing
Supply Chain

Mondelez's Sustainability Monitoring System

Mondelez International utilises an AI-powered monitoring system within its Harmony Academy Digital Platform to drive sustainable wheat farming. By analysing real-time environmental data from supplier farms, the automation provides actionable insights that optimise agricultural inputs and ensure high-level ESG compliance across the global supply chain.

Use Case
Sustainable Agriculture Monitoring
Tools
Harmony Digital Platform
Input
Farm-level data including greenhouse gas emissions, nitrogen use, pesticide application, soil health metrics, and biodiversity indicators
Process
AI tools analyze farm-level environmental data in real time to generate data-driven recommendations for input optimization and continuous ESG KPI monitoring
Output
Real-time visibility into sustainability performance and improved traceability of raw material origins
Outcome
Advances the commitment to source 100% of wheat through the Harmony programme and achieves measurable improvements in regenerative agriculture practices
Food and Beverage Manufacturing
Sustainability

Nestle's Faster Ideation Cycles

Nestlé S.A. leverages AI-driven concept engines and machine learning to revolutionise the R&D cycle, enabling the rapid translation of social media trends and consumer data into viable product proposals while minimising the need for costly physical prototyping.

Use Case
Accelerating New Product Development
Tools
Internal Tools
Input
Social media data, consumer preference datasets, historical R&D data, and market trend signals
Process
ML models analyze historical data and social insights to generate product concepts while AI clusters trend data into actionable proposals and facilitates virtual prototyping
Output
Faster ideation cycles, reduced physical trials, and unbiased ingredient exploration
Outcome
64% reduction in development time (from 33 months down to 12 months)
Food and Beverage Manufacturing
Product

Komatsu's Automated Invoice Processing

Komatsu Australia, the local arm of the global construction and mining equipment manufacturer, used Microsoft Power Automate and AI Builder to build a Robotic Process Automation solution for invoice fixing. Going from licence purchase to a production RPA solution in just four weeks, the automation saved 300 hours per year on invoicing for a single supplier and is being expanded to cover all suppliers.

Use Case
Automated invoice processing and correction using RPA to eliminate manual data entry and fix supplier invoices across legacy systems
Tools
Microsoft Power Automate
Input
Supplier invoices requiring manual correction due to errors or format mismatches in legacy systems
Process
Power Automate Desktop flows combined with AI Builder automatically detect, process, and correct invoice data across Windows and web applications without human intervention
Output
Corrected, validated invoices ready for approval and payment processing, with errors resolved automatically
Outcome
Saved 300 hours per year for a single supplier and achieved full production deployment within 4 weeks of licence purchase.
Discrete Manufacturing
Finance

Siemens AI-Powered Supplier Discovery

Siemens deployed Scoutbee's AI-powered procurement platform to automate and accelerate supplier discovery across 18 business units, reducing procurement workload by up to 90% and enabling faster, data-driven sourcing decisions at scale.

Use Case
Automated Supplier Discovery and Scouting
Tools
Internal Tools & Scoutbee
Input
Procurement briefs, sourcing requirements, supplier capability criteria, and existing supplier data from 18 Siemens business units
Process
Scoutbee's AI platform analyses procurement requirements and searches a global supplier database, automatically enriching supplier profiles
Output
Qualified supplier shortlists with enriched profiles with centralised project documentation and RFI responses
Outcome
Procurement workload reduced by up to 90% with improved supply chain resilience against tariff and disruption risk
Discrete Manufacturing
Procurement

SOP Documentation Automation at Eaton Using Microsoft 365 Copilot

Eaton, a global power management company, used Microsoft 365 Copilot to automate the creation of standard operating procedures (SOPs) during a major accounting centralisation programme. The finance team needed to document 9,000 SOPs within a strict timeline; Copilot reduced SOP creation time by 83%, from over an hour each to just 10 minutes.

Use Case
Finance process documentation and SOP creation automation
Tools
Microsoft 365 Copilot
Input
Existing process knowledge held by finance team members, prior SOP drafts, and internal organisational data accessible via Microsoft 365
Process
Finance staff use Microsoft 365 Copilot to generate initial SOP drafts by prompting the tool with process descriptions. Copilot draws on internal documents and Microsoft Graph data to produce structured, formatted SOPs ready for review. Copilot for Service is additionally used to surface CRM insights and speed up customer support response times.
Output
Over 1,000 completed SOP documents generated with AI assistance; faster customer service response times via CRM-integrated Copilot for Service
Outcome
SOP creation time dropped from over 60 minutes to 10 minutes per document (83% reduction); more than 650 hours saved across the SOP programme; customer service response times projected to fall by 20%; finance teams freed to focus on strategic work rather than manual documentation
Discrete Manufacturing
Finance
Operations
See all 60 Business Process Automation examples