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

11 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

Heineken's Mercury Marketing Spend Optimiser

Heineken deploy Mercury, an AI-driven marketing budget allocation engine that uses Bayesian analysis and linear programming to determine the optimal distribution of above- and below-the-line spend across all brands. The system is complemented by Promo Advisor, which enables brand managers to simulate promotional campaign outcomes before committing budget.

Use Case
AI-Driven Marketing Budget Allocation and Promotion Simulation
Tools
Internal Tools
Input
Historical campaign performance data; brand spend allocations; market data; promotional calendars across all Heineken brands
Process
Mercury applies Bayesian analysis to decompose campaign effectiveness, then uses a linear programming model to recommend the most profitable allocation of marketing investment; Promo Advisor runs what-if simulations for promotional scenarios before execution
Output
Optimised marketing spend allocations per brand per market; promotional ROI forecasts; scenario simulation outputs for brand managers
Outcome
Incremental gross profit delivered across key markets
Food and Beverage Manufacturing
Marketing

Siemens Digital Industries' Intent Data Lead Qualification

Siemens Digital Industries deploy Bombora's Company Surge intent data to identify companies actively researching factory automation solutions early in their buying journey, before competitors gain visibility. The initiative increases sales acceptance of marketing-qualified leads from 1% to 90% and achieves a 94% win/loss rate across 400+ new pipeline opportunities.

Use Case
AI-Powered Buyer Intent Data for Sales Lead Prioritisation
Tools
Bombora
Input
Bombora Company Surge intent signals drawn from over 5,000 B2B websites, combined with Siemens' CRM data, account lists and firmographic profiles
Process
Bombora's AI algorithms analyse content consumption patterns across the web to identify companies showing elevated research activity on automation-relevant topics; intent scores are integrated into Siemens' CRM and campaign platforms to prioritise outreach and target programmatic advertising to in-market accounts
Output
Ranked and scored account lists of in-market buyers; intent-driven programmatic ad targeting; telequalification lead lists prioritised by purchase propensity
Outcome
MQL acceptance rises from 1% to 90%, with a 94% win rate, 400+ new pipeline opportunities, and telequalification costs cut by 99%
Industrial Equipment and Engineering Services
Sales

Diageo's Foresight System Consumer Trend Intelligence

Diageo use a proprietary AI-powered listening tool, the Foresight System, built in partnership with Share Creative and Kantar, that continuously scans over 160 million online conversations to identify emerging consumer trends across global beverage alcohol markets. Insights feed directly into brand strategy, campaign planning, and product innovation.

Use Case
AI-Powered Consumer Trend Monitoring and Insight Generation
Tools
Codec AI
Input
160 million+ online conversations from social media, forums, YouTube, and digital media in English, Mandarin, and Spanish
Process
Codec AI algorithms classify conversations by shared interests, values, and behaviours; NLP and topic modelling identify net-new micro-trends and track macro-trend evolution year-on-year; outputs are synthesised into dashboards and the annual Distilled trends report
Output
Actionable consumer trend intelligence by macro-trend, region, and brand; real-time foresight dashboard for campaign and product teams; annual Distilled report published globally
Outcome
Five macro-trends tracked continuously and used to inform brand activations and channel strategy; Distilled 2025 identified the zebra striping non-alcoholic consumption trend, directly influencing Diageo's portfolio and campaign decisions
Food and Beverage Manufacturing
Marketing

Siemens' Celonis Order-to-Cash Process Automation

Siemens deploy Celonis Process Mining across their global sales and Order-to-Cash operations, enabling 1,500 sales users to identify and eliminate process inefficiencies across over one million customers. The initiative delivers a 24% increase in automation rate and reduces manual touches by 10 million per year.

Use Case
AI-Powered Order-to-Cash Process Mining and Automation
Tools
Celonis
Input
End-to-end Order-to-Cash process event data across 200+ manufacturing plants, 100,000+ suppliers, and over 1 million customers
Process
Celonis Process Mining ingests ERP event logs, maps process variants, and flags rework and deviation patterns; automation then eliminates the identified inefficiencies.
Output
Global process transparency dashboards; automation and rework rate benchmarks by country, division, and customer; targeted automation recommendations for sales order workflows
Outcome
Automation rate increases by 24% globally, reducing rework by 11% leading to 10 million fewer manual touches per year across Order-to-Cash
Industrial Equipment and Engineering Services
Sales

Coca-Cola's Fizzion Brand Compliance Automation

Coca-Cola deploy Fizzion, a co-developed AI design intelligence system with Adobe, that encodes brand guidelines into a machine-readable StyleID. Creative teams and agency partners generate hundreds of localised campaign variations at up to ten times the speed of traditional production, without compromising brand integrity.

Use Case
Automated Brand-Compliant Content Localisation
Tools
Adobe Firefly
Input
Designer workflows within Adobe Creative Cloud; existing brand guidelines; campaign briefs across 200+ markets
Process
Fizzion observes designer decisions in real-time, encodes creative intent as a StyleID, and uses Adobe Firefly generative AI to apply brand rules automatically across formats, platforms, and markets
Output
Hundreds of on-brand, locally adapted campaign variants ready for deployment across 200+ markets
Outcome
Content production speed increases by up to 10x; brand consistency maintained at scale; creative teams freed to focus on storytelling rather than formatting
Food and Beverage Manufacturing
Marketing

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 83 Business Process Automation examples