AI-driven process intelligence to unlock consumer goods and retail growth

Consumer goods and retail enterprises run on intertwined, complex processes. Demand planning, trade promotion, ecommerce, order to cash, store operations, and shared services often sit on separate platforms and in siloed teams. You only see the symptoms – margin pressure, service issues, and working capital lockups – but the real cause stays hidden.

 

AI-driven process intelligence changes that. It reconstructs how the business really operates by tracing digital footprints across ERP, supply chain, finance, and retail systems. Instead of static process maps, executives get a living model of the enterprise that delivers end-to-end process visibility and value streams from supplier to shelf and from order to cash, with every deviation and bottleneck quantified.

 

This end-to-end process visibility reveals where processes truly perform, where complexity adds value, and where it simply slows you down. It shows points of simplification, standardization, and enterprise process automation, so you can build an agile, resilient operation ready for whatever the market brings.

Customer and shopper experience

Connect service journeys across channels to see where customers drop off or complain. Identify process breaks that drive dissatisfaction and redesign journeys to lift loyalty and lifetime value.

 

Finance

Pinpoint the root causes of profit leaks from deductions and chargebacks. Stop duplicate invoice payments and use predictive models to optimize cash flows.

 

Supply chain

Reduce forecast errors and improve on-time, in-full (OTIF) delivery. Ensure on-shelf availability by identifying the real drivers of stockouts and delays.

 

Commercial

Measure true trade promotion effectiveness and ROI. Spot price compliance issues and analyze returns data to identify product or process flaws.

 

Store operations

Create smarter labor schedules using data. Identify the hidden causes of shrinkage and validate planogram compliance to maximize sales.

 

Manufacturing and logistics

Pinpoint the causes of equipment downtime and slow changeovers. Identify and eliminate sources of waste in your production lines.

 

Procurement

Map source to pay end to end. Expose off-contract and maverick spend, track supplier performance against agreed terms, and consolidate demand to improve cost, service, and risk profiles.

 

IT, data, and digital

Know how systems are actually used, where workarounds and manual steps persist, and which changes would unlock the most process value. Use these insights to prioritize the digital roadmap and de-risk large platform investments.

 

HR and shared services

Analyze how work flows through HR, finance, and other services. Identify rework, handoff issues, and policy bottlenecks, then redesign processes to improve employee experience while reducing cost to serve.

Start by exploring the potential of AI-driven process intelligence.

 

Step 1: Choose where you want impact

Select a small number of clear outcomes, such as reducing days sales outstanding, improving OTIF for key customers, or cutting promotion waste. Turn these into a simple project brief that spells out the targets, processes in scope, data you will use, and ownership, so business and technology teams are working toward the same goals.

 

Step 2: Prove, industrialize, and scale

Start with a focused proof of value on a single process, brand, or region that is big enough to matter but small enough to manage. Use it to validate data, deliver a tangible P&L impact, and codify a playbook. Then industrialize the solution and replicate it across markets, customers, and functions.

 

Step 3: Institutionalize technology plus expertise

Build a joint engine that combines process mining and AI platforms with deep domain expertise in category management, revenue growth, logistics, and financial planning. Embed this capability in a cross-functional CPG and retail digital transformation office that prioritizes use cases, tracks impact, and continually refreshes the roadmap.

 

For a global retail pharmacy leader, we deployed bespoke solutions powered by Celonis for enterprise process automation – duplicate checks, reduced debit balances, optimized payment terms and processes, and insights with AI. The results? Open goods receipt/invoice receipt (GR/IR) dropped to $2 million from $93 million, and the debit balance was reduced by over 65%, resulting in a $30 million P&L impact for FY2025 and a working capital opportunity of $12 million.

Solutions with super agents will move beyond reporting to orchestrating work across planning, merchandising, and operations. These agents will continuously scan process mining signals, detect risks and opportunities, run root-cause analysis, and simulate scenarios such as pricing moves, promotion changes, or inventory reallocations with quantified P&L and service impact. Enterprise process automation will cover routine corrections within defined guardrails, and only high-value trade-offs will reach the leaders. In effect, super agents will institutionalize best-in-class decision-making at scale and materially increase the return on CPG and retail digital transformation investments.

As a senior leader, you already see where growth, margin, and service are at risk. AI-driven process intelligence gives you a single, trusted view of how value actually flows across the enterprise so you can focus capital, talent, and time on the few changes that matter most.