How Can Automation Help Your Order to Cash (O2C) Process? [2023]

Automating the order to cash (O2C) process can help companies dramatically accelerate order fulfillment, reduce errors, optimize working capital, and improve customer satisfaction. By deploying robotic process automation (RPA), artificial intelligence (AI), machine learning (ML) and other technologies, businesses can achieve 40-80% improvements across their O2C operations.

The O2C process spans everything from order placement to payment collection and involves both financial and logistical components. Let‘s examine how intelligent automation can drive efficiency gains in each area.

The Opportunity in Order to Cash Automation

O2C automation presents a $50 billion opportunity according to McKinsey[1]. The reasons are compelling:

  • 60% lower operating costs by reducing repetitive manual work
  • 50% faster order fulfillment through supply chain automation
  • 80% fewer errors in order and invoice processing
  • 20% improvement in working capital with accelerated collections

However, despite these potential benefits, current adoption remains low. Only 17% of firms have automated more than 50% of their O2C processes according to an S&P Global study[2].

This means tremendous potential still exists to leverage intelligent automation to transform O2C.

Automating the Financial Aspects of O2C

The financial components of O2C consist of customer credit checks, invoicing, payment collection and revenue recognition. Let‘s look at how automation can optimize each element.

Instant and Accurate Credit Verification

Inefficient credit checks can lead to incorrect risk decisions and cash flow disruptions. Automating the credit process can significantly mitigate these issues.

AI-based credit risk models incorporate hundreds of data variables to deliver near-instant credit decisions with 90% accuracy[3]. This ensures customers do not wait days to receive credit terms.

Augmenting traditional credit data with alternative sources like social media, web traffic, and behavioral analytics using big data pipelines and web scraping further improves analysis.

Continuously updated ML algorithms also allow credit policies to adapt dynamically based on the latest customer trends.

Error-Free Invoice Generation

Manual invoice processing takes over 15 minutes per document and is prone to 40-80% errors[4].

Automated solutions can extract order data from ERPs, OMS, ecommerce platforms and instantly generate accurate invoices. RPA bots can further validate invoice accuracy to eliminate manual mistakes.

This reduces invoice processing costs by up to 80% while improving accuracy.

Proactive Payment Collection

Slow or missed payments severely affect cash flow. According to an AFP study, 74% of firms struggle with collections using manual methods[5].

Automation enables persistent and personalized payment follow-up:

  • RPA bots trigger automated payment reminders via SMS, email, and voice calls to match customer preferences
  • Predictive analytics identify late payments before they occur allowing for proactive outreach
  • Workflow engines consistently follow up until payment is received

Leading firms using these techniques have reduced DSO by over 15% while recovering 2-3% more receivables.

Flawless Revenue Recognition

Disorganized financial records lead to revenue leaks and compliance issues. Automation provides a solution.

Multi-channel sales data can be funneled into financial systems using cloud integrations and RPA. Clean data ensures all revenue is accounted for.

AI algorithms can further classify transactions into appropriate categories for precise recognition. This eliminates human error prone manual coding.

With automation, firms gain data integrity, reduce close times by 50%, and minimize revenue leakage.

Optimizing the Logistics Components of O2C

Logistical O2C elements include order promising, warehouse management, and shipping. Connecting these areas is vital for efficient fulfillment.

Order Orchestration Hub

Order management systems (OMS) create an information hub to connect logistics:

  • Centralized order data from all channels provides real-time visibility
  • Inventory and shipment orchestration optimizes fulfillment execution
  • Embedded analytics offer insights to optimize planning

With order orchestration, firms gain complete visibility into end-to-end order lifecycles. This results in up to 30% faster fulfillment with improved customer satisfaction.

Intelligent Warehouse Management

Automating warehousing helps overcome inventory inaccuracies, capacity constraints, and labor shortages – issues that plague 94% of firms[6].

  • Autonomous mobile robots automate picks and putaways to improve throughput by 2-3x
  • Automated storage and retrieval (ASRS) systems double storage density
  • AI-powered demand planning balances inventory across network nodes

These warehouse automation technologies offer 20-40% productivity gains, 50% lower shipping errors, and significant capacity expansion.

Building an Integrated O2C Automation Strategy

While point automation delivers some upside, studies show integrated end-to-end automation yields 2-3x higher ROI[7].

Experts recommend assembling a unified O2C automation fabric spanning credit, invoicing, payments, order management, logistics and analytics.

Key guiding principles include:

  • Take an agile approach – prioritize pain points and scale up
  • Combine RPA, AI, and workflow tools – no one technology solves everything
  • Integrate across financial and operational systems – break down enterprise silos
  • Measure progress with O2C KPIs – monitor leads, cash flow, working capital
  • Nurture employee adoption via training and engagement

With this framework, leading companies have automated 50-80% of their O2C, achieving hard dollar ROI north of $200 million annually.

The numbers speak for themselves – integrated O2C automation is a must-have for boosting efficiency, cash flow, and the overall customer experience. The time to act is now.


  1. Order to Cash Automation – McKinsey & Company
  2. Overcoming Barriers to Digital Finance Transformation – S&P Global
  3. Role of AI in Credit Risk Modeling – Global Association of Risk Professionals
  4. Order to Cash Automation Use Cases – Blue Prism
  5. 2022 AFP Payment Survey Report – Association for Financial Professionals
  6. Warehousing Automation – Gartner
  7. The Total Economic Impact of Automation – Forrester

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