# Fundamentals

## Overview

The Customer Order Manager is an AI-powered Digital Worker designed to free order processing teams from manual data entry so they can focus on the work that actually requires human expertise. It handles incoming customer orders, extracts critical information from various document formats, validates order details against IFS Cloud, and creates complete order records automatically.

By transforming unstructured, manual order intake into a fast, reliable, and error-resistant process, the Customer Order Manager gives teams their time back for building customer relationships, resolving complex issues, and managing exceptions that require genuine judgment.

## Key benefits

**Universal format handling:** Processes orders arriving in any format, PDFs, images, Excel sheets, emails, EDI, eliminating format fragmentation and standardizing intake across all channels.

**Accuracy and speed combined:** Intelligent validation eliminates part number mismatches, unit conversion errors, and duplicate orders, while delivering instant customer acknowledgment.

**Error prevention built-in:** The system cross-checks part numbers, quantities, prices, and delivery details against system records before creating any order. Issues are flagged before they become problems.

**Seamless scalability:** Handles high-volume and peak-season periods without bottlenecks, processing orders consistently regardless of volume.

**Human expertise elevated:** Routine order creation is handled automatically. Teams focus on exceptions, customer relationships, and decisions that require business judgment.

## The Challenge It Solves

Customer order management is often manual and fragmented. Teams must interpret incoming requests, validate details, and create orders across multiple systems. This leads to delays in order processing, errors in data entry, inconsistent customer communication, and limited visibility into order status.

In practice, this means teams are spending time on tasks like opening email attachments, re-entering data into ERP systems, manually validating part numbers, converting units, chasing clarifications, and sending acknowledgment emails. High order volumes and inconsistent incoming formats compound the problem, creating bottlenecks during peak periods and increasing the risk of errors that require costly correction.

## Before and after

### Before

Before the Customer Order Manager, order processing requires manual effort at every stage:

{% stepper %}
{% step %}
Process inbox and review purchase orders via email, EDI, or portal
{% endstep %}

{% step %}
Extract order details manually
{% endstep %}

{% step %}
Validate customer pricing and terms
{% endstep %}

{% step %}
Check availability constraints
{% endstep %}

{% step %}
Handle discrepancies via email back-and-forth
{% endstep %}

{% step %}
Send acknowledgments
{% endstep %}

{% step %}
Update ERP
{% endstep %}

{% step %}
Follow up on exceptions
{% endstep %}
{% endstepper %}

This manual process introduces data entry errors, inconsistent validation, slow processing cycles, and a poor customer experience during the wait for confirmation.

### After

With the Customer Order Manager, the same cycle is compressed into four automated steps:

{% stepper %}
{% step %}
Extract unstructured purchase orders from multiple channels
{% endstep %}

{% step %}
Validate pricing and terms, handle discrepancies
{% endstep %}

{% step %}
Check availability and handle exceptions
{% endstep %}

{% step %}
Update ERP and send automated acknowledgments
{% endstep %}
{% endstepper %}

Routine orders are processed without any human involvement. Exceptions are routed to the right person with full context already attached.

## How it works

The Customer Order Manager executes a comprehensive automated workflow that handles the complete order lifecycle from intake to confirmation.

**Extraction and initial setup:** The Digital Worker applies extraction rules to pull relevant information from incoming order documents. It retrieves default values such as site ID and coordinator information, identifies the customer by searching for and retrieving the customer ID from the system, and applies site mapping by checking if the customer is registered to a specific site ID using predefined dictionary mapping.

**Validation and cross-referencing:** Before creating the order, the system verifies the customer PO number doesn't already exist in IFS Cloud to prevent duplicates, retrieves customer-specific order defaults, and resolves any differences between the customer's part numbers and internal sales part numbers.

**Part number resolution:** The system cross-references customer part numbers with sales part numbers and retrieves conversion factors to translate between different quantity representations. This handles scenarios where customers count parts in bulk, such as sets of 12, while the system tracks individual units.

**Address matching:** The Digital Worker fetches all addresses stored for the customer and matches the delivery address from the purchase order with system records to ensure accurate fulfilllment.

**Order creation:** The system creates the complete customer order in IFS Cloud with all validated information and updates the part number registry if new parts have been added.

**Customer communication:** The Digital Worker sends acknowledgments and confirmations back to customers, ensuring timely communication throughout the process.


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