Project Overview

Title: ERP System Upgrade

Description: The company's current ERP system, which is critical for managing and integrating various business processes, is running on an outdated version and technology stack. This project aims to upgrade the existing ERP system to the latest version of SAP S/4HANA, a modern and intelligent ERP solution designed for the digital age.

The project will involve a comprehensive assessment of the existing ERP system, data migration, system configuration, integration with other systems, user training, and a well-planned deployment strategy to minimize disruption to ongoing business operations.

Successful completion of this project will position the company for long-term competitiveness by leveraging the latest ERP technology, optimizing business processes, and enabling data-driven decision-making capabilities.

Budget: $2,285,000.00

Current State: The current ERP system is outdated and does not support recent business process changes.

Target Architecture: SAP S/4HANA

Key Policies: The upgrade must ensure business continuity and data integrity.

Restrictions: The system downtime during the upgrade must be minimized.

Company Information

Company Name: Vertex Dynamics

Website: www.vertexdynamicsinc.com

Vertex Dynamics is an industry leader in the distribution of high-quality electronics and consumer goods, leveraging an advanced ERP system to streamline its sales and warehouse operations. Our integrated approach ensures that every aspect of the business, from order processing to inventory control, operates at peak efficiency. With a strong online presence and a commitment to customer satisfaction, Vertex Dynamics offers a reliable supply chain solution and exceptional service, solidifying our reputation as a trusted partner in the global market.

Project Stakeholders

Project Sponsor

Bob Johnson, Director of Sales bob.johnson@vertexdynamicsinc.com

PMO Director

Tim Snyder, Director of Project Management tim.snyder@vertexdynamicsinc.com

Goals

Goal: Process Optimization

Leverage the enhanced features and capabilities of SAP S/4HANA to streamline and optimize business processes across various functional areas, such as finance, supply chain, procurement, manufacturing, and sales.

Goal: User Experience

Enhance the user experience by adopting SAP S/4HANA's modern and intuitive user interface, which supports mobile devices and provides personalized dashboards and visualization tools.

Goal: Technology Modernization

Migrate the ERP system to SAP S/4HANA, which is built on the advanced in-memory database SAP HANA, enabling real-time data processing, advanced analytics, and faster transaction processing.

Goal: Digital Transformation

Embrace digital transformation by leveraging SAP S/4HANA's integration with cutting-edge technologies like the Internet of Things (IoT), machine learning, and predictive analytics, enabling data-driven decision-making and intelligent automation.

Goal: Compliance and Scalability

Ensure compliance with evolving regulatory requirements and industry standards while providing a scalable and future-proof platform to support the company's growth and changing business needs.

Processes

Process: Customer Order Process

The workflow diagram depicts the process of creating a customer order. It begins with a sales representative opening the order creation module. If the customer is not in the system, a new customer record is created. Otherwise, the existing customer is selected. Products are added to the order, which the system then checks for inventory availability. If any items are out of stock, the sales rep is notified, and the products are either backordered or the customer's order is revised and out-of-stock items are ordered. Any applicable discounts are applied before the order is reviewed with the customer. If the customer approves, the order is processed; if not, it is cancelled. The workflow ends after processing or cancelling the order. Areas for optimization may include streamlining inventory checks and automating discount application to reduce manual steps for the sales representative.

Roles

• Sales Representative
• System

Inputs

• Customer Information
• Products to be ordered
• Inventory Availability

Outputs

• Customer Record
• Order Confirmation
• Notification of Out-of-Stock Items
• Processed Order or Cancellation

Process: Inventory Management

The workflow diagram describes the inventory management process in a warehouse setting, handled by a Warehouse Worker and facilitated by an ERP system. The process begins with the receipt of stock, followed by the creation of a stock receipt in the ERP system. Stock is then moved, requiring a transfer ticket to be created in the ERP system. Physical inventory counting is performed periodically, which leads to an inventory review. The ERP system plays a critical role in updating inventory levels and locations, and in comparing physical counts with records to generate discrepancy reports. If discrepancies are found, they are reviewed and investigated, potentially leading to a recount of items with discrepancies. Based on the investigation's outcome, the ERP system updates are finalized, and a management report is generated. This workflow highlights the integration between manual processes and automated systems, and suggests an area for optimization in automating the initial receiving and stock movement documentation to reduce manual entry errors and improve efficiency.

Roles

• Warehouse Worker
• ERP System

Inputs

• Stock
• Shipment
• Stock Transfer Ticket
• Physical Inventory Counts

Outputs

• Stock Receipt
• Updated Inventory Levels
• Updated Inventory Locations
• Discrepancy Report
• Management Report

Process: Procurement and Purchasing

The workflow diagram represents the process of managing purchase requisitions (PR) and purchase orders (PO) within an ERP system, involving decision-making by a Buyer role. Initially, the ERP system triggers a purchase request when a product reaches its re-order point. For standard vendors, the ERP automatically generates a PO. The Buyer reviews the PR, and based on the authorization decision, the PO can either proceed as is, be modified for manual orders, or be canceled. If the PR is authorized for a standard order and no modifications are needed, the ERP sends the PO directly to vendors. If the PR requires a manual order, the Buyer creates a PO based on PR data. The workflow ends once the PO is sent to vendors or canceled.

Roles

• ERP System
• Buyer

Inputs

• Requisitions
• Re-order point notification
• Purchase request
• Purchase Order data
• Buyer review and authorization decisions

Outputs

• Purchase Order to vendors
• Decision on Purchase Order execution

Process: Logistics

The workflow diagram illustrates the process of picking and shipping an order in a distribution center. The process starts with the ERP system generating a pick list for the order, which prompts a Warehouse Worker to pick the items, deliver them to the shipping table, and mark the pick as complete. The system then notifies the Shipping Coordinator of the picked order. Subsequently, a Packer packs the order, stages it for shipper pickup, and marks it as packed. The Shipping Coordinator is notified to ship the order, after which the order is marked as shipped and the stock is removed from inventory. The process concludes when the order status is updated to 'done'. Key decision points include the transitions between picking, packing, and shipping, which are crucial for tracking order progress and inventory management. The workflow lacks explicit error handling and contingency plans for stock shortages or discrepancies, which could be areas for optimization.

Roles

• ERP System
• Warehouse Worker
• Packer
• Shipping Coordinator

Inputs

• Order details
• Inventory data

Outputs

• Pick list
• Notification of picked order
• Packed order
• Notification to ship
• Order shipped status
• Updated inventory

Finance Process Optimization

This functional area focuses on leveraging the enhanced features of SAP S/4HANA to streamline and optimize finance-related processes within the ERP system. By utilizing the advanced capabilities of SAP S/4HANA, such as real-time data processing and advanced analytics, this area aims to improve financial data accuracy, reporting efficiency, and decision-making. This aligns with the project goal of Process Optimization (PRCS) and Technology Modernization (TECH).

Feature: Real-time Financial Reporting

This feature will enable real-time financial reporting by leveraging the advanced capabilities of SAP S/4HANA. It is designed to provide up-to-date and accurate financial data for informed decision-making and improved financial transparency. This feature aligns with the Process Optimization (PRCS) and Technology Modernization (TECH) goals.

Feature: Automated Invoice Processing

This feature is designed to automate the invoice processing workflow within the ERP system using SAP S/4HANA. By automating this process, it ensures that invoices are processed efficiently, reducing manual errors and improving overall process efficiency. This feature supports the Process Optimization (PRCS) goal.

Requirement: Automated Invoice Data Extraction (Functional)

Reference: ERPUPGD-176

The system must automatically extract relevant data from incoming invoices to populate the ERP system fields. This functionality is crucial for reducing manual data entry errors and improving processing efficiency within the Automated Invoice Processing feature of the Finance Process Optimization Functional Area.

Acceptance Criteria

• System accurately extracts invoice data fields,
• Extracted data is correctly mapped to corresponding ERP fields

Gherkin Scenarios

Scenario: Automated data extraction from invoices
Given an incoming invoice is received
When the system processes the invoice for data extraction
Then the relevant data fields are accurately extracted
And the extracted data is correctly mapped to ERP fields

Requirement: Automated Invoice Approval Workflow (Functional)

Reference: ERPUPGD-177

The system must automate the approval workflow for processed invoices, routing them to the appropriate stakeholders for review and approval. This feature enhances the efficiency of invoice processing and ensures timely approvals within the Automated Invoice Processing feature of the Finance Process Optimization Functional Area.

Acceptance Criteria

• Invoices are automatically routed to designated approvers based on predefined rules,
• Approvers can review and approve invoices within the system

Gherkin Scenarios

Scenario: Automated invoice approval workflow
Given an invoice is processed and ready for approval
When the system routes the invoice to the designated approver
Then the approver can review and approve the invoice within the system

Requirement: Performance Optimization (Non-Functional)

Reference: ERPUPGD-178

The system must process automated invoice data within 2 seconds to ensure efficient and timely processing, enhancing overall system performance and user satisfaction. This requirement is crucial for meeting the goal of Process Optimization and Technology Modernization.

Acceptance Criteria

• Automated invoice processing completes within 2 seconds

Gherkin Scenarios

Scenario: Automated invoice processing time
Given the system is processing an automated invoice
When the processing time is measured
Then the processing time should be less than or equal to 2 seconds

Requirement: Security Compliance (Non-Functional)

Reference: ERPUPGD-179

The system must comply with industry-standard security protocols and regulations to ensure the confidentiality and integrity of financial data during the automated invoice processing. This requirement is essential for maintaining data security and meeting regulatory requirements.

Acceptance Criteria

• System complies with ISO 27001 standards for data security

Gherkin Scenarios

Scenario: Security compliance during automated invoice processing
Given the system is processing an automated invoice
When the security measures are audited
Then the system should meet ISO 27001 standards

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-180

The system must be able to handle a minimum of 1000 automated invoice transactions per hour to accommodate future business growth and increased transaction volumes. This requirement ensures that the system can scale effectively with the organization's needs.

Acceptance Criteria

• System processes 1000 automated invoice transactions per hour without performance degradation

Gherkin Scenarios

Scenario: System scalability with automated invoice transactions
Given the system is processing automated invoices
When the system is handling 1000 transactions per hour
Then the system should maintain performance without degradation

Requirement: Automated Invoice Data Extraction (Business)

Reference: ERPUPGD-181

The system must automatically extract invoice data from incoming invoices to eliminate manual data entry. This requirement is crucial for improving efficiency and reducing errors in the invoice processing workflow.

Acceptance Criteria

• System extracts invoice data accurately,
• Data extraction process is completed within seconds

Gherkin Scenarios

Scenario: Automated Invoice Data Extraction
Given an incoming invoice is received
When the system automatically extracts data from the invoice
Then the extracted data is accurate
And the extraction process is completed within seconds

Requirement: Automated Invoice Approval Workflow (Business)

Reference: ERPUPGD-182

The system should route extracted invoices for approval based on predefined rules and hierarchies. This requirement ensures that invoices are approved promptly and in compliance with company policies.

Acceptance Criteria

• Invoices are routed to the correct approvers,
• Approvers receive notifications for pending invoices

Gherkin Scenarios

Scenario: Automated Invoice Approval Workflow
Given an invoice is extracted and ready for approval
When the system routes the invoice to the correct approver
Then the approver receives a notification for the pending invoice

Requirement: Automated Invoice Data Extraction (Technical)

Reference: ERPUPGD-183

Implement a feature to automatically extract invoice data from incoming invoices within the ERP system. This functionality will utilize OCR technology to extract relevant data fields such as invoice number, date, amount, and vendor information. This will streamline the data entry process and reduce manual errors in invoice processing.

Acceptance Criteria

• System extracts invoice number, date, amount, and vendor information accurately from scanned invoices,
• Extracted data is populated into the corresponding fields in the ERP system

Gherkin Scenarios

Scenario: Automated Invoice Data Extraction
Given an incoming invoice is received
When the system processes the invoice using OCR technology
Then the system accurately extracts invoice number, date, amount, and vendor information
And populates the corresponding fields in the ERP system

Requirement: Automated Invoice Approval Workflow (Technical)

Reference: ERPUPGD-184

Develop an automated workflow for invoice approvals within the ERP system. This feature will route invoices to the appropriate approvers based on predefined rules and thresholds. It will provide real-time notifications to approvers and ensure timely processing of invoices.

Acceptance Criteria

• Invoices are automatically routed to the designated approvers based on predefined rules,
• Approvers receive real-time notifications for pending invoices

Gherkin Scenarios

Scenario: Automated Invoice Approval Workflow
Given an invoice is ready for approval
When the system routes the invoice to the designated approver
Then the designated approver receives a real-time notification
And can approve or reject the invoice within the system

Requirement: Compliance with GDPR Regulations (Legal and Regulatory)

Reference: ERPUPGD-185

Ensure that the Automated Invoice Processing feature complies with all General Data Protection Regulation (GDPR) requirements related to handling and processing personal data. This is crucial to protect the privacy and rights of individuals whose data is included in the invoices.

Acceptance Criteria

• System encrypts all personal data in invoices,
• Users can only access personal data on a need-to-know basis

Gherkin Scenarios

Scenario: Ensure GDPR Compliance for Invoice Processing
Given that personal data is included in an invoice
When the system processes the invoice
Then all personal data is encrypted to GDPR standards
And access to personal data is restricted to authorized users only

Requirement: Audit Trail for Invoice Processing (Legal and Regulatory)

Reference: ERPUPGD-186

Implement an audit trail functionality within the Automated Invoice Processing feature to ensure that all actions related to invoice processing are logged and traceable. This is essential for compliance with financial regulations and internal audit requirements.

Acceptance Criteria

• System logs all actions taken during invoice processing,
• Audit trail is tamper-proof and cannot be altered

Gherkin Scenarios

Scenario: Audit Trail for Invoice Processing
Given that an invoice is being processed
When actions are taken within the system
Then all actions are logged in the audit trail
And the audit trail is immutable and secure

Requirement: Real-time Invoice Processing (Strategic)

Reference: ERPUPGD-187

Enable real-time processing of invoices within the ERP system to ensure timely and accurate financial data updates. This requirement aligns with the goal of leveraging SAP S/4HANA's real-time capabilities to enhance process efficiency.

Acceptance Criteria

• Invoices are processed instantly upon receipt,
• Financial data is updated in real-time after invoice processing

Gherkin Scenarios

Scenario: Real-time Invoice Processing
Given an invoice is received in the system
When the system processes the invoice in real-time
Then the financial data is immediately updated
And the invoice status is marked as processed

Requirement: Automated Approval Workflow (Strategic)

Reference: ERPUPGD-188

Implement an automated approval workflow for invoices to streamline the approval process and reduce manual intervention. This requirement supports the goal of optimizing finance processes by automating manual tasks.

Acceptance Criteria

• Invoices are automatically routed to the appropriate approver based on predefined rules,
• Approvers can review and approve invoices within the system

Gherkin Scenarios

Scenario: Automated Approval Workflow
Given an invoice is ready for approval
When the system automatically routes the invoice to the designated approver
Then the approver can review and approve the invoice within the system
And the approval status is updated in real-time

Requirement: Automated Invoice Data Extraction (Other)

Reference: ERPUPGD-189

The system must automatically extract relevant data from incoming invoices to populate the ERP system fields. This requirement is crucial for streamlining the invoice processing workflow and reducing manual data entry errors.

Acceptance Criteria

• System extracts invoice number, date, amount, and vendor details accurately,
• Extracted data is populated in the respective fields within the ERP system

Gherkin Scenarios

Scenario: Automated Invoice Data Extraction
Given an incoming invoice is received
When the system processes the invoice
Then the system accurately extracts and populates invoice data in the ERP system

Requirement: Automated Invoice Approval Workflow (Other)

Reference: ERPUPGD-190

The system should route invoices through an automated approval workflow based on predefined rules and thresholds. This requirement aims to expedite the approval process and ensure timely payment processing.

Acceptance Criteria

• Invoices are automatically routed to the appropriate approvers based on predefined rules,
• Approvers receive notifications for pending invoices requiring approval

Gherkin Scenarios

Scenario: Automated Invoice Approval Workflow
Given an invoice is ready for approval
When the system applies predefined approval rules
Then the invoice is routed to the appropriate approvers and notifications are sent

Feature: Predictive Financial Analytics

This feature will leverage advanced analytics capabilities of SAP S/4HANA to provide predictive financial analytics. By analyzing historical data and trends, it is designed to forecast financial outcomes and identify potential risks or opportunities. This feature aligns with the Process Optimization (PRCS) and Technology Modernization (TECH) goals.

Requirement: Generate Predictive Financial Reports (Functional)

Reference: ERPUPGD-191

The system must be able to generate predictive financial reports based on historical data and trends. This functionality will allow users to forecast financial outcomes and identify potential risks or opportunities. It aligns with the Predictive Financial Analytics feature and the Finance Process Optimization functional area.

Acceptance Criteria

• System can generate predictive financial reports,
• Reports include forecasted financial outcomes and identified risks/opportunities

Gherkin Scenarios

Scenario: Generate predictive financial reports
Given historical financial data and trends are available in the system
When a user requests a predictive financial report
Then the system generates a report with forecasted financial outcomes and identified risks/opportunities

Requirement: Automate Financial Data Analysis (Functional)

Reference: ERPUPGD-192

The system should automate the analysis of financial data to provide insights for decision-making. This automation will leverage SAP S/4HANA's advanced analytics capabilities to improve efficiency and accuracy in financial data analysis. It aligns with the Predictive Financial Analytics feature and the Finance Process Optimization functional area.

Acceptance Criteria

• System automates financial data analysis,
• Insights provided are accurate and support decision-making

Gherkin Scenarios

Scenario: Automate financial data analysis
Given financial data is available in the system
When the system initiates automated analysis
Then accurate insights are provided to support decision-making

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-193

The system must provide predictive financial analytics with minimal latency to ensure timely decision-making based on real-time data analysis. This requirement is crucial for enhancing the efficiency of financial forecasting and risk identification within the Predictive Financial Analytics feature of the Finance Process Optimization Functional Area.

Acceptance Criteria

• System delivers predictive financial analytics within 2 seconds of data input,
• System can handle a minimum of 100 concurrent users performing predictive analytics without performance degradation

Gherkin Scenarios

Scenario: Real-time Predictive Analytics
Given the system has received the latest financial data
When a user requests predictive analytics
Then the system responds with the analysis results within 2 seconds
And the system maintains performance with 100 concurrent users

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-194

The system must be scalable to accommodate an increasing volume of historical financial data for predictive analytics. This requirement ensures that the Predictive Financial Analytics feature can handle the growth of data without compromising performance or accuracy.

Acceptance Criteria

• System can process and analyze historical financial data spanning 5 years,
• System can scale to support a 50% increase in data volume without performance degradation

Gherkin Scenarios

Scenario: Scalability Test
Given the system has historical financial data for the past 5 years
When the system processes the entire dataset for predictive analytics
Then the system successfully analyzes the data without performance issues
And the system can handle a 50% increase in data volume

Requirement: Financial Forecasting Requirement (Business)

Reference: ERPUPGD-195

The system must provide accurate financial forecasting based on historical data and trends to support decision-making processes within the Predictive Financial Analytics feature of the Finance Process Optimization functional area.

Acceptance Criteria

• System accurately predicts financial outcomes based on historical data and trends,
• System identifies potential risks and opportunities through financial forecasting

Gherkin Scenarios

Scenario: Financial forecasting based on historical data
Given historical financial data is available in the system
When the system analyzes the data and trends
Then accurate financial forecasts are generated
And potential risks or opportunities are identified

Requirement: Risk Identification Requirement (Business)

Reference: ERPUPGD-196

The system must proactively identify and alert users to potential financial risks based on the analysis of real-time data, aligning with the goal of Process Optimization and Technology Modernization.

Acceptance Criteria

• System detects and alerts users to potential financial risks in real-time,
• System provides detailed information on the identified risks

Gherkin Scenarios

Scenario: Real-time financial risk identification
Given real-time financial data is being processed
When the system detects a potential risk
Then the system alerts the users immediately
And provides detailed information on the identified risk

Requirement: Data Integration with SAP S/4HANA (Technical)

Reference: ERPUPGD-197

Integrate external data sources with SAP S/4HANA to ensure seamless data flow for predictive financial analytics. This requirement is crucial for leveraging the advanced analytics capabilities of SAP S/4HANA and providing accurate predictive insights.

Acceptance Criteria

• External data sources are successfully integrated with SAP S/4HANA,
• Data flow between external sources and SAP S/4HANA is seamless

Gherkin Scenarios

Scenario: Data Integration with SAP S/4HANA
Given external data sources are available
When the integration process is initiated with SAP S/4HANA
Then verify that external data is successfully flowing into SAP S/4HANA
And ensure the data is accurate and up-to-date

Requirement: Model Training for Predictive Analytics (Technical)

Reference: ERPUPGD-198

Develop and train predictive models using historical financial data within SAP S/4HANA. This requirement is essential for generating accurate predictions and identifying potential risks or opportunities based on historical trends.

Acceptance Criteria

• Predictive models are successfully developed using historical financial data,
• Models are trained to forecast financial outcomes with a high degree of accuracy

Gherkin Scenarios

Scenario: Model Training for Predictive Analytics
Given historical financial data is available in SAP S/4HANA
When predictive models are developed and trained using the data
Then validate that the models can accurately forecast financial outcomes
And ensure the models can identify risks and opportunities

Requirement: Compliance with GDPR Regulations (Legal and Regulatory)

Reference: ERPUPGD-199

Ensure that all predictive financial analytics processes comply with the General Data Protection Regulation (GDPR) to protect the privacy and data rights of individuals. This requirement is crucial for maintaining legal compliance and data security within the Finance Process Optimization Functional Area and the Predictive Financial Analytics Feature.

Acceptance Criteria

• All predictive financial analytics processes adhere to GDPR regulations,
• Data anonymization and encryption techniques are implemented to protect personal data

Gherkin Scenarios

Scenario: Ensure GDPR compliance in predictive financial analytics
Given that predictive financial analytics processes are being executed
When personal data is involved in the analysis
Then ensure that data anonymization and encryption techniques are applied
And verify that all processes comply with GDPR regulations

Requirement: Financial Reporting Compliance (Legal and Regulatory)

Reference: ERPUPGD-200

Ensure that the predictive financial analytics results comply with all financial reporting regulations and standards, such as GAAP (Generally Accepted Accounting Principles) and IFRS (International Financial Reporting Standards). Compliance with these regulations is essential for accurate financial reporting and decision-making within the Finance Process Optimization Functional Area and the Predictive Financial Analytics Feature.

Acceptance Criteria

• Predictive financial analytics results align with GAAP and IFRS standards,
• Financial reports generated from predictive analytics are accurate and compliant with regulatory requirements

Gherkin Scenarios

Scenario: Verify financial reporting compliance in predictive financial analytics
Given that predictive financial analytics results are available
When generating financial reports based on the analytics
Then ensure that the reports adhere to GAAP and IFRS standards
And validate the accuracy and compliance of the reports

Requirement: Integration with SAP S/4HANA (Strategic)

Reference: ERPUPGD-201

The system must seamlessly integrate with SAP S/4HANA to leverage its advanced analytics capabilities for predictive financial analytics. This integration is crucial for accessing real-time data processing and historical data analysis.

Acceptance Criteria

• System integrates with SAP S/4HANA successfully,
• System can access real-time data processing features,
• System can analyze historical data for predictive analytics

Gherkin Scenarios

Scenario: Integration with SAP S/4HANA
Given the system is connected to SAP S/4HANA
When real-time data processing is initiated
Then the system can analyze historical data for predictive analytics

Requirement: Forecast Accuracy (Strategic)

Reference: ERPUPGD-202

The feature must ensure high accuracy in financial forecasts generated using predictive analytics. Accuracy is critical for decision-making processes based on the forecasted outcomes.

Acceptance Criteria

• Financial forecasts have a margin of error less than 5%,
• Forecasts align closely with actual financial outcomes

Gherkin Scenarios

Scenario: Forecast Accuracy
Given historical data and trends are analyzed
When financial forecasts are generated
Then the margin of error is less than 5%

Supply Chain Automation

This functional area aims to automate and optimize supply chain processes within the ERP system by integrating SAP S/4HANA's advanced functionalities. By leveraging features like real-time inventory tracking, demand forecasting, and automated order processing, this area seeks to enhance supply chain efficiency, reduce lead times, and improve inventory management. This aligns with the project goal of Process Optimization (PRCS) and Compliance and Scalability (COMPL).

Feature: Real-Time Inventory Tracking

This feature will enable real-time tracking of inventory levels within the ERP system, providing up-to-date information on stock availability, locations, and movement. By integrating with SAP S/4HANA's advanced functionalities, this feature ensures that inventory data is accurate and accessible, supporting efficient supply chain operations.

Requirement: Real-Time Inventory Update Trigger (Functional)

Reference: ERPUPGD-203

The system must trigger real-time updates to inventory levels whenever a new stock receipt is recorded in the ERP system. This functionality ensures that inventory data remains accurate and up-to-date, supporting efficient supply chain operations and enabling timely decision-making.

Acceptance Criteria

• System triggers inventory update upon recording a new stock receipt in real-time

Gherkin Scenarios

Scenario: Real-time inventory update trigger upon stock receipt
Given a new stock receipt is recorded in the ERP system
When the system processes the stock receipt
Then the inventory levels are updated in real-time
And the updated inventory data is accessible for viewing

Requirement: Inventory Location Tracking (Functional)

Reference: ERPUPGD-204

The system must track the location of each inventory item within the warehouse in real-time. This feature enables warehouse workers to quickly locate specific items, reducing search times and improving overall operational efficiency.

Acceptance Criteria

• System tracks the location of each inventory item in real-time

Gherkin Scenarios

Scenario: Inventory location tracking in real-time
Given an inventory item is received in the warehouse
When the item is scanned into the system
Then the system updates the item's location in real-time
And the updated location is accessible for retrieval

Requirement: Inventory Movement Validation (Functional)

Reference: ERPUPGD-205

The system must validate and log each inventory movement transaction to ensure accurate tracking of stock transfers within the warehouse. By maintaining a comprehensive record of inventory movements, this functionality supports audit trails and helps identify discrepancies in stock movement.

Acceptance Criteria

• System validates and logs each inventory movement transaction

Gherkin Scenarios

Scenario: Inventory movement validation and logging
Given an inventory transfer ticket is created in the ERP system
When the stock movement is executed
Then the system validates the transaction and logs the movement
And the transaction details are recorded for audit purposes

Requirement: Real-Time Inventory Tracking Performance (Non-Functional)

Reference: ERPUPGD-206

The system must ensure real-time inventory tracking performance meets the defined service level agreements (SLAs) to provide up-to-date information on stock availability and movement within seconds. This requirement is crucial for supporting efficient supply chain operations and decision-making processes.

Acceptance Criteria

• Inventory tracking updates must occur within seconds of any stock movement,
• System response time for inventory queries must not exceed 1 second

Gherkin Scenarios

Scenario: Real-Time Inventory Tracking Performance
Given the system is tracking inventory in real-time
When a stock movement occurs
Then the inventory levels are updated within seconds
And the system responds to inventory queries within 1 second

Requirement: Data Accuracy and Integrity (Non-Functional)

Reference: ERPUPGD-207

The system must maintain data accuracy and integrity in real-time inventory tracking to ensure that stock availability, locations, and movement information are always up-to-date and reliable. This requirement is essential for supporting decision-making processes and preventing errors in supply chain operations.

Acceptance Criteria

• Inventory data must be synchronized across all relevant systems in real-time,
• Data discrepancies between physical inventory and system records must be resolved within 24 hours

Gherkin Scenarios

Scenario: Data Accuracy and Integrity in Inventory Tracking
Given the system is tracking inventory in real-time
When discrepancies between physical inventory and system records are identified
Then the discrepancies are resolved within 24 hours
And inventory data is synchronized across all relevant systems

Requirement: Scalability and Performance (Non-Functional)

Reference: ERPUPGD-208

The system must be scalable to handle increasing volumes of inventory data and transactions while maintaining optimal performance levels. This requirement ensures that the real-time inventory tracking feature can support the company's growth and evolving supply chain needs without compromising system responsiveness.

Acceptance Criteria

• The system must handle a 50% increase in inventory transactions without performance degradation,
• Scalability tests must be conducted quarterly to assess system performance under increased loads

Gherkin Scenarios

Scenario: Scalability and Performance Testing
Given the system is processing inventory transactions
When the transaction volume increases by 50%
Then the system performance is monitored for degradation
And scalability tests are conducted quarterly

Requirement: Real-Time Inventory Visibility (Business)

Reference: ERPUPGD-209

The system must provide real-time visibility of inventory levels, locations, and movements to support efficient supply chain operations. This requirement aligns with the goal of Process Optimization by streamlining inventory tracking processes.

Acceptance Criteria

• Users can view current inventory levels and locations in real-time,
• Inventory movements are updated instantly in the system,
• System alerts users of low stock levels or discrepancies immediately

Gherkin Scenarios

Scenario: Real-Time Inventory Visibility
Given the user is logged into the system
When the user navigates to the inventory tracking section
Then the system displays real-time inventory levels and locations
And alerts the user of any low stock levels or discrepancies

Requirement: Automated Stock Replenishment (Business)

Reference: ERPUPGD-210

The system should automatically generate stock replenishment orders based on predefined inventory thresholds to ensure optimal stock levels. This requirement supports the goal of Compliance and Scalability by maintaining adequate inventory levels to meet demand.

Acceptance Criteria

• System generates replenishment orders when stock levels fall below set thresholds,
• Orders are created automatically without manual intervention,
• Users can review and approve generated orders before processing

Gherkin Scenarios

Scenario: Automated Stock Replenishment
Given the system has predefined stock thresholds
When stock levels drop below the thresholds
Then the system generates replenishment orders automatically
And allows users to review and approve orders before processing

Requirement: Real-Time Inventory Data Integration (Technical)

Reference: ERPUPGD-211

Integrate real-time inventory data from SAP S/4HANA into the ERP system to ensure accurate and up-to-date information on stock levels, locations, and movements. This integration is crucial for enabling real-time inventory tracking within the system.

Acceptance Criteria

• Real-time inventory data is successfully integrated into the ERP system,
• Stock levels are updated automatically in real-time,
• Locations of inventory items are accurately reflected in the system,
• Movements of stock are tracked and recorded instantly

Gherkin Scenarios

Scenario: Real-time inventory data integration
Given the SAP S/4HANA system has updated inventory data
When the data is integrated into the ERP system
Then stock levels, locations, and movements are updated in real-time

Requirement: Inventory Data Accuracy Validation (Technical)

Reference: ERPUPGD-212

Implement validation checks to ensure the accuracy and consistency of inventory data within the ERP system. This validation process is essential for maintaining data integrity and reliability for supply chain operations.

Acceptance Criteria

• Inventory data is validated for accuracy upon integration,
• Data inconsistencies are flagged and reported for review,
• Validation process includes checks for stock levels, locations, and movements,
• System alerts are triggered for any discrepancies found

Gherkin Scenarios

Scenario: Inventory data accuracy validation
Given inventory data is integrated into the ERP system
When validation checks are performed
Then any discrepancies are flagged for review and alerts are triggered

Requirement: Compliance with Data Privacy Regulations (Legal and Regulatory)

Reference: ERPUPGD-213

Ensure that the Real-Time Inventory Tracking feature complies with all relevant data privacy regulations, such as GDPR, CCPA, and industry-specific data protection laws. This requirement is crucial to protect sensitive inventory data and maintain legal compliance within the supply chain automation process.

Acceptance Criteria

• The system must encrypt all inventory data in transit and at rest,
• Users must be able to request and delete their inventory data upon request

Gherkin Scenarios

Scenario: Ensuring Data Privacy Compliance
Given the system is processing inventory data
When data is transmitted or stored
Then the data must be encrypted to protect privacy
And users should have the ability to request and delete their data

Requirement: Compliance with Product Safety Regulations (Legal and Regulatory)

Reference: ERPUPGD-214

Ensure that the Real-Time Inventory Tracking feature complies with product safety regulations, such as FDA requirements for tracking perishable goods or hazardous materials. This requirement is essential to prevent legal liabilities and ensure the safety of products within the supply chain.

Acceptance Criteria

• The system must provide alerts for expired or recalled products,
• Users must be able to trace the origin of products in case of safety concerns

Gherkin Scenarios

Scenario: Ensuring Product Safety Compliance
Given the system is tracking inventory levels
When an expired or recalled product is detected
Then the system should alert users
And users should be able to trace the product's origin for safety measures

Requirement: Real-Time Inventory Visibility (Strategic)

Reference: ERPUPGD-215

Ensure that the system provides real-time visibility into inventory levels, locations, and movements to support efficient supply chain operations within the ERP system. This requirement is essential for enabling timely decision-making and optimizing inventory management processes.

Acceptance Criteria

• System displays accurate real-time inventory levels,
• System tracks inventory movements and updates locations promptly,
• System provides visibility into stock availability for all relevant stakeholders

Gherkin Scenarios

Scenario: Real-Time Inventory Visibility
Given the system is operational
When a new inventory item is received
Then the system updates the inventory levels in real-time
And the system reflects the new item location

Requirement: Integration with SAP S/4HANA Advanced Functionalities (Strategic)

Reference: ERPUPGD-216

Ensure seamless integration with SAP S/4HANA's advanced functionalities to leverage features like demand forecasting, automated order processing, and data analytics. This requirement is critical for maximizing the benefits of the ERP system and enhancing supply chain efficiency.

Acceptance Criteria

• System integrates with SAP S/4HANA APIs for real-time data exchange,
• System utilizes SAP S/4HANA's demand forecasting capabilities,
• System automates order processing through SAP S/4HANA workflows

Gherkin Scenarios

Scenario: Integration with SAP S/4HANA
Given the system is connected to SAP S/4HANA
When a new order is received
Then the system triggers automated order processing in SAP S/4HANA
And the system updates inventory levels based on demand forecasts

Requirement: Real-Time Inventory Data Accuracy (Other)

Reference: ERPUPGD-217

Ensure that the real-time inventory tracking feature provides accurate and reliable data on stock levels, locations, and movements. This requirement is crucial for supporting efficient supply chain operations and decision-making processes within the ERP system.

Acceptance Criteria

• System displays real-time stock levels accurately,
• System updates inventory locations promptly,
• System tracks stock movements in real-time

Gherkin Scenarios

Scenario: Real-Time Inventory Data Accuracy
Given the system is tracking inventory in real-time
When stock levels change due to transactions
Then the system updates the inventory data immediately
And the updated information is reflected accurately

Requirement: Inventory Data Accessibility (Other)

Reference: ERPUPGD-218

Ensure that inventory data is easily accessible to authorized users, allowing them to view real-time stock availability, locations, and movements. This requirement supports informed decision-making and efficient supply chain management.

Acceptance Criteria

• Authorized users can access real-time inventory data,
• Data is presented in a user-friendly format for easy interpretation,
• Access controls restrict data visibility based on user roles

Gherkin Scenarios

Scenario: Inventory Data Accessibility
Given the user has the necessary permissions to access inventory data
When the user requests real-time stock information
Then the system displays the data in a user-friendly format
And restricts access to sensitive information based on user roles

Feature: Demand Forecasting

This feature is designed to leverage historical data and predictive analytics to forecast demand for products accurately. By utilizing SAP S/4HANA's forecasting capabilities, this feature helps in optimizing inventory levels, reducing stockouts, and improving overall supply chain efficiency.

Requirement: Generate Demand Forecast (Functional)

Reference: ERPUPGD-219

The system must be able to generate accurate demand forecasts based on historical data and predictive analytics. This requirement is crucial for optimizing inventory levels, reducing stockouts, and improving overall supply chain efficiency within the Demand Forecasting feature of the Supply Chain Automation Functional Area.

Acceptance Criteria

• System generates demand forecast accurately,
• Forecast considers historical data and predictive analytics,
• Forecast helps optimize inventory levels and reduce stockouts

Gherkin Scenarios

Scenario: System generates demand forecast
Given historical data and predictive analytics are available
When the system processes the data to generate a demand forecast
Then the demand forecast is accurate and optimized for inventory levels

Requirement: Integrate Forecast with Order Processing (Functional)

Reference: ERPUPGD-220

The system must integrate the generated demand forecast seamlessly with the automated order processing functionality. This integration ensures that order processing is aligned with forecasted demand, improving supply chain efficiency and reducing lead times.

Acceptance Criteria

• Demand forecast is automatically used in order processing,
• Orders are processed based on forecasted demand,
• Integration reduces lead times and improves supply chain efficiency

Gherkin Scenarios

Scenario: Integration of demand forecast with order processing
Given the demand forecast is generated
When an order is received
Then the system processes the order based on the forecasted demand

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-221

The system must be able to generate demand forecasts within seconds to support real-time decision-making and planning. This requirement is crucial for ensuring that users can access timely and accurate demand predictions to optimize inventory levels and enhance supply chain efficiency.

Acceptance Criteria

• Demand forecasts are generated within 5 seconds of initiating the request,
• The system can handle a minimum of 1000 forecast calculations per hour without performance degradation

Gherkin Scenarios

Scenario: Generate demand forecast quickly
Given the system is operational
When a user requests a demand forecast
Then the system generates the forecast within 5 seconds
And the forecast is available for review

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-222

The system must be scalable to accommodate an increasing volume of historical data for demand forecasting without compromising performance. This requirement ensures that the system can handle growth in data volume and user load as the business expands.

Acceptance Criteria

• The system can store and process at least 5 years of historical demand data,
• Performance remains consistent when the system load increases by 50%

Gherkin Scenarios

Scenario: Test system scalability
Given the system is operational
When the historical demand data volume is increased by 50%
Then the system continues to perform efficiently
And can handle the increased data load without issues

Requirement: Data Security (Non-Functional)

Reference: ERPUPGD-223

The system must ensure the confidentiality, integrity, and availability of demand forecasting data to prevent unauthorized access, data breaches, or loss of critical information. This requirement is essential for maintaining data privacy and compliance with industry regulations.

Acceptance Criteria

• Access to demand forecasting data is restricted to authorized users only,
• Data encryption is applied to protect sensitive information during transmission and storage

Gherkin Scenarios

Scenario: Ensure data security
Given the system contains demand forecasting data
When a user attempts unauthorized access to the data
Then the system denies access and logs the security breach
And sensitive data is encrypted during transmission and storage

Requirement: Demand Forecasting Accuracy (Business)

Reference: ERPUPGD-224

The system must accurately forecast demand for products based on historical data and predictive analytics. This requirement is crucial for optimizing inventory levels, reducing stockouts, and improving overall supply chain efficiency within the Demand Forecasting feature of the Supply Chain Automation Functional Area.

Acceptance Criteria

• System forecasts demand within +/- 5% accuracy compared to actual demand,
• Forecasting model considers seasonality and market trends,
• Forecasting results are updated in real-time based on incoming data

Gherkin Scenarios

Scenario: System accurately forecasts demand
Given historical data and predictive analytics are available
When the system generates a demand forecast
Then the forecasted demand should be within +/- 5% accuracy compared to actual demand
And the forecast should consider seasonality and market trends
And the forecast should be updated in real-time

Requirement: Forecast Visualization and Reporting (Business)

Reference: ERPUPGD-225

The system must provide visualizations and reports based on demand forecasting data to aid decision-making processes. This requirement enhances the usability and effectiveness of the Demand Forecasting feature within the Supply Chain Automation Functional Area.

Acceptance Criteria

• System generates visualizations such as demand trend graphs and forecast accuracy charts,
• Reports include key metrics like forecast error rates and inventory optimization recommendations,
• Users can customize visualization settings and export reports

Gherkin Scenarios

Scenario: System provides demand forecast visualizations and reports
Given demand forecasting data is available
When users request visualizations and reports
Then the system should generate demand trend graphs and forecast accuracy charts
And reports should include key metrics like forecast error rates and inventory optimization recommendations
And users should be able to customize visualization settings and export reports

Requirement: Integration with SAP S/4HANA Forecasting Module (Technical)

Reference: ERPUPGD-226

This requirement involves integrating the demand forecasting feature with SAP S/4HANA's forecasting module to leverage its advanced predictive analytics capabilities. This integration ensures accurate demand forecasting based on historical data and enhances supply chain efficiency.

Acceptance Criteria

• Demand forecasting feature seamlessly integrates with SAP S/4HANA's forecasting module,
• Historical data is utilized for accurate demand predictions,
• Predictive analytics capabilities are leveraged for forecasting accuracy

Gherkin Scenarios

Scenario: Integration with SAP S/4HANA Forecasting Module
Given the demand forecasting feature is active
When the integration with SAP S/4HANA's forecasting module is initiated
Then historical data is retrieved for demand forecasting
And predictive analytics are applied for accurate predictions

Requirement: Real-time Data Synchronization (Technical)

Reference: ERPUPGD-227

This requirement focuses on ensuring real-time data synchronization between the demand forecasting feature and SAP S/4HANA's inventory tracking system. It enables immediate updates on inventory levels based on demand forecasts, enhancing supply chain responsiveness.

Acceptance Criteria

• Data synchronization occurs in real-time,
• Inventory levels are updated immediately based on demand forecasts,
• System response time for data synchronization is within defined thresholds

Gherkin Scenarios

Scenario: Real-time Data Synchronization
Given the demand forecasting feature is active
When demand forecasts are generated
Then inventory levels are updated in real-time
And system response time meets defined thresholds

Requirement: Compliance with Data Privacy Regulations (Legal and Regulatory)

Reference: ERPUPGD-228

Ensure that the demand forecasting feature complies with all relevant data privacy regulations, such as GDPR, CCPA, and industry-specific data protection laws. This requirement is crucial to protect customer data and maintain legal compliance within the supply chain automation process.

Acceptance Criteria

• Demand forecasting feature adheres to GDPR, CCPA, and industry-specific data privacy regulations

Gherkin Scenarios

Scenario: Ensure compliance with data privacy regulations
Given that the demand forecasting feature processes customer data
When the feature is executed
Then the feature complies with GDPR, CCPA, and industry-specific data privacy regulations

Requirement: Accuracy of Demand Forecasting Models (Legal and Regulatory)

Reference: ERPUPGD-229

Mandate that the demand forecasting models used in the feature meet legal standards for accuracy and transparency. This requirement ensures that the predictions generated by the models are reliable and can be audited for compliance purposes.

Acceptance Criteria

• Demand forecasting models have a documented accuracy rate of at least 90%,
• Model algorithms are transparent and auditable

Gherkin Scenarios

Scenario: Validate accuracy of demand forecasting models
Given that historical data is used to generate demand forecasts
When the forecasting models are executed
Then the models achieve a minimum accuracy rate of 90%
And the model algorithms are transparent and auditable

Requirement: Demand Forecasting Accuracy (Strategic)

Reference: ERPUPGD-230

The system must accurately forecast demand for products based on historical data and predictive analytics. This requirement is crucial for optimizing inventory levels, reducing stockouts, and improving overall supply chain efficiency within the Demand Forecasting feature of the Supply Chain Automation functional area.

Acceptance Criteria

• System forecasts demand with 95% accuracy,
• Forecast accuracy is validated against historical sales data,
• Forecasting model adjusts dynamically based on market trends

Gherkin Scenarios

Scenario: System accurately forecasts demand
Given historical sales data and predictive analytics are available
When the system generates a demand forecast
Then the forecast accuracy is validated
And the forecasting model adjusts based on market trends

Requirement: Integration with SAP S/4HANA Forecasting Module (Strategic)

Reference: ERPUPGD-231

The system must seamlessly integrate with SAP S/4HANA's forecasting module to leverage its advanced capabilities for demand forecasting. This integration is essential for optimizing supply chain processes and ensuring alignment with the project goal of Process Optimization.

Acceptance Criteria

• System integrates with SAP S/4HANA's forecasting module without data loss,
• Forecasting data is synchronized in real-time between systems,
• Integration supports automated data updates and alerts

Gherkin Scenarios

Scenario: System integrates with SAP S/4HANA Forecasting Module
Given the system and SAP S/4HANA are connected
When forecasting data is updated in SAP S/4HANA
Then the system synchronizes the data in real-time
And automated alerts are triggered for any discrepancies

Requirement: Integration with Historical Data Sources (Other)

Reference: ERPUPGD-232

This requirement involves integrating the demand forecasting feature with historical data sources to leverage past sales data, market trends, and customer behavior patterns. By incorporating historical data, the system can generate more accurate demand forecasts, leading to optimized inventory levels and improved supply chain decision-making.

Acceptance Criteria

• System successfully integrates with historical data sources,
• Demand forecasts are based on historical data analysis,
• Forecast accuracy improves by X% compared to previous methods

Gherkin Scenarios

Scenario: Integration with Historical Data Sources
Given historical sales data, market trends, and customer behavior patterns are available
When the system integrates with the historical data sources
Then demand forecasts are generated based on historical data analysis
And the forecast accuracy improves by X% compared to previous methods

Requirement: Real-time Data Updates (Other)

Reference: ERPUPGD-233

This requirement focuses on ensuring that the demand forecasting feature receives real-time updates on inventory levels, sales data, and market conditions. Real-time data updates enable the system to adjust demand forecasts dynamically, leading to more accurate predictions and proactive decision-making.

Acceptance Criteria

• System receives real-time updates on inventory levels,
• Sales data updates are reflected in demand forecasts immediately,
• Market condition changes trigger forecast adjustments

Gherkin Scenarios

Scenario: Real-time Data Updates
Given the system is connected to real-time inventory and sales data sources
When inventory levels change or new sales data is recorded
Then demand forecasts are updated immediately
And market condition changes trigger forecast adjustments

Feature: Automated Order Processing

This feature will automate the order processing workflow within the ERP system, from order creation to fulfillment. By integrating with SAP S/4HANA's automation tools, this feature streamlines the customer order process, reduces manual intervention, and enhances order accuracy and speed.

Requirement: Automated Order Creation (Functional)

Reference: ERPUPGD-234

The system must automatically generate customer orders based on predefined triggers or customer requests. This functionality aims to reduce manual order creation efforts and ensure timely processing of orders.

Acceptance Criteria

• System can automatically create customer orders based on triggers or requests

Gherkin Scenarios

Scenario: Automated Order Creation
Given that a trigger or customer request is received
When the system processes the trigger or request
Then a customer order is automatically generated
And the order details are accurate

Requirement: Automated Order Fulfillment (Functional)

Reference: ERPUPGD-235

The system must automatically fulfill customer orders by processing inventory availability, scheduling shipments, and updating order status. This feature aims to streamline the order fulfillment process and improve customer satisfaction.

Acceptance Criteria

• System can automatically fulfill customer orders based on inventory availability and shipment scheduling

Gherkin Scenarios

Scenario: Automated Order Fulfillment
Given that a customer order is ready for fulfillment
When the system checks inventory availability and schedules shipment
Then the order is marked as fulfilled
And the customer is notified of shipment details

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-236

The system must process customer orders within 5 seconds to ensure timely order fulfillment and customer satisfaction. This requirement is crucial for optimizing the order processing workflow and meeting customer expectations.

Acceptance Criteria

• Customer orders are processed within 5 seconds of submission.

Gherkin Scenarios

Scenario: Process customer order efficiently
Given a customer submits an order
When the system processes the order
Then the order is completed within 5 seconds

Requirement: Security Compliance (Non-Functional)

Reference: ERPUPGD-237

The system must adhere to industry-standard security protocols to protect sensitive customer data and ensure secure order processing. This requirement aligns with the goal of Compliance and Scalability by safeguarding customer information and maintaining regulatory compliance.

Acceptance Criteria

• System data encryption meets industry standards,
• Access controls are in place to protect customer data

Gherkin Scenarios

Scenario: Ensure system security compliance
Given the system processes customer orders
When data is transmitted and stored
Then data encryption meets industry standards

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-238

The system must be able to handle a 20% increase in order volume without performance degradation to support business growth. This requirement ensures that the system can scale effectively to accommodate future order processing demands.

Acceptance Criteria

• System performance remains consistent with a 20% increase in order volume

Gherkin Scenarios

Scenario: Test system scalability under increased order volume
Given the system processes a standard order volume
When the order volume increases by 20%
Then the system performance remains stable

Requirement: Automated Order Creation (Business)

Reference: ERPUPGD-239

The system must automatically generate customer orders based on predefined criteria and trigger the order creation process within the ERP system. This requirement aims to streamline the order initiation process and reduce manual intervention, aligning with the goal of Process Optimization and enhancing supply chain efficiency.

Acceptance Criteria

• System automatically generates customer orders based on demand forecasting and inventory levels,
• Orders are created in the ERP system without manual intervention,
• Orders are triggered for processing as soon as they are generated

Gherkin Scenarios

Scenario: Automated Order Creation
Given the system has demand forecasting and inventory data
When the predefined criteria are met for order generation
Then the system automatically creates a customer order in the ERP system

Requirement: Automated Order Fulfillment (Business)

Reference: ERPUPGD-240

The system must automate the order fulfillment process by integrating with SAP S/4HANA's advanced functionalities to ensure timely and accurate order processing. This requirement aims to reduce lead times, improve order accuracy, and enhance customer satisfaction, supporting the goal of Process Optimization.

Acceptance Criteria

• Orders are automatically processed for fulfillment upon creation,
• Inventory availability is checked in real-time to fulfill orders accurately,
• Order status updates are provided to customers in real-time

Gherkin Scenarios

Scenario: Automated Order Fulfillment
Given the system has received a customer order for processing
When the system checks inventory availability in real-time
Then the system processes the order for fulfillment and updates the order status

Requirement: Automated Order Creation (Technical)

Reference: ERPUPGD-241

Automate the process of creating customer orders within the ERP system to reduce manual effort and improve order processing efficiency. This requirement plays a crucial role in streamlining the order processing workflow within the Supply Chain Automation Functional Area and aligns with the goal of Process Optimization.

Acceptance Criteria

• System can automatically generate customer orders based on predefined criteria,
• Orders are created accurately and promptly without manual intervention,
• Automated orders are seamlessly integrated into the ERP system for further processing

Gherkin Scenarios

Scenario: Automated Order Creation
Given the system criteria for order creation are met
When the system processes the criteria and generates a customer order
Then the order is created accurately and promptly without manual intervention
And the order is seamlessly integrated into the ERP system for further processing

Requirement: Real-time Inventory Sync (Technical)

Reference: ERPUPGD-242

Implement real-time synchronization of inventory data between the ERP system and SAP S/4HANA to ensure accurate and up-to-date inventory tracking. This requirement is essential for enhancing supply chain efficiency and improving inventory management within the Supply Chain Automation Functional Area.

Acceptance Criteria

• Inventory data is synchronized in real-time between the ERP system and SAP S/4HANA,
• Changes in inventory levels are immediately reflected in both systems,
• Inventory discrepancies are promptly identified and resolved through synchronization

Gherkin Scenarios

Scenario: Real-time Inventory Sync
Given the ERP system and SAP S/4HANA are connected for inventory synchronization
When changes occur in inventory levels in either system
Then the inventory data is immediately synchronized between the systems
And discrepancies are promptly identified and resolved

Requirement: Data Privacy Compliance (Legal and Regulatory)

Reference: ERPUPGD-243

Ensure that the automated order processing feature complies with data privacy regulations such as GDPR, CCPA, and other relevant laws. This requirement is crucial to protect customer data and maintain legal compliance within the supply chain automation functional area.

Acceptance Criteria

• Customer data is encrypted during transmission and storage,
• Customers have the option to opt-out of data processing for marketing purposes

Gherkin Scenarios

Scenario: Data Privacy Compliance
Given that customer data is being processed in the system
When customer data is transmitted or stored
Then ensure that data is encrypted to protect privacy
And provide customers with the option to opt-out of marketing data processing

Requirement: Audit Trail Logging (Legal and Regulatory)

Reference: ERPUPGD-244

Implement audit trail logging to track all activities related to order processing within the ERP system. This requirement ensures transparency, accountability, and compliance with auditing standards and regulations.

Acceptance Criteria

• All order processing activities are logged with timestamps and user identifiers,
• Logs are tamper-proof and accessible only to authorized personnel

Gherkin Scenarios

Scenario: Audit Trail Logging
Given that an order is being processed in the system
When the order processing workflow is executed
Then log all activities with timestamps and user IDs
And ensure that logs are secure and tamper-proof

Requirement: Automated Order Validation (Strategic)

Reference: ERPUPGD-245

Ensure that all incoming orders are automatically validated against inventory availability and customer credit limits to prevent processing errors and delays. This requirement plays a crucial role in enhancing order accuracy, reducing fulfillment lead times, and improving customer satisfaction within the Automated Order Processing feature of the Supply Chain Automation Functional Area.

Acceptance Criteria

• System validates order against real-time inventory levels,
• System checks customer credit limit before order processing

Gherkin Scenarios

Scenario: Automated Order Validation
Given that a customer places an order
When the system validates the order against inventory levels
And checks the customer's credit limit
Then the order is either processed or flagged for review

Requirement: Automated Order Status Updates (Strategic)

Reference: ERPUPGD-246

Implement automated order status updates to provide real-time visibility to customers and internal stakeholders regarding order progress and fulfillment status. This requirement contributes to improving communication, transparency, and operational efficiency within the Automated Order Processing feature of the Supply Chain Automation Functional Area.

Acceptance Criteria

• Customers receive automated notifications on order status changes,
• Internal stakeholders can track order progress in real-time

Gherkin Scenarios

Scenario: Automated Order Status Updates
Given that an order status changes
When the system updates the status automatically
Then customers and internal stakeholders receive notifications

Requirement: Automated Order Validation (Other)

Reference: ERPUPGD-247

The system must validate each automated order for accuracy and completeness before processing to ensure that all required information is present and accurate.

Acceptance Criteria

• System validates all mandatory fields in the order,
• System checks for duplicate orders before processing

Gherkin Scenarios

Scenario: Automated order validation
Given an automated order is created
When the system validates the order
Then all mandatory fields are checked for completeness
And duplicate orders are identified and flagged

Requirement: Automated Order Confirmation (Other)

Reference: ERPUPGD-248

The system must automatically confirm orders with customers once they have been successfully processed to provide real-time updates and improve customer satisfaction.

Acceptance Criteria

• System sends order confirmation email to customer,
• Customer receives order confirmation within 24 hours of order processing

Gherkin Scenarios

Scenario: Automated order confirmation
Given an order has been successfully processed
When the system confirms the order
Then an email confirmation is sent to the customer
And the customer receives the confirmation within 24 hours

Manufacturing Process Enhancement

This functional area focuses on enhancing manufacturing processes within the ERP system using SAP S/4HANA's intelligent automation capabilities. By integrating machine learning algorithms, IoT technologies, and predictive analytics, this area aims to optimize production scheduling, resource allocation, and quality control. This aligns with the project goal of Digital Transformation (DIGTLXFORM) and Compliance and Scalability (COMPL).

Feature: Predictive Maintenance Optimization

This feature will utilize machine learning algorithms and IoT technologies to predict equipment failures before they occur. By analyzing real-time data from sensors, the system will automatically schedule maintenance tasks, ensuring optimal equipment performance and minimizing downtime.

Requirement: Equipment Failure Prediction (Functional)

Reference: ERPUPGD-249

The system must predict equipment failures using machine learning algorithms and IoT data to schedule maintenance tasks proactively. This requirement is essential for optimizing equipment performance and minimizing downtime within the Manufacturing Process Enhancement Functional Area and the Predictive Maintenance Optimization Feature.

Acceptance Criteria

• System accurately predicts equipment failures based on real-time sensor data,
• Maintenance tasks are automatically scheduled before equipment failures occur

Gherkin Scenarios

Scenario: Equipment failure prediction
Given the system has access to real-time sensor data
When the machine learning algorithms analyze the data
Then the system predicts equipment failures
And schedules maintenance tasks proactively

Requirement: Maintenance Task Automation (Functional)

Reference: ERPUPGD-250

The system must automate the scheduling of maintenance tasks based on predicted equipment failures. This requirement ensures optimal equipment performance and supports the goal of Digital Transformation and Compliance and Scalability.

Acceptance Criteria

• Maintenance tasks are scheduled automatically based on predicted equipment failures,
• Scheduled maintenance tasks are communicated to relevant personnel

Gherkin Scenarios

Scenario: Maintenance task automation
Given the system has predicted equipment failures
When the system automatically schedules maintenance tasks
Then relevant personnel are notified of the scheduled tasks

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-251

The system must be able to process and analyze real-time sensor data efficiently to predict equipment failures in a timely manner. This requirement is crucial for ensuring that maintenance tasks are scheduled proactively to minimize downtime and optimize equipment performance.

Acceptance Criteria

• System can process real-time sensor data within milliseconds,
• Predictive maintenance alerts are generated within seconds of detecting potential equipment failures

Gherkin Scenarios

Scenario: System processes real-time sensor data efficiently
Given the system is receiving real-time sensor data
When the system processes the data within milliseconds
Then predictive maintenance alerts are generated within seconds

Requirement: Reliability and Availability (Non-Functional)

Reference: ERPUPGD-252

The system must have high reliability and availability to ensure continuous monitoring of equipment and timely scheduling of maintenance tasks. This requirement is essential for preventing unexpected equipment failures and minimizing production downtime.

Acceptance Criteria

• System uptime of at least 99.9%,
• Maintenance scheduling system available 24/7

Gherkin Scenarios

Scenario: System reliability and availability
Given the system is operational
When the system uptime is at least 99.9%
Then the maintenance scheduling system is available 24/7

Requirement: Security and Data Privacy (Non-Functional)

Reference: ERPUPGD-253

The system must ensure the security and privacy of sensitive equipment data and maintenance schedules. This requirement is critical for complying with data protection regulations and safeguarding confidential information.

Acceptance Criteria

• Data encryption for sensitive equipment data,
• Role-based access control for maintenance schedules

Gherkin Scenarios

Scenario: System security and data privacy
Given the system contains sensitive equipment data
When data encryption is applied to the data
Then role-based access control is implemented for maintenance schedules

Requirement: Equipment Failure Prediction (Business)

Reference: ERPUPGD-254

The system must predict equipment failures using machine learning algorithms and IoT technologies. This requirement is crucial for optimizing maintenance schedules and minimizing downtime, aligning with the goal of Predictive Maintenance Optimization within the Manufacturing Process Enhancement functional area.

Acceptance Criteria

• System accurately predicts equipment failures based on real-time sensor data,
• Maintenance tasks are automatically scheduled before equipment failures occur

Gherkin Scenarios

Scenario: Equipment failure prediction
Given the system has access to real-time sensor data
When the machine learning algorithms analyze the data
Then the system predicts potential equipment failures
And schedules maintenance tasks preemptively

Requirement: Integration with SAP S/4HANA (Business)

Reference: ERPUPGD-255

The system must integrate seamlessly with SAP S/4HANA to leverage its intelligent automation capabilities for predictive maintenance optimization. This requirement ensures that the feature aligns with the Digital Transformation goal of embracing cutting-edge technologies.

Acceptance Criteria

• System integrates with SAP S/4HANA without data loss or errors,
• Utilizes SAP S/4HANA's machine learning and IoT integration for predictive maintenance

Gherkin Scenarios

Scenario: Integration with SAP S/4HANA
Given the system is connected to SAP S/4HANA
When data is transferred between systems
Then the integration is successful
And the system leverages SAP S/4HANA's capabilities for predictive maintenance

Requirement: Real-time Sensor Data Integration (Technical)

Reference: ERPUPGD-256

Integrate real-time sensor data from manufacturing equipment with the ERP system to enable predictive maintenance. This requirement is crucial for collecting and analyzing data for equipment health monitoring and failure prediction.

Acceptance Criteria

• System can receive real-time sensor data,
• Data is processed and stored for analysis,
• Predictive maintenance alerts are triggered based on data analysis

Gherkin Scenarios

Scenario: Real-time sensor data integration
Given the system is connected to manufacturing equipment sensors
When real-time data is received from the sensors
Then the system processes and stores the data for analysis
And triggers predictive maintenance alerts based on the data

Requirement: Automated Maintenance Task Scheduling (Technical)

Reference: ERPUPGD-257

Automate the scheduling of maintenance tasks based on predictive maintenance alerts generated by the system. This requirement ensures that maintenance activities are proactively planned and executed to prevent equipment failures.

Acceptance Criteria

• System can automatically schedule maintenance tasks,
• Maintenance schedules are adjusted based on real-time data analysis,
• Maintenance tasks are executed as per the schedule

Gherkin Scenarios

Scenario: Automated maintenance task scheduling
Given predictive maintenance alerts are generated by the system
When the system automatically schedules maintenance tasks
Then maintenance schedules are adjusted based on real-time data analysis
And maintenance tasks are executed as per the schedule

Requirement: Data Privacy Compliance (Legal and Regulatory)

Reference: ERPUPGD-258

Ensure that the Predictive Maintenance Optimization feature complies with data privacy regulations such as GDPR, CCPA, and industry-specific data protection laws. Data collected and processed for predictive maintenance must adhere to strict privacy guidelines to protect sensitive information.

Acceptance Criteria

• Data collected for predictive maintenance is anonymized and encrypted,
• Access to predictive maintenance data is restricted to authorized personnel only

Gherkin Scenarios

Scenario: Data Privacy Compliance for Predictive Maintenance
Given that data is collected for predictive maintenance purposes
When the data is processed and stored in the system
Then ensure that data is anonymized and encrypted
And restrict access to authorized personnel only

Requirement: Equipment Maintenance Record Keeping (Legal and Regulatory)

Reference: ERPUPGD-259

Maintain accurate and up-to-date records of equipment maintenance activities performed based on predictive maintenance alerts. Compliance with industry regulations requires detailed documentation of maintenance tasks, including dates, procedures, and outcomes.

Acceptance Criteria

• Maintenance records are updated in real-time when maintenance tasks are performed,
• Records include details of maintenance procedures, dates, and outcomes

Gherkin Scenarios

Scenario: Equipment Maintenance Record Keeping
Given that a maintenance task is performed based on predictive maintenance alert
When the maintenance task is completed
Then update the maintenance records in real-time
And ensure records include details of procedures, dates, and outcomes

Requirement: Real-time Equipment Monitoring (Strategic)

Reference: ERPUPGD-260

Implement real-time monitoring of equipment performance to detect anomalies and potential failures proactively. This requirement is crucial for enhancing predictive maintenance optimization within the Manufacturing Process Enhancement functional area.

Acceptance Criteria

• System monitors equipment performance in real-time,
• Anomalies and potential failures are detected and flagged for further analysis

Gherkin Scenarios

Scenario: Real-time equipment monitoring
Given the system is actively monitoring equipment performance
When an anomaly or potential failure is detected
Then the system flags the issue for further analysis
And notifies the maintenance team for immediate action

Requirement: Predictive Maintenance Scheduling (Strategic)

Reference: ERPUPGD-261

Automate the scheduling of maintenance tasks based on predictive analytics to optimize equipment performance and minimize downtime. This requirement aligns with the goal of Predictive Maintenance Optimization for the Digital Transformation and Compliance and Scalability goals.

Acceptance Criteria

• Maintenance tasks are scheduled automatically based on predictive analytics,
• Downtime is minimized due to proactive maintenance scheduling

Gherkin Scenarios

Scenario: Predictive maintenance scheduling
Given the system has predicted an equipment failure
When the maintenance schedule is automatically adjusted
Then the maintenance tasks are scheduled proactively
And downtime is minimized as a result

Requirement: Real-time Sensor Data Integration (Other)

Reference: ERPUPGD-262

Integrate real-time sensor data from manufacturing equipment into the system to enable predictive maintenance alerts and scheduling. This requirement is crucial for leveraging IoT technologies and machine learning algorithms to predict equipment failures.

Acceptance Criteria

• System can receive real-time sensor data,
• Predictive maintenance alerts are triggered based on sensor data analysis

Gherkin Scenarios

Scenario: Real-time sensor data integration
Given that sensor data is being collected in real-time
When the system receives the sensor data
Then the system processes the data for predictive maintenance alerts

Requirement: Automated Maintenance Task Scheduling (Other)

Reference: ERPUPGD-263

Implement automated scheduling of maintenance tasks based on predictive maintenance alerts generated by the system. This requirement ensures timely maintenance to prevent equipment failures and minimize downtime.

Acceptance Criteria

• Maintenance tasks are automatically scheduled based on predictive alerts,
• Maintenance schedule is updated in real-time

Gherkin Scenarios

Scenario: Automated maintenance task scheduling
Given that a predictive maintenance alert is triggered
When the system schedules a maintenance task
Then the maintenance schedule is updated in real-time

Feature: Quality Control Automation

This feature is designed to automate quality control processes by integrating predictive analytics. By continuously monitoring production data and identifying patterns, the system will proactively detect defects, reduce waste, and maintain high product quality standards.

Requirement: Automated Defect Detection (Functional)

Reference: ERPUPGD-264

The system must automatically detect defects in the production process by analyzing real-time data and comparing it against predefined quality standards. This functionality plays a crucial role in improving product quality and reducing waste within the manufacturing process enhancement feature.

Acceptance Criteria

• System detects defects in real-time data,
• System compares data against quality standards,
• Defect detection reduces waste and improves product quality

Gherkin Scenarios

Scenario: Automated Defect Detection
Given the system is monitoring real-time production data
When a defect is detected that does not meet quality standards
Then the system alerts the quality control team
And the defective product is removed from the production line

Requirement: Predictive Maintenance Scheduling (Functional)

Reference: ERPUPGD-265

The system should predict maintenance requirements for manufacturing equipment based on historical data and usage patterns. By proactively scheduling maintenance tasks, the feature aims to minimize downtime, optimize resource allocation, and ensure continuous production efficiency.

Acceptance Criteria

• System predicts maintenance tasks based on historical data,
• Maintenance scheduling minimizes equipment downtime,
• Resource allocation is optimized through proactive maintenance

Gherkin Scenarios

Scenario: Predictive Maintenance Scheduling
Given the system analyzes historical equipment data and usage patterns
When maintenance tasks are predicted for specific equipment
Then the system schedules proactive maintenance
And resources are allocated for the scheduled maintenance tasks

Requirement: Data Security (Non-Functional)

Reference: ERPUPGD-266

Ensure that the Quality Control Automation feature complies with data security standards to protect sensitive production data from unauthorized access or breaches. This requirement is crucial for maintaining the integrity and confidentiality of the manufacturing process data.

Acceptance Criteria

• Quality Control Automation feature encrypts all production data at rest and in transit,
• Access to production data is restricted based on role-based permissions

Gherkin Scenarios

Scenario: Data Security compliance for Quality Control Automation
Given that production data is being processed by the Quality Control Automation feature
When data is stored or transmitted
Then it must be encrypted to protect confidentiality
And access to the data is restricted based on user roles

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-267

Ensure that the Quality Control Automation feature can scale seamlessly to accommodate increased production volumes and data processing requirements. This requirement is essential to support the company's growth and evolving manufacturing needs.

Acceptance Criteria

• Quality Control Automation feature can handle a 20% increase in production data volume without performance degradation,
• System resources scale dynamically based on demand

Gherkin Scenarios

Scenario: Scalability testing for Quality Control Automation
Given that production data volume increases by 20%
When the Quality Control Automation feature is operational
Then it should maintain performance without degradation
And system resources should scale dynamically to meet demand

Requirement: Automated Defect Detection (Business)

Reference: ERPUPGD-268

The system must automatically detect defects in the production process by analyzing real-time production data. This requirement is essential for improving product quality and reducing waste in the manufacturing process.

Acceptance Criteria

• System detects defects in real-time production data,
• Defect detection leads to waste reduction and improved product quality

Gherkin Scenarios

Scenario: Automated Defect Detection
Given the system is monitoring real-time production data
When a defect is detected in the production process
Then the system proactively alerts the quality control team
And the defect is logged for further analysis

Requirement: Predictive Maintenance Alerts (Business)

Reference: ERPUPGD-269

The system should provide predictive maintenance alerts based on machine learning algorithms to prevent equipment failures and minimize downtime. This requirement aligns with the goal of ensuring compliance and scalability by optimizing resource allocation.

Acceptance Criteria

• System generates predictive maintenance alerts based on machine learning algorithms,
• Alerts help prevent equipment failures and minimize downtime

Gherkin Scenarios

Scenario: Predictive Maintenance Alerts
Given the system is monitoring equipment performance
When a potential equipment failure is predicted
Then the system sends a maintenance alert to the maintenance team
And the maintenance team schedules preventive maintenance

Requirement: Real-time Defect Detection Algorithm Integration (Technical)

Reference: ERPUPGD-270

Integrate a real-time defect detection algorithm into the quality control automation feature. This algorithm will continuously analyze production data to identify defects as they occur, enabling proactive quality control measures.

Acceptance Criteria

• Defect detection algorithm successfully integrated into the quality control automation feature,
• Algorithm accurately identifies defects in real-time production data

Gherkin Scenarios

Scenario: Real-time defect detection algorithm integration
Given the defect detection algorithm is integrated into the system
When a defect occurs in the production data
Then the algorithm accurately identifies the defect in real-time

Requirement: Automated Waste Reduction System Implementation (Technical)

Reference: ERPUPGD-271

Implement an automated waste reduction system as part of the quality control automation feature. This system will analyze production data to identify opportunities for waste reduction and implement corrective actions automatically.

Acceptance Criteria

• Automated waste reduction system successfully implemented and operational,
• System identifies and reduces waste in production processes

Gherkin Scenarios

Scenario: Automated waste reduction system implementation
Given the waste reduction system is implemented
When the system analyzes production data
Then the system identifies and reduces waste in production processes

Requirement: Data Privacy Compliance (Legal and Regulatory)

Reference: ERPUPGD-272

Ensure that the Quality Control Automation feature complies with data privacy regulations such as GDPR, HIPAA, and CCPA. This requirement is essential to protect sensitive production data and maintain legal compliance.

Acceptance Criteria

• System encrypts all production data at rest and in transit,
• Access to production data is restricted based on user roles and permissions

Gherkin Scenarios

Scenario: Ensure data privacy compliance
Given that the system processes production data
When data is stored or transmitted
Then the data must be encrypted to meet data privacy regulations
And access to the data is restricted based on user roles

Requirement: Product Quality Standards Compliance (Legal and Regulatory)

Reference: ERPUPGD-273

Ensure that the Quality Control Automation feature maintains compliance with industry quality standards such as ISO 9001. This requirement is critical to uphold product quality and meet customer expectations.

Acceptance Criteria

• System detects and flags any deviations from quality standards,
• Automated alerts are sent to quality control team for immediate action

Gherkin Scenarios

Scenario: Maintain product quality standards compliance
Given that the system monitors production data
When a deviation from quality standards is detected
Then an alert is generated for the quality control team
And immediate action is taken to address the deviation

Requirement: Real-time Defect Detection (Strategic)

Reference: ERPUPGD-274

Implement real-time defect detection using predictive analytics to identify and flag production defects as soon as they occur. This requirement plays a crucial role in automating quality control processes within the Quality Control Automation feature of the Manufacturing Process Enhancement functional area.

Acceptance Criteria

• System detects and flags production defects in real-time,
• Defect identification accuracy rate is above 95%,
• Automated alerts are sent to quality control team upon defect detection

Gherkin Scenarios

Scenario: Real-time defect detection
Given the production process is ongoing
When a defect occurs in the production line
Then the system immediately flags the defect
And alerts the quality control team

Requirement: Waste Reduction Optimization (Strategic)

Reference: ERPUPGD-275

Optimize waste reduction by analyzing production data trends and patterns to minimize material wastage and improve resource efficiency. This requirement aligns with the goal of reducing waste and enhancing resource allocation within the Manufacturing Process Enhancement functional area.

Acceptance Criteria

• Material wastage is reduced by 15% within the first quarter of implementation,
• Resource efficiency improves by 10% based on production data analysis,
• Production costs decrease by optimizing waste reduction strategies

Gherkin Scenarios

Scenario: Waste reduction optimization
Given historical production data is available
When the system analyzes data trends and patterns
Then material wastage is minimized
And resource efficiency improves

Requirement: Real-time Defect Detection (Other)

Reference: ERPUPGD-276

Implement real-time defect detection capability to identify and flag production defects as soon as they occur. This requirement enhances the Quality Control Automation feature by enabling immediate corrective actions to maintain high product quality standards.

Acceptance Criteria

• System detects defects in real-time,
• Defects are flagged for immediate action

Gherkin Scenarios

Scenario: Real-time defect detection
Given the production process is ongoing
When a defect occurs in the production data
Then the system immediately flags the defect for corrective action

Requirement: Automated Quality Alerts (Other)

Reference: ERPUPGD-277

Introduce automated quality alerts to notify relevant stakeholders when quality thresholds are not met. This requirement ensures timely awareness of quality issues and facilitates prompt decision-making to address deviations from quality standards.

Acceptance Criteria

• Automated alerts triggered when quality thresholds are not met,
• Alerts include details on the quality issue

Gherkin Scenarios

Scenario: Automated quality alerts
Given the quality threshold is not met
When the system detects a quality issue
Then automated alerts are sent to relevant stakeholders with detailed information

Feature: Real-time Production Monitoring

The feature will enable real-time monitoring of production processes by leveraging IoT sensors and data analytics. This ensures that production activities are closely monitored, deviations are promptly identified, and corrective actions are taken to optimize efficiency and quality.

Sales Performance Analytics

This functional area aims to implement advanced sales performance analytics within the ERP system using SAP S/4HANA's real-time reporting and visualization tools. By providing personalized dashboards, sales forecasting models, and customer segmentation analysis, this area seeks to improve sales team productivity, customer engagement, and revenue growth. This aligns with the project goal of User Experience (USER) and Digital Transformation (DIGTLXFORM).

Feature: Personalized Sales Dashboards

This feature will enable sales representatives to access personalized dashboards within the ERP system, powered by SAP S/4HANA's real-time reporting capabilities. These dashboards will provide a comprehensive view of individual sales performance metrics, such as revenue generated, deals closed, and customer interactions. By offering tailored insights, this feature ensures that sales teams can make data-driven decisions to enhance productivity and target specific areas for improvement.

Requirement: Access Personalized Sales Dashboards (Functional)

Reference: ERPUPGD-278

Sales representatives must be able to access personalized dashboards within the ERP system to view individual sales performance metrics. This requirement is essential for enabling data-driven decision-making and enhancing productivity.

Acceptance Criteria

• Sales representatives can log in to the ERP system and access their personalized sales dashboard,
• The dashboard displays revenue generated, deals closed, and customer interactions for the sales representative,
• Sales representatives can customize the dashboard layout and metrics displayed

Gherkin Scenarios

Scenario: Sales representative accesses personalized sales dashboard
Given the sales representative is logged into the ERP system
When the sales representative navigates to their personalized dashboard
Then they should see metrics such as revenue generated, deals closed, and customer interactions
And they should be able to customize the dashboard layout and metrics

Requirement: View Sales Forecasting Models (Functional)

Reference: ERPUPGD-279

Sales representatives must have access to sales forecasting models within the ERP system to predict future sales trends and make informed decisions. This requirement supports the goal of improving revenue growth through data-driven insights.

Acceptance Criteria

• Sales representatives can view sales forecasting models within the ERP system,
• The models provide predictions on future sales trends based on historical data and market analysis,
• Sales representatives can adjust parameters and scenarios to simulate different sales outcomes

Gherkin Scenarios

Scenario: Sales representative views sales forecasting models
Given the sales representative is logged into the ERP system
When they navigate to the sales forecasting section
Then they should see predictions on future sales trends
And they should be able to adjust parameters and scenarios for simulations

Requirement: Analyze Customer Segmentation (Functional)

Reference: ERPUPGD-280

Sales representatives must be able to analyze customer segmentation data within the ERP system to identify target customer groups and tailor sales strategies. This requirement facilitates personalized customer engagement and supports revenue growth objectives.

Acceptance Criteria

• Sales representatives can access customer segmentation analysis tools within the ERP system,
• The tools provide insights on customer groups based on demographics, behavior, and purchasing patterns,
• Sales representatives can create targeted marketing campaigns based on segmentation analysis

Gherkin Scenarios

Scenario: Sales representative analyzes customer segmentation data
Given the sales representative is logged into the ERP system
When they access the customer segmentation analysis tools
Then they should see insights on customer groups based on demographics, behavior, and purchasing patterns
And they should be able to create targeted marketing campaigns

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-281

The system must load personalized sales dashboards within 3 seconds to ensure quick access to real-time data for sales representatives, enhancing their decision-making process and productivity.

Acceptance Criteria

• Sales dashboards load within 3 seconds

Gherkin Scenarios

Scenario: Sales representative accesses personalized dashboard
Given the sales representative opens the ERP system
When the sales representative navigates to the personalized dashboard section
Then the personalized sales dashboard loads within 3 seconds

Requirement: Security and Data Privacy (Non-Functional)

Reference: ERPUPGD-282

All data displayed on the personalized sales dashboards must adhere to company security policies and data privacy regulations to ensure the confidentiality and integrity of sales performance metrics and customer interactions.

Acceptance Criteria

• Data displayed on dashboards is encrypted in transit and at rest,
• Access to personalized dashboards is restricted based on user roles

Gherkin Scenarios

Scenario: Data security on personalized sales dashboards
Given the sales representative accesses the personalized dashboard
When data is displayed on the dashboard
Then the data is encrypted in transit and at rest
And access to specific dashboard sections is restricted based on user roles

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-283

The system must support a scalable number of concurrent users accessing personalized sales dashboards without performance degradation, ensuring smooth operations during peak usage periods.

Acceptance Criteria

• System performance remains consistent with 1000 concurrent users accessing dashboards

Gherkin Scenarios

Scenario: Scalability testing for personalized sales dashboards
Given 1000 concurrent users accessing the system
When users navigate to their personalized sales dashboards
Then the system performance remains consistent without degradation

Requirement: Access Personalized Sales Dashboards (Business)

Reference: ERPUPGD-284

Sales representatives must be able to access personalized dashboards within the ERP system to view individual sales performance metrics, including revenue generated, deals closed, and customer interactions. This requirement is essential for enabling data-driven decision-making and enhancing productivity.

Acceptance Criteria

• Sales representatives can log in to the ERP system and access their personalized sales dashboard,
• The dashboard displays revenue generated, deals closed, and customer interactions for the sales representative,
• Sales representatives can interact with the dashboard to view detailed information and insights

Gherkin Scenarios

Scenario: Sales representative accesses personalized sales dashboard
Given the sales representative is logged into the ERP system
When the sales representative navigates to their personalized dashboard
Then they should see metrics such as revenue generated, deals closed, and customer interactions
And they should be able to interact with the dashboard to access detailed information

Requirement: View Sales Forecasting Models (Business)

Reference: ERPUPGD-285

Sales representatives should have access to sales forecasting models within the ERP system to predict future sales trends and opportunities. This requirement is crucial for enabling proactive decision-making and strategic planning.

Acceptance Criteria

• Sales representatives can view sales forecasting models for different time periods,
• The forecasting models provide insights into future sales trends and opportunities,
• Sales representatives can adjust parameters and scenarios in the forecasting models

Gherkin Scenarios

Scenario: Sales representative views sales forecasting models
Given the sales representative has access to the ERP system
When they navigate to the sales forecasting section
Then they should see models for different time periods with insights into future sales trends
And they should be able to adjust parameters and scenarios in the models

Requirement: Utilize Customer Segmentation Analysis (Business)

Reference: ERPUPGD-286

Sales representatives must be able to utilize customer segmentation analysis tools within the ERP system to identify customer segments based on various criteria. This requirement is essential for targeting specific customer groups effectively and improving customer engagement.

Acceptance Criteria

• Sales representatives can access customer segmentation analysis tools,
• The tools allow segmentation based on criteria such as demographics, purchasing behavior, and engagement level,
• Sales representatives can generate reports and insights from the segmentation analysis

Gherkin Scenarios

Scenario: Sales representative utilizes customer segmentation analysis
Given the sales representative has access to the ERP system
When they navigate to the customer segmentation analysis tools
Then they should be able to segment customers based on demographics, purchasing behavior, and engagement level
And they should be able to generate reports and insights from the segmentation analysis

Requirement: Real-time Data Integration (Technical)

Reference: ERPUPGD-287

Enable real-time data integration between the ERP system and SAP S/4HANA for up-to-date sales performance metrics on the personalized dashboards. This requirement ensures that sales representatives have access to the most current data for informed decision-making.

Acceptance Criteria

• System updates sales data in real-time,
• Sales representatives can view real-time data on their personalized dashboards

Gherkin Scenarios

Scenario: Real-time data integration
Given the ERP system generates new sales data
When the data is synchronized with SAP S/4HANA in real-time
Then sales representatives can view the updated data on their personalized dashboards

Requirement: Data Security Measures (Technical)

Reference: ERPUPGD-288

Implement robust data security measures to protect sensitive sales performance data displayed on the personalized dashboards. This requirement ensures that only authorized users can access and view the sales metrics.

Acceptance Criteria

• Data encryption for secure transmission,
• Role-based access control for personalized dashboard viewing

Gherkin Scenarios

Scenario: Data security measures
Given sensitive sales data is displayed on the personalized dashboards
When data is encrypted during transmission and stored securely
Then only authorized users with the appropriate roles can access and view the data

Requirement: Dashboard Customization Options (Technical)

Reference: ERPUPGD-289

Provide customization options for sales representatives to personalize their dashboards based on their specific preferences and key performance indicators. This requirement enhances user experience and allows for tailored insights.

Acceptance Criteria

• Ability to add/remove widgets on the dashboard,
• Customizable data visualization settings

Gherkin Scenarios

Scenario: Dashboard customization options
Given a sales representative accesses their personalized dashboard
When they can add or remove widgets based on their preferences
Then the dashboard reflects the customized layout and data visualization settings

Requirement: Data Privacy Compliance (Legal and Regulatory)

Reference: ERPUPGD-290

Ensure that the Personalized Sales Dashboards feature complies with all data privacy regulations, such as GDPR, CCPA, and any industry-specific requirements. This requirement is crucial to protect customer data and avoid legal repercussions.

Acceptance Criteria

• Sales representatives can only access data relevant to their role and permissions,
• Customer data is encrypted both in transit and at rest

Gherkin Scenarios

Scenario: Sales representative accesses personalized dashboard data
Given the sales representative is logged into the ERP system
When the sales representative accesses the personalized dashboard
Then only data relevant to the sales representative's role and permissions is displayed
And the data is encrypted for security

Requirement: Audit Trail Compliance (Legal and Regulatory)

Reference: ERPUPGD-291

Implement an audit trail mechanism within the Personalized Sales Dashboards feature to track all user interactions and changes made to the data. This requirement ensures transparency, accountability, and compliance with auditing standards.

Acceptance Criteria

• All user interactions within the dashboard are logged and timestamped,
• Changes to data are recorded with details of the user making the change

Gherkin Scenarios

Scenario: User interacts with the personalized sales dashboard
Given the user is viewing the personalized sales dashboard
When the user performs an action or makes a change
Then the system logs the action with a timestamp
And records the user responsible for the action

Requirement: Real-time Sales Data Visualization (Strategic)

Reference: ERPUPGD-292

Enable real-time visualization of sales data within the personalized sales dashboards. This requirement ensures that sales representatives have access to up-to-date information on revenue trends, customer interactions, and deal statuses, empowering them to make informed decisions promptly.

Acceptance Criteria

• Sales data is updated in real-time on the dashboards,
• Interactive charts and graphs display key sales metrics,
• Users can drill down into specific data points for detailed analysis

Gherkin Scenarios

Scenario: Sales data visualization is real-time
Given the sales representative accesses the personalized dashboard
When new sales data is entered into the system
Then the dashboard updates immediately with the latest information

Requirement: Performance Metrics Tracking (Strategic)

Reference: ERPUPGD-293

Implement tracking mechanisms for key performance metrics on the personalized sales dashboards. This requirement ensures that sales representatives can monitor their progress towards sales targets, identify areas of improvement, and track their individual performance over time.

Acceptance Criteria

• Sales targets are clearly defined and visible on the dashboards,
• Performance metrics include revenue generated, deals closed, and customer interactions,
• Users receive notifications when performance targets are met or exceeded

Gherkin Scenarios

Scenario: Performance metrics are tracked on the dashboard
Given the sales representative views their personalized dashboard
When the sales representative closes a deal or generates revenue
Then the corresponding metrics are updated in real-time on the dashboard

Requirement: Data Visualization Requirements (Other)

Reference: ERPUPGD-294

This requirement involves implementing data visualization features within the personalized sales dashboards. The data visualization tools should allow sales representatives to easily interpret and analyze sales performance metrics through interactive charts, graphs, and visual representations. By incorporating intuitive and informative visualizations, users can quickly identify trends, patterns, and outliers in their sales data.

Acceptance Criteria

• Sales representatives can view sales performance metrics through interactive charts and graphs,
• Data visualization tools provide clear and informative representations of sales data

Gherkin Scenarios

Scenario: Sales representatives view sales performance metrics through data visualization
Given the sales representative accesses the personalized sales dashboard
When the representative selects the data visualization feature
Then interactive charts and graphs displaying sales performance metrics are displayed
And the visual representations are clear and informative

Requirement: Customization Options (Other)

Reference: ERPUPGD-295

This requirement focuses on providing customization options for the personalized sales dashboards. Sales representatives should be able to personalize their dashboard layout, choose specific metrics to display, and set preferences for data visualization styles. By offering customization features, users can tailor their dashboard to suit their individual needs and preferences, enhancing usability and user satisfaction.

Acceptance Criteria

• Sales representatives can customize the layout of their personalized dashboard,
• Users can select specific sales performance metrics to display on the dashboard,
• Customization options include setting preferences for data visualization styles

Gherkin Scenarios

Scenario: Sales representative customizes their personalized sales dashboard
Given the sales representative accesses the personalized sales dashboard
When the representative selects the customization options
Then the layout of the dashboard can be personalized
And specific sales performance metrics can be selected for display
And preferences for data visualization styles can be set

Feature: Sales Forecasting Models

This feature is designed to implement advanced sales forecasting models within the ERP system, leveraging SAP S/4HANA's predictive analytics capabilities. By analyzing historical sales data, market trends, and customer behavior, these models will provide accurate predictions of future sales performance. Sales teams can use this feature to anticipate demand, optimize inventory levels, and develop targeted sales strategies to drive revenue growth.

Requirement: Generate Sales Forecasting Report (Functional)

Reference: ERPUPGD-296

The system must allow users to generate a detailed sales forecasting report based on historical sales data, market trends, and customer behavior. This report will provide insights into future sales performance, enabling sales teams to make informed decisions.

Acceptance Criteria

• Users can generate a sales forecasting report,
• Report includes historical sales data, market trends, and customer behavior analysis

Gherkin Scenarios

Scenario: Generate Sales Forecasting Report
Given the user has access to the sales forecasting feature
When the user selects to generate a sales forecasting report
Then the system compiles historical sales data, market trends, and customer behavior analysis
And presents the sales forecasting report to the user

Requirement: Customize Sales Forecasting Model Parameters (Functional)

Reference: ERPUPGD-297

Users should be able to customize parameters of the sales forecasting models to tailor predictions according to specific business needs. This customization feature enhances the accuracy and relevance of the sales forecasting models.

Acceptance Criteria

• Users can adjust parameters of the sales forecasting models,
• Changes in parameters reflect in updated sales predictions

Gherkin Scenarios

Scenario: Customize Sales Forecasting Model Parameters
Given the user has access to the sales forecasting customization feature
When the user modifies parameters of the sales forecasting model
Then the system recalculates sales predictions based on the new parameters
And displays updated sales forecasts to the user

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-298

The system must generate sales forecasting models within 5 seconds to ensure real-time decision-making and responsiveness for sales teams.

Acceptance Criteria

• Sales forecasting models are generated within 5 seconds of request.

Gherkin Scenarios

Scenario: Generate sales forecasting model efficiently
Given the sales forecasting model request is initiated
When the system processes the request
Then the sales forecasting model is generated within 5 seconds

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-299

The system must support a minimum of 1000 concurrent users accessing the sales forecasting models without performance degradation.

Acceptance Criteria

• System supports 1000 concurrent users accessing sales forecasting models without performance degradation.

Gherkin Scenarios

Scenario: Test system scalability with concurrent users
Given 1000 users are accessing sales forecasting models simultaneously
When the system is under load
Then the system supports all users without performance degradation

Requirement: Data Security (Non-Functional)

Reference: ERPUPGD-300

The system must encrypt all sales forecasting model data at rest and in transit to ensure the confidentiality and integrity of sensitive sales data.

Acceptance Criteria

• Sales forecasting model data is encrypted at rest and in transit.

Gherkin Scenarios

Scenario: Ensure data security of sales forecasting models
Given the sales forecasting model data is stored or transmitted
When the system processes the data
Then the data is encrypted to maintain confidentiality and integrity

Requirement: Define Sales Forecasting Requirements (Business)

Reference: ERPUPGD-301

Define the specific requirements for the sales forecasting models to be implemented within the ERP system. These requirements will outline the data sources, algorithms, and key performance indicators (KPIs) to be used in generating accurate sales predictions.

Acceptance Criteria

• Sales forecasting requirements document is created with input from sales, marketing, and finance teams,
• Data sources for historical sales data, market trends, and customer behavior are identified and integrated into the forecasting models,
• Algorithms for predictive analytics are selected and configured to generate accurate sales predictions,
• Key performance indicators (KPIs) for evaluating the accuracy and effectiveness of the forecasting models are defined

Gherkin Scenarios

Scenario: Define Sales Forecasting Requirements
Given that input is gathered from sales, marketing, and finance teams
When data sources are identified and integrated into the forecasting models
Then algorithms are selected and configured for accurate predictions
And key performance indicators (KPIs) are defined for evaluation

Requirement: Implement Sales Forecasting Dashboard (Business)

Reference: ERPUPGD-302

Implement a user-friendly dashboard within the ERP system that displays the sales forecasting results generated by the predictive analytics models. The dashboard should provide real-time insights into sales performance, trends, and predictions to enable informed decision-making by the sales team.

Acceptance Criteria

• Sales forecasting dashboard is designed with input from sales and marketing teams,
• Dashboard displays accurate sales predictions based on historical data and market trends,
• Real-time updates are enabled to reflect the latest sales performance metrics,
• User interface is intuitive and customizable for different user roles

Gherkin Scenarios

Scenario: Implement Sales Forecasting Dashboard
Given that input is gathered from sales and marketing teams for dashboard design
When accurate sales predictions are displayed based on historical data and market trends
Then real-time updates are enabled for latest metrics
And user interface is intuitive and customizable

Requirement: Integration with SAP S/4HANA Predictive Analytics (Technical)

Reference: ERPUPGD-303

This requirement involves integrating the sales forecasting models feature with SAP S/4HANA's predictive analytics capabilities. The integration will enable the feature to leverage historical sales data, market trends, and customer behavior for accurate sales predictions.

Acceptance Criteria

• Sales forecasting models are successfully integrated with SAP S/4HANA predictive analytics,
• Historical sales data, market trends, and customer behavior are utilized for accurate sales predictions

Gherkin Scenarios

Scenario: Integration with SAP S/4HANA Predictive Analytics
Given the sales forecasting models feature is active
When historical sales data, market trends, and customer behavior are inputted into SAP S/4HANA predictive analytics
Then accurate sales predictions are generated
And the sales team can access the forecasts for decision-making

Requirement: Real-time Data Visualization (Technical)

Reference: ERPUPGD-304

This requirement involves implementing real-time data visualization capabilities within the sales forecasting models feature. It allows sales teams to view up-to-date sales performance metrics and trends for informed decision-making.

Acceptance Criteria

• Real-time data visualization is successfully integrated with the sales forecasting models feature,
• Sales performance metrics and trends are displayed in real-time

Gherkin Scenarios

Scenario: Real-time Data Visualization
Given the sales forecasting models feature is active
When real-time sales performance metrics and trends are visualized
Then the sales team can make informed decisions based on up-to-date data

Requirement: Compliance with Data Privacy Regulations (Legal and Regulatory)

Reference: ERPUPGD-305

Ensure that the sales forecasting models comply with all relevant data privacy regulations such as GDPR, CCPA, and any industry-specific regulations. This requirement is crucial to protect customer data and maintain legal compliance within the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Sales forecasting models adhere to GDPR, CCPA, and industry-specific data privacy regulations

Gherkin Scenarios

Scenario: Ensure compliance with data privacy regulations
Given that the sales forecasting models are being developed
When the models are reviewed for compliance with GDPR, CCPA, and industry-specific regulations
Then the models must meet all requirements to protect customer data and ensure legal compliance

Requirement: Accuracy and Transparency in Sales Forecasting (Legal and Regulatory)

Reference: ERPUPGD-306

Mandate that the sales forecasting models provide accurate predictions based on historical sales data, market trends, and customer behavior. Transparency in the forecasting process is essential to ensure that sales teams make informed decisions and avoid misleading information.

Acceptance Criteria

• Sales forecasting models provide accurate predictions based on historical data and market trends,
• Forecasting process is transparent and easily understandable for sales teams

Gherkin Scenarios

Scenario: Ensure accuracy and transparency in sales forecasting
Given the historical sales data, market trends, and customer behavior data are available
When the sales forecasting models generate predictions
Then the predictions must align with actual sales performance
And the forecasting process must be transparent and easily interpretable by sales teams

Requirement: Sales Forecasting Accuracy (Strategic)

Reference: ERPUPGD-307

The sales forecasting models must achieve a minimum accuracy rate of 90% in predicting future sales performance. This requirement is crucial for enabling sales teams to make informed decisions based on reliable forecasts, optimizing inventory levels, and maximizing revenue growth within the Sales Forecasting Models feature of the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Sales forecasting models achieve a minimum accuracy rate of 90% in predicting future sales performance

Gherkin Scenarios

Scenario: Validate Sales Forecasting Accuracy
Given historical sales data, market trends, and customer behavior are analyzed
When the sales forecasting models predict future sales performance
Then the accuracy rate is calculated and must be at least 90%

Requirement: Real-time Data Integration (Strategic)

Reference: ERPUPGD-308

The sales forecasting models must integrate real-time data feeds from external sources, such as market data providers and customer relationship management systems, to ensure that the predictions are based on the most up-to-date information available. This requirement is essential for enhancing the accuracy and relevance of the forecasts, enabling sales teams to react promptly to changing market conditions and customer behaviors.

Acceptance Criteria

• Sales forecasting models integrate real-time data feeds from external sources

Gherkin Scenarios

Scenario: Validate Real-time Data Integration
Given external data feeds from market data providers and CRM systems are available
When the sales forecasting models are updated with real-time data
Then the predictions reflect the most current information

Requirement: Data Source Integration (Other)

Reference: ERPUPGD-309

The system must support integration with multiple data sources to gather historical sales data for the sales forecasting models. This requirement is essential for ensuring the accuracy and reliability of the predictions generated by the models.

Acceptance Criteria

• System can integrate with at least three different data sources,
• Historical sales data from all integrated sources is successfully imported and processed for analysis

Gherkin Scenarios

Scenario: Data Source Integration
Given the system has access to multiple data sources
When the system integrates with the data sources
Then historical sales data from all sources is successfully imported and processed

Requirement: Model Training Automation (Other)

Reference: ERPUPGD-310

Automate the process of training the sales forecasting models using machine learning algorithms. This requirement aims to streamline the model training process, reduce manual intervention, and ensure the models are always up-to-date with the latest data.

Acceptance Criteria

• Model training process is automated and scheduled to run daily,
• Model accuracy is monitored regularly to ensure optimal performance

Gherkin Scenarios

Scenario: Model Training Automation
Given the sales forecasting models are in place
When the system automatically trains the models daily
Then model accuracy is monitored and maintained

Requirement: Scenario Analysis (Other)

Reference: ERPUPGD-311

Enable scenario analysis capabilities within the sales forecasting models to simulate various business scenarios and assess their impact on future sales performance. This requirement empowers sales teams to make informed decisions based on different what-if scenarios.

Acceptance Criteria

• Users can create and run different business scenarios within the models,
• Impact of each scenario on sales performance is clearly visualized and analyzed

Gherkin Scenarios

Scenario: Scenario Analysis
Given the sales forecasting models are operational
When users create and run different business scenarios
Then the impact of each scenario on sales performance is visualized and analyzed

Feature: Customer Segmentation Analysis

This feature will enable sales teams to conduct customer segmentation analysis using SAP S/4HANA's advanced data analytics tools. By categorizing customers based on demographics, purchasing behavior, and preferences, this feature aims to identify high-value segments, personalize marketing strategies, and improve customer engagement. Through targeted communication and tailored offerings, sales representatives can enhance customer relationships and drive sales performance.

Requirement: Customer Segmentation Criteria Definition (Functional)

Reference: ERPUPGD-312

Sales teams must be able to define customer segmentation criteria based on demographics, purchasing behavior, and preferences to categorize customers effectively for targeted marketing strategies and personalized offerings.

Acceptance Criteria

• Sales teams can input demographic data for customer segmentation,
• Sales teams can input purchasing behavior data for customer segmentation,
• Sales teams can input preference data for customer segmentation

Gherkin Scenarios

Scenario: Sales team defines customer segmentation criteria
Given the sales team has access to demographic data, purchasing behavior data, and preference data
When the sales team inputs the demographic, purchasing behavior, and preference data for customer segmentation
Then the customers are categorized based on the defined criteria

Requirement: Customer Segment Analysis Report Generation (Functional)

Reference: ERPUPGD-313

The system must generate detailed reports on customer segments identified through the analysis, providing insights on high-value segments, marketing strategies, and customer engagement opportunities.

Acceptance Criteria

• System generates reports on high-value customer segments,
• Reports include marketing strategies tailored to each segment,
• Insights on customer engagement opportunities are provided in the reports

Gherkin Scenarios

Scenario: System generates customer segment analysis report
Given the system has identified high-value customer segments
When the system generates reports on marketing strategies for each segment
Then the reports include insights on customer engagement opportunities

Requirement: Performance Efficiency (Non-Functional)

Reference: ERPUPGD-314

The system must perform customer segmentation analysis within 5 seconds to ensure real-time insights for sales teams. This requirement is crucial for enabling quick decision-making and enhancing sales team productivity.

Acceptance Criteria

• Customer segmentation analysis completes within 5 seconds

Gherkin Scenarios

Scenario: Perform customer segmentation analysis within 5 seconds
Given the system is running
When a sales representative initiates customer segmentation analysis
Then the analysis completes within 5 seconds

Requirement: Scalability (Non-Functional)

Reference: ERPUPGD-315

The system must support a minimum of 100,000 customer records for segmentation analysis to accommodate the growing customer base. This requirement ensures that the feature can handle increased data volume without performance degradation.

Acceptance Criteria

• System can handle segmentation analysis for 100,000 customer records

Gherkin Scenarios

Scenario: System handles segmentation analysis for 100,000 customer records
Given the system has 100,000 customer records for analysis
When a sales representative initiates customer segmentation analysis
Then the system successfully processes the analysis

Requirement: Data Security (Non-Functional)

Reference: ERPUPGD-316

Customer data used for segmentation analysis must be encrypted both in transit and at rest to ensure compliance with data protection regulations and safeguard sensitive information. This requirement is essential for maintaining customer trust and meeting legal requirements.

Acceptance Criteria

• Customer data is encrypted in transit and at rest

Gherkin Scenarios

Scenario: Ensure customer data encryption for segmentation analysis
Given customer data is being used for segmentation analysis
When the data is transmitted or stored
Then the data is encrypted to protect confidentiality

Requirement: Identify High-Value Customer Segments (Business)

Reference: ERPUPGD-317

Sales teams must be able to identify high-value customer segments based on demographics, purchasing behavior, and preferences. This requirement is essential for improving targeted marketing strategies and enhancing customer engagement within the Customer Segmentation Analysis feature of the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Sales teams can categorize customers into high-value segments based on demographics, purchasing behavior, and preferences,
• High-value customer segments are clearly defined and distinguishable from other segments

Gherkin Scenarios

Scenario: Sales team identifies high-value customer segments
Given that sales teams have access to customer data and analytics tools
When the sales team categorizes customers based on demographics, purchasing behavior, and preferences
Then high-value customer segments are identified
And these segments are clearly defined and distinguishable

Requirement: Personalize Marketing Strategies (Business)

Reference: ERPUPGD-318

Sales representatives should be able to personalize marketing strategies for different customer segments identified through the Customer Segmentation Analysis feature. This requirement is crucial for enhancing customer relationships and driving sales performance within the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Sales representatives can create personalized marketing strategies for each identified customer segment,
• Marketing strategies are tailored to the specific preferences and behaviors of each segment

Gherkin Scenarios

Scenario: Sales representative personalizes marketing strategies
Given that sales representatives have access to customer segment data
When sales representatives create marketing strategies for each identified segment
Then marketing strategies are personalized to match the preferences and behaviors of each segment

Requirement: Customer Segmentation Algorithm Integration (Technical)

Reference: ERPUPGD-319

Integrate a customer segmentation algorithm within the SAP S/4HANA system to automate the process of categorizing customers based on demographics, purchasing behavior, and preferences. This integration will enhance the efficiency and accuracy of customer segmentation analysis, enabling sales teams to identify high-value segments effectively.

Acceptance Criteria

• Customer segmentation algorithm is successfully integrated within the SAP S/4HANA system,
• Algorithm categorizes customers based on demographics, purchasing behavior, and preferences accurately

Gherkin Scenarios

Scenario: Customer segmentation algorithm integration
Given the customer segmentation algorithm is developed
When the algorithm is integrated within the SAP S/4HANA system
Then the system categorizes customers accurately based on demographics, purchasing behavior, and preferences

Requirement: Real-time Data Processing (Technical)

Reference: ERPUPGD-320

Implement real-time data processing capabilities to ensure that customer data used for segmentation analysis is up-to-date and accurate. This feature will enable sales teams to make informed decisions based on the most recent customer information.

Acceptance Criteria

• System processes customer data in real-time,
• Customer segmentation analysis reflects the most recent data

Gherkin Scenarios

Scenario: Real-time data processing for customer segmentation
Given the system receives customer data updates in real-time
When the segmentation analysis is performed
Then the analysis reflects the most recent customer data

Requirement: GDPR Compliance for Customer Data (Legal and Regulatory)

Reference: ERPUPGD-321

Ensure that the customer segmentation analysis feature complies with the General Data Protection Regulation (GDPR) requirements to protect customer data privacy and security. This requirement is crucial for maintaining legal compliance and safeguarding customer information within the ERP system.

Acceptance Criteria

• Customer data is encrypted at rest and in transit,
• Customers have the ability to opt-out of data collection and processing,
• Regular audits are conducted to ensure GDPR compliance

Gherkin Scenarios

Scenario: Ensure GDPR Compliance for Customer Data
Given that customer data is being processed for segmentation analysis
When customer data is stored in the ERP system
Then ensure that the data is encrypted and secure
And provide customers with the option to opt-out of data processing

Requirement: Data Retention Policy Compliance (Legal and Regulatory)

Reference: ERPUPGD-322

Implement a data retention policy that aligns with industry regulations and legal requirements for storing customer segmentation data. This requirement ensures that data is retained for the necessary period and securely disposed of when no longer needed, reducing compliance risks and data security vulnerabilities.

Acceptance Criteria

• Define data retention periods for customer segmentation data,
• Automate data deletion processes based on retention policies,
• Maintain audit logs of data retention and disposal actions

Gherkin Scenarios

Scenario: Data Retention Policy Compliance for Customer Segmentation Data
Given that customer segmentation data is stored in the ERP system
When data retention policies are defined and implemented
Then automate data deletion based on retention periods
And maintain audit logs of data retention and disposal actions

Requirement: Customer Segmentation Criteria Definition (Strategic)

Reference: ERPUPGD-323

Define clear criteria for customer segmentation based on demographics, purchasing behavior, and preferences. This requirement is crucial for accurately categorizing customers into high-value segments and personalizing marketing strategies within the Customer Segmentation Analysis feature of the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Clear criteria for customer segmentation defined based on demographics, purchasing behavior, and preferences

Gherkin Scenarios

Scenario: Define Customer Segmentation Criteria
Given the sales team has access to demographic, purchasing behavior, and preference data
When the team defines clear criteria for customer segmentation
Then the criteria are established for categorizing customers into segments

Requirement: Segment-Specific Marketing Strategy Development (Strategic)

Reference: ERPUPGD-324

Develop segment-specific marketing strategies based on the identified high-value customer segments. This requirement aims to tailor marketing efforts towards different customer segments to enhance customer engagement and drive sales performance within the Customer Segmentation Analysis feature of the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Segment-specific marketing strategies developed for high-value customer segments

Gherkin Scenarios

Scenario: Develop Segment-Specific Marketing Strategies
Given the high-value customer segments are identified
When segment-specific marketing strategies are developed for each segment
Then marketing efforts are tailored towards enhancing customer engagement and driving sales performance

Requirement: Data Privacy Compliance (Other)

Reference: ERPUPGD-325

Ensure that the customer segmentation analysis feature complies with all data privacy regulations and policies, such as GDPR and CCPA. This requirement is crucial to protect customer data and maintain legal compliance within the Sales Performance Analytics Functional Area.

Acceptance Criteria

• Customer data is securely stored and encrypted,
• Access to customer data is restricted based on role permissions,
• Customers have the option to opt-out of data collection and analysis

Gherkin Scenarios

Scenario: Data privacy compliance for customer segmentation analysis
Given that customer data is being processed for segmentation analysis
When customer data is stored in the system
Then customer data is encrypted and access is restricted based on permissions
And customers have the option to opt-out of data processing

Requirement: Training and Adoption Plan (Other)

Reference: ERPUPGD-326

Develop a comprehensive training and adoption plan for sales teams to effectively utilize the customer segmentation analysis feature. This plan should include training sessions, user guides, and ongoing support to ensure successful implementation and utilization of the feature.

Acceptance Criteria

• Training sessions scheduled and conducted for all sales team members,
• User guides and documentation provided for reference,
• Ongoing support available for troubleshooting and questions

Gherkin Scenarios

Scenario: Training and adoption plan for customer segmentation analysis
Given that the customer segmentation analysis feature is implemented in the system
When training sessions are scheduled and conducted for sales team members
Then user guides and documentation are provided for reference
And ongoing support is available for troubleshooting and questions

Project Charter: ERP System Upgrade

Description: The company's current ERP system, which is critical for managing and integrating various business processes, is running on an outdated version and technology stack. This project aims to upgrade the existing ERP system to the latest version of SAP S/4HANA, a modern and intelligent ERP solution designed for the digital age.

The project will involve a comprehensive assessment of the existing ERP system, data migration, system configuration, integration with other systems, user training, and a well-planned deployment strategy to minimize disruption to ongoing business operations.

Successful completion of this project will position the company for long-term competitiveness by leveraging the latest ERP technology, optimizing business processes, and enabling data-driven decision-making capabilities.

Project Goals

• Process Optimization: Leverage the enhanced features and capabilities of SAP S/4HANA to streamline and optimize business processes across various functional areas, such as finance, supply chain, procurement, manufacturing, and sales. (Reference: PRCS)
• User Experience: Enhance the user experience by adopting SAP S/4HANA's modern and intuitive user interface, which supports mobile devices and provides personalized dashboards and visualization tools. (Reference: USER)
• Technology Modernization: Migrate the ERP system to SAP S/4HANA, which is built on the advanced in-memory database SAP HANA, enabling real-time data processing, advanced analytics, and faster transaction processing. (Reference: TECH)
• Digital Transformation: Embrace digital transformation by leveraging SAP S/4HANA's integration with cutting-edge technologies like the Internet of Things (IoT), machine learning, and predictive analytics, enabling data-driven decision-making and intelligent automation. (Reference: DIGTLXFORM)
• Compliance and Scalability: Ensure compliance with evolving regulatory requirements and industry standards while providing a scalable and future-proof platform to support the company's growth and changing business needs. (Reference: COMPL)

Project Objectives

• Budget: $2,285,000.00
• Current State: The current ERP system is outdated and does not support recent business process changes.
• Target Architecture: SAP S/4HANA
• Key Policies: The upgrade must ensure business continuity and data integrity.
• Restrictions: The system downtime during the upgrade must be minimized.

Company Information

Company Name: Vertex Dynamics

Industry: Sales and Distrbution

Website: www.vertexdynamicsinc.com

Description: Vertex Dynamics is an industry leader in the distribution of high-quality electronics and consumer goods, leveraging an advanced ERP system to streamline its sales and warehouse operations. Our integrated approach ensures that every aspect of the business, from order processing to inventory control, operates at peak efficiency. With a strong online presence and a commitment to customer satisfaction, Vertex Dynamics offers a reliable supply chain solution and exceptional service, solidifying our reputation as a trusted partner in the global market.

Functional Areas Overview

The project is structured into several functional areas, each containing specific features aimed at enhancing the capabilities and efficiency of the ERP system. Below is an overview of these key functional areas and their respective features:

Finance Process Optimization

• Feature: Real-time Financial Reporting - This feature will enable real-time financial reporting by leveraging the advanced capabilities of SAP S/4HANA. It is designed to provide up-to-date and accurate financial data for informed decision-making and improved financial transparency. This feature aligns with the Process Optimization (PRCS) and Technology Modernization (TECH) goals.
• Feature: Automated Invoice Processing - This feature is designed to automate the invoice processing workflow within the ERP system using SAP S/4HANA. By automating this process, it ensures that invoices are processed efficiently, reducing manual errors and improving overall process efficiency. This feature supports the Process Optimization (PRCS) goal.
• Feature: Predictive Financial Analytics - This feature will leverage advanced analytics capabilities of SAP S/4HANA to provide predictive financial analytics. By analyzing historical data and trends, it is designed to forecast financial outcomes and identify potential risks or opportunities. This feature aligns with the Process Optimization (PRCS) and Technology Modernization (TECH) goals.

Supply Chain Automation

• Feature: Real-Time Inventory Tracking - This feature will enable real-time tracking of inventory levels within the ERP system, providing up-to-date information on stock availability, locations, and movement. By integrating with SAP S/4HANA's advanced functionalities, this feature ensures that inventory data is accurate and accessible, supporting efficient supply chain operations.
• Feature: Demand Forecasting - This feature is designed to leverage historical data and predictive analytics to forecast demand for products accurately. By utilizing SAP S/4HANA's forecasting capabilities, this feature helps in optimizing inventory levels, reducing stockouts, and improving overall supply chain efficiency.
• Feature: Automated Order Processing - This feature will automate the order processing workflow within the ERP system, from order creation to fulfillment. By integrating with SAP S/4HANA's automation tools, this feature streamlines the customer order process, reduces manual intervention, and enhances order accuracy and speed.

Manufacturing Process Enhancement

• Feature: Predictive Maintenance Optimization - This feature will utilize machine learning algorithms and IoT technologies to predict equipment failures before they occur. By analyzing real-time data from sensors, the system will automatically schedule maintenance tasks, ensuring optimal equipment performance and minimizing downtime.
• Feature: Quality Control Automation - This feature is designed to automate quality control processes by integrating predictive analytics. By continuously monitoring production data and identifying patterns, the system will proactively detect defects, reduce waste, and maintain high product quality standards.
• Feature: Real-time Production Monitoring - The feature will enable real-time monitoring of production processes by leveraging IoT sensors and data analytics. This ensures that production activities are closely monitored, deviations are promptly identified, and corrective actions are taken to optimize efficiency and quality.

Sales Performance Analytics

• Feature: Personalized Sales Dashboards - This feature will enable sales representatives to access personalized dashboards within the ERP system, powered by SAP S/4HANA's real-time reporting capabilities. These dashboards will provide a comprehensive view of individual sales performance metrics, such as revenue generated, deals closed, and customer interactions. By offering tailored insights, this feature ensures that sales teams can make data-driven decisions to enhance productivity and target specific areas for improvement.
• Feature: Sales Forecasting Models - This feature is designed to implement advanced sales forecasting models within the ERP system, leveraging SAP S/4HANA's predictive analytics capabilities. By analyzing historical sales data, market trends, and customer behavior, these models will provide accurate predictions of future sales performance. Sales teams can use this feature to anticipate demand, optimize inventory levels, and develop targeted sales strategies to drive revenue growth.
• Feature: Customer Segmentation Analysis - This feature will enable sales teams to conduct customer segmentation analysis using SAP S/4HANA's advanced data analytics tools. By categorizing customers based on demographics, purchasing behavior, and preferences, this feature aims to identify high-value segments, personalize marketing strategies, and improve customer engagement. Through targeted communication and tailored offerings, sales representatives can enhance customer relationships and drive sales performance.

Business Processes Overview

The project involves several critical business processes, detailed below with workflow diagrams and descriptions:

Customer Order Process

Description: The workflow diagram depicts the process of creating a customer order. It begins with a sales representative opening the order creation module. If the customer is not in the system, a new customer record is created. Otherwise, the existing customer is selected. Products are added to the order, which the system then checks for inventory availability. If any items are out of stock, the sales rep is notified, and the products are either backordered or the customer's order is revised and out-of-stock items are ordered. Any applicable discounts are applied before the order is reviewed with the customer. If the customer approves, the order is processed; if not, it is cancelled. The workflow ends after processing or cancelling the order. Areas for optimization may include streamlining inventory checks and automating discount application to reduce manual steps for the sales representative.Roles Involved: Sales Representative, SystemInputs: Customer Information, Products to be ordered, Inventory AvailabilityOutputs: Customer Record, Order Confirmation, Notification of Out-of-Stock Items, Processed Order or CancellationDiagram:

Inventory Management

Description: The workflow diagram describes the inventory management process in a warehouse setting, handled by a Warehouse Worker and facilitated by an ERP system. The process begins with the receipt of stock, followed by the creation of a stock receipt in the ERP system. Stock is then moved, requiring a transfer ticket to be created in the ERP system. Physical inventory counting is performed periodically, which leads to an inventory review. The ERP system plays a critical role in updating inventory levels and locations, and in comparing physical counts with records to generate discrepancy reports. If discrepancies are found, they are reviewed and investigated, potentially leading to a recount of items with discrepancies. Based on the investigation's outcome, the ERP system updates are finalized, and a management report is generated. This workflow highlights the integration between manual processes and automated systems, and suggests an area for optimization in automating the initial receiving and stock movement documentation to reduce manual entry errors and improve efficiency.Roles Involved: Warehouse Worker, ERP SystemInputs: Stock, Shipment, Stock Transfer Ticket, Physical Inventory CountsOutputs: Stock Receipt, Updated Inventory Levels, Updated Inventory Locations, Discrepancy Report, Management ReportDiagram:

Procurement and Purchasing

Description: The workflow diagram represents the process of managing purchase requisitions (PR) and purchase orders (PO) within an ERP system, involving decision-making by a Buyer role. Initially, the ERP system triggers a purchase request when a product reaches its re-order point. For standard vendors, the ERP automatically generates a PO. The Buyer reviews the PR, and based on the authorization decision, the PO can either proceed as is, be modified for manual orders, or be canceled. If the PR is authorized for a standard order and no modifications are needed, the ERP sends the PO directly to vendors. If the PR requires a manual order, the Buyer creates a PO based on PR data. The workflow ends once the PO is sent to vendors or canceled.Roles Involved: ERP System, BuyerInputs: Requisitions, Re-order point notification, Purchase request, Purchase Order data, Buyer review and authorization decisionsOutputs: Purchase Order to vendors, Decision on Purchase Order executionDiagram:

Logistics

Description: The workflow diagram illustrates the process of picking and shipping an order in a distribution center. The process starts with the ERP system generating a pick list for the order, which prompts a Warehouse Worker to pick the items, deliver them to the shipping table, and mark the pick as complete. The system then notifies the Shipping Coordinator of the picked order. Subsequently, a Packer packs the order, stages it for shipper pickup, and marks it as packed. The Shipping Coordinator is notified to ship the order, after which the order is marked as shipped and the stock is removed from inventory. The process concludes when the order status is updated to 'done'. Key decision points include the transitions between picking, packing, and shipping, which are crucial for tracking order progress and inventory management. The workflow lacks explicit error handling and contingency plans for stock shortages or discrepancies, which could be areas for optimization.Roles Involved: ERP System, Warehouse Worker, Packer, Shipping CoordinatorInputs: Order details, Inventory dataOutputs: Pick list, Notification of picked order, Packed order, Notification to ship, Order shipped status, Updated inventoryDiagram: