Automation Archives - Sparsh Communications PVT LTD https://sparsh-communications.com/portfolio-category/automation/ Wed, 09 Apr 2025 12:51:56 +0000 en hourly 1 https://wordpress.org/?v=6.9 AI-Driven Dynamic Pricing System for Park Avenue Hospitality https://sparsh-communications.com/portfolio/ai-driven-dynamic-pricing-system-for-park-avenue-hospitality/ Thu, 03 Apr 2025 12:21:35 +0000 https://sparsh-communications.com/?post_type=portfolio&p=31345 In the competitive hospitality industry, optimizing room rates based on demand, competitor pricing, and various external factors is critical for maximizing revenue.

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AI-Driven Dynamic Pricing System for Park Avenue Hospitality

Challenge

In the competitive hospitality industry, optimizing room rates based on demand, competitor pricing, and various external factors is critical for maximizing revenue. Park Avenue Hospitality faces challenges in adjusting their room rates dynamically to reflect real-time occupancy, seasonal fluctuations, local events, and competitor activities. The need for a scalable and intelligent pricing system to enhance revenue management and improve pricing strategies is more urgent than ever.

 

Key Challenges:

  1. Real-Time Rate Adjustments:
    Accurately adjusting prices based on fluctuating occupancy levels, competitor activity, and external events.
  2. Competitor Price Monitoring:
    Continuously tracking competitor rates across multiple online travel agencies (OTAs) and direct booking channels.
  3. Event and Seasonal Pricing:
    Applying premium pricing during high-demand periods (e.g., local festivals or seasonal events).
  4. Forecasting Demand:
    Predicting future demand trends to set optimal prices, especially during unpredictable market conditions like weather changes or economic shifts.

Solution

The proposed solution involves a two-phase implementation of an AI-driven dynamic pricing system that leverages industry best practices, including insights from leaders like Marriott and Four Seasons. The system will adjust room rates dynamically in response to real-time occupancy, competitor pricing, and event schedules, with a plan to enhance its capabilities through advanced forecasting and personalized pricing.

Phase 1: Core Dynamic Pricing Implementation

Objective: Deploy a foundational system that optimizes room rates based on real-time data inputs, including occupancy, competitor pricing, seasonal trends, and local events.  

Key Features of Phase 1:

  1. Competitor Benchmarking: Daily scraping of competitor rates using AWS Lambda and custom APIs to compare pricing across OTAs and direct channels.
  2. Occupancy Tracking: Real-time integration with the Property Management System (PMS) to monitor room availability and adjust rates accordingly.
  3. Event-Based Pricing: Integration with local event calendars to apply premium pricing during high-demand events like Shanghai Fashion Week or the Singapore Grand Prix.
  4. Rule-Based Adjustments: Automatically adjust room rates by 10–15% when occupancy exceeds 70%, based on industry benchmarks by Altexsoft.

Deliverables for Phase 1:

  1. Dynamic Pricing Dashboard:
    1. Real-time heatmaps showing occupancy levels across all properties.
    2. Side-by-side comparison of competitor rates.
    3. Analysis of event impacts, including predicted demand spikes during local festivals and events.
  2. API Integration: Seamless connection with Park Avenue’s PMS and channel managers (e.g., SiteMinder) for automatic pricing adjustments.
  3. Alert System: Notifications sent to revenue teams when competitor rates fall below 5% of Park Avenue’s prices, enabling timely rate adjustments.
Timeline: 16 weeks to complete Phase 1.

Phase 2: Advanced Pricing Scenarios

Objective: Expand the system to incorporate more sophisticated pricing models, customer segmentation, demand forecasting, and personalized pricing options.

 

Key Features of Phase 2:

  1. AI Demand Forecasting:
    Use TensorFlow and historical data to predict demand up to 90 days in advance, helping to set optimal pricing based on anticipated market conditions.
  2. Personalized Pricing:
    Integrate with Park Avenue’s CRM (e.g., Salesforce) to offer personalized discounts and promotions to repeat guests or loyalty members, improving customer retention.
  3. Open Pricing Engine:
    Adjust prices for specific room types and views (e.g., premium pricing for ocean-view rooms) to account for demand variability by room category.
  4. Price Elasticity Models:
    Implement A/B testing frameworks to determine the most effective rate ranges by testing customer responses to different pricing strategies and maximizing revenue per customer segment.

Deliverables for Phase 2:

  1. Advanced Pricing Engine:
    Incorporating AI-driven demand predictions, customer segmentation, and dynamic adjustments for specific room types and views.
  2. Personalized Pricing Platform:
    Implement personalized discounts for loyalty members and repeat customers based on CRM data, driving higher customer retention rates.
  3. Real-Time Demand Forecasting Dashboard:
    An advanced dashboard to visualize predictive demand models and adjust pricing strategies accordingly.

Timeline: Phase 2 will be implemented after Phase 1, with an estimated duration of 12–16 weeks.

Key Benefits

  1. Increased Revenue:
    Real-time pricing adjustments based on occupancy, competitor rates, and event-based demand allow Park Avenue Hospitality to maximize revenue during peak periods.
  2. Competitive Edge:
    By continuously monitoring competitor pricing and integrating event schedules, Park Avenue can remain competitive, attracting more guests by offering the most attractive rates compared to nearby hotels.
  3. Better Demand Forecasting:
    Advanced AI-driven demand forecasting allows the company to anticipate booking trends, helping to set optimal rates well in advance, reducing the risk of underpricing or overpricing.
  4. Enhanced Customer Experience:
    Personalized pricing based on customer segmentation ensures that repeat guests and loyalty members receive better deals, improving customer satisfaction and loyalty.
  5. Scalable Solution:
    The phased implementation ensures that the system is scalable, with the flexibility to expand across multiple properties, integrate with existing systems, and handle increasing demand as Park Avenue grows.
  6. Optimized Operational Efficiency:
    Automating price adjustments and integrating real-time data feeds reduces the manual effort required from the revenue team, allowing them to focus on strategic decision-making and customer engagement.

Conclusion 

 

This AI-driven dynamic pricing system will allow Park Avenue Hospitality to optimize room rates dynamically based on real-time occupancy, competitor activity, seasonal fluctuations, and local events. By leveraging advanced AI algorithms and predictive models, the system will help the company increase revenue, stay competitive, and enhance customer satisfaction. With a phased implementation approach, the solution is scalable, flexible, and adaptable to the growing needs of Park Avenue Hospitality. 

Got a Brilliant Idea but Facing Technical Hurdles? Let Sparsh Turn Your Vision into a Seamless Solution!

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]]> Food Wastage Detection System https://sparsh-communications.com/portfolio/food-wastage-detection-system/ Thu, 03 Apr 2025 12:12:03 +0000 https://sparsh-communications.com/?post_type=portfolio&p=31326 Food wastage is a pervasive issue in university dining halls, contributing to unnecessary operational costs, environmental concerns, and inefficient resource management.

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Computer Vision-Based Food Wastage Detection System in University Dining Halls

Challenge

Food wastage is a pervasive issue in university dining halls, contributing to unnecessary operational costs, environmental concerns, and inefficient resource management. The challenge lies in accurately detecting and classifying food wastage, understanding the consumption patterns, and holding individuals accountable without creating an intrusive or complex monitoring system.

 

Key Challenges:

  1. Inaccurate Waste Detection:
    Manually tracking food wastage is prone to human error and inconsistencies.
  2. Identifying Repeated Offenders:
    Tracking frequent food wasters and linking them to specific individuals without violating privacy.
  3. Over-portioning in Kitchen:
    Determining food wastage caused by over-portioning and food handling errors during the serving process.
  4. Data Collection & Reporting:
    Gathering actionable insights from food waste data in real-time and generating automated reports for university administrators.

Solution

To address these challenges, we developed a Computer Vision-Based Food Wastage Detection System that employs AI-driven image processing to detect and classify food waste in real-time. The system is designed to capture and analyze images of leftover food, track consumption behaviors, and provide insights for better food waste management.

Key Features of the Solution

  1. Advanced Camera Setup: High-resolution IP cameras capture detailed images of food waste at strategic disposal points. Infrared cameras are added for scale-up phases to ensure accurate detection under varying lighting conditions. Edge AI cameras provide real-time processing and analytics, reducing the need for heavy cloud computing.
  2. Food Waste Detection: The system uses deep learning models such as YOLOv8, Faster R-CNN, and custom CNNs to identify food items on plates before disposal, classify the type of food, and quantify the amount of waste.
  3. User Tracking: Integration with university systems, including Face Recognition or mobile apps, enables tracking of users who frequently waste food. This allows for identification and accountability.
  4. Automated Reporting & Alerts: Automated reports are triggered at predefined intervals, detailing specific offenders and the amount of food wasted. Real-time alerts are sent to stakeholders for immediate action when significant waste patterns are detected.
  5. Real-Time Monitoring Dashboard: A web-based analytics dashboard allows university administration to monitor food wastage in real-time, visualize consumption patterns, and track waste reduction efforts over time.
  6. Scalable Deployment Strategy: The system is implemented in phases, starting with a single disposal point and expanding to multiple points across the cafeteria. Future phases will include integration with kitchen stations and serving areas to monitor over-portioning trends.

Key Benefits

  1. Cost Savings: By detecting food wastage in real-time, the system helps reduce food waste, which translates into significant cost savings for the university’s dining services.
  2. Environmental Impact Reduction: With better monitoring and reduction of food waste, the system contributes to reducing the carbon footprint associated with food production and disposal.
  3. Accountability & Behavioral Change: The ability to track and identify individuals responsible for food wastage encourages students to consume responsibly and reduce unnecessary waste. This behavior shift can significantly cut down on waste over time.
  4. Data-Driven Decision Making: The automated reporting and analytics dashboard provide university administrators with insights into wastage patterns, enabling them to make informed decisions about portion sizes, menu planning, and waste reduction strategies.
  5. Efficient Waste Management: The system’s automated nature reduces the need for manual monitoring and reporting, streamlining waste management operations and allowing staff to focus on other tasks.
  6. Scalable & Future-Proof: The system is designed to be scalable, allowing it to expand across multiple dining halls and other university areas (e.g., kitchen, serving stations) as needed. Future enhancements may include integrating predictive analytics for even more efficient waste reduction.
  7. Real-Time Monitoring & Alerts: Stakeholders receive real-time notifications when waste patterns deviate from acceptable levels, ensuring quick corrective actions are taken, minimizing wastage before it becomes a larger problem.
  8. Improved Dining Experience: By optimizing food portions and reducing waste, students enjoy a better dining experience with better-served meals and an overall enhanced university dining environment.

Conclusion 

 

The Computer Vision-Based Food Wastage Detection System is an innovative solution to a long-standing problem in university dining halls. By leveraging the power of AI and computer vision, the system not only reduces food wastage and associated costs but also promotes responsible consumption and sustainability. The phased implementation and scalable nature of the system provide universities with an effective tool for managing food waste while improving operational efficiency and contributing to environmental sustainability. The system’s ability to track, classify, and report waste will lead to more informed decision-making, better resource allocation, and, ultimately, a more sustainable dining experience for students. 

Got a Brilliant Idea but Facing Technical Hurdles? Let Sparsh Turn Your Vision into a Seamless Solution!

[contact-form-7]

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]]> Student Records Management Automation https://sparsh-communications.com/portfolio/student-records-management-automation/ Thu, 03 Apr 2025 07:30:19 +0000 https://sparsh-communications.com/?post_type=portfolio&p=31123 Mohan Babu University faced significant challenges in managing and processing student records, with a manual and time-consuming process across multiple platforms

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Student Records Management Automation

The Challenge

Mohan Babu University faced significant challenges in managing and processing student records, with a manual and time-consuming process across multiple platforms. The key challenges included:

  1. Student Record Retrieval:
    Full-Time Employees (FTEs) manually accessed the Salesforce application to fetch student records and updated a Master file with the status “N” (new) for each student record.
  2. LRS Application Login:
    For each new student record, FTEs logged into the LRS application and searched for student details using Name, Date of Birth (DOB), and Postal Code, which was repetitive and inefficient.
  3. Record Handling:
    • If a student record existed, FTEs downloaded files, created organized subfolders, and saved them in a shared directory.
    • If no record was found, FTEs manually took a screenshot of the search result and stored it in the appropriate directory.
  4. File Organization:
    Manual creation of subfolders (Application Pack, Contract Pack, Functional Skills, Completion) was time-consuming, error-prone, and added to the overall inefficiency of the process.

The entire process was resource-intensive, repetitive, and prone to delays, negatively impacting productivity and data accuracy.


Business Applications: PLR Website, Salesforce App

RPA Tool: Microsoft Power Automate

Our Solution

To address these challenges, we implemented an RPA-based solution to streamline the student records management process, automating the retrieval, updating, and file organization tasks:

  1. Retrieve Student Records:
    The bot automatically accesses the Salesforce application and fetches student records.
    It updates the Master file with the fetched records, assigning a status of “N” (new) for each student.
  2. Login to LRS Application:
    For each student with the status “N,” the bot logs into the LRS application and searches for the student using their Name, DOB, and Postal Code.
  3. Record Handling:
    • If the student record is found:
      The bot downloads the application file and saves it in a shared directory under a folder named after the student.
      It automatically creates organized subfolders within the student’s folder, including:
      • Application Pack
      • Contract Pack
      • Functional Skills
      • Completion
    • If no student record is found:
      The bot captures a screenshot of the search result and saves it in the same shared directory under the respective student’s folder.

Benefits Realized

  1. Automated Workflow:
    The process of record retrieval, updating, and file organization was automated, eliminating manual intervention.
  2. Improved Accuracy:
    Automation reduced errors in data updates, file handling, and directory organization, ensuring consistent and accurate records.
  3. Time Savings:
    The automation led to faster student record processing and organization, significantly improving turnaround time.
  4. Cost Savings:
    40% FTE Redeployment was achieved, allowing staff to focus on higher-value tasks.
  5. Structured File Management:
    The bot ensured consistent and well-organized subfolders for file storage, maintaining an orderly directory structure.
  6. Scalable Solution:
    The solution can easily scale to handle increased record volumes with minimal adjustments, supporting growth.

Got a Brilliant Idea but Facing Technical Hurdles? Let Sparsh Turn Your Vision into a Seamless Solution!

[contact-form-7]

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]]> Warehouse and Delivery Management https://sparsh-communications.com/portfolio/warehouse-and-delivery-management/ Thu, 03 Apr 2025 07:19:36 +0000 https://sparsh-communications.com/?post_type=portfolio&p=31107 Toshiba Singapore faced several inefficiencies and delays in their Warehouse and Delivery Management process due to manual interventions and dependency on human effort.

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Warehouse and Delivery Management

The Challenge

Toshiba Singapore faced several inefficiencies and delays in their Warehouse and Delivery Management process due to manual interventions and dependency on human effort. The key challenges included:

  1. Order Retrieval:
    FTEs (Full-Time Employees) manually logged into the orders portal to retrieve order details, which was time-consuming.
  2. Pick Slip Generation:
    FTEs printed Pick Slips to alert warehouse staff for packing items, leading to delays and lack of automation in the process.
  3. Package Scanning:
    FTEs recorded package details like dimensions and weight and completed the scanning process, which added to the processing time.
  4. Shipment Creation:
    FTEs manually created shipments in logistics portals (DHL/UPS) and updated the warehouse application with on-hand stock details. This required constant monitoring and was prone to delays.
  5. Manual Process Dependency:
    The entire process relied heavily on manual input, which was slow, error-prone, and led to operational inefficiencies.

Business Applications: TGCS Web Application, DHL Web Application

RPA Tool: Microsoft Power Automate

Our Solution

To streamline and optimize the Warehouse and Delivery Management process, we implemented an RPA-based automated solution:


Scheduled Automation
  1. Bots automatically logged into the orders portal every 10 minutes during shift hours to retrieve order details.
  2. Bots printed Pick Slips, Invoices, Delivery Orders (DO), and Overpack details for warehouse staff, eliminating the need for manual intervention.
Package Scanning and Shipment Creation
  1. Bots extracted dimensions and weight details from the scanning portal.
  2. Shipments were automatically created in DHL/UPS portals, and waybills were printed for each package, ensuring faster processing.
Stock Update
  1. Bots updated the warehouse application with accurate on-hand stock details, providing real-time inventory visibility and reducing stock discrepancies.

Benefits Realized

  1. Improved Efficiency:
    Automation eliminated manual tasks, ensuring seamless warehouse and delivery management with minimal human effort.
  2. 3 FTE ROI Achieved:
    Significant reduction in staffing requirements while maintaining operational excellence, resulting in a quick return on investment.
  3. Enhanced Accuracy:
    Automation minimized errors in order processing, scanning, and shipment creation, ensuring consistent and error-free operations.
  4. Faster Turnaround:
    Automated workflows led to quicker order processing and package delivery, reducing lead times and improving customer satisfaction.
  5. Scalable Solution:
    The solution is easily adaptable to increased order volumes, allowing the warehouse operations to scale up with minimal adjustments and overhead costs.

Got a Brilliant Idea but Facing Technical Hurdles? Let Sparsh Turn Your Vision into a Seamless Solution!

[contact-form-7]

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]]> Supplier Survey Automation https://sparsh-communications.com/portfolio/supplier-survey-automation/ Wed, 02 Apr 2025 12:59:52 +0000 https://sparsh-communications.com/?post_type=portfolio&p=30872 The client faced significant inefficiencies in managing the Supplier Survey process, which was manually intensive and error-prone

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Supplier Survey Automation

The Challenge

The client faced significant inefficiencies in managing the Supplier Survey process, which was manually intensive and error-prone:

  1. Manual Data Compilation:
    Employees manually extracted Supplier details (e.g., Name, Code, Contact Information, Part Numbers, and Descriptions) from databases or spreadsheets for further processing.
  2. Document Preparation:
    Employees manually populated multiple survey and compliance templates with Supplier data, including:
    • Environmental Survey
    • Compliance Declarations
    • Procurement Templates
    • Conflict Materials Reports

    Each document preparation process took 20 minutes to 30 minutes per Supplier.

  3. Emailing Documents:
    Employees manually emailed completed documents to Suppliers.
  4. Mailbox Monitoring:
    Employees monitored mailboxes for Supplier replies, downloaded attachments, and categorized the documents based on type (e.g., Environmental Survey, Compliance Forms).
  5. Validation and Upload:
    Each document was validated to ensure mandatory fields were completed before being uploaded to a Supplier Database or file server.
  6. Overall Issues:
    • High time consumption
    • Risk of human errors
    • Excessive reliance on manual processes

Business Applications: Email Client, ERP System

Automation Tool: Robotic Process Automation (RPA)

Our Solution

To address these challenges, we designed and implemented an RPA-driven solution to automate the entire process. The solution was divided into two main components for optimized execution:


Part 1: Document Automation and Emailing

  1. RPA bots automatically populated the required survey and compliance templates (e.g., Environmental Survey, Compliance Declarations, Procurement Templates, Conflict Materials Reports) with Supplier data sourced from databases or spreadsheets.
  2. The bots then automatically emailed the completed documents to Suppliers, eliminating manual intervention.

Part 2: Mailbox Monitoring and Document Validation

  1. The bots continuously monitored designated email inboxes for Supplier replies.
  2. Attachments were downloaded and categorized by document type.
  3. The bots validated the contents of the received documents using predefined business rules, ensuring all mandatory fields were completed.
  4. Once validated, the documents were uploaded to the Supplier Database or file repository.

Results and Benefits

  1. Increased Efficiency:
    Reduced processing time per Supplier from hours to minutes, enabling a faster turnaround.
  2. Error Reduction:
    Automation ensured greater accuracy in document preparation and validation, reducing human errors.
  3. Cost Savings:
    The reduction in manual effort allowed employees to focus on more strategic tasks, leading to cost savings.
  4. Scalability:
    The solution was scalable, designed to handle an increasing number of Suppliers with minimal additional effort.

Benefits Realized

  1. 100% Operational Accuracy: Eliminated human errors in document handling.
  2. 30% Cost Savings: Achieved within the first six months.
  3. 60% Reduction in Turnaround Time (TAT): Improved service quality and customer satisfaction.
  4. 30% FTE Redeployment: Employees were freed up to focus on higher-value tasks.
  5. Scalable Solution: The bot workforce can be scaled up or down based on process volume with minimal additional costs.
  6. Improved Productivity: Sustainable, error-free operations ensured significant efficiency gains.

Industry Benchmarks

Our solution aligns with industry standards for RPA automation:

  1. Accuracy: 90–100% improvement
  2. Productivity: 120–250% increase
  3. Expense Reduction: 30–80% savings

Got a Brilliant Idea but Facing Technical Hurdles? Let Sparsh Turn Your Vision into a Seamless Solution!

[contact-form-7]

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