Type
Restaurant Management and Ordering System
Objective
The largest restaurant chain in Spain was looking to standardize management and ordering across a number of stores. Their bottom-line objective was improved ordering
accuracy, customer satisfaction, and getting a clearer view of operating efficiency. They also wanted to use analytics to understand the customers’ preferences and trends to improve menu item offerings and promotions.The client needed a comprehensive solution that should handle large scale data coming from multiple sources, integrate with existing systems, and provide a seamless experience for customers and restaurant staff.
Technologies
- Front-end: We will be using React Native in order to develop mobile applications
that can work on iOS and Android. - Back-end: We will make use of PHP along with the Laravel framework in order to
manage the restaurant management system as well as for order processing. - Data Processing: Utilizing Apache Spark in Big Data technologies for
processing huge volumes of transactional and customer data. - Data Visualization: Using Tableau to produce animated dashboards and reports
that create insightful data.
Country
Spain
Project Attributes
Engagement Model
Contractual staffing
Duration
8 months
App Users
Restaurant managers, staff, customers, and administrators
Challenges
- Order Management Complexity: The ability to manage so many orders in
several locations – it had dine-in, takeout, and delivery locations. What the client
wanted was a system to integrate all those orders across the board. - Data Overload: There was a very large volume of data coming in from all the
different restaurant locations for customer preferences, sales, and stock levels.
The issue was how to get meaningful insights out of all that data. - Customer Experience: The general customer experience was necessary to
ensure the proper order and delivery in time along with receiving feedback. - Operational Inefficiencies: Restaurant operations from processing orders to
keeping track of the inventory, needed something more integrated and
automated.
Solutions
- management system using PHP and Laravel, which could manage all types of
- orders.
- Mobile Application for Customers: The mobile application, that has been
designed using ReactNative, allows them to place orders with ease, where it is
and provide feedback about the same. - Big Data Analytics with Spark: We had integrated Apache Spark to process
large volumes of transactional data in real time, enabling us to analyze the order
pattern, customer preferences, and operational data for our client to make better
data-driven decisions.
- Mobile Application for Customers: The mobile application, that has been
- Automated Inventory Management: One more feature was automated
inventory monitoring, helping restaurant managers maintain the level of supplies
and preventing waste.
a fully featured Tableau dashboard to view key performance indicators, like sales
trends, level of inventories and customer feedback.
Results:
- Improved Order Accuracy: The error to the reduced orders was due to the system checking to ensure that every order was free from error. Reduced Operational Costs: Operational costs decreased by 20% in all of the restaurants following automation and improved control over inventory management.
- Increased Customer Engagement: Customer engagement increased by 25% with the introduction of the mobile application.
- Data-Driven Decision Making: The management team of the client used the Tableau dashboard in a way that enables faster and fact-based decision making.
- Operations: Restaurant order processing improved by 35%, which has led to increased speed of delivery and customer retention.
Conclusion:
This has been the power and effectiveness of a data-driven restaurant management system that not just boosts customer satisfaction but also positions the client as a leader in the restaurant industry.