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Driver

Client: JS Global SpA
Duration: 3 months
People involved: 3

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About the Project

Overview

“Driver” is an advanced software solution designed for a logistics company to streamline and optimize various aspects of data management and performance monitoring.

Solution

This robust platform focuses on automating data extraction, computing daily performance metrics, tracking daily revenues by drivers, and monitoring monthly performance and revenues for each branch.

Results

By integrating these functionalities, Driver enables the logistics company to enhance operational efficiency, ensure accurate revenue tracking, and make data-driven decisions to improve overall performance.
Key Features
1

Automated Data Extraction

DATA INTEGRATION

Driver integrates with various data sources, including delivery management systems, driver logs, and financial databases, to automatically extract relevant data. This eliminates the need for manual data entry, reducing errors and saving time.

DATA PARSING AND CLEANING

The platform employs sophisticated data parsing algorithms to process and clean the extracted data, ensuring it is accurate and ready for analysis. This involves handling missing values, correcting inconsistencies, and standardizing data formats.

REAL-TIME DATA SYNCING

With real-time data syncing capabilities, Driver ensures that the latest data is always available for analysis. This is achieved through continuous data monitoring and automatic updates, providing up-to-date insights for decision-makers.

2

Daily Performance Computation

DELIVERY TRACKING

Driver tracks daily deliveries for each branch, comparing the actual number of deliveries made against the expected deliveries. This involves collecting data on delivery times, routes, and completion status.

PERFORMANCE METRICS CALCULATION

The platform calculates various performance metrics, such as delivery success rates, average delivery times, and deviations from expected performance. These metrics are crucial for understanding operational efficiency and identifying areas for improvement.

PERFORMANCE DASHBOARD

Interactive dashboards display daily performance metrics for each branch, allowing managers to quickly assess performance and take corrective actions if necessary. The dashboards are customizable, enabling users to focus on the most relevant metrics.

3

Daily Revenue Computation

REVENUE ATTRIBUTION

Driver attributes daily revenues to individual drivers based on the deliveries they complete. This involves matching delivery records with financial transactions to ensure accurate revenue tracking.

DRIVER PERFORMANCE

The platform analyzes driver performance by evaluating metrics such as the number of deliveries, revenue generated, and delivery success rates. This helps in identifying top performers and providing targeted support to underperforming drivers.

REVENUE REPORTS

Detailed revenue reports are generated daily, providing insights into each driver's contribution to the company's revenue. These reports can be used for performance reviews, incentive calculations, and strategic planning.

4

Branch Monitoring

BRANCH PERFORMANCE

Driver monitors the performance of each branch on a monthly basis, aggregating daily performance data to provide a comprehensive overview. This includes analyzing trends, identifying patterns, and comparing performance across branches.

REVENUE ANALYSIS

The platform conducts an in-depth analysis of monthly revenues for each branch, breaking down the contributions of individual drivers and assessing the impact of performance metrics on revenue generation.

COMPARATIVE ANALYTICS

Driver offers comparative analytics to benchmark branch performance against company-wide averages and industry standards. This helps in identifying best practices and areas where improvements are needed.

Technical Implementation

APIS AND WEBHOOKS

At its core, Driver utilizes APIs and webhooks to integrate with various data sources, such as delivery management systems and financial databases, enabling real-time data syncing.

ETL PROCESSES

The platform employs Extract, Transform, Load (ETL) processes to handle data extraction, transformation, and loading into a centralized data warehouse. This ensures data consistency and readiness for analysis.

DATA WAREHOUSE OPTIMIZATION

The data warehouse, optimized for fast querying and analysis, supports the large volumes of data Driver handles, enabling real-time insights and efficient data processing.
Project Tech Stack

ANGULAR

LARAVEL

AWS

POSTGRESQL

KUBERNETES

ADOBE XD

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