Retailing in a Digital Age: A Data-Driven Transformation



Assessment Toolkit

Tech Stack


Reduction in Cost and Manpower

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Company Overview and the Importance of Data

An iconic global fast-food chain has etched an impressive footprint in the history of the fast-food industry. Recognized for offering a foreign-inspired cuisine with a unique American twist, the brand has expanded significantly over the years with thousands of locations globally and more than 350 franchises.

In the era of digital transformation, the company has leveraged data analytics to enhance customer experience and streamline operations. They use data to understand consumer behavior, preferences, and trends, which aid in menu development, promotional strategies, and operational efficiency. The use of data analytics underscores their commitment to innovation and adaptability, securing their position as a leader in the fast-food industry.

Navigating the Data Maze: Top Challenges They Faced

One of their major challenges was a centralized data management system that caused operational inefficiencies. This in turn impacted inventory management, supply chain operations, and overall performance. 

Limited data autonomy was also a challenge. Sharing data with the parent company restricted their ability to make independent data-driven decisions and leverage their data assets effectively for business insights and decision-making. It also limited localized decision-making which made it a challenge to analyze local customer behavior, preferences, and market trends. 

Due to operating centrally, there was also limited differentiation from their mother brand which hinders competitive advantage in local markets. A lack of agility and innovation with their operations prevented quick responses to market changes and experimentation with new ideas. Specific data insights give companies the ability to develop unique customer experiences, personalized marketing campaigns, or loyalty programs, as opposed to standardized strategies and offering. It enables distinct brand identities that give companies a competitive edge.

Turning Tides: How Eon Unlocked Their Potential

1. Assessment and Modernization Planning

We use ADEPT, our proprietary tool, to conduct a comprehensive assessment at the beginning of every modernization journey. It allows us to understand the existing setup, identify assets requiring migration, and perform an impact analysis for an informed transformation process. We are also able to determine the cost of modernization, create a modernization schedule year by year, and utilize automation within our toolset to significantly reduce costs.

2. Data Warehouses

  • eCommerce Data Warehouse

We developed a Greenfield Data Vault warehouse for the eCommerce Division, along with creating all Tableau reports to gain insights into customer behavior, product performance, and revenue trends.

  • Financial Data Warehouse

We transitioned their financial data warehouse into a Redshift environment, previously housed on legacy systems and a traditional data warehousing solution, facilitating better data management and financial reporting.

  • Technology Transition

We executed a shift to a cloud-based AWS platform, ensuring a smooth handoff of data between different divisions of the company and developing a new data warehouse using the data vault methodology. This transition also supported better data management across the organization through modernized ETL processes.

3. Supply Chain Management Systems Modernization

We migrated and updated the supply chain data into Redshift and AWS, and partnered with MicroStrategy to enhance supply chain decision-making capabilities.

4. ETL Transformation

We streamlined the ETL process which led to a remarkable reduction from 64,000 reports to less than 32,000. Through ADEPT, we got a detailed analysis of report usage, identifying over 30,000 reports that had not been utilized in years, thus preventing unnecessary data migration and reducing both transformation and data storage costs.

We also transitioned from a traditional ETL tool to Talend, through automation tools within our technology toolkit. We realized a 50% reduction in cost and manpower and expedited a process that typically would have taken twice the time and resources.

Talend, one of our technology partners,  enables the extraction of data from various sources, transforms it into a consistent format, and loads it into target systems or data warehouses. Talend’s graphical interface and extensive connectors make it easy to manage complex data integration workflows, addressing data integration challenges, ensuring data quality, and automating the data pipeline process.

5. Analytics and Reporting Optimization

ADEPT allowed us to identify data patterns within their technology environment and offer MicroStrategy cloud solutions to further optimize data management and reporting capabilities.

Transforming Data Into Profits

Implementing these data solutions brought significant benefits such as:

  • Improved Decision-Making

Access to consolidated and real-time data enabled them to make informed, data-driven decisions. This led to better menu optimization, pricing strategies, marketing campaigns, and operational planning, enhancing customer experience, loyalty, sales, and profitability.

  • Operational Efficiency and Cost Optimization

Improved data processes and ETL optimizations enhanced operational efficiency and reduced costs. The transition to modern data warehousing and cloud solutions, along with better financial data visibility, led to effective resource allocation, and sustained profitability. The use of automated transformation within our ADEPT toolkit further cut costs and manpower by 50%,  causing a significant operational and financial improvement.

  • Targeted Marketing and Sales

Data solutions allow them to segment customers based on demographics, purchase history, and preferences. More targeted marketing campaigns and promotions result in higher conversion rates and increased sales.

  • Competitive Advantage

By using data to personalize customer experiences, optimize operations, and deliver targeted marketing campaigns, they gained a competitive edge. This resulted in increased market share, customer loyalty, and brand recognition.

  • Scalability and Growth

The strategic transition to a cloud-based AWS platform and a Redshift environment for data warehousing provided enhanced scalability to meet the company’s expanding data needs, supporting effective data management across multiple locations and facilitating business growth.

The QSR/retail industry is making substantial strides in advanced analytics and Big Data adoption to maintain competitiveness in the face of growing e-commerce and customer loyalty challenges. A survey by NASSCOM indicates that 70% of companies in this sector are focusing on revenue growth through investments in AI and related technologies. 


Customer Success Story with Leading Manufacturing Company



Tech Stack


Reduction in Supply Chain Costs

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Building the Future: Redefining Industries through Innovation

In the following case study, we will explore our journey with a leading global corporation recognized for its commitment to innovation and quality across diverse industries, including manufacturing, consumer goods, energy, security, and healthcare.

They recognize the immense value of data in driving their business operations, enhancing product development, optimizing supply chain management, and creating personalized customer experiences.

Using the power of data, they have reshaped their data operations and practices, leading to accelerated growth and a culture of continuous innovation.

Challenges: Breaking Barriers

With a long history of growth through mergers and acquisitions (M&As), they struggled with diverse systems, processes, and standards across the company. This fragmentation led to increased costs from inconsistencies and inefficiencies. 

Their existing data infrastructure – an outdated combination of legacy data warehouses and data lakes – presented serious limitations. Maintaining this system drained IT resources while performance lagged behind modern solutions. 

Slow response times and inefficient data retrieval prevented a satisfactory experience for business users. With data difficult to access and leverage, user productivity suffered along with decision-making capabilities. 

They recognized the need for a strategic overhaul on their data foundation to achieve standardization, boost IT agility, and empower users with timely insights. Only then could they transition from a decentralized conglomerate to an integrated enterprise. Having guided dozens of organizations through M&As, we understand these data pitfalls intimately. Our team has extensive experience with assessments, strategically planning and implementing the technical integration work required to unify data and systems.

Eon's Approach: Innovate, Automate, Elevate

1. Assessment

Using our internal toolkit, ADEPT, we began with a comprehensive assessment of their current landscape, identified assets that needed migration, and conducted an impact analysis to ensure a successful and informed modernization process.

2. Frameworks

We utilized key frameworks to establish blueprints within the organization that allow standardization and automation. Here are some of the frameworks that we used for this modernization process:

  • Ingestion Framework

Our team updated the ingestion framework and templates to serve as a blueprint for modernization efforts, facilitating the smooth movement of data and accelerating the adoption of modern technologies. The template allowed for the creation of a robust staging area within a Snowflake database. Snowflake, one of our technology partners, is a cloud-based data platform known for its scalability, performance, and ease of use.

  • Generic Data Processing Framework

To address the challenge of data processing, we employed a generic data processing framework to allow users to consume and build additional data assets from ingested data.

  • Data Mart Framework

To optimize data organization and presentation, we established a data mart framework, enabling the creation of easily consumable data marts for specific business functions or user groups. We also implemented data operations practices, utilizing metadata to automate data operations, including lineage, quality checks, and cataloging.

3. Data Migration

We handled data migration through the design and implementation of efficient data pipelines. This ensured seamless and reliable transfer of their historical data from one massively parallel processing (MPP) system to Snowflake. The ingestion framework we used above also handled historical data. 

The Aftermath: Driving Results, Empowering Industries

  1. Improved Performance and Cost Optimization

    • By modernizing their data infrastructure and migrating to Snowflake, they experienced enhanced performance and cost optimization capabilities.
    • This move allowed them to have faster query speeds and improved data access, leading to more efficient data processing, transformation, and analytics. The adoption of Snowflake also facilitated faster decision-making processes.
  2. Standardized Frameworks and Processes:

    • We were able to establish consistent frameworks, processes, and practices on their data platform. This standardization improves efficiency, reduces errors, and enables better collaboration.
  3. Efficient and Scalable Data Operations:

    • Adopting dbt provided a standardized framework and repeatable processes for managing data transformations and analytics pipelines.
    • Data operations practices enabled better management of the data lifecycle, increasing efficiency, scalability and reliability.


According to Statista in 2021, It is estimated that by 2025, there will be over 75 billion Internet of Things (IoT) devices worldwide, many of which will be used in manufacturing to collect and analyze data for process optimization.