CASE STUDIES
Retail Data-Driven Insights
If you’re tired of sifting through mountains of scattered data and you’re struggling to make informed decisions for your business, this story might be worth your time.
Tires-Easy, a leading tire retail company, was faced with the ever-growing challenge of managing their extensive product catalog, sales data, and inventory information. As the company expanded, so did the complexity of their operations. They recognized the need for a robust solution that could not only streamline their data processes but also provide valuable insights for better decision-making.
THE CHALLENGE
THE CHALLENGE
Our client faced a twofold challenge. First, they needed to efficiently centralize and manage their data sources, which included sales, pricing, inventory, and more. Second, they sought to gain deeper insights into their business operations to provide a better service for their customers, fuel growth and stay up-to-date in the highly competitive retail industry.
Their existing systems and processes were in several data silos, making it difficult to extract meaningful insights from the data. The lack of historical data analysis made it difficult for them to identify trends, optimize pricing, and make informed decisions. They started their journey into data analytics by constructing tabular reports, yet these reports turned out to be excessively inflexible, challenging to read and put into practice, and had a significant negative impact on their live system.
Recognizing the potential for data-driven transformation, Tires-Easy embarked on a journey to find a solution. Their opportunity lay in harnessing the power of their data to gain understanding, enhance operations, optimize pricing strategies, reduce costs and ultimately deliver a superior customer experience.
THE SOLUTION
They partnered with us, Evozon’s data science team, to address their challenge. After extensive discussions focused on understanding their needs and expectations, the solution came in the form of a robust data warehouse that would serve as the backbone of their data analytics infrastructure. We implemented a data warehouse tailored to their unique needs. This data repository ingested, transformed, and stored data from all their various sources, creating a unified, clean, and reliable dataset.
This new house for their data is not a copy of their original dataset. It helps them in 5 key aspects:
1. Centralized data storage:
2. Improved data quality:
3. Faster reporting and analysis:
4. Scalability:
5. Data governance and security:
The data warehouse would become the foundation of their data analysis infrastructure. As such, through extensive and enlightening discussions with our clients, we collaboratively dug into their Business Intelligence (BI) requirements. Together, we gained a deeper understanding of their specific informational needs, key performance indicators (KPIs), and the most effective way to visually represent their data in order to craft a narrative that’s easy to comprehend. This collaborative effort resulted in the development of an intricate collection of reports and visualizations designed for their specific business needs.
Centralized data storage:
a. A simple business inquiry should not require users to look blindly through various different database tables, spreadsheets and external CRMs or ERPs. All data needed to answer business related questions should be easy to access, is a simple flat form-factor containing all relevant properties of a topic.
b. The way data is stored in a relational database is perfect for making sure it is non-redundant and standardized. Information related to a sale can be found in multiple tables (even multiple sources) each with a very specific purpose. However, keeping track of sale KPIs will usually require data from all these different tables and systems. This segregation of data, while immensely important for data integrity, is slow and cumbersome for querying. For analysis, we would like all the information related to sales to be in one place, simple and clear, so that anyone can use it to answer their business questions.
Improved data quality
a. Garbage in, garbage out. If the data is not accurate, the decisions won’t be either. A single corrupt revenue amount can result in invalid reports, visualizations or KPIs. In addition, corrupt data can be quite tricky to find and fix. In complex systems, it is surprisingly common that niche issues, like a wrong formula to go unnoticed for a long time, after irreparable damage has been done.
b. The data in the data warehouse goes through a process of cleansing and validation before it is stored. This can help reduce and outright eliminate errors and inconsistencies, and ensures that the data is accurate and up-to-date. As for difficult to find issues, a system of automated alerts can also notify key employees when suspicious activity is seen in the data which allows addressing issues before they become a major problem.
Faster reporting and analysis
a. The transition from gut-feeling to data-driven decisions should occur effortlessly and promptly. Visualizations and reports to inform these decisions should be just as easy to make.
b. The data warehouse expedites reporting and analysis by offering a preaggregated, finely-tuned data perspective. This empowers users to rapidly generate reports, engage in spontaneous analysis, and extract valuable insights regarding business performance without the need to be technical trained.
Scalability
a. Business intelligence is usually performed through monitoring trends and being aware of historical data. As such, capable analysis is usually performed on a large dataset. Sales performance from the past years can give context to present day situations. As such, reviewing a dataset for trend analysis should pose no issue.
b. The data warehouse can handle large volumes of data and complex data sets. It is the ideal way to future-proof the client’s data infrastructure and ensure that it can keep pace with their organization’s growth. Moreover, any data analysis, business inquiries, or AI training will occur independently from their operational systems. This facilitates cutting costs and enhancing system performance and reliability.
Data governance and security
a. Maintaining a secure data infrastructure and handling confidential information with diligence are paramount concerns for Tires-Easy and Evozon (as it should be for everyone).
b. The data warehouse helps ensure that the data they keep is governed and secured properly. Through the data warehouse, they have a framework for managing data access, enforcing data policies, and ensuring compliance with regulatory requirements. The data warehouse enhance security by implementing measures such as encryption, authentication, and authorization protocols, safeguarding sensitive information from unauthorized access. It also supports audit trails and monitoring mechanisms further strengthening data governance.
THE RESULTS
As part of our implementation process, we have delivered the following components:
- Data Warehouse Structure and Schema
- Automated and configurable ETL process
- Server infrastructure and configuration
- Suite of dashboards and visualizations
- Documentation & Training
Here are some key results of the solution:
1. Performance Improvements: The new solution significantly improved system performance. Reports that once took minutes to load were now accessible in seconds, even for complex analyses. Intuitive UI and enhanced filtering capabilities empowered users to extract insights with ease.
2. Report Building & Visualizations: Users can now leverage the data warehouse with various BI reporting tools, perform manual analytics, and it even allowed us to integrate it into AI/ML projects. This versatility expanded their capabilities far beyond traditional reporting. The reports and visualizations are flexible and easily adjustable, allowing even non-technical users to create new ones to address specific business inquiries or satisfy their curiosity.
3. Historical Data Analysis: Storing historical data allowed to uncover valuable insights, track trends, and predict future outcomes. Even where the data was not originally historical in nature. The data warehouse does this by keeping timestamped and versioned instanced for data entries showing their progress in time. For instance, storing historical data for prices enables them to adjust pricing strategies for better profitability. Likewise, preserving historical records of sales status changes provide clear insights into areas of opportunity for optimizing the order fulfillment process.
4. Data Quality Processes: Robust data quality processes during the data ingestion process ensured the accuracy and reliability of stored information, addressing data inconsistencies, errors, and duplicates.
They say a picture is worth a thousand words, so here are a few images showing what we achieved through this collaboration. All the data was simulated to prevent the disclosure of confidential information related to the business or its customers.
LOOKING TOWARDS THE FUTURE
LOOKING TOWARDS THE FUTURE
Our collaboration with Tires-Easy evolved into a true partnership, where mutual learning became the cornerstone of our interactions. At Evozon, we gained invaluable insights into not only the specific challenges of their business but also their core values and needs. This deeper understanding helped us develop and implement more effective data warehousing solutions tailored to their unique requirements. On the other side, they delved deeper into the intricacies of their data, uncovering hidden patterns and gaining a holistic view of their operations. Additionally, they were able to identify the real root causes of their pain points, leading to more precise and effective strategies for growth. Together, we also learned the importance of open communication, adaptability, and the immense value of collaboration.
The data warehouse solution enabled the taking of data-driven decisions, optimizations of operations, and provided a superior customer experience. As they continue to expand their data capabilities, they are poised for a future of continued success in the highly competitive tire retail industry.
Tires-Easy’s dedication to constant improvement and commitment to customer satisfaction is truly commendable. Their growth mindset not only drives them to continually raise the bar but also underscores their strong emphasis on delivering value to their customers. Our recent collaboration in helping them harness the stories within their data is a testament to their forward-thinking approach. By embracing data-driven decision-making, they have shown a willingness to leverage technology to enhance their operations, ensuring they stay innovative.
