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Automated retail reporting for rapid insight generation

With their commitment to building their company based on service, quality and continuous improvement, it was time this client's data and analytics maturity caught up.

This auto parts retailer has been on the Inc. 5000 Fastest-Growing Private Companies list six times. They have a 75,000 square foot distribution center that stocks more than $14 million in inventory, as well a highly efficient distribution model that allows them to ship most orders within 24 hours.

Overview

THE CHALLENGE

The auto parts retailer was looking to modernize their analytics posture as it related to tools, technologies and analytical capabilities.

THE SOLUTION

Ollion provided an accelerated data assessment within the span of four weeks, aiming to transform the data into a more standard and reusable design, creating a centralized data platform that will also support their internal analysis and reporting.

THE OUTCOME

The most impactful outcome of this implementation is the processes put in place to better the company long term. Carving out a few hours a week to do manual data entry takes away from more important tasks that accelerate the company.

The challenge

For this auto parts retailer, some of their most critical reports required excessive time and attention for preparation. The client sought assistance in the reframing and/or refactoring of key reports from Periscope and Google Sheets to Power BI, enabling automation of reports and reduction of manual input. In partnership with Ollion, they then wanted to jointly create a roadmap to build, integrate, model and visualize key data driving business decisions.

The solution

For this client, Ollion provided an accelerated data assessment within the span of four weeks. Because of this project’s time constraints, our data consultants primarily focused on restructuring a subset of the data and analytics platform to create a framework the client could work off of in the future. The main subset involved performance summary metrics that we implemented in Coalesce, a user-friendly data transformation tool that reduces the amount of coding involved.

Our client’s main goal was to move away from spreadsheets and into Snowflake. Their current state showed there was no centralized data warehouse prior to this project. All data was manually input into Google Sheets from numerous sources, with different people owning different pieces of the data. Overall, this state was not scalable as the business grew.

All data was previously ingested into the raw layer in Snowflake. Our job was to transform the data into a more standard and reusable design, creating a centralized data platform that will support the client's internal analysis and reporting. When creating the future state, we wanted to make sure the data model was flexible enough to support new data sources if they were to be introduced in the future.

The outcome

Before implementation, multiple employees spent a majority of every Monday manually entering data. Moving all data to a centralized data warehouse saves time and money, as having time to analyze data will give employees the ability to make educated decisions and focus on other tasks they previously put off due to time constraints.

As businesses want to analyze more data and gain better insights, automation will reduce human error and day-to-day efficiency will accelerate growth to new levels.

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