Large Scale Industrial Supply Company consolidates data silos and improves operational efficiency



Overview

A unified data service layer on cloud to deliver a seamless consolidated analytics experience for more than 200 warehouses distributed throughout the United States to track, monitor and forecast procurement and inventory management analytics.


This solution helped to transform the company strategic planning, stocking, procurement, expenses, cash flows management accounts payables and receivables, etc. and deliver near real time insights for senior leadership and further able to track down to the facility level to adjust company operations to fit dynamic needs during unprecedented times.



Industry: Procurement and Inventory Management, Supply Chain
Areas of Expertise: Modern Stack Data Services and BI
Tools: Ultralake, Data Lake Query Engine, Power BI

Customer Challenges

The large-scale industrial material supply company has warehouses across the nation in more than 200 locations. A group of warehouses within the same region have their regional hub and siloed IT applications with a dedicated technical team to support their operations and reporting.


This infrastructure resulted in siloed data hubs within the organization and caused high operating costs. Lacking visibility into its operations from a bird's eye top down perspective, the financial controllers couldn’t see progress aligned to their overall strategy, despite multiple million dollars expenses on the balance sheet. In addition to operational expenses, the Company had invested several million dollars on software licensing to store, process and consume data at each region level.


All the warehouses were managing their own unique data marts per region. The planning team staged an additional project to consolidate the data from each individual data marts into a central data warehouse. The business users were not happy with the quality of individual data marts as the reports were not meeting SLA’s and the huge backlog piled up and requests are time consuming.


“The software and IT solutions were legacy and they were designed to support the needs of regional warehouses/facilities with limited focus on a small group of people. There were challenges to get the information in the hands of leadership teams and business executives when they need it the most. Most of the time spent on collecting the data from all the warehouses and a lot of manual effort in reconciling end to end. The excess spending on resourcing and legacy infrastructure and feeding data from these data marts for strategic projects is only as strong as its weakest link.” - The senior executive shared.

Given the low confidence on individual data marts, the leadership team lacked confidence in proceeding with the consolidation project. XtraLeap came in as an industry expert and strategic advisor to analyze their processes, software and infrastructure, data quality challenges, their licensing and labor costs.


The proposed solution was to consolidate the data from all of their warehouses into a unified data service layer, deliver self-service capabilities for all the business users across each region to consume data without compromising on role based security integrity.



The Solution

XtraLeap proposed a cost-effective solution which replaced the expensive, legacy software and infrastructure appliances by saving 45% costs over a 3 years span, consisting of Ultralake and Data Lake Query Engine deployed on cloud infrastructure to fit more dynamic workload needs. This architecture separates the storage and computing saving more than 30% monthly on infrastructure. This solution proved lowest price to performance compared to other leading proprietary solutions considered.


The solution consisted of three key components. Ultralake collects the data from more than 200 warehouses, cleanses it, and stores it on object storage in a tabular format. Ultralake capacity is scaled out to perform data sourcing and processing work loads twice a day. This resulted in the billing for the time when the servers are used. Data Lake Query Engine is placed on top of data lake and acts as a query engine to provide results back to the client using its lightning-fast query processing technology. This eliminated the manual effort required to collect reports from siloed data marts. This showed an improvement up to 100X for complex and critical business questions. Power BI is used as a self-service analytics platform that connects and fires live queries to Data Lake Query Engine. Power BI was able to answer business questions and provide insights to end-users with a speed that was never seen before. This enabled the business team to visually explore, drill-down, and download reports on their own without having to queue the technical team and rely on their availability, also resulting in freeing up the expensive technical resources to do more strategic, mission critical efforts.


"Making adjustments to procurement and inventory across all warehouses by connecting the links is simple like never before. Having access to data from more than 200 warehouses working together dynamically in real-time is a huge game-changer and a lot of improvement in productivity and profitability. It is one of the examples of how Data Analytics drives cost savings and intelligent decision making." says a key business operations head.


Successful Outcomes

  • Self-service Analytics capabilities for business users along with data science capabilities for forecasting, predictive analytics capabilities.

  • Saving costs by separating storage and compute and adjust capacity as needed.

  • Improved visibility of material procurement, visibility and cashflow.

  • Cloud agnostic technology to avoid a vendor lock-in and benefit from strategic technology investment prospective.

  • Reduction in operational overhead and disconnect among warehouses across different regions.