Problem

LSE were attempting to build a cloud platform in Azure; due to inexperience it was a prolonged process of trial and error which was inefficient and costly, and at the point we were engaged had not been successful.

Solution

A fully secure and resilient completed Azure architecture which enabled them to migrate from their existing on-premise solution, and establishing a solid technical foundation for building advanced data and analytics capabilities.

Benefit

A 50% monthly reduction on their Cloud architecture costs on completion, with an opportunity to increase this to 80% on decommissioning the on-premise architecture.

The Anumana Way

Phase 1 - Digital Transformation

“As an e-commerce retailer that has grown rapidly, we were data rich but unsure about how to utilise it. We wanted to bring all our data together but didn’t have the necessary experience to achieve those goals.“

For projects like this, we believe our role is to identify solutions on the client’s behalf based on the goals and objectives given to us. Utilising a ‘lakehouse’ architecture, data from standard retail platforms were housed in a cloud-based data lake. A proof of concept data warehouse was constructed to replace an existing code-based process, ultimately delivering an automated report to the Executive Board. This process replaced an existing schedule that was regularly failing. The platform has been utilised for an analytical deep-dive into new customer acquisition and is designed to incorporate future growth.

 

We supported the LSE employees by providing technical training and upskilling as part of our service. A robust project management framework was used throughout to manage the project, ensuring quality was never compromised. Through weekly progress reporting we were able to foresee any potential hurdles, taking an Agile approach and delivering benefits as early as possible. We believe communication is key, and regularly held sessions to present back what we had built, to highlight findings and opportunities, and to ensure the product being delivered remained aligned with LSE’s expectations.

 

“We found great value from the initial approach by Anumana; asking the right questions of the business and making us think about what was truly important. We felt confident with the Anumana team who showed experience and credibility. It was important for us to work with people that actually understood the retail sector as well as the technical elements, which Anumana quickly demonstrated with their immediate understanding of common retail specific terms”

 

By the time the project completed, LSE were able to start realising a 50% reduction of their monthly costs from their existing cloud architecture. The low code solution was more useable and maintainable for a less technical audience. Redundant services were removed, improving efficiency, and security was improved, mitigating against exploitation risks.

There was a further 30% cost saving accessible upon migration away from, and decommissioning of, the on-premise infrastructure. In an extension to the original project scope, we were also able to automate key business reporting, removing manual and onerous manipulation of Excel data. Most importantly, we left LSE with a platform that enabled them to press forward with their ambitious plans for growth.

 

“We’re operating in a completely different way now. We can make better decisions using data that previously was unavailable to us e.g. Amazon, Facebook and Ebay APIs. It’s given us an ability to better understand what we’ve done operationally and what we can do better. Anumana would enable us to think about things in very different ways to how we’ve been thinking before. We now know that there is far more to data and analytics than what we initially thought was available. Not only that, they were always true to their word and our budgets. They provided us with alternatives and options to still provide us value within our budget constraints, rather than saying no.”

Outputs

  • Optimised “Lakehouse” Architecture in Microsoft Azure
  • Proof of concept Data Warehouse
  • Decommission plan for on-premise infrastructure