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data tools to drive better
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A full-service Big Data cloud, based on Hadoop and Spark, that
meets rigorous demands for reliability, scalability, and security

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Cases Studies

Big Data Solutions

Problem statement

In order to enhance the quality of analytics and decision support system, prominent UK retailer wanted to replace their legacy data warehousing solution with a Cloudera BigData solution that could manage high volumes of data and provide deeper interactive visualizations (historical and longitudinal reporting, trend analysis, etc.) and a platform to run ad-hoc analytical queries by the data scientist on massive retail datasets. However, the BigData management is a problem right now and It is very difficult to manage due to various characteristics.

Solution

Cloudaeon built and delivered secure multi-node on-premises Cloudera BigData platform to manage high volumes of data which facilitate deeper interactive visualizations (historical and KPI reporting, trend analysis, etc.) and allows to run ad-hoc analytical queries by the data scientist on massive retail datasets.

Cloudaeon is also providing 24/7 Cloudera platform support.

Result

Built and manage (24/7) robust multi-node Cloudera BigData platform to support 200+ analysts, visualization developer and data scientist.

Problem statement

For any retailer, one of the key aspects of success is ensuring a steady store stock availability. With all retailers focusing on stock levels to drive improved sales and a better customer experience, it is essential to have an efficient and reliable system in place.

In a complex supply chain, one of the most important factors in maintaining high levels of store availability is to ensure supplier delivery accuracy. We were tasked by a UK retailer and their supplier network to develop a solution which would improve and maintain delivery accuracy. Even though the whole supply chain was working towards the same goal, they were struggling to find a solution.

Our solution

With over 150 suppliers and more than 8000 product lines we knew we would have to work very closely with the supply chain planner (SCP) and the various suppliers. To improve supplier delivery accuracy, we set up an automated consolidation of the relevant delivery data at the most granular (PO) level.

We built a transparent and easy to access system of automated insights for both the retailers and suppliers. The insights were designed to show clear patterns and to help the whole network discover delivery accuracy facts. To guarantee ease of access we designed an app which could be instantly accessed through mobile devices. This app would provide the retailer and suppliers with insights relating to deliveries whenever they might need it.

The result

Once the solution was implemented the network experienced an impressive 1.72% increase in supplier delivery accuracy. By working together using the same insights both the retailer and suppliers were able to access the same KPIs, to improve collaboration and delivery performance.

To ensure every business involved in the supply chain is able to monitor performance and establish new ways to improve, the system is designed to provide performance trend insights. This information can be used by the suppliers to find the root cause of any delivery issues, to quickly find ways to improve.

The problem

The number one threat which most grocery stores face today is the loss of stock through shoplifting. The high threat level on valuable items means that stores across the UK are implementing measures to make products harder to steal. Although these measures can lower the levels of theft, they can also make it difficult for customers to purchase products due to accessibility issues.

We were approached by a UK-based food grocery store who were struggling with the impact of shoplifting. The profits were significantly impacted, with both floor planners and store managers becoming frustrated in their efforts to avoid large losses.

Our solution

Our first step in assisting the company was to find a way to reduce the level of loss on high-value stock. The Cloudaeon team consolidated a variety of data sets at the most granular level possible, which enabled the team to build region specific store insights.

This insightful information was designed to highlight patterns and also the most likely root causes of stock loss. Once the insight tool was ready our team ran a trial for twelve weeks by collaborating with both floor planners and store managers.

The result

Using the actionable insights together we were able to make changes to the floor plan, which helped in reducing high-value stock loss without having a negative impact on sales. These changes led to a £700,000 year-on-year reduction in stock loss against like for like stores.

The problem

One of the most important aspects within retail and logistical businesses is establishing an efficient route to market. The distribution chain will play a significant factor in a variety of issues from the end-to-end cost price through to the carbon emission levels.

In an ever-changing market with complex demand forecasts, there is a requirement behind the scenes for a constantly developing intelligence system. We were tasked by UK-based retailer 3PL to overhaul their transport strategy, to ensure that each aspect was working at optimum level.

The company were struggling to find the right solution which would address their ‘Route to Market’ cost challenges, within the constrained capacity of their struggling distribution centres.

Our solution

The first stage in establishing a solution for our client was to optimise the current ‘Route to Market’ strategy, which involved 8 distribution centres and over 1000 stores. The Cloudaeon team were able to build a fully explainable on demand AI model, which is designed to fit seamlessly with the whole business network.

The model is able to perform billions of permutation combinations, which result in a reduction of vehicle miles and lower carbon emissions. Before launching our complete solution, we ran a series of trials together with 3PL which were based on the output of our AI model. This included changing transport links between the different distribution centres and trial stores, with results showing a clear reduction in vehicle miles.

The result

Once the trials were complete our AI model was implemented across the business, through an on-demand user-controlled system. The system was able to address supply chain issues to establish the best possible ‘Route to Market’. By the end of the year the company was able to reduce annual miles by an impressive 7 million.

The problem

In all warehouses poor availability is a major concern, as the impact is felt at every point in the supply chain, from distribution through to the retailers. Availability issues quickly impact profitability and can cause significant issues for businesses of all sizes. It is easy to believe that a large warehouse must have great availability levels, but this is not always the case.

The client we worked with was struggling to meet availability requirements, due to the pressure of holding large levels of undue stock at the expense of capital expenditure. As an ambient food warehouse based in the UK, the challenge to balance availability with year on year stock reduction targets is not uncommon.

Our solution

The warehouse held over 2000 product lines in stock, so we understood that our solution would need to take this vast inventory into account when planning availability and stock reduction methods.

The Cloudaeon team began by analysing and consolidating multimillion row data sets to gain an insight into the warehouse product flows. This meant we could create an insight tool to highlight the causes of poor availability and undue stock holding issues.

The insight tool was used to create actionable insights which the operations team could put into action. Once the tool was incorporated into the workflows, it became clear that there were significant improvements to the line availability and stock holding positions. The insight tool also took into account the capacity of the warehouse to meet demands in the future should the business grow and expand.

The result

It was clear that our system led to significant improvements in the warehouse with a 3.7% increase in individual line availability. Our system also took into account the future demands of the warehouse, by reducing stock holding by 15% year-on-year.

The problem

A large food retailer in the UK was spending vast amounts of time performing manual checks of ‘Date Expire Food’, to both the front of the store and the back storage area. Although this met strict compliance regulations and reduced wastage, the labour-intensive activities were having a negative impact on productivity.

The store managers knew that the team were struggling to meet productivity targets, which were set to ensure waste reduction tasks were performed on time. The managers were becoming increasingly frustrated with the difficult task of planning resources for the labour-intensive processes, whilst also needed to adhere to strict waste regulations.

Our solution

We knew that the key to improving productivity and efficiency was to overhaul the current system in place to check the ‘Date Expire Food’. The same processes were being followed in over 700 stores, so we understood that the system we implemented would need to be fully flexible and easy to understand and follow.

The Cloudaeon team quickly redesigned the whole process with store-specific fully automated actionable insights. This meant every store had a unique system and set of procedures which met their own individual requirements.

Before rolling out the system within the stores, our team ran a collaborative trial with a variety of stores. By hand-picking a small selection of stores, we were able to ensure our solution worked across the range of retail environments within the chain. Once the results were analysed it was clear that our system brought a sustained improvement to the productivity and waste levels within the stores.

The result

Once the system was implemented, the stores experienced impressive results including a saving of £1.056m on labour costs and the redeployment of labour. The system also provided increased visibility of the out of date products, which resulted in less waste and also an increase in profits through price reductions rather than disposal of spoiled items.

By implementing an efficient and effective system the staff were able to focus their time on the customers rather than time-consuming tasks.

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