SUCCESS STORY

Single view of finance drives effective decisions, operational efficiency and innovation

Kagool transformed the client's finance analytics reporting systems to enable data-driven decision-making, improving operational efficiency and driving innovation.

About the Client

Founded over a century ago, the client has a rich and colourful history of continuous improvement and innovation. They have transformed themselves into a leader within the retail and drug industry.

The Vision

As part of its 'Finance for the Future' programme, the client is bringing 10,000 retail stores into SAP S4/HANA, and they needed an analytics platform to support the transformation.

The client envisioned an automated end-to-end process for generating analytics reports from multiple data sources. They require interactive, accessible and easy-to-use dashboards, served by accurate and up-to-date data, to track key financial KPIs in near real-time.

The solution has to be scalable and adaptable to the business growth strategy.

Our Solution

Kagool collaborated with the client to deliver on their vision. Kagool bring a combination of products and expertise which together enable SAP based big data analytics in Microsoft Azure and Power BI. After a successful Proof of Concept to show the value of Azure as a leading Modern Data Platform, Kagool was chosen to implement the analytics programme.


The first priority was to build a finance general ledger data model using aggregated balance data from SAP BW and IBM Cognos. This data was enriched with store hierarchy and master data from the client's Oracle based location database. 


Using Azure Databricks, Kagool applied layers of transformation to the data which represent financial allocation models. The data is then pushed into an Azure Analysis Services (AAS) model which can be accessed through Power BI and Excel.

The GL data model provides the foundation from which multiple finance data models are produced, and enables advanced data-driven decisions across the enterprise, serving various end user requirements.


In Power BI, Kagool has created a finance reporting application which hosts the client's income statement, income analysis, and a number of control reports. 550 million rows of data are processed and refreshed every 30 minutes in Power BI, ensuring near real-time insights.


The resulting centralised SOX compliant data platform gives the client a single source of the truth and protects investors by improving the accuracy and reliability of corporate disclosures.

Complex row level security is applied on multiple dimensions, ensuring appropriate governance with sensitive data.


The income statement reports are tailored, with multiple hierarchies to serve different consumers with the insights most relevant to them.


Kagool integrated use of Zebra BI, a third-party visual which better suits business requirements and provides enhanced functionality.


As well as using reports created by Kagool, the Power BI data model enables employees to easily create their own analytics dashboards, even without expertise in data or SAP.

Outcomes

The client is empowered to drive their business strategy and financial decisions with insights generated from accurate and up-to-date data. 


The next phase of project will be to bring general ledger transaction data from S4/HANA into Azure using Kagool's leading product Velocity, and enable Power BI drill-through from general ledger balances to SAP transactional data, using Azure Synapse Analytics.

Benefits

Effective decisions

Financial decisions are always driven by accurate and up-to-date data

Saves time

The end-to-end reporting process for financial data is automated, saving valuable time

Accurate reports

A Single View of Finance ensures figures in reports are consistent and up to date

Efficient processes

Increases productivity through efficient reporting processes, enabling time to be spent on analysing reports rather than creating them

Adaptable

Adaptable and scalable data model for continually evolving IT landscape

Innovative

Innovation ready data platform for leveraging Artificial Intelligence (AI), Machine Learning (ML), the Internet of Things (IoT), and more

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