Building for the future: The Evolution of Data Management in Experian’s Global Finance Services

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Paul Rodwell
Paul Rodwell
07/26/2024

data management

“Companies have tons and tons of data, but [success] isn’t about data collection, it’s about data management and insight.”- Prashanth Southekal, Head of the Data for Business Performance Institute). 

Whilst the previous article outlined the value and importance of establishing a single or, at least, standard Finance ERP as the solid foundation, the focus needs to turn to data management. Establishing the essential building blocks – the bricks and mortar - needed to build on that foundation and create the structure for consistent and meaningful internal and external reporting, data-driven finance, and business insights. 

However, in that data management journey, data quality should not be overlooked. Veda Bawo, Director of Data Governance at Raymond James phrased it well: 

“You can have all of the fancy tools, but if [your] data quality is not good, you're nowhere”. 

So, just as reliable materials are important to the success of any construction project, the quality and consistency of the finance “bricks and mortar” are truly fundamental for effective global reporting. Without the same types of revenue or costs being recorded against the same (correct) accounts and standard hierarchies for aggregation, consistent and meaningful global finance reporting across multiple businesses, countries, and regions is hard to achieve. 

Experian GFS' Data Management Journey

In 2010, alongside the implementation of the single global instance Oracle EBS (for Finance and HR), Oracle EPM (Hyperion Suite), the Global Chart of Accounts, and the Finance Shared Services organization, Experian established a Finance Master Data Management team. A team specifically responsible for setting up, managing, and maintaining all customer and supplier master data in Oracle EBS as well as the 8-segments of the Global Chart of Accounts shared by Oracle EBS (for finance transaction processing) and Oracle EPM (for consolidation, budgeting, forecasting, and reporting).  

In 2019, the ever-growing importance of data management and data quality drove an evolution of that team into a centralized Global Enterprise Data Management Team. This enabled GFS to support more standard and consistent global finance and business reporting, include other enterprise solutions (such as Salesforce CRM), and leverage the increasing availability and maturity of technologies such as Big Data and Tableau. This extended scope comprised two key areas:

1. Enterprise Master Data Management - responsible for all key master data within the Enterprise systems. This brought together existing master data teams in Finance and Sales Operations, creating synergies and opportunities for greater end-to-end data alignment and process automation.  

In addition to customers, suppliers, products, and the Global Chart of Accounts (GCoA), this team also maintains several other elements that are key to driving global standards essential for improved finance data quality and governance. Elements such as supplier type, customer type, fixed asset categories and sub-categories, expense types, purchasing categories and sub-categories – as well as validation rules within the GCoA – all serve to ensure the correct and consistent coding of the finance and sales transactions that make up the basis for subsequent consolidation, reporting, and analysis.  
 
This has created a Global Centre of Expertise for the wider enterprise, providing end-to-end governance of master data across the various enterprise systems and the data lake. As a global team, it supports the global finance and sales teams across multiple regions and time zones, leveraging cross-training on the systems and data, data standards, processes, controls, and automation to improve effectiveness.  

It also created the scale to enable investments in a range of data and process automation tools to drive productivity and further improve the speed, accuracy, alignment, and quality in the master data setup and maintenance processes, data governance (including approval workflows, validation, and internal controls) and reporting hierarchies, etc.

In addition, the team is also an integral part of ensuring the smooth integration of new acquisitions, migrating customer and supplier master data from legacy systems, mapping to the global chart of accounts, and aligning the new acquisition’s data to Experian’s standards and policies from the outset.  
 
2. Enterprise Data Management - responsible for creating and managing the data in the Enterprise Data Lake, defining and applying global data standards and governance to ensure data availability and quality. This new GFS team works closely with the business, technology, and reporting teams to ingest new data sources from many areas of the business to create and maintain a growing single repository of curated finance, procurement, sales, and other operational data sets – a “single source of truth” - for enhanced enterprise reporting. Having this within a single team, within Global Finance Services, coupled with the advances in data and reporting technology, has provided much greater visibility and capability to integrate and combine data from different areas of the business in a way that was not previously possible.

Key Master Data Challenges

However, even with standardized global Finance, Sales, and other systems and a central team maintaining the key master data within and between each of them, there remain several significant challenges to ensuring alignment across the global eco-system from a process and reporting perspective: 

Firstly, when creating new master data records - such as a new customer - different standard systems within the wider global eco-system (eg: Oracle, Salesforce, Billing, and Operations) each generate and use their unique codes for what is, essentially, the same thing. 

This is further compounded by different views of that same thing within the different functions. For instance, Finance will likely view the “Customer” as the legal entity being invoiced whereas Sales may view it as a division within that legal entity and Operations may view it as the individual(s) using the service or product. Similarly, with Product, Finance will invoice and account for/report on products at a different level to what Sales sell and what Operations use to deliver the service.  

And, last but not least, the need to ensure that the setup and maintenance of customers and products, etc is completed accurately across each of the different systems and end-to-end processes, including any mapping and other maintenance needed to reliably ensure full alignment for processing and reporting.  

To that end, to ensure clear end-to-end alignment within the process, data and reporting:

  • The various functions across the business need to be clear and aligned on the terminology, taxonomy, and coding of what they each use.
  • The data maintenance team needs to establish and maintain effective processes to set up and map the master data and relevant codes between the different systems.   

Master data management solutions (such as Oracle’s DRM), data governance/dictionary/lineage tools (such as Data360), and automation/data management tools (such as Alteryx) - centrally managed and operated by the Enterprise Data Management Team - are pivotal in achieving the necessary alignment and automation across and between the various functions and systems. 


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