Success Stories

Streamlining Financial Data to Boost Productivity

Using data governance & master data management to drive efficiencies and improved data quality

Cheerful woman celebrating at computer
Home  >  Success Stories

Project Overview

A global Communications Service Provider required an extensible data governance framework and master data management re-engineering to streamline key financial data and processes. These data-focused optimizations would reduce manual efforts, improve data quality, and help decrease overall financial close cycle times.

Client Challenge

Delayed Financial Close – Multiple data integrity and efficiency challenges contributed to delays in producing key financial metrics needed for critical organizational visibility and direction.

Inefficient [Master] Data Management – “Swivel chair data entry” (manually entering data into one system and then entering the same data into another system) and manual approval processes caused inefficiencies and contributed to data quality discrepancies.

Disparate Data and System Landscape – Many disparate master data sources, versions, and hierarchies posed challenges in attaining a trusted source of truth for key financial data elements. Additionally, limited data lineage visibility posed challenges with effective Root Cause Analysis.

Solution

RevGen worked with each business unit’s leadership and technology teams to approach the challenges collaboratively and with a sharp focus on process optimization for financial data.The solution included partnering with the client to:

  • Create an extensible Data Governance Framework to establish cross-functional collaboration, prioritization, and alignment on solving key organizational data challenges.
  • Develop actionable plans and solutions for efficiently managing master data for the Finance organization.
  • Review the data landscape to better understand data lineage, identify potential sources of truth, breakage points, and define clear data ownership and stewardship responsibilities.
  • Facilitate prioritization of foundational data assets through the creation of a data inventory and corresponding prioritization matrix.
  • Onboard data influencers (data owners, stewards, custodians, other) and form working groups to focus and resolve top priority data issues within their domain.
  • Design and implement a Master Data Management solution to re-engineer and streamline processes via automation, improve data quality, and reduce manual swivel chair activities.

Results

  • Reduction in manual data manipulation activities allowed for re-focus of personnel on higher value-add activities.
  • Accelerated monthly financial close cycle time enabling leadership to run the business with timely financial metrics.
  • Reduced time and effort required to investigate and correct downstream data discrepancies.
  • Improved data quality controls and enforcement to prevent bad data and support reliable analytics.
  • An extensible framework to facilitate cross-functional collaboration and focus on addressing the top priority data challenges of the organization.

Success Stories

More Success Stories
A person types on a laptop. Above the laptop hovers icons of various checklists, representing data quality controls.

The Power of Frontline Data Quality Controls

Execution as a Service

Improving data quality was key to ensuring our financial services client retained data integrity and accuracy while also reducing time and money spent on after-hours issues. 

Read More About The Power of Frontline Data Quality Controls
Three wooden blocks spelling out MQL. The "M" block tips over to reveal an "S"

Automating for Efficiency: Turning Marketing Leads into Sales Contacts

Technology ServicesAnalytics & Insights

The transfer of marketing leads to sales teams is critical for customer acquisition, however our client’s process was time consuming and heavily manual. RevGen built a proof-of-concept solution that automated the entire handoff.

Read More About Automating for Efficiency: Turning Marketing Leads into Sales Contacts
A pie chart divided into three sections, with representative people tokens in those same colors to show a customer segmentation model.

Developing a Future-Proof Customer Segmentation Model

Artificial IntelligenceAnalytics & InsightsCustomer Experience

To improve sales efficiency, our client needed an “At-a-Glance” customer segmentation model that could evolve with their business.

Read More About Developing a Future-Proof Customer Segmentation Model

Let's Talk

Learn More About RevGen

Subscribe to our Newsletter

Get the latest updates and Insights from RevGen delivered straight to your inbox.

Subscribe