Case Studies > Workflow Engine Streamlines Variance Reporting and Analysis

Workflow Engine Streamlines Variance Reporting and Analysis

Customer Company Size
Large Corporate
Region
  • America
Country
  • United States
Product
  • Vena
  • Microsoft Excel
Tech Stack
  • Excel Integration
  • Central Data Repository
  • Workflow Engine
  • Audit Trail
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Customer Satisfaction
  • Productivity Improvements
  • Digital Expertise
Technology Category
  • Application Infrastructure & Middleware - Data Exchange & Integration
  • Application Infrastructure & Middleware - Data Visualization
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Pharmaceuticals
  • Finance & Insurance
Applicable Functions
  • Business Operation
  • Quality Assurance
Use Cases
  • Process Control & Optimization
Services
  • System Integration
  • Software Design & Engineering Services
About The Customer
A leading pharmaceutical company was manually aggregating budgeting data and forecasting at a very granular level – by month, deal, product, and customer. The company's Finance team faced significant challenges due to the lack of a structured data aggregation process, making it difficult to compare budgets to actuals and determine the reasons for data discrepancies. The manual processes involved in data aggregation and analysis were time-consuming and prone to errors, leading to inefficiencies and delays in financial reporting and decision-making. The company sought a solution to streamline its budgeting and forecasting processes, improve data accuracy, and enhance the ability to perform in-depth analyses.
The Challenge
The Finance team was manually aggregating budgeting and forecasting data from a variety of sources through a series of daily emails. This manual aggregation led to issues with version control and email overload. Additionally, the Finance team had to manually extract historical figures from their GL and paste them into reports to perform analyses. The client could not provide explanations for budget discrepancies within their Excel templates and needed to document details about the discrepancies in separate reports.
The Solution
Vena seamlessly integrates with the client’s GL and stores all data in a central, secure repository. This central data repository automatically pre-populates relevant spreadsheets with up-to-date data, eliminating the need for manual data aggregation. The commentary input feature allows users to embed written explanations of figures directly into Excel spreadsheets, facilitating more accurate and timely analyses. The powerful drill-through feature enables the Finance team to uncover the transactions and source details behind reported numbers with the click of a button. The workflow engine allows management to assign tasks and deadlines to particular users and monitor their status in near real-time. Email notifications are automatically sent to both managers and users when a deadline has passed and when a task has been completed and a template is ready for review and approval. The audit trail feature date-, time- and user-stamps each change made to a spreadsheet and records information about user activity in an easy-to-read log.
Operational Impact
  • Central data repository stores the most up-to-date information and keeps the entire organization in sync.
  • Automatic consolidation of spreadsheets eliminates the need for the Finance team to manually aggregate data through email.
  • Central data repository automatically rolls actuals into dynamic Excel templates, saving the Finance team hours of manual, error-prone work.
  • Drill-through feature gives management instant access to the reasons for data discrepancies, facilitating more timely and insightful analysis.
  • Audit trail enhances user accountability and provides a clear record of changes and user activity.
Quantitative Benefit
  • Reduced manual data aggregation time by 50%.
  • Improved data accuracy by 30%.
  • Increased efficiency in budgeting and forecasting processes by 40%.

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