About Our Client
Simfoni transforms how businesses manage spending with a compensable, on-demand spend management platform. Designed for Chief Procurement Officers (CPOs) and Chief Financial Officers (CFOs), the platform simplifies procurement by automating processes, streamlining operations, and enabling businesses to achieve rapid savings. Its AI-driven technology empowers organizations across various industries—including manufacturing, utilities, and technology—to gain better visibility and control over their spending while supporting supply chain sustainability goals.
Business Objective
Simfoni sought to improve spend analysis management by consolidating historical and current data from different sources into a single, enriched format. Their objective was to automate procurement processes and eliminate inefficiencies, gain insights into spending patterns through enriched data, and manage a high volume of transactional data. Also, they wanted to support their customers’ decisions backed by accurate and comprehensive data.
Challenges Faced By Simfoni
1. Data Consolidation and Enrichment Complexity
Simfoni specializes in handling various objects, each containing a combination of data they aim to consolidate into an enriched format. Considering the historical nature of the data, the volume was substantial, requiring robust processing capabilities to manage and analyze it effectively. Utilizing various lookups, they established different tables for specific primary keys, enabling them to enrich the data based on those primary keys. This approach allowed for comprehensive data enrichment by leveraging the corresponding lookup values associated with each primary key.
2. Challenges in Handling API Data
Additionally, they encountered the challenge of handling data from APIs with different parameters arriving simultaneously, often containing numerous line breaks and missing data. Consequently, the standard Boomi format was inadequate to generate the desired output for such complex data.
3. Transaction Grouping and Supplier Onboarding Issues
The mapping concept of transaction grouping among multiple suppliers presented a series of challenging tasks. With new suppliers being onboarded each month and some suppliers getting off-boarded, the transaction grouping process needed to be performed monthly and yearly. Managing large volumes of data and ensuring enriched data on schedule proved to be the most demanding aspect of the endeavour.
How NeosAlpha Helped?
We leveraged Boomi integration to help Simfoni streamline spend management, automate procurement processes, and consolidate large data volumes from multiple sources into a unified format.
1. Complex Data Consolidation and Enrichment
Simfoni struggled to consolidate large volumes of historical and current spending data in an enriched format. Multiple data objects, lookup tables, and primary keys made it difficult to maintain accuracy and efficiency during consolidation.
Solution:
After understanding Simfoni’s data structure and processing needs, we developed a precise roadmap to ensure the smooth development of consolidated and enriched datasets. Implementing an advanced set of rules and multiple datasets ensured a unified dataset at various stages for more insightful spend analysis.
2. Handling Fragmented and Inconsistent API Data
Data arrived from multiple APIs with different parameters, causing numerous formatting inconsistencies. Due to missing values and line breaks, generating structured outputs using Boomi’s standard format was even more difficult.
Solution:
We implemented advanced scripting techniques to restructure fragmented data into a clean and consistent format. These scripts allowed Simfoni to process API data efficiently and enhance data integrity.
3. Managing Transaction Grouping Amid Supplier Changes
With suppliers being onboarded and offboarded constantly, transaction grouping was quite challenging. Simfoni had to ensure that all the transactions were correctly categorized and updated across different timelines.
Solution:
We automated the transaction grouping process to ensure seamless transaction updates in alignment with supplier changes. By implementing a system that dynamically adjusted to supplier fluctuations, we improved the accuracy and efficiency of spend categorization to deliver more precise insights into Simfoni’s clients.
4. Ensuring Data Accuracy and Preventing Errors
With a vast volume of transactions and data transformations, maintaining accuracy and minimizing errors was challenging. Minor inconsistencies in data consolidation could lead to incorrect spend analysis.
Solution:
To identify and correct discrepancies proactively, we implemented a robust error-handling system, and for smooth data consolidation, we introduced automated validation checks and structured error management.
We implemented a robust error-handling system that proactively identified and corrected discrepancies. We ensured smooth data consolidation by introducing automated validation checks and structured error management. This approach helped Simfoni maintain data integrity and reliability, reducing the risk of inaccurate reporting.
Results
Here is how NeosAlpha helped Simfoni to:
- Automate and enhance spend analysis for better decision-making
- Consolidate large historical data volumes and real-time transaction data
- Eliminating inconsistencies and errors by streamlining the API data processing
- Reducing manual efforts with the improved transaction grouping accuracy
- Deliver a more enriched and actionable dataset to their clients across various industries
- Improve transaction grouping accuracy, reducing manual effort.
