Navigating the Complexities: How to Manage Data Across Multiple ERP Systems?

In today’s dynamic business landscape, organizations often find themselves grappling with the challenge of managing data across multiple Enterprise Resource Planning (ERP) systems. Whether it’s due to a transition period, varying geographical locations, regulatory requirements, or management preferences, the use of multiple ERPs simultaneously is not uncommon.   

Challenges of Disparate Datasets

In fact, each ERP is operating with its own set of reference numbers, currencies, units, and even product names in different languages. Therefore, maintaining alignment becomes a daunting task. This diversity often leads to inconsistencies in data, leading to erroneous insights, hindering operational efficiency and wasted resources.  

The Staggering Impact of the Volume of Manual Reconciliation

The sheer volume of mismatched data makes manual reconciliation a time-consuming and error-prone process. According to Gartner, poor data quality costs organizations an average $12.9 million per year. Furthermore, Gartner also pointed out that data scientists spend 80% of their time cleaning and organizing data. *

Leveraging the Power of AI

Enterprises facing these challenges can now turn to platforms like Olympe to build solutions which leverage the power of Artificial Intelligence (AI) to streamline data reconciliation processes. By automating the identification and matching of similar items across disparate datasets, it provides organizations with a comprehensive tool to pinpoint the most accurate matches. 

Orchestrating Data Reconciliation

The key benefit of Olympe lies in its ability to orchestrate capabilities. Such as fetching data from ERP and matching criteria along with AI-driven algorithms that suggest potential matches. While some matching processes can be fully automated, others may require human intervention to ensure accuracy and completeness. 

Case Study: How Did Olympe Tackle Complex ERP Environments?

Consider, for example, a global organization that has acquired three European companies. This acquisition leads to a scenario where purchased goods data is scattered across various ERP systems and is in three distinct languages.

This complexity has made it costly and difficult for the finance department to generate consolidated reports. As well as for procurement teams to conduct spending analyses and engage in effective planning. 

 The versatility and flexibility of the Olympe platform made it an ideal choice for this organization. Olympe not only facilitated the matching of diverse datasets by involving AI. The platform also empowered users to visualize  the data and act on it through customizable dashboards.  

Moreover, the integration capability of Olympe’s Gateway ensures flawless synchronization with every data source. 


Ready to Streamline Multi-ERP Data Reconciliation?

In conclusion, the challenge of handling data reconciliation in multi-ERP environments can be effectively addressed with tailored solutions built on the Olympe Platform.  

By harnessing the capabilities of AI organizations save significant time to execution. 

With the right capabilities and technologies at their disposal, businesses can navigate the complexities of multi-ERP environments with confidence and agility.  



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