How to unify multiple instances of an ERP for better, streamlined consolidated reporting

Enterprise Resource Planning (ERP) systems help manage and automate business processes. They provide a centralized framework that allows data sharing among various departments, such as finance, human resources, supply chain, manufacturing, and services. 

ERP systems are the backbone of a company's operations, providing a single source of truth for all business processes. They enhance efficiency, improve data accuracy, and support data-driven decision-making. 

Ideally, global SaaS companies will use the same ERP software in every market in which they operate because doing so makes data consolidation across all instances of the ERP easier. However, this is not always possible for a number of reasons, which we discuss in our article on consolidating data across different ERPs.  

In this article, we explore the complexities and benefits of consolidating data from multiple instances of the same ERP system. 

What is ERP consolidation?

ERP consolidation merges data from various processes and departments, such as accounts payable, procurement, customer relations, and employee data, into one cohesive system. It streamlines workflows, enhances data accuracy, and reduces operational redundancies to improve business agility.

More and more SaaS businesses are expanding operations across different regions or countries, as a result of mergers and acquisitions, regional regulatory requirements, even for specialized functionalities unique to certain departments and products. 

In these situations, they tailor their tools and processes per the specific geographic or functional needs and often end up using multiple instances of the same ERP software. However, maintaining multiple ERPs across your business can lead to data silos and inconsistencies.

By consolidating data from all the different instances of their ERP software, CXOs gain greater visibility into the business performance, reporting, and analytics. 

Single-instance vs Multi-instance ERP

A single-instance ERP has one central ERP installation for the entire organization. In contrast, multiple-instance ERP systems have separate ERP installations for different business units, regions, or subsidiaries. Each instance operates independently, but data consolidation is necessary for comprehensive, consolidated reporting for the business.

For example, if you’re a SaaS company based in Australia with subsidiaries in the US and UK, you might be using multiple instances of Netsuite across different departments in each region. 

However, your consolidated financial data must reflect the revenue from all regions in a single dashboard, which means your data mapping has to be accurate. 

This also means that you need to convert all the currency from the different locations to Australian Dollars (since that is the functional currency of the business) for accurate financial analysis and reporting. You must ensure there are no discrepancies between the consolidated data and the source systems.

Advantages and disadvantages of multi-instance ERP integration

A multi-instance ERP system decentralizes data management, which allows for customization. It caters to specific regional or functional requirements, making it easier to comply with local regulations and manage diverse business needs. However, the complexity of consolidating data from multiple instances may lead to data inaccuracies and inconsistencies.

Let’s take a look at some of the advantages s of multi-instance ERP:

• Flexibility: Helps meet the specific needs of different units or regions.
• Scalability: Has the flexibility to support the organization’s growth needs, such as acquisition of new business units..
• Compliance: It is easier to comply with local regulations and business practices.
• Risk management: Problems are limited to one instance and do not affect others.

There are, of course, a few disadvantages as well, including:

• Data silos: Each instance operates independently, leading to data silos and difficulties in reporting and analysis.
• Inconsistency: Data and processes may be inconsistent across different units.
• Higher Costs: Managing multiple licenses, upgrades, and maintenance can increase operational costs.

How to consolidate data across multiple instances of the same ERP

Consolidating data from numerous instances of the same ERP system requires careful planning and coordination. It is typically is a two-step process:

Step 1: Data mapping:  

The first step involves mapping the data sources, that is, determining how the data from each ERP instance corresponds to the other. 

Data mapping from one ERP for the purposes of consolidation requires that you look at the data in each and every data field to find its corresponding destination in the target ERP. This process must be repeated for every instance of the ERP you’re using. 

This process, while straightforward, can be time-consuming due to the sheer volume of data. Further, different systems might have different names for the same type of data. 

The objective of data mapping is to ensure that the receiving platform knows how to interpret the data you are bringing in from the other systems, so that nothing is left out during the import process. 

Using Excel templates helps structure the data so the receiving system can properly integrate it. 

In the example below, we have two instances of the same ERP (System A and System B). We want to consolidate the charts of accounts from both systems into a third ERP to support the creation of consolidated financial statements. 

To do this, we first must decide which data set will be the "master" dataset. In this case, the master data set is a third instance of the ERP, which is represented by the FP&A Mapping column.

Note that the structure of the data in one ERP may be different from that of another. So, they may not match up line for line or in how the fields are named.  And, you won’t always know how to map every field, which means you’ll need to work with the data steward for the local ERP to help you figure it out.  Thus, the larger your datatables are in your ERP, the more arduous the data mapping task can be.

Step 2: Data integration

Once you have all the data for each ERP instance mapped out, the next step in the consolidation process is actually getting that data transferred into the receiving system. 

This requires the use of ETL (extract, transform, load) tools that pull the data from the source system, make any changes needed to its structure and format based on your data mapping, and upload it into the target system.

Understanding how local charts of accounts can impact data consolidation

In a company using different instances of the same ERP, it’s not uncommon for the charts of accounts (COA) to differ on local or regional regulations, business practices, and reporting requirements. These variations lead to differences in how financial data is categorized and reported. Data diversity can complicate the process of consolidation.

Mapping local COA ensures that financial entries from different regions are accurately translated into a unified master dataset. For example, what one region records as “Sales Revenue” might be classified under a different account in another region. Therefore, each line item in the local COA must be carefully mapped to the master dataset to maintain consistency and accuracy in consolidated financial statements.

Easily consolidate data across multi-instance ERPs with Drivetrain

By default, multiple instances of the same ERP creates data silos in your business, not to mention inconsistencies and higher operational costs. While you can use spreadsheets to map and consolidate the data they contain, it is a highly manual and time-consuming process. Further, as data volumes grow, spreadsheets become unwieldy and difficult to manage.

Strategic FP&A tools like Drivetrain ease the data consolidation process across multi-instance ERPs. Drivetrain offers a robust solution for data consolidation, allowing you to define metrics at the global, regional, or entity level. 

Drivetrain’s financial forecasting capabilities also allow you to use consolidated data for strategic forecasting and planning in addition to consolidated reporting. 

Here’s how Drivetrain supports data consolidation across multi-instance ERPs:

• Automated data consolidation: You can easily connect every instance of your ERP to flow your data into Drivetrain and access it in real time. 
• User-driven data mapping: After your initial set up, Drivetrain retains the data mapping for each instance of your ERP and facilitates fast and easy in-platform collaboration features to resolve any questions with local data stewards. 
• Currency conversions: Drivetrain simplifies currency conversions, allowing you to seamlessly convert financial data from multiple currencies and account for foreign exchange (FX) gains and losses in your financial reporting. 
• ERP compatibility: With 200+ integrations and the ability to create custom integrations, Drivetrain is compatible with your ERP. 
• Customized models and reports: Drivetrain allows a ton of flexibility in designing custom data consolidation models and generating business-specific reports.

Learn more about how Drivetrain can power your business with accurate data and generate actionable insights for informed decision-making.