Automation without Changing Your ERP: Resolving the Data Jam Between Export and Reporting

The month-end close is approaching. The transactions are recorded in the ERP system, and the balances are reconciled. Now the work begins to create meaningful reports from this raw data. For many finance teams in Swiss SMEs, this involves a manual process: exporting data, preparing it in Excel, and converting it into the correct formats. The task to automate ERP export to Excel is often postponed. Yet, the data jam between the core system and the final reporting costs valuable time and increases the risk of errors.

The Limitations of Established ERP Systems

An Enterprise Resource Planning (ERP) system is the backbone of the finance department. It records business transactions and ensures the integrity of the accounts. Its strength lies in transaction processing. In areas such as flexible reporting, the consolidation of group companies, or agile planning, many of these systems reach their limits. The standard reports often fail to meet the specific requirements of management or the board of directors.

This discrepancy between the functional scope of the ERP and the needs of its users is also reflected in satisfaction levels. In a comprehensive study of over 1,500 rated ERP installations in German-speaking countries, users gave the systems an average score of 1.89 in 2026. This figure has slightly worsened compared to the last survey in 2024 (Trovarit-Studie 2026). This suggests that the expectations of finance teams for flexibility and user-friendliness are not always being met.

Changing an ERP system, however, is a major project. It is expensive, risky, and ties up significant internal resources for months or even years. Furthermore, many companies are bound to their existing system by long-term contracts or industry-specific solutions. The solution for better reporting, therefore, does not necessarily lie in replacing the core system. It lies in optimising the processes that follow on from the ERP.

The Manual Chain: From Export to Final Figure

The path from an ERP export to the finished report is often a long, manual process chain. It begins with exporting raw data, usually as a CSV or Excel file, from systems such as SAP, Abacus, bexio, or Microsoft Dynamics. This file is rarely usable straight away. It often contains superfluous columns, incorrect formats, or unstructured information.

The real manual labour then begins in Excel. Data must be cleaned, sorted, and filtered. Charts of accounts are mapped using VLOOKUP functions to create an understandable structure. Various exports, for instance from the general ledger and sub-ledgers, have to be merged. Pivot tables summarise the data before it is manually copied into the final reporting templates. Each of these steps is a potential source of error.

An incorrect formula, a typo while copying, or using an outdated file version can jeopardise the accuracy of the entire analysis. Troubleshooting is time-consuming and frustrating. Moreover, the process is slow. Valuable working hours that could be spent analysing the figures and deriving recommendations for action are instead channelled into the mechanical preparation of data. The potential time saved through a targeted link between ERP and Excel is substantial.

Automation as the Solution — Without Replacing the ERP

The most effective response to these challenges is not to replace the ERP system, but to specifically automate the downstream processes. Skopa automates the Excel layer that exists around a company's ERP. We do not replace the ERP itself. The focus is on the chain from data export and recurring reports through to submissions.

In this context, automation means creating a robust and traceable process that runs with significantly fewer manual interventions. Instead of an employee exporting and transforming data in Excel, an automation solution takes over this task. It follows predefined rules to validate, clean, and enrich the data.

Excel is not eliminated in this process. For many controllers and CFOs, it remains the familiar and flexible tool for analysing and presenting financial data. Automation aims to significantly reduce the manual preparatory work. The prepared, validated data flows directly into finished Excel templates, Power BI dashboards, or other peripheral systems. The finance team works with consistently prepared figures and can concentrate on its core competence: interpreting the results.

What Does an Automated Process Look Like?

An automated reporting process begins where the manual one starts today: with the data export. However, instead of a manual click, the export is triggered by a script or a scheduled task. The data is stored in a central directory, where the automation process picks it up.

In a second step, the raw data is processed. This part of the automation is the core element. Here, the data is cleaned, for example by removing blank rows or correcting date formats. Account numbers are mapped to a management chart of accounts, cost centres are grouped, and hierarchies are built. Multiple data sources, for instance from different modules or subsidiaries, are consolidated. These transformation steps are hard-coded or configured. They are documented, versioned, and repeatable.

The result of this processing is consistently structured data sets. In the final step, these are converted into the target formats. This could be a series of Excel files for monthly reporting, a data model for Power BI, or a CSV file for uploading to a planning tool. The process runs largely in the background. The finance team receives a notification as soon as the new reports are available. The role of the controller shifts from creator to reviewer and analyst.

What You Can Do This Month

Complete automation is a project. The first step, however, is simple and requires no investment. It involves gaining clarity on existing manual workflows. Pick a single, clearly defined, and recurring report that regularly takes up a lot of your time. Do not try to analyse the entire month-end close process at once.

Document the process for creating this one report in as much detail as possible. Note down the individual clicks, formulas, and manual copy-paste operations. This exercise may seem trivial, but it is the foundation for successful automation. It creates a shared understanding and reveals the true time sinks and sources of error.

• Select a single, recurring report, for example, the monthly sales report by division.
• Write down every single manual step, from the export out of the ERP to the ready-to-send file.
• Measure the time you or your team need for this process. Be honest about it.
• Identify the three most error-prone or time-consuming steps. These are often manual adjustments or merging data from different sources.

With this documentation, you hold a precise description of the problem in your hands. It forms the basis for a discussion about possible solutions — whether through optimising existing Excel files, using built-in tools like Power Query, or collaborating with an external automation partner. This first step creates value, regardless of the path taken afterwards.

SAP, Abacus, bexio, Sage, Odoo, Microsoft Dynamics, Excel, and Power BI are registered trademarks of their respective owners.