Digitalisation of the Finance Department: Why Data Quality Is Not Guaranteed

The digital transformation of the finance department promises higher accounting data quality. Reliable figures are the foundation for every strategic decision and efficient corporate management. Finance teams therefore invest time and resources in new tools and systems. A recent study confirms that digital transformation fundamentally improves the quality of accounting information (doi.org 2024a). However, this benefit is not guaranteed under all circumstances. During periods of high economic uncertainty, established processes can come under pressure. This presents a challenge for security-oriented finance teams. A solid data foundation is crucial for the stability of the company, especially in volatile times.

The Fundamental Benefit of Digitalisation for Accounting

Digital transformation improves the quality of accounting information on several levels. A study confirms a positive and statistically significant effect (doi.org 2024a). The change goes beyond mere efficiency gains and strengthens confidence in the financial figures.

A key advantage is increased transparency. Financial data is captured more systematically and made accessible to all authorised individuals. Information is no longer isolated in individual spreadsheets on local drives but is part of a traceable system. Every value can be traced back to its origin. Digitalisation also reduces information asymmetries between management and external stakeholders such as investors or banks. An automated process for calculating key figures quickly provides a verifiable answer. In contrast, manual analysis in a complex spreadsheet is slow and non-transparent. This can weaken the negotiating position in financing discussions.

Digital processes can also limit opportunistic behaviour by management (doi.org 2024a). Standardised and automated workflows create a clear audit trail. Manual adjustments to figures to meet short-term targets are made more difficult, or at least visible. As a consequence, this leads to a clearer and more reliable picture of a company's financial situation. On this basis, management can make better decisions and strengthen the trust of supervisory bodies and investors.

Economic Uncertainty as a Stress Test for Processes

However, the benefit of digitalisation is not equally strong under all circumstances. Research shows that digital technologies are particularly important for maintaining information quality under uncertain business conditions (doi.org 2024a). The challenge lies not in the technology itself, but in the human processes under pressure.

Economic uncertainty manifests itself for SMEs in many forms. Volatile commodity prices, fluctuating exchange rates or unforeseeable changes in the supply chain require rapid responses. Management demands new analyses, scenarios and forecasts immediately. The standardised monthly report is no longer sufficient. The controller is asked to 'just quickly' prepare an analysis. This often leads to an ad-hoc export of data from the ERP system into a new Excel file.

This manual analysis solves an acute problem but creates a new one. The analysis exists outside the standardised and controlled digital environment. As such requests increase, a confusing landscape of separate Excel files emerges. Each of these files can contain its own version of the truth. The connection to the central data source, the ERP, becomes fragile. The benefits of the original digitalisation initiative are partially nullified by these manual workarounds. The quality of the information becomes fragile, even though the underlying systems are digital.

Process Complexity as a Driver of Erroneous Reports

These manual work steps increase process complexity. Complex processes in financial reporting are an independent risk factor. Research shows that the complexity of financial reporting is a significant predictor of erroneous or even fraudulent financial statements (doi.org 2024a). The risk is not just a minor rounding error, but a material misstatement.

Every manual step, every data transfer between systems and every confusing Excel spreadsheet is a potential source of error. A typical example is monthly reporting. The chain from the ERP export to the final management report is often characterised by such manual steps. Data is exported from several ERP modules and consolidated in a central Excel file. Links, manual adjustments and undocumented corrections make the file complex and prone to errors. Such constructs are difficult to audit and hardly maintainable when changes are needed.

These weaknesses become particularly relevant in uncertain times. The pressure on the finance department increases and there is no time for careful checks. The quick, manual route seems more efficient, but the costs of troubleshooting and correction are often higher. This is where a significant risk to data quality lies, which cannot be solved by simply introducing a new ERP system.

The Solution: A Robust and End-to-End Process Chain

A robust digitalisation strategy focuses not just on individual tools, but on the entire process. The goal is a continuously automated chain — 'the chain' — from the ERP system to the finished report. Skopa automates the Excel layer that many companies have built around their ERP for reporting, planning and consolidation. The ERP system itself is not replaced. The automation starts where the data leaves the ERP and is processed manually.

By automating these recurring workflows, complexity is reduced. The processes become standardised, traceable and less prone to manual errors. An automated solution applies a defined, repeatable logic to process data from the ERP. This creates a reliable 'Single Source of Truth' for reporting. Such a process is resilient. It functions consistently even under time pressure. This ensures that data quality remains high even in volatile phases when it is most needed. The integrity of the chain is secured.

What You Can Check This Month

To assess the robustness of your own processes, you can take concrete steps. Conduct an inventory of your most important recurring reports. This analysis will help you identify the greatest risks to your data quality and take targeted measures.

• Identify the most time-critical or complex report in your month-end closing. This is often the report that causes the most overtime.
• Document every single step from data extraction from the ERP to the final figure. Who exports the data? Where is the file saved? What manual steps follow?
• Mark all manual interventions: copying and pasting data, typing numbers from a PDF, manual calculations and formula-based adjustments without documentation.
• Assess where the greatest susceptibility to error lies. What happens if the report has to be prepared under extreme time pressure? What happens if the person responsible is unavailable?

This analysis reveals the weakest links in your process chain. It forms the basis for targeted improvements to secure the data quality in your finance department sustainably, even in uncertain times.

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