Data-driven governance

Data analysis as the basis for automatic and continuous monitoring of your risks, compliance with laws and regulations, and the effectiveness of internal controls. At ARC People, we call this: Data-driven governance.

Technological developments as a catalyst for data-driven governance

Due to the increase in technological developments within organizations for both primary and support processes, more and more data and capacity is becoming available. Think, for example, of the extensive logging of activities within systems that can provide insight into all kinds of transactions, actions by employees, process flows, authorizations, etc.

Where can your company use data-driven governance?

This data can be assessed in various ways. Examples include data analysis to perform quantitative analysis, process mining to perform process-based analyses, and continuous monitoring, which provides real-time insight into the control of objects.

Data-driven governance can be applied within internal audit, risk management, and compliance. This application can also create added value for the front line, as it provides insights into processes that were previously unavailable.

Examples of data-driven governance in practice

Here are a few examples. For the internal audit department of a large manufacturer, we used data analysis to provide insights into the sales process, specifically focusing on the granting of discounts and their amounts. In addition, we used data analysis for all investments at a pension fund to determine whether they complied with the CSR investment policy, in support of a complex investigation.

We applied process mining at a software provider to map the process from the sales order request to the delivery and payment of the order. Based on this type of analysis, we were able to determine how mature the process is and to what extent the established procedure is followed throughout the year.

Data-driven governance and AI

Data-driven governance also offers opportunities to assess the functioning of AI applications based on the underlying logging. For example, the application of Process Mining can be used to assess whether consistent choices are being made by an AI application and on what basis these choices are made.

What advantages does data-driven governance offer your organization?

Data-driven governance offers the following advantages:

• Insight is provided into the entire population rather than a partial observation of the population.
• Automatic risk management.
• Stronger qualitative and quantitative substantiation of findings.
• Real-time compliance monitoring.
• Digital audit solutions.
• Performing work more efficiently, or even automating it completely.