Dr. Juan Castañedo, a researcher at the Universidad Internacional Iberoamericana (UNIB), together with professionals from other areas, develops a method that accelerates the collection and analysis of data to streamline the procurement processes of companies in real time.
In today's constantly evolving business landscape, monitoring the activities of a company's various departments can be challenging. Traditional methods of data collection and analysis often lead to confusion and limited interdepartmental visibility. Fortunately, the advent of modern information systems, such as enterprise resource planning (ERP) systems, provide organizations with a solution to these problems.
ERP systems provide a centralized repository for an organization's data, ensuring quick access to information for all departments. By viewing the organization as a whole as a single system and individual departments as subsystems, ERP systems seamlessly integrate and automate data. Acting as powerful business process management software, ERP systems bring together crucial internal and external information, such as finance, procurement and customer relationship management. As various events occur in an organization, these systems capture them in structured records, which serve as an easily accessible history for analysis and evaluation.
Auditors have difficulty identifying accounting errors or fraudulent activities due to the limitation of traditional systems and conditional tools that make them difficult to detect. Organizations need comprehensive knowledge to make informed business decisions, so internal process optimization is critical. The process modeling approach requires significant investment, and models and systems are often outdated. This is where process mining technology shines. By automatically extracting data from activity records, process mining offers a dynamic solution that efficiently complements and updates process models.
This technology employs a variety of tools, strategies and methods to analyze activity logs and extract useful information. It accurately identifies, monitors and improves real-world processes, displaying key metrics such as performance, bottlenecks and variations that drive process analysis. ERP systems, being data-rich environments, are an excellent source for process mining. As real-time processes unfold within an ERP system, the data that is generated accurately updates the model, promoting the agility of organizations to adapt to changing requirements.
From a practical perspective, the primary application domain of data mining is the discovery phase, where process models are revealed and analyzed based on extensive analysis of activity logs that provide similar information within specific environments. By integrating diverse algorithms and leveraging activity logs, process mining provides a complete, automatically updated synthesis of models, effectively capturing and visualizing control flows and business operations in real time.
Conformance, a critical aspect of the analysis, focuses on assessing the accuracy of the models by analyzing the discovered or ideal process patterns against real-life situations. Any deviations detected during the analysis allow auditors and decision makers to identify who, what, when and where within a given process cause deviations within the process, facilitating the monitoring of issues related to policy violations, efficiency defects or other procedural violations. Through accurate comparison, this analytical effort driven by ERP systems ensures the optimal transformation of insight into action in the dynamic business world.
In conclusion, it is clear that leveraging ERP systems in conjunction with process mining technology enables organizations to overcome traditional obstacles, improve efficiency and guide data-driven decision making, where buying or selling an organization comes in.
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The Universidad Internacional Iberoamericana (UNIB) offers a Master's Degree in Strategic Management with a specialty in Information Technology. This program provides students with the foundations to lead organizational change, lead projects and advise companies that want to respond to the competitiveness of new businesses.