Process Mining is a valuable discipline for analyzing and improving business processes. However, organizations often struggle with the cost of implementing Process Mining solutions. Here we will highlight key elements and common mistakes in process mining architectures to help organizations leverage its power while maintaining cost control.
Data extraction is often complex and time-consuming, consuming a significant portion of project resources. Organizations should prioritize proper planning and avoid hasty extraction pipelines. Extracting big data requires well-developed extraction jobs to prevent unnecessary costs and performance impact. Cloud computing resources, such as AWS, Azure, or GCP, offer cost-effective options by eliminating upfront investment and allowing pay-as-you-go scalability. Storage solutions like Amazon S3, Azure Blob Storage, or Google Cloud Storage provide scalable options at a fraction of the cost of process mining storage systems. Utilizing cost-effective alternatives and leveraging lightweight data preprocessing techniques can save both time and money.
While some Process Mining Tools can be expensive, there are economical alternatives available. Tools like Process Science, ProM, and Disco provide comprehensive capabilities without the hefty price tag. It’s important to consider multiple Process Mining Tools to avoid unnecessary costs for low ROI-use cases and ensure valuable process insights are achieved. Collaboration within the organization is another cost-saving aspect, allowing for resource sharing, expertise pooling, and reducing duplication of efforts.
Process Mining offers tremendous potential for organizations seeking to optimize their business processes. While many organizations start Process Mining projects euphorically, the costs set an abrupt end to the party. Implementing a low-cost and collaborative architecture can help to create a sustainable value for the organization. By leveraging cloud-based infrastructure, cost-effective storage solutions, big data engineering techniques, process mining tools, well developed data extractions, lightweight data preprocessing techniques, and fostering collaboration, organizations can embark on process mining initiatives without straining their budgets. With the right approach, organizations can unlock the power of process mining and drive operational excellence without losing cost control.
One might argue that implementing process mining is not only about the costs. In the end each organization must consider the long-term benefits and return on investment (ROI). But with a cost controlled and sustainable process mining approach, return on investment is likely higher and less risky.
DATANOMIQ is the independent consulting and service partner for business intelligence, process mining and data science. We are opening up the diverse possibilities offered by big data and artificial intelligence in all areas of the value chain. We rely on the best minds and the most comprehensive method and technology portfolio for the use of data for business optimization.