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6 process mining steps for CIOs, IT leaders
Process mining is particularly relevant for CIOs and IT leaders in the context of ongoing digital transformation initiatives. Learn what steps to follow.
Digital transformation initiatives have streamlined the flow of information, making virtually every step of every business process available for analysis. The availability of so much detailed data has led to more organizations using process mining to optimize their workflows and get higher ROIs from their ERP and CRM systems.
Process mining uses event logs and transactions from ERP, CRM and other systems to map workflows, identify anomalies, spot inefficiencies and recommend process improvements. Traditional workflow mapping simply documents theoretical business processes. In contrast, process mining uses business data to convey real-world results.
Process mining is particularly relevant for CIOs and IT leaders in the context of ongoing digital transformation initiatives. It can help companies identify underutilized features, ensure compliance with regulations such as GDPR and improve organizational agility.
Here are six key steps that can help CIOs, IT directors, ERP/HR application managers and enterprise architects achieve process mining success.
1. Gather the right data
Every process mining initiative must start with relevant, high-quality data. Identify and collect event logs and transactions from various sources, such as ERP software, supply chain management systems and CRM platforms. Data should include what happened at each step of the process, when it happened and who performed each action.
Data should also be clean, complete and compliant from the outset. Incomplete data sets can lead to skewed results, while non-compliant data could lead to regulatory penalties. Remove duplicates, address any data gaps, and automate the process of extracting and transforming data for ongoing analysis. Including data governance teams in these processes helps ensure accuracy and compliance.
2. Define process mining KPIs and business goals
Establish clear, measurable business objectives. Common goals for process mining include cost reduction through increased automation, improved cycle times for faster delivery, improved compliance reporting and a streamlined customer experience.
Considering objectives from the perspective of various stakeholders, including the CIO or CFO, can be helpful. For example, a process mining initiative should deliver a quantifiable ROI, so a goal might be a 20% to 30% improvement in delivery times or a 10% to 15% reduction in cost through automation. Involving a variety of stakeholders can help define the KPIs that matter most.
Identify likely areas for performance issues, such as bottlenecks in order-to-cash cycles, and connect potential improvements to the organization's strategic priorities. Making those connections can help secure process mining buy-in from executive leadership.
3. Select process mining tools that integrate with core systems
Choosing the right process mining tool is important. Look for a platform that integrates easily with existing core systems, such as ERP, CRM, supply chain management and HR applications. Prebuilt data connectors are valuable, but a robust API is equally essential.
If the company's existing vendors offer a process mining tool, using that may be easier than adding a brand-new tool. For example, companies already using SAP may benefit from easier integration with Signavio Process Intelligence. Other popular options include Celonis, which excels at visual analytics and ERP integration, and IBM Process Mining, which delivers AI-driven insights.
Evaluate options based on their scalability, user-friendliness and vendor support.
4. Conduct compatibility and compliance checks
Rigorous testing for compatibility and regulatory adherence must take place before full deployment. Verifying alignment with standards like GDPR for data privacy, HIPAA for healthcare processes and Sarbanes-Oxley Act for financial reporting might be necessary, depending on a company's industry.
Analyzing features such as role-based access controls, encrypted data handling and comprehensive audit trails can help mitigate risks. Assess how each tool interacts with legacy systems and cloud environments and ensure that strong cybersecurity safeguards are in place.
Enterprise architects play an essential role here, as they define security protocols and conduct vulnerability assessments.
5. Pilot a process mining initiative and measure results
Start small with a proof-of-concept pilot that's built around a single process, such as procure-to-pay or order-to-cash.
Solicit input from cross-functional teams when setting measurable objectives and identifying potential focus areas, then gather ongoing feedback.
This iterative approach allows for ongoing adjustments. In addition, a pilot's quick wins can help build confidence among stakeholders, which could potentially lead to more funds in the future.
6. Scale process mining across the enterprise
Once a successful pilot has occurred, the process mining initiative can be expanded to encompass additional workflows. Align the rollout with the roadmap for ERP, CRM and other key business systems. In addition, a comprehensive user training program and integration with automation tools can help with scaling.
Monitor ongoing performance and refine approaches if needed, using AI for predictive insights. As the process mining initiative evolves, it will bring about strategic transformation, fostering a culture of continuous improvement.
James Kofalt spent 16 years at SAP working with SME business applications and was a product manager for integration technology at Microsoft's Business Solutions division. He is currently the president of DX4 Research, a technology advisory practice specializing in ERP and digital transformation.
