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Summary – With growing complexity in IT modernizations and supply chains, companies still rely on faulty assumptions, causing bottlenecks, delays and cost overruns. Process intelligence continuously collects and unifies transactional data (ERP, CRM, WMS, custom), automatically reconstructs actual flows, highlights deviations, critical loops and best practices, and prioritizes initiatives by business impact and effort. Solution: deploy a modular open-source/hybrid platform with standard connectors or APIs to drive performance and secure your transformations.
In an environment where IT modernization projects, supply chain optimization initiatives, and ERP deployments follow one another, organizations still too often rely on assumptions to describe their processes. The challenge today is to shift to a fact-based approach, leveraging each transaction to reconstruct the true operational flow.
Process intelligence puts data back at the heart of transformation, precisely measuring flows, variations, and blind spots. Insights derived from process intelligence pave the way for greater transparency, the identification of best practices, and prioritization based on objective criteria.
Reconstructing the Operational Reality of Processes
Process intelligence uses transactional data to reveal the actual behavior of each flow. The approach goes beyond documentation: it automatically maps out variations, bottlenecks, and exceptions.
System Data Collection and Integration
The first step is to gather logs and execution traces from all business systems: ERP, CRM, WMS, and custom applications. Each transactional record is extracted, cleaned, and normalized to ensure cross-system consistency. This centralization provides a unified foundation for all analyses and prevents the biases associated with partial dashboards or manual reports.
Hybrid architectures, combining open-source solutions with proprietary modules, can be integrated via standard connectors or custom APIs, such as to integrate a web business workflow into SAP or Microsoft Dynamics. The objective is to ensure uninterrupted data collection without disrupting existing operations or creating vendor lock-in.
Once the data is consolidated, a data warehouse or data lake becomes the entry point for analysis algorithms, massively ensuring traceability of every event and laying the groundwork for the process reconstruction phase.
Automated Reconstruction of Actual Flows
The process intelligence engine reconstructs transactional paths by linking successive records. From the order creation date to payment, each step is automatically identified and sequenced. Sequencing discrepancies or unexpected loops become immediately apparent.
Unlike idealized models, this reconstruction accounts for wait times, manual corrections, and task rerouting. For example, a support ticket subject to multiple reassignments before resolution will be detected as an exception, providing an indicator of operational friction.
With this approach, organizations gain agility: they can visualize—without resorting to tedious business interviews—the actual path taken by every transaction and identify areas of hidden complexity.
Identifying Deviations and Inefficiencies
Once flows are reconstructed, the system highlights deviations from the target process: delays, superfluous tasks, and bypassed steps. These deviations are measured by frequency and temporal or financial impact, providing a quantified view of inefficiencies.
Variations between teams or geographic sites are also compared to identify internal best practices. Rather than a one-off snapshot, process intelligence provides an end-to-end map of actual performance.
Example: A mid-sized logistics company discovered that 25% of its orders—which were documented to undergo automatic validation—were handled manually, resulting in an average delay of six hours. This analysis demonstrated the need to revise workflow routing rules and improve operator training, thereby reducing processing times by 30%.
End-to-End Transparency and Prioritization of Improvement Levers
Complete visibility into your processes enables you to identify critical loops and assess their impact on outcomes. Dashboards built from factual data provide a means to prioritize transformation actions based on their potential gains.
Global Visualization of Critical Loops
Process intelligence tools generate schematic views of processes, where each node represents a business step and each connection represents a transactional handoff. Repetitive loops are highlighted, ensuring a quick understanding of bottlenecks.
This visualization lets you observe the most traversed paths as well as occasional deviations, providing a clear view of areas to optimize. For example, an invoice approval loop that cycles multiple times may be linked to SAP configuration or a lack of crucial data entry.
Beyond the graphical representation, metrics on frequency, duration, and attributed cost for each loop enrich transparency and facilitate decision-making.
Internal Benchmarking and Identifying Best Practices
By comparing performance across different sites or teams, process intelligence identifies the most efficient practices. Internal benchmarks then serve as references for deploying optimal standards organization-wide.
Teams can draw inspiration from the shortest transactional paths, including system configurations, levels of autonomy, and task distribution. This approach promotes the dissemination of best practices without costly manual audits.
Example: An industrial components manufacturer analyzed three plants and found that the top performer completed its production cycle 20% faster thanks to an automated verification step integrated into the ERP. This practice was replicated at the other two sites, resulting in a global reduction in production times and a 15% increase in capacity.
Fact-Based Prioritization of Transformation Projects
Quantified insights from process intelligence allow projects to be ranked along two axes: business impact (delay, cost, quality) and implementation effort. This matrix guides you toward launching the most ROI-optimized initiatives.
Rather than adding new ERP modules or simultaneously overhauling all processes, the data-driven approach ensures that every investment addresses a concretely identified issue.
These defined priorities facilitate sponsor buy-in and resource mobilization by demonstrating from the outset the expected leverage effect on overall operational performance.
Edana: strategic digital partner in Switzerland
We support companies and organizations in their digital transformation
Securing Your Technological Transformation Projects
Process intelligence anticipates risks before each deployment by validating scenarios and measuring potential impacts. This foresight enhances the reliability of ERP projects, IT modernization efforts, and supply chain reengineering.
Pre-deployment Validation for ERP Rollouts
Before any switch to a new version or additional module, process intelligence simulates and verifies existing transactional paths. Each use case is reconstructed in light of historical data to detect any side effects.
This proactive approach limits functional regressions and adjusts the future ERP configuration based on real cases rather than assumptions. It shortens testing cycles and strengthens stakeholder confidence during the deployment phase.
Additionally, IT teams can document areas of concern and prepare targeted mitigation plans, ensuring a smoother transition and fewer post-go-live fixes.
Continuous Supply Chain Optimization
Near real-time transactional monitoring highlights bottlenecks across the supply chain, from supplier to end customer, aligning with an ecosystem approach to supply chains. Transit times, unloading durations, and non-conforming returns are measured and correlated with the resources used.
The analyses enable dynamic adjustments: reallocating transport capacities, modifying delivery windows, and rationalizing inventory. This continuous responsiveness strengthens resilience to disruptions and optimizes operational costs.
The transparency provided by process intelligence transforms every link into a decision point based on concrete indicators, rather than simple aggregated KPIs.
Enhancing Financial Cycles and Reducing Errors
Monthly and quarterly closings benefit from detailed tracking of accounting transactions. Each entry is traced from creation to final approval, enabling the detection of data entry delays and bank reconciliation anomalies.
This granularity reduces the risk of manual errors and accelerates the close-to-report cycle. Finance teams can thus focus their energy on variance analysis rather than data gathering.
Example: A Swiss distribution network reduced its monthly close time from six to three days by analyzing invoicing and payment processes. The company identified multiple bottlenecks in manual approvals and automated systematic checks, improving the reliability of key figures.
Establishing a Data-Driven Culture and Continuous Improvement
Process intelligence becomes a lever for cultural transformation, encouraging data-driven decision-making and cross-functional collaboration. It places the employee at the center and rewards effective behaviors.
Process Governance and Team Accountability
Process governance relies on regular committees where the IT department, business leaders, and service providers jointly review performance dashboards. Each deviation is assigned to an owner, and action plans are defined in a shared backlog.
This agile structure bolsters accountability and creates a virtuous cycle: teams observe the tangible impact of their initiatives and continuously refine their practices. Process intelligence then serves as a common language, streamlining trade-offs and budget decisions.
Key metrics, such as average processing time or compliance rate, become live measures monitored in real time by all stakeholders.
People Analytics to Understand the Human Impact
Beyond flows, process intelligence enables the analysis of human interactions: time spent by role, friction points related to skill development, and interdepartmental collaboration. This reliable HR data reveals areas where workloads are misdistributed or organizational bottlenecks emerge.
By combining these insights with internal satisfaction surveys, it becomes possible to adjust training, rethink roles, and promote targeted upskilling paths, contributing to better change adoption.
Organizations thus gain digital maturity by placing the human dimension at the heart of continuous improvement.
Continuous Monitoring and Agile Adaptation
Control dashboards deliver real-time alerts on key indicators, allowing for rapid process adjustments in case of deviations. Workflows are periodically reviewed in light of new data, ensuring constant alignment with market shifts and strategic priorities.
This continuous feedback loop transforms each project into an ongoing improvement cycle, where every adjustment is measured and fed back into the analysis, ensuring the sustainability of operational performance.
Drive Your Transformation with Process Intelligence
Process intelligence transforms a hypothesis-driven approach into an objective, operational data-based methodology. It provides end-to-end visibility, highlights best practices, secures technological projects, and establishes a culture of continuous improvement within your teams.
Our experts guide organizations in implementing these contextual, modular solutions, favoring open source and an evolving, secure, vendor-lock-in-free architecture. They help you define your key indicators, structure your dashboards, and deploy data-driven steering aligned with your strategy.
