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Peyman
Advisor
Advisor
The SAP Signavio Process Transformation Suite provides a broad range of analytical capabilities. In today’s post I will primarily focus on the analytical features of SAP Signavio Process Manager and SAP Signavio Journey Modeler to emphasize the criticality of process and journey modeling in analysis, especially when process data is limited or unavailable. A few examples of processes for which it can be challenging to obtain data from source systems are: 

  1. Customer service interactions: It can be difficult to capture all customer service interactions, as they may take place on several different channels, such as over the phone, via email, or on social media platforms. 

  2. Physical production processes: Data on physical production processes, such as those in a factory or manufacturing setting, may not be fully captured by automated systems and may require manual data collection. 

  3. Research and development processes: The nature of research and development processes can be highly variable and exploratory, making it difficult to capture process data in a standardized way. 

  4. Healthcare processes: Healthcare processes involve a wide range of interactions and data sources, including patient data, physician notes, and medical equipment data, which may not always be easily integrated into a single data source. 

  5. Supply chain processes: Supply chain processes can be highly complex, involving multiple partners and systems, making it challenging to collect and integrate data from all relevant sources. 


Process modeling is a base that provides a standardized approach to analyzing processes and ensures that all stakeholders can collaborate effectively. It provides a visual representation of all process steps, actors, and decisions. By modeling the process, stakeholders gain a clear understanding of how the process works, how it is currently performed, and where there may be opportunities for improvement. Modeling also allows for the identification of process bottlenecks, inefficiencies, and other issues that can be addressed through process improvement initiatives. 

Even when data is not readily available from source systems, process analysis remains critical to the overall process management and can provide insights into how the process is working in practice. By collecting data from process participants, such as through surveys & interviews, as well as capabilities such as simulation, process comparison, resource consumption analysis, and cost reports it is possible to analyze process performance and identify areas for improvement. 

Example 1 

In customer service interactions, even if not all interactions are captured in the source system, modeling the process can still help identify areas where the process can be streamlined, or customer satisfaction can be improved. It is possible to identify pain points in the process and develop solutions to address them by analyzing customer feedback or other indicators of customer satisfaction. 

Example 2 

In healthcare processes, process modeling can help identify inefficiencies and areas for improvement, even if all relevant data is not available in a single system. Analyzing patient outcomes, clinical decision-making, or other process metrics can help identify opportunities to improve patient care and reduce costs. 

With SAP Signavio Process Manager and SAP Signavio Journey Modeler, users can create detailed process and journey models that provide a powerful platform including a variety of analytical capabilities for process analysis. Here are a few analysis examples: 

  1. Simulation: SAP Signavio supports process simulation, which allows users to create and simulate business process models. With process simulation, users can test and compare different process scenarios and analyze the impact of changes to the process (such as to the cycle times and costs) before implementing them in the live environment. This helps to identify potential bottlenecks or issues and optimize the process for better performance.Figure 1. Process simulation capability

  2. Process comparison: it helps modelers and analysts to understand process evolution and track process changes over time. In SAP Signavio, process comparison is a feature that allows users to compare different versions of a process model or compare two different process models to identify changes and improvements. This feature shows a side-by-side comparison of the two models and highlights the differences between them, making it easy to identify changes and track improvement. For example, it can be leveraged in fit-to-standard workshops in order to compare best practice models with discovered/designed as-is process models. It can also be used by process owners who want to compare standard processes against process variants and define necessary changes that must be applied to the variants.Figure 2. Process comparison capability

  3. Reports for analytics: Figure 3. Reporting capabilities

    • Risks and controls report provides an overview of potential risks and related controls identified in the selected process models. It provides insights if relevant process risks and control measures and requirements are identified. 

    • Process cost analysis enables users to evaluate the financial impact of different process scenarios and identify cost-saving opportunities. By assigning costs to each activity within the process, users can identify areas for cost-saving opportunities. For example, a financial services company might use cost analysis to identify the most expensive activities within their loan approval process and develop strategies to reduce costs.

    • Resource consumption analysis enables tracking the time and effort required to complete each activity within the process. This technique is useful for identifying areas where process performance can be improved. For example, a logistics company might use resource consumption analysis to identify activities that are taking longer than expected and develop strategies to reduce processing time. Figure 4. Process cost and resource consumption analysis

    • Responsibility assignment matrix / RACI report provides an overview of the assigned responsibilities (responsible, accountable, consulted, and informed) within the selected diagrams. It clarifies roles and helps to understand transitions and handoffs while showing priorities in communication between teams and roles. Figure 5. Responsibility assignment matrix/ RACI

    • Process model metrics report generates a statistics report for your diagrams including type, revisions, and the number of elements along with other metrics. This report supports process analysis such as by identifying process complexity regarding the breakdown of elements used in a process model. 

    • Document usage matrix reports the assignment of documents to tasks and checks the overall usage of documents in each process. This report supports process analysis by specifying missing documents in models and overall reporting on the utilization of documents. 

    • Process characteristics with element details report provides an overview of elements and attribute values found in the selected diagrams. It summarizes the attribute values and provides insights on which attributes in which models require attention. Without this report, every attribute of every model would have to be checked manually. 

    • IT systems usage matrix report creates an assignment matrix that shows which IT systems are used for the execution of process activities. You can choose whether the assignments refer to diagrams (summarizing all activities under one diagram and reporting on IT systems used for each activity) or roles (showing IT systems used per roles that are assigned to activities). With this report, you can control whether the correct IT systems are assigned to activities, understand if some systems are forgotten in the model, and check the overall usage of systems in each process. Figure 6. IT systems usage matrix

    • Responsibility handovers matrix report displays the responsibility handovers by highlighting internal and external handovers for selected diagrams.  It shows process activities and collaboration needed between resources for execution and provides insights into the number of handovers as an indicator of process complexity. 

    • Modeling conventions report checks whether the selected diagrams are compliant according to a specified modeling convention. It supports detecting non-compliant process models and gives process analysts and owners hints on where model quality improvements are required. 



  4. Attribute visualization: The attribute visualization feature allows users to visually analyze process models by displaying process elements and their associated attributes in a clear and organized way. This feature enables users to gain insights into the relationships between process elements and their attributes, making it easier to identify patterns and areas for improvement. Process elements such as activities, events, and gateways can be assigned attributes such as the responsible role, duration, cost, and input/output data. Once attributes are assigned, users can use the attribute visualization feature to display these attributes on the process diagram. Attributes can be displayed using different visualization options such as color coding, size, and shape. This allows users to quickly and easily identify process elements with specific attributes. Users can also filter process elements based on their attributes, allowing them to focus on specific areas of the process that need further analysis.Figure 7. Attribute Visualization configuration Figure 8. Attribute Visualization in the editor (overlays) 

  5. Journey model dimensions: Journey model dimensions is a great addition for journey modelers and owners! With just one click, it is possible to get a bird's-eye view of the entire journey model, including the number of processes, touchpoints, steps, and personas. And let's face it, trying to count all those elements visually can be a daunting task, especially if the journey model is complex and sprawling. This capability provides reports so you can see exactly how big the journey model is and how it performs. With journey model dimensions, it is possible to see how many rows and cells are filled or empty, and provides a complete picture of the journey model's health.Figure 9. Journey model dimensions 

  6. Complexity score: Complexity score allows journey owners and modelers to get an instant overview of their journey complexity based on underlying processes. And that's not all - SAP Signavio provides a complexity benchmark to see where you stand compared to others. This capability provides another indication to prioritize process improvements and transformation efforts alongside other critical data, such as customer experience feedback. Plus, with SAP Signavio's journey modeler, it is possible to visualize and analyze journey complexity score on each journey step and quickly identify areas for improvement.Figure 10. Complexity score


Summary 

Analytics is an essential part of every transformation project. Process modeling is a critical tool for analytics, providing a standardized approach to analyzing processes. SAP Signavio Process Manager and SAP Signavio Journey Modeler offer a range of analytical capabilities such as simulation, process comparison, cost analysis, resource consumption, attribute visualization, and journey dimensions & complexity. By using different types of analysis with process and Journey modeling, organizations can optimize their processes & journeys, reduce costs, improve efficiency and effectiveness, and overall lead to operational excellence. 

While process modeling is a powerful tool that provides a standardized approach to analyzing processes, the real power of analysis can be fully realized when modeling and data-driven analysis (e.g., process mining) are combined, providing a comprehensive understanding of the processes and revealing actionable insights. Process modeling offers a structured approach to analyzing processes and process mining uses actual data to uncover inefficiencies and opportunities for improvement in real-world processes. By integrating both process modeling and process mining, organizations can gain a holistic view of their processes, identify potential areas for optimization, and drive continuous improvement. Thus, the true power of analysis can be gained when modeling and data-driven analysis via mining are coming together. Check this blog post on how modeling and mining can support each other and why it matters to have both for a successful process transformation.
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