This guide will walk you through each step of simulating the hiring process, with a focus on setting property parameters and configuring gateway logic to reflect real-world decision-making. Along the way, you’ll learn how to define process behavior, model parallel and exclusive paths, and explore how different configurations affect outcomes like hiring time and resource usage.
Here’s an overview of the areas we’ll cover:
Setting property parameters on elements
Define property parameters on different elements, such as the start event and tasks, to assign and track values like candidate numbers or salary offers. These parameters enable your simulation to reflect realistic decisions and control process flow.
Explore how gateways control process flow by splitting or joining paths and modeling decisions. Learn how parallel and exclusive gateways are used in the hiring process to represent simultaneous tasks and conditional outcomes.
Configuring probability-based sequence flows
Assign probabilities to outgoing sequence flows to control how likely different paths are taken during simulation. Learn how these probabilities influence decisions like candidate advancement, making outcomes realistic and measurable.
Configuring condition-based sequence flows
Apply conditions on outgoing sequence flows to control decisions based on specific rules or properties. Use self-contained or data-driven expressions to route tokens according to values like candidate count or offer amounts.
Run the simulation to see how candidates move through the hiring process and observe the impact of properties, probabilities, and conditions. Use the first run as a baseline to identify bottlenecks, dropout points, and timeline accuracy for future comparisons.
Using the heatmap and bar chart for insights
Analyze simulation results with the heatmap and bar chart to spot bottlenecks and compare task performance across the process. Use these visualizations to identify delays, measure processing times, and understand why outcomes fall short of expectations.
Optimizing parameters to speed up the process
Adjust task parameters to reduce processing times and make the hiring process more efficient. Rerun the simulation with these optimized values to see how improvements help candidates progress to the final stages within the expected timeline.
Comparing baseline and optimized results
Compare baseline and optimized simulation results using heatmaps and bar charts to see how process improvements reduce bottlenecks and speed up candidate progression. Use these visual and numerical insights to understand the impact of optimization and guide further refinements.