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Why you Need a Standalone Process Simulation Tool
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Why you Need a Standalone Process Simulation Tool

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  1. This is it.

Process Simulation tools are part of the innovative methodology in delivering the vision of the Digital Twin of the Organisation to enterprises. It builds on the process understanding that firms have established over the previous two decades through large-scale Process Mapping and Process Mining initiatives.

Indeed, there is a sense among Process Excellence professionals that after an organisation has ‘completed’ Mapping or Mining a process, a daunting leap is still required to make decisions about how to transform it.

It is at exactly this point that Process Simulation comes into its own by connecting process insights to business impacts. This enables the quantitative analysis of the expected impact of any conceivable process transformation activity on the business, reducing uncertainty and risk.

It is worth noting that many Process Mapping and Mining tools include very limited simulation functionality. This article outlines the differences between the basic simulation features used in BPM & Process Mining today. We will also focus on the opportunities available by leveraging the latest advances in Business Process Simulation (BPS) and the AI/ML tooling that sits on top of true Digital Twins of Business Processes to create valuable and reliable insights. Read on to discover the benefits of using Process Simulation tools, and in particular, a standalone process simulation tool.

Process Simulation Hierarchy

There are 5 levels of Process Simulation that build on a qualitative description of a process (Level 0). For a Process Simulation tool to achieve a given level, it must also satisfy all of the capabilities of the levels before. That is to say that a ‘Level 4 platform’ can do everything in Levels 1-3, as well as satisfy the requirements of Level 4. It goes without saying that an organisation should take preceding levels as prerequisites for more advanced levels.

Level 0: Qualitative graphical models of processes

A graphical model can be a map or graph that describes the relationships between the assets and processes in a business workflow, whether created through manual BPM, or automatically generated based on event logs using Process Mining.

These graphs are common among large enterprises because they provide a comprehensive, in-depth understanding of processes useful for training and onboarding, eliminating obvious inefficiencies, communicating changes, and compliance.

However, while they can communicate what a process looks like, they cannot quantify the impact of changes to the process at all, presenting a fundamental limitation of Process Mapping.

Level 1: Real-time analytics and parameterisation

Using Level 1 simulation features, companies can parameterise large-scale Digital Twins with real-time data from multiple systems. Those parameters can come from:

  1. Statistical parameters extracted via Process Mining
  2. Data from enterprise systems (e.g. Number of Orders from CRM, or Purchase Orders in an ERP)
  3. Assumptions and proxies layered in by expert judgement (e.g. FTE cost per hour, average touch time per order)

Real-time parameterisation allows businesses to monitor the process, generate more reliable input values to overcome data quality issues and improve the experience using the Digital Twin. This is the core of Process Mining. It extracts the process graph as well as critical values from historical and real-time data. Companies can use these values to generate very limited what-if scenarios. However, they are unable to verify if an improvement to a single activity scales up to the entire process, and they are limited to simple back-of-the-envelope maths, with all its pitfalls.

Level 2: Run scenarios over selected parameters

At Level 2, simulation software allows companies to change parameters and generate scenarios that describe the incoming cases (i.e. how many new cases arrive), the resources working on the process (e.g. FTEs per resource pool), the activities (including their wait times, manual processing times, and automation rates), and the connections between those activities (e.g. branching probabilities). Level 2 simulation features ensure that all activities are connected to make certain that changes affect the entire process as realistically as possible.

Using a Level 2 simulation tool, businesses can run simple scenarios over these parameters. This allows them to answer very basic questions, including:

  • What is the impact on throughput time if we increase the automation rate of an activity?
  • What is the impact of reducing the manual processing time of a step on backlogs?
  • If case volumes change, where do bottlenecks occur?

The limited capabilities of Process Mapping and Mining based simulation features usually are at this level as their providers stay close to their Mapping and Mining capabilities. However, Process Simulation tools are still very limited and have no ability to extend beyond a single process structure.

Level 3: Modify and extend the structure beyond a single end-to-end process

Many transformation teams looking into simulations try to connect end-to-end processes, connect processes to commercial outcomes, and investigate potential side effects of their changes. However, at Levels 1 and 2, they cannot add additional structure to their Digital Twin that extends processes beyond the limits of what can be successfully extracted from process data.

At Level 3, a Digital Twin could include a model structure that determines the branching probabilities in a given process, connects process outcomes to complex financial models, or connects processes together. These models could include elements that are not available in the process data, which allows businesses to overcome data silos to create large-scale Digital Twins that can answer questions including:

  • How do changes in the lead-to-order process affect the order-to-cash process?
  • What capacity is required in the order-to-cash process based on the leads in the sales funnel?
  • How do process improvements affect our working capital model and financial statements?

However, simulation features at Level 3 are still limited to an extended version of the current, as-is process.

Level 4: Generate variants of the Digital Twin

Changing input values can help companies experiment with a process similar to their existing as-is process. However, what happens if a firm wants to redesign its processes entirely? In such cases, the current as-is process becomes less relevant, and a simulation tool should focus on potential alternative variants of the process.

At Level 4, companies can create copies of a Digital Twin (or parts of a Digital Twin) and create alternative process variants based on changes to the structure of the graphical model, as well as the parameters of the Digital Twin.

This allows businesses to compare competing and combinatory process designs to identify the optimal process design based on its impact on one or more processes and/or commercial KPIs. Level 4 simulations can answer questions including:

  • What is the impact of removing undesirable activities or connections?
  • What is the impact of adding activities or connections?
  • What are the performance differences between a standard and differently customised processes?
  • What is the impact of reassigning activities to different teams?

However, companies still need to identify potential process changes and create alternative versions of the Digital Twin, or parts of it, to simulate and compare the different process variants.

Level 5: Autonomous recommendations via Process Simulation tools

At Level 5, the simulation software deploys autonomous AI agents to explore the Digital Twin by continuously running scenarios across control parameters (e.g. staffing levels, automation rates) and process structure variants to generate real-time recommendations for optimising day-to-day process operations, as well as re-engineering the process.

Autonomous recommendations accelerate the time-to-value significantly and help businesses to answer questions including:

  • Which parts of the process require attention from the transformation team?
  • What kind of changes should the transformation team investigate?
  • Which process redesign achieves targets most effectively?
  • What combination of process changes has the highest ROI in the next five years?
  • Where do I need to intervene to stay on track regarding the KPIs promised to stakeholders?

Comparison of BPMN, Process Mining, and BPS Process Simulation tools

Level Functionality What it Enables BPMN Process Mining Process Mining Simulation Tools Business Process Simulation
0 Qualitative Graphical Process Model Shared understanding of target as-is process structure
1 Live Data Connections Connect in to multiple systems (ERP, CRM, etc) to enable real-time data synchronisation
2 Scenarios on Parameters Limited changes to input variables like automation rates or branch probabilities
3 Extensible Quantitative Graphical Process Model Extend process simulation model beyond ERP / mined process structure to include commercial outcomes like staff costs or revenue, as well as connect process to each other (e.g. Lead-to-Order + Order-to-Cash)
4 Generate Variants of the Digital Twin Simulate process variants (changing structure and parameters) to evaluate impact of process re-engineering
5 Process Recommendations based on Digital Twin Run pre-defined AI & ML algorithms to find points of leverage and optimal settings for key process steps