Published: 27 June, 2024
Contributors: Ivan Belcic, Cole Stryker
Process modeling is the practice of creating data-driven visual representations of key business processes. It gives organizations a common language with which they can understand and optimize workflows
If an organization wants to earn strong returns on its research and development investments, resolve IT issues with minimal downtime or create an accurate lead qualification workflow, it needs to understand these processes on an objective and comprehensive level. Even the business users directly involved in these processes might lack total transparency into exactly what happens every step of the way.
Business analysts and other stakeholders can gain end-to-end views of the current state of their business process lifecycle through process modeling. It is a business process management (BPM) technique that creates data-driven visualizations of workflows. These process models help organizations document workflows, surface key metrics, pinpoint potential problems and intelligently automate processes.
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A process model is a graphical representation of a business process or workflow and its related subprocesses. Process modeling generates comprehensive, quantitative activity diagrams and flowcharts containing critical insights into the functioning of a particular process, including:
Events and activities that occur within a workflow.
Who owns or initiates those events and activities.
Decision points and the different paths workflows can take based on their outcomes.
Devices involved in the process.
Timelines of the overall process and each step in the process.
Success and failure rates of the process.
Algorithm-driven: Process models are produced by data mining algorithms that use the data contained within event logs to construct models of the workflows as they exist.
Objective: Because process models are based on quantitative data, they offer genuinely objective views of workflows as they exist in practice and include key data, metrics or events for more thorough process analysis.
By creating a flow diagram of its new account creation process, a software company might discover that a significant number of customers are abandoning the sign-up process because it takes too long. A model can even help the company pinpoint the exact stage at which these drop-offs occur.
Standardized: Process models typically use one of two standardized styles of graphical business process notation: business process modeling notation (BPMN)—also called business process model and notation—or unified modeling language (UML).
Within these notation systems, certain visual elements have universally recognized meanings when used in a process model. Whether an organization uses UML diagrams or BPMN diagrams, these standardized notation methodologies allow process models to be readily shared and read by anyone. Here's how different elements are represented within these diagrams:
Arrows represent sequence flows.
Diamonds represent decision points or gateways.
Ovals represent the beginnings and endpoints of processes.
Rectangles represent specific activities within a workflow.
Swimlanes identify who owns which components of a process.
Event logs and process mining are essential business process modeling tools that underpin modern business process modeling techniques.
Most enterprise IT systems maintain event logs. These event logs are digital records that automatically track state changes and activities, known as events, within the system. Anything that happens within a system can be an event. Here are some common event examples:
A user logs in.
A user updates a record.
A user submits a form.
Information is transferred between systems.
Event logs track both the occurrence of events and information surrounding these events, such as the device performing an activity and how long the activity takes. Event logs act as the inputs during the production of process models.
Process mining is the application of a data-mining algorithm to all of this event log data. The algorithm identifies trends in the data and uses the results of its analysis to generate a visual representation of the process flow within the system.
This visual representation is the process model. Depending on the process targeted for modeling, process-mining algorithms can be applied to a single system, multiple systems or entire technological ecosystems and departments.
Business process modeling shouldn’t be confused with process mapping and process mining. Process maps are manually created based on employee reports and provide higher-level workflow process diagrams. Process mining analyzes organizational data to produce process models, which use that data to create present more objective workflow diagrams.
Process models offer transparency into company workflows, making them a key business process management tool. Process models can be used in any scenario that requires analyzing business processes. These are some of the most common use cases:
A single process model can contain a wealth of workflow data, allowing team members to analyze a workflow from multiple perspectives. Business analysts often use process modeling to highlight these workflow components:
- Control flow: The order in which steps and commands occur within a process is known as its control flow. A process model depicts a flowchart of a process so that a team can see what steps are taken and when. This perspective also helps the team identify any dependencies between steps.
- Organization: A process model can capture who is involved in a process—including people, teams, systems and devices—and how they interact with each other. This perspective illuminates the connections between people and systems that form the organizational social network. In this way, a process model offers insight into how various components of a business function together.
- Time: A process model can record how long a process takes, overall and how long each step takes, allowing the team to identify delays, slowdowns and bottlenecks within the workflow.
- Case: A process model can offer a general view of how a workflow plays out, or it can reflect a particular case—or instance—of a workflow. Teams often use this case perspective to analyze anomalous process outcomes. For example, if a specific instance of a workflow results in lower-than-average outcome quality, teams can isolate exactly what went wrong.
Process models accurately reflect existing workflow inefficiencies and redundancies, simplifying the identification of opportunities for process optimization. When workflows have been optimized, businesses can use process modeling to standardize workflows across the entire enterprise.
The model acts as a template for how processes should play out, helping to ensure that every team and employee approaches the same process in the same way. This leads to more predictable workflows and outcomes overall.
Process models can take the guesswork out of implementing and evaluating new business processes. By creating a model of a new process, business users can get a real-time look at how that workflow is performing, allowing them to make adjustments as necessary to achieve process optimization.
Process models can help companies track whether money and resource investments produce suitable returns. For example, by creating a model of the standard sales process, an organization can see how sales representatives are using the tools and systems at their disposal.
It might turn out that a certain tool is used much less frequently in the process steps than anticipated, in which case, the organization can choose to disinvest from the tool and spend that money on a solution the sales team uses throughout the entire process.
Process models transform complex processes into concrete images, simplifying the dissemination and discussion of processes throughout the organization, especially useful for standardizing project management. For example, if one department has an efficient process for troubleshooting technical problems, the business can create a model of this process to guide implementation on an organization-wide scale.
Process modeling arms an enterprise with objective business intelligence that supports more informed decisions for resource allocation, process improvement and overall business strategy. With a clear view of processes, enterprise teams can ensure that workflows consistently yield optimal results. As a result, operating costs are lower, revenue is higher and business outcomes are stronger.
With process modeling, companies can:
Without a process model, teams are limited to discussing and analyzing workflows in qualitative and subjective terms.
As a result, teams might not accurately understand their workflows. They might make business decisions based on misunderstandings, assumptions or incomplete knowledge.
Process modeling grants access to quantitative workflow data, including success and error rates, allowing for a more rigorous analysis of business processes.
Before a process can be automated, an organization needs a clear understanding of how that process plays out in reality, including the business logic underpinning each decision point.
A process model illuminates both the way that a workflow unfolds and the relationships between events, actors, tools and systems within and between processes.
This viewpoint helps a team document the process itself and the business rules that guide its execution. This information simplifies the process of effectively automating workflows the first time, and then iterating for continuous improvement.
Process models provide organizations with a simpler way to identify opportunities for process optimization. As a result, business processes require less investment to maintain and generate positive outcomes at a lower cost.
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