Why Process Modeling or Simulation?
The goal of Process Modeling is to create a simplified but useful model of a business enterprise. The enterprise can be a small work group or development team, a particular division, a related set of departments, or even an entire company. The model allows an analyst to study the Processes in a business in order to:
- Determine bottlenecks or wasted effort
- Devise revisions to the Process to correct performance problems
- Select Process designs that give the best results
- Provide cost justification
- Establish performance targets for the new Process implementation.
Many types of tools and techniques are available for Process Modeling. Frequently, a simple diagram or flowchart can expose the obvious redundancies, unnecessary work, and inefficiencies in a given Process. Tools which provide simple diagramming of a Process are called static modeling tools. However, to expose less obvious bottlenecks and costs intrinsic to the Process requires information about the resources employed in the Process, measurements of the Processing capacity of the resources, and some measure of the expected workflow through the Process.
Many static Process modeling tools do not allow a quantified analysis of the Process under study. Some of those do not take into account the:
- Time-varying nature of many Processes
- Non-linear interactions among elements of a Process
- Random behavior of most real Processes
- Unexpected events in the business environment
The bottom line is that most Processes are not well characterized by deterministic, mathematical models. A dynamic business Process modeling tool, which can simulate the behavior of the Process as it responds to the events occurring in the business environment, is required to analyze time-varying business processes.
Why Dynamic Modeling?
A computerized dynamic model simulates the flow of materials and information through the Process. The dynamic model accounts for the random variations in how work is done and the way materials (and information) flow through the real world. Simulation offers several advantages over a simple pictorial abstraction of a business Process. Discrete event simulation captures the time-varying nature of the Process under study. Advantages include:
- The analyst can correlate the data produced by the model with measurements taken from the real Processes to increase certainty that the model has adequately captured the essential features of the real Process.
- The model will generate quantified Process measurements such as: excess capacity or bottlenecks, the time it takes work items to flow through the Process, and the percentage of time expended in value-adding Processes versus non-value-adding Processes.
- The model allows the analyst to evaluate, in quantified terms, the effects of re-engineering the Process.
Dynamic simulation allows managers to use models to make better decisions based on predictions of how various controlling variables will influence the business system. The models represent complex business activities from a functional perspective, and focus on understanding and thus changing business practices.
A model mimics the operations of a business by stepping through the events in compressed time while displaying an animated picture of the flow. The simulation allows the manager to measure the processes, people, and technology within the model. The simulation model makes it possible for a manager to evaluate the company’s current business practices and look for ways to improve them.
Within a simulation model, a manager can analyze time, cost, resources, throughput, capacity, and bottlenecks. The model also allows the manager to design and test improvements in resource allocation and system streamlining. Together with performance and financial data, these factors allow the manager to make informed business decisions.
See Process Mapping and Simulation for more information.