Process Analytics Glossary ​

Key Terms and important information about Process Analytics

Core Terms

Activity:

Activities are the subparts of a process. It is an event that has a distinct beginning and ending. The activity usually results into an output.

Active Time:

Active Time is the amount of time spent on the activity explicitly.

Attribute:

An Attribute is a dimension of a record.

Bottleneck:

The Bottleneck of a process is the event that stalls production. The bottleneck is the event that requires the longest amount of time. The bottleneck holds back the whole process. The goal for many organizations is to remove or minimize the effects of the bottleneck in order to increase efficiency. In process discovery tools there are unique features that allow for bottleneck analysis so that people do not need to manually determine where the bottleneck is.

Case:

A Case is one instance of an event.

Case ID:

A Case ID a unique identifier of one case. A Case ID is associated with each record within the event log. This is what ties together all of the events related to one case and allows for processing.

Data Attribute:

Data Attribute is a characteristic of a piece of data.

Digital Twin:

Digital Twin is the online documentation of something that occurs in real life. A duplicate of the process is then stored electronically, making a digital twin.

Dimension:

A Dimension is an event’s attribute which is declared as dimension. The declaration could be automatic or manual by the user. The automatic declaration is based on the series of rules such as:
• The type of the data in the attribute is String or Number
• The count of unique values of this attribute is between 2 and 2000.
If both conditions are met, the attribute is considered a dimension. This happens during the post-load analysis.

Event Name:

The Event Name is the text that identifies what happened within the process. This could be something such as “Patient Discharged,” “Form Created,” etc.

Filtering:

Filtering puts a set of if statements onto a set of data. Filtering only outputs data that follows the terms. Filtering is a good way to find anomalies within the data and focus on the data that you want.

Financial Analysis:

Financial Analysis focuses on the cost of the process. Financial Analysis can be useful to determine what processes are costing the most for the business. Financial Analysis can help be a good start to the analysis process in order to find opportunities to cut costs.

Frequency Analysis:

Frequency Analysis focuses on the number of times an event is performed in a particular order. Frequency Analysis can be useful to determine how often processes that do not apply to conformance or other problems. Frequency Analysis can help be a good start to the analysis process.

Performance Analysis:

Performance Analysis focuses on the results of a process. This could be a positive or negative result.

Process Analysis:

Process Analysis is the step after Process Discovery. In Process Analysis the processes executed in the company are analyzed in order to understand where and how improvements are possible. Analysis consists of analyzing the “as-is” process, finding problems, and optimizing the process.

Process Animation:

Process Animation allows for simplistic visualization of a process. Process visualization shows the process flow through animation such as dots that follow the process to show speed ,lags, and flow.

Process Compare:

Process Compare allows for multiple processes to be placed side by side and analyzed. This allows for process analysis between similar processes.

Process Discovery:

Process Discovery is the first part of process intelligence. This step of the process discovers the “as-is” process execution and presents an intuitive visualization that is easily explorable. Discovery consists of extracting the data, mapping the events, and creating the “as-is” visualization. There are many software platforms that help with process discovery.

Process Instance:

A Process Instance is one particular occurrence of the process.

Process Map:

A process map is a visualization of a process. A process map can map an actual process or of the standard process.

Process Mining:

Process Mining is the process of extracting information from event logs and doing analysis in order to support the business processes.

Process Monitoring:

Process Monitoring is a way of continuously evaluating a process without having to watch flashing monitors waiting for a change. Process monitoring allows a user to input protocols. As the data is uploaded in real time the program watches for these protocols. When the protocol is violated the violation can trigger alerts to a person’s phone or email.

Protocol:

A Protocol is a predefined sequence of activities typically in a prescriptive form, i.e. the protocols are supposed to be followed. One could think of a protocol as an instruction or a cookbook. The examples of protocols: Resuscitating a patient with a cardiac arrest; Onboarding a customer with 401K rollover; Selling a product to a new customer, Defending PhD thesis, and so on.

A protocol doesn’t have to be a single linear sequence. There could be multiple protocols depending on the nature of the object (one for cardiac patient another for gunshot). There could be multiple branches within the same protocol: do something, check the result, if A – go one way, if B – go another way. There could be the protocols which happen within another protocol, for example, in the middle of patient admission process she developed the acute cardiac arrest. Moreover, the “inner” or “child” protocol could be triggered by some step in the “parent” protocol (a protocol to create new employee’s email account is triggered as one step in the overall employee onboarding process) or start completely independently by some external event, as in the case of the medical emergency during the admission process.

Process Variant:

Process Variant are the different unique paths that a process can take. Traditional process discovery will not take into account the unique process variants but rather just the most commonly followed path. TimelinePI uses its timeline analysis approach in order to show every single process variant in a timeline form.

Timeline:

A Timeline is the history of a process instance. It is the history of a sales order, an invoice, an insurance claim, a service ticket, or any other specific process over time. A timeline simply consists of events which state that something happened to this “thing” at specific time.

Timeline ID:

Refer to Case ID

Timestamp:

A Timestamp is a piece of information created with a record of information that indicates the time that the step occurred. This allows for the Timeline analysis of processes. With the timestamp the process is able to be tracked over time.

Transaction Log:

Transaction Log is the history of the processes within a business. These transaction logs are kept within systems used to do do your processes

Waiting Time:

Waiting Time is the time that comes after one event has ended and the next event has not yet begun.

Other Terms

Benchmarking:

Activities are the subparts of a process. It is an event that has a distinct beginning and ending. The activity usually results into an output.

Active Time:

Active Time is the amount of time spent on the activity explicitly.

Attribute:

An Attribute is a dimension of a record.

Bottleneck:

The Bottleneck of a process is the event that stalls production. The bottleneck is the event that requires the longest amount of time. The bottleneck holds back the whole process. The goal for many organizations is to remove or minimize the effects of the bottleneck in order to increase efficiency. In process discovery tools there are unique features that allow for bottleneck analysis so that people do not need to manually determine where the bottleneck is.

Case:

A Case is one instance of an event.

Case ID:

A Case ID a unique identifier of one case. A Case ID is associated with each record within the event log. This is what ties together all of the events related to one case and allows for processing.

Data Attribute:

Data Attribute is a characteristic of a piece of data.

Digital Twin:

Digital Twin is the online documentation of something that occurs in real life. A duplicate of the process is then stored electronically, making a digital twin.

Dimension:

A Dimension is an event’s attribute which is declared as dimension. The declaration could be automatic or manual by the user. The automatic declaration is based on the series of rules such as:
• The type of the data in the attribute is String or Number
• The count of unique values of this attribute is between 2 and 2000.
If both conditions are met, the attribute is considered a dimension. This happens during the post-load analysis.

Event Name:

The Event Name is the text that identifies what happened within the process. This could be something such as “Patient Discharged,” “Form Created,” etc.

Filtering:

Filtering puts a set of if statements onto a set of data. Filtering only outputs data that follows the terms. Filtering is a good way to find anomalies within the data and focus on the data that you want.

Financial Analysis:

Financial Analysis focuses on the cost of the process. Financial Analysis can be useful to determine what processes are costing the most for the business. Financial Analysis can help be a good start to the analysis process in order to find opportunities to cut costs.

Frequency Analysis:

Frequency Analysis focuses on the number of times an event is performed in a particular order. Frequency Analysis can be useful to determine how often processes that do not apply to conformance or other problems. Frequency Analysis can help be a good start to the analysis process.

Performance Analysis:

Performance Analysis focuses on the results of a process. This could be a positive or negative result.

Process Analysis:

Process Analysis is the step after Process Discovery. In Process Analysis the processes executed in the company are analyzed in order to understand where and how improvements are possible. Analysis consists of analyzing the “as-is” process, finding problems, and optimizing the process.

Process Animation:

Process Animation allows for simplistic visualization of a process. Process visualization shows the process flow through animation such as dots that follow the process to show speed ,lags, and flow.

Process Compare:

Process Compare allows for multiple processes to be placed side by side and analyzed. This allows for process analysis between similar processes.

Process Discovery:

Process Discovery is the first part of process intelligence. This step of the process discovers the “as-is” process execution and presents an intuitive visualization that is easily explorable. Discovery consists of extracting the data, mapping the events, and creating the “as-is” visualization. There are many software platforms that help with process discovery.

Process Instance:

A Process Instance is one particular occurrence of the process.

Process Map:

A process map is a visualization of a process. A process map can map an actual process or of the standard process.

Process Mining:

Process Mining is the process of extracting information from event logs and doing analysis in order to support the business processes.

Process Monitoring:

Process Monitoring is a way of continuously evaluating a process without having to watch flashing monitors waiting for a change. Process monitoring allows a user to input protocols. As the data is uploaded in real time the program watches for these protocols. When the protocol is violated the violation can trigger alerts to a person’s phone or email.

Protocol:

A Protocol is a predefined sequence of activities typically in a prescriptive form, i.e. the protocols are supposed to be followed. One could think of a protocol as an instruction or a cookbook. The examples of protocols: Resuscitating a patient with a cardiac arrest; Onboarding a customer with 401K rollover; Selling a product to a new customer, Defending PhD thesis, and so on.

A protocol doesn’t have to be a single linear sequence. There could be multiple protocols depending on the nature of the object (one for cardiac patient another for gunshot). There could be multiple branches within the same protocol: do something, check the result, if A – go one way, if B – go another way. There could be the protocols which happen within another protocol, for example, in the middle of patient admission process she developed the acute cardiac arrest. Moreover, the “inner” or “child” protocol could be triggered by some step in the “parent” protocol (a protocol to create new employee’s email account is triggered as one step in the overall employee onboarding process) or start completely independently by some external event, as in the case of the medical emergency during the admission process.

Process Variant:

Process Variant are the different unique paths that a process can take. Traditional process discovery will not take into account the unique process variants but rather just the most commonly followed path. TimelinePI uses its timeline analysis approach in order to show every single process variant in a timeline form.

Timeline:

A Timeline is the history of a process instance. It is the history of a sales order, an invoice, an insurance claim, a service ticket, or any other specific process over time. A timeline simply consists of events which state that something happened to this “thing” at specific time.

Timeline ID:

Refer to Case ID

Timestamp:

A Timestamp is a piece of information created with a record of information that indicates the time that the step occurred. This allows for the Timeline analysis of processes. With the timestamp the process is able to be tracked over time.

Transaction Log:

Transaction Log is the history of the processes within a business. These transaction logs are kept within systems used to do do your processes

Waiting Time:

Waiting Time is the time that comes after one event has ended and the next event has not yet begun.

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About TimelinePI, Inc.
TimelinePI provides the most comprehensive process intelligence platform designed to empower users to understand, optimize and monitor any business process. TimelinePI’s patent-pending Timeline Analysis approach is designed to allow healthcare providers, banks, insurance companies, government agencies, etc. take control of their data and Raise their Process IQ™. To learn more, we invite you to visit www.timelinepi.com or email us at info@timelinepi.com.