Ultimate Guide to Process Mining

Ultimate Guide to Process Mining

How Does Process Mining Work?


Every single task or action that is performed on a daily basis at your business is recorded. These records are called event logs and they have existed in business for years; however, that information was never really used until process mining came along. The date and time, who performed the action, what the specific activity was, and other related information is all stored in the event log.

Process mining depends on those event logs so it starts with something called event collection. The event collection gathers all of the information that was previously untouched in the event logs and puts it together in an organized sequence to help you examine every single activity or task that is part of a specific process. Event collection gathers all of that data together. Then, the next phase of process mining takes place.

Process mining software uses algorithms to create a dynamic representation of everything going on in your processes. So, all of the rules, calculations, and other parameters that you set in your software organize your event logs which is where that true bird's eye view comes in. This is what sets process mining apart from other methods; all of the fact-based rules that you set and the data in your event logs is what creates that picture of how every single task plays out in your day to day operations.

Process mining is a method of investigating your business at every level. So, once you have all of that information in one place, you can start to answer questions and fill in any gaps. Who is doing what? When and how are they doing it? How is that serving your business? How can these things be improved? This data is automatically collected from your event logs so you don't have to piece it together on your own. Instead, you can hit the ground running when it comes to optimizing your business.

All process mining software is going to give you the tools to discover your processes and will help you analyze those processes. Some of the more full-featured programs have additional tools that go beyond those basic levels of process mining, which you will read more about later on.

The Methodology of Process Mining

Now that you understand how process mining works, we're going to examine how it gets broken down into steps. Santiago Aguirre outlined one of the most thorough methodologies in his book “Process Mining: Fundamentals and Methodology of Application." He breaks process mining down into four stages.

Stage One: Define The Project. In this stage, it is mostly preparation. This is the stage in which you will determine the problem that you're trying to solve with process mining. You'll look at the individual process you want to examine and understand the workflow associated with the process, then analyze any gaps that you may find. You will also decide on what your goals or objectives are for the process mining project, or pose any relevant questions.

Stage Two: Prepare Relevant Data. In this stage, this is when you will go through the process of event collection or your software will do this for you. You will find all of the data related to the process and extract it from all of the relevant sources. The software you choose should be able to extract all of this data and then present it to you in an organized format. You may need to double-check the quality of the data and make sure that all of the information is relevant to the process. This book was originally written in 2018 and the tools used in process mining have come a long way, so most of this can be executed entirely by the right process mining software.

Stage Three: Analyze The Process. In this stage, you will be able to look at all the data that was put together and discover the real process model as it is occurring. Using process mining allows you to strip away the ideal workflow and look at what is really going on. You can use all of this information to make sure that you're remaining compliant with any laws or regulations that your business may be subject to, you can analyze your employees' performance, as well as how the process is actually performing. You will be able to see any problems or areas throughout the workflow that might be a weak spot. After all of the data is in one place, you can use it to examine your processes and draw conclusions based on real processes rather than assumed processes.

Stage Four: Redesign The Process. In this final stage, you will determine how to improve the process based on the information that you found and your analysis of that information. In this stage, you can consider the alternatives for how the process is being carried out and determine which one is going to be the strongest option in terms of creating additional value, reducing error, increasing efficiency, and so on. This stage is also when you begin to implement the changes you decided to make and then monitor the process on an ongoing basis to ensure that those changes are providing you with the desired results.


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Three Main Types of Process Mining

Process mining uses all of the data that is stored in your event logs to help you analyze those real processes. Of course, as you've already read, this is the most basic way to describe process mining. To build on that definition, there are three main types of process mining that you can do, each serving a different purpose.

Discovery: Discovery process mining is the most simple type. This type of process mining takes your event logs as they are, with no prior information, and produces a process model based on the data in those logs. This type of process mining doesn't use any additional information; instead, the algorithms examine the event logs and create models of the real processes that are taking place. This approach is typically used just to create those models.

Conformance: Conformance process mining is a very useful approach that helps businesses find discrepancies. This type of process mining uses the event logs to create process models just like discovery; however, you will input your ideal process models into the software as well. The software uses this information in conjunction with the event logs to determine if there are any deviations in the real process versus the ideal process models. This is a diagnostic type of process mining that is used to make sure that your real processes are conforming to the outlines you have in place for how they should occur.

Enhancement: This is an extension of conformance process mining. After you've executed the diagnostic phase, this type of process mining is where you would use the information that was gathered to improve your processes and create more efficient or effective process models going forward.


Why Is Process Mining Important?

When it comes to investing in any new strategy or tool, it is important to understand how that implementation will impact and add value to your business. There are two main problems that a lot of businesses run into and process mining answers both of those in a streamlined way.

The first problem comes up in business process re-engineering. This isn't a new concept by any means; however, with the increasing capabilities of technology and the push towards automation, it tends to take center stage for a lot of businesses. This is a business management strategy that focuses on redesigning workflows to make improvements. It is a good strategy, which is why it has been around for almost half a century. However, when businesses get too caught up in how they want processes to be performed, they can neglect to examine things as they currently are. When you don't understand what is going on in your business, you can't make effective decisions on improving those processes. It's hard to tell what investments are worth it and where the problems exist when you're not examining real processes. You do not have a clear view of all of the variables. Process mining solves this problem by giving those businesses an effective blueprint for forward movement based on the reality of how things are operating.

The second problem is on the other end of the spectrum. Businesses that choose to focus on making incremental improvements instead of completely overhauling their processes all at once can get too narrow of a view on things as they are. Companies that take this approach aren't very likely to invest in something like process mining because they are only making small changes over time. This doesn't allow them to have the same overview of the data and the way that processes flow because they don't use any tools that completely integrate the information. Process mining solves this problem by putting all of the relevant data in one place and allowing those companies to examine the processes as they are but in context. Instead of interviews and disconnected data sets, process mining brings everything together so the improvements can be made objectively.

Even if your business doesn't seem to be struggling in either of these areas or falls somewhere in between on the spectrum, process mining still can provide a host of benefits.

Is Process Mining Too Old School?

One question that you may have is whether or not process mining is already outdated because of all of the different tools that exist. The concept has been around for years now and technology has already changed the shape of the business industry over the course of the last decade. This may leave you wondering if it is worth it at all, or if you would be better off putting your resources towards more modern solutions.

Dr. Gero Decker, the CEO of Signavio, said that stand-alone process mining was likely to disappear in 2019. More specifically, he said “Process mining will soon be subsumed as an inherent capability within any good professional business process analysis tool.” The main point of his argument is that process mining falls short in comparison to process discovery tools that are based on machine learning.

Reality paints a different picture. Many process mining software tools now integrate AI and machine learning. Process mining software doesn't exist independently of automation tools anymore. Instead, over the past year, those tools have become enriched by machine learning and other advanced technologies and this allows them to fit seamlessly into any existing automation strategy that you may have. In fact, process mining allows you to find places where automation could add significant value to your business and help you meet your goals more effectively.

Instead of being replaced with Automated Business Process Discovery, process mining has become the new standard of ABPD through pattern recognition advancements and AI integration. Process mining provides a strong advantage to businesses that are working towards process automation, RPA, and hyperautomation. It does so because of how detailed the data is and the fact that process mining really stresses contextual relevance.

Process mining is not at all outdated. In fact, it is taking shape as one of the strongest future strategies for businesses because it allows you to fully understand how a process takes place so it can be optimized before it is automated rather than the other way around.


How Does Process Mining Work?


Every single task or action that is performed on a daily basis at your business is recorded. These records are called event logs and they have existed in business for years; however, that information was never really used until process mining came along. The date and time, who performed the action, what the specific activity was, and other related information is all stored in the event log.

Process mining depends on those event logs so it starts with something called event collection. The event collection gathers all of the information that was previously untouched in the event logs and puts it together in an organized sequence to help you examine every single activity or task that is part of a specific process. Event collection gathers all of that data together. Then, the next phase of process mining takes place.

Process mining software uses algorithms to create a dynamic representation of everything going on in your processes. So, all of the rules, calculations, and other parameters that you set in your software organize your event logs which is where that true bird's eye view comes in. This is what sets process mining apart from other methods; all of the fact-based rules that you set and the data in your event logs is what creates that picture of how every single task plays out in your day to day operations.

Process mining is a method of investigating your business at every level. So, once you have all of that information in one place, you can start to answer questions and fill in any gaps. Who is doing what? When and how are they doing it? How is that serving your business? How can these things be improved? This data is automatically collected from your event logs so you don't have to piece it together on your own. Instead, you can hit the ground running when it comes to optimizing your business.

All process mining software is going to give you the tools to discover your processes and will help you analyze those processes. Some of the more full-featured programs have additional tools that go beyond those basic levels of process mining, which you will read more about later on.

The Methodology of Process Mining

Now that you understand how process mining works, we're going to examine how it gets broken down into steps. Santiago Aguirre outlined one of the most thorough methodologies in his book “Process Mining: Fundamentals and Methodology of Application." He breaks process mining down into four stages.

Stage One: Define The Project. In this stage, it is mostly preparation. This is the stage in which you will determine the problem that you're trying to solve with process mining. You'll look at the individual process you want to examine and understand the workflow associated with the process, then analyze any gaps that you may find. You will also decide on what your goals or objectives are for the process mining project, or pose any relevant questions.

Stage Two: Prepare Relevant Data. In this stage, this is when you will go through the process of event collection or your software will do this for you. You will find all of the data related to the process and extract it from all of the relevant sources. The software you choose should be able to extract all of this data and then present it to you in an organized format. You may need to double-check the quality of the data and make sure that all of the information is relevant to the process. This book was originally written in 2018 and the tools used in process mining have come a long way, so most of this can be executed entirely by the right process mining software.

Stage Three: Analyze The Process. In this stage, you will be able to look at all the data that was put together and discover the real process model as it is occurring. Using process mining allows you to strip away the ideal workflow and look at what is really going on. You can use all of this information to make sure that you're remaining compliant with any laws or regulations that your business may be subject to, you can analyze your employees' performance, as well as how the process is actually performing. You will be able to see any problems or areas throughout the workflow that might be a weak spot. After all of the data is in one place, you can use it to examine your processes and draw conclusions based on real processes rather than assumed processes.

Stage Four: Redesign The Process. In this final stage, you will determine how to improve the process based on the information that you found and your analysis of that information. In this stage, you can consider the alternatives for how the process is being carried out and determine which one is going to be the strongest option in terms of creating additional value, reducing error, increasing efficiency, and so on. This stage is also when you begin to implement the changes you decided to make and then monitor the process on an ongoing basis to ensure that those changes are providing you with the desired results.


Three Main Types of Process Mining

Process mining uses all of the data that is stored in your event logs to help you analyze those real processes. Of course, as you've already read, this is the most basic way to describe process mining. To build on that definition, there are three main types of process mining that you can do, each serving a different purpose.

Discovery: Discovery process mining is the most simple type. This type of process mining takes your event logs as they are, with no prior information, and produces a process model based on the data in those logs. This type of process mining doesn't use any additional information; instead, the algorithms examine the event logs and create models of the real processes that are taking place. This approach is typically used just to create those models.

Conformance: Conformance process mining is a very useful approach that helps businesses find discrepancies. This type of process mining uses the event logs to create process models just like discovery; however, you will input your ideal process models into the software as well. The software uses this information in conjunction with the event logs to determine if there are any deviations in the real process versus the ideal process models. This is a diagnostic type of process mining that is used to make sure that your real processes are conforming to the outlines you have in place for how they should occur.

Enhancement: This is an extension of conformance process mining. After you've executed the diagnostic phase, this type of process mining is where you would use the information that was gathered to improve your processes and create more efficient or effective process models going forward.


Why Is Process Mining Important?

When it comes to investing in any new strategy or tool, it is important to understand how that implementation will impact and add value to your business. There are two main problems that a lot of businesses run into and process mining answers both of those in a streamlined way.

The first problem comes up in business process re-engineering. This isn't a new concept by any means; however, with the increasing capabilities of technology and the push towards automation, it tends to take center stage for a lot of businesses. This is a business management strategy that focuses on redesigning workflows to make improvements. It is a good strategy, which is why it has been around for almost half a century. However, when businesses get too caught up in how they want processes to be performed, they can neglect to examine things as they currently are. When you don't understand what is going on in your business, you can't make effective decisions on improving those processes. It's hard to tell what investments are worth it and where the problems exist when you're not examining real processes. You do not have a clear view of all of the variables. Process mining solves this problem by giving those businesses an effective blueprint for forward movement based on the reality of how things are operating.

The second problem is on the other end of the spectrum. Businesses that choose to focus on making incremental improvements instead of completely overhauling their processes all at once can get too narrow of a view on things as they are. Companies that take this approach aren't very likely to invest in something like process mining because they are only making small changes over time. This doesn't allow them to have the same overview of the data and the way that processes flow because they don't use any tools that completely integrate the information. Process mining solves this problem by putting all of the relevant data in one place and allowing those companies to examine the processes as they are but in context. Instead of interviews and disconnected data sets, process mining brings everything together so the improvements can be made objectively.

Even if your business doesn't seem to be struggling in either of these areas or falls somewhere in between on the spectrum, process mining still can provide a host of benefits.

Is Process Mining Too Old School?

One question that you may have is whether or not process mining is already outdated because of all of the different tools that exist. The concept has been around for years now and technology has already changed the shape of the business industry over the course of the last decade. This may leave you wondering if it is worth it at all, or if you would be better off putting your resources towards more modern solutions.

Dr. Gero Decker, the CEO of Signavio, said that stand-alone process mining was likely to disappear in 2019. More specifically, he said “Process mining will soon be subsumed as an inherent capability within any good professional business process analysis tool.” The main point of his argument is that process mining falls short in comparison to process discovery tools that are based on machine learning.

Reality paints a different picture. Many process mining software tools now integrate AI and machine learning. Process mining software doesn't exist independently of automation tools anymore. Instead, over the past year, those tools have become enriched by machine learning and other advanced technologies and this allows them to fit seamlessly into any existing automation strategy that you may have. In fact, process mining allows you to find places where automation could add significant value to your business and help you meet your goals more effectively.

Instead of being replaced with Automated Business Process Discovery, process mining has become the new standard of ABPD through pattern recognition advancements and AI integration. Process mining provides a strong advantage to businesses that are working towards process automation, RPA, and hyperautomation. It does so because of how detailed the data is and the fact that process mining really stresses contextual relevance.

Process mining is not at all outdated. In fact, it is taking shape as one of the strongest future strategies for businesses because it allows you to fully understand how a process takes place so it can be optimized before it is automated rather than the other way around.