Business Intelligence (BI) and Process Mining assist decision-makers in analyzing organizational data.
Business processes can be complicated and spread out across different systems in larger companies. Analyzing these processes through traditional methods can be time-consuming and involve a lot of manual work to gather and refine data. However, process mining simplifies this process by automating many of the necessary steps, allowing you to concentrate on improving your processes to achieve better outcomes.
Finding and connecting the data
The first step in building a process mining engine is finding the data you want to analyze, and why. For most companies, this comes from the data already available in IT tools and systems, like your:
- Enterprise resource planning (ERP)
- Enterprise asset management (EAM)
- Enterprise service management (ESM)
- IT service management (ITSM)
- Supply chain management (SCM)
- Human resource management (HRM)
- Customer relationship management (CRM)
To perform process mining, all you need is time-stamped action or event data. The advantage of process mining over other data analytics areas is that it uses very detailed event data, such as the precise time when an order was placed, so there are hardly any concerns about data quality.
Once you’ve linked the right data and systems to your process mining platform, you can take a break and let the platform do the work of connecting the dots while you grab a cup of coffee.
Process discovery
For some companies, this may be the first time seeing their operations and processes from a bird’s eye view and at scale.
Process mining tools use a special code, like an order number or customer ID, to sort out data and create event logs that show what activities were done and when along with other details. They focus on collecting the data that will help improve the process.
Process and root cause analysis
Root Cause Analysis is a method to identify why problems occur in your processes, such as bottlenecks, rework, or exceptions. It shows these issues in flowcharts and ranks them based on how much they affect business results. This helps you decide which problems to tackle first and take action to improve your business operations.
As you can see in the diagram below, this organization is now able to see the as-is flow of their Order to Cash process, along with the initial bottlenecks and errors.
Conformance analysis
Automation
After improving your processes, process mining can identify which ones are best suited for automation, in order of priority. By evaluating the expected ROI, you can determine which processes should be automated, and easily scale up automation efforts. In simpler terms, process mining can help you decide which processes are worth automating by looking at the potential return on investment, allowing you to prioritize automation and scale it up easily.
Reference: The business leader’s guide to process mining
Business Intelligence (BI) and Process Mining assist decision-makers in analyzing organizational data.
Business processes can be complicated and spread out across different systems in larger companies. Analyzing these processes through traditional methods can be time-consuming and involve a lot of manual work to gather and refine data. However, process mining simplifies this process by automating many of the necessary steps, allowing you to concentrate on improving your processes to achieve better outcomes.
Finding and connecting the data
The first step in building a process mining engine is finding the data you want to analyze, and why. For most companies, this comes from the data already available in IT tools and systems, like your:
- Enterprise resource planning (ERP)
- Enterprise asset management (EAM)
- Enterprise service management (ESM)
- IT service management (ITSM)
- Supply chain management (SCM)
- Human resource management (HRM)
- Customer relationship management (CRM)
To perform process mining, all you need is time-stamped action or event data. The advantage of process mining over other data analytics areas is that it uses very detailed event data, such as the precise time when an order was placed, so there are hardly any concerns about data quality.
Once you’ve linked the right data and systems to your process mining platform, you can take a break and let the platform do the work of connecting the dots while you grab a cup of coffee.
Process discovery
For some companies, this may be the first time seeing their operations and processes from a bird’s eye view and at scale.
Process mining tools use a special code, like an order number or customer ID, to sort out data and create event logs that show what activities were done and when along with other details. They focus on collecting the data that will help improve the process.
Process and root cause analysis
Root Cause Analysis is a method to identify why problems occur in your processes, such as bottlenecks, rework, or exceptions. It shows these issues in flowcharts and ranks them based on how much they affect business results. This helps you decide which problems to tackle first and take action to improve your business operations.
As you can see in the diagram below, this organization is now able to see the as-is flow of their Order to Cash process, along with the initial bottlenecks and errors.
Conformance analysis
Automation
After improving your processes, process mining can identify which ones are best suited for automation, in order of priority. By evaluating the expected ROI, you can determine which processes should be automated, and easily scale up automation efforts. In simpler terms, process mining can help you decide which processes are worth automating by looking at the potential return on investment, allowing you to prioritize automation and scale it up easily.
Reference: The business leader’s guide to process mining
Business Intelligence (BI) and Process Mining assist decision-makers in analyzing organizational data.
Business processes can be complicated and spread out across different systems in larger companies. Analyzing these processes through traditional methods can be time-consuming and involve a lot of manual work to gather and refine data. However, process mining simplifies this process by automating many of the necessary steps, allowing you to concentrate on improving your processes to achieve better outcomes.
Finding and connecting the data
The first step in building a process mining engine is finding the data you want to analyze, and why. For most companies, this comes from the data already available in IT tools and systems, like your:
- Enterprise resource planning (ERP)
- Enterprise asset management (EAM)
- Enterprise service management (ESM)
- IT service management (ITSM)
- Supply chain management (SCM)
- Human resource management (HRM)
- Customer relationship management (CRM)
To perform process mining, all you need is time-stamped action or event data. The advantage of process mining over other data analytics areas is that it uses very detailed event data, such as the precise time when an order was placed, so there are hardly any concerns about data quality.
Once you’ve linked the right data and systems to your process mining platform, you can take a break and let the platform do the work of connecting the dots while you grab a cup of coffee.
Process discovery
For some companies, this may be the first time seeing their operations and processes from a bird’s eye view and at scale.
Process mining tools use a special code, like an order number or customer ID, to sort out data and create event logs that show what activities were done and when along with other details. They focus on collecting the data that will help improve the process.
Process and root cause analysis
Root Cause Analysis is a method to identify why problems occur in your processes, such as bottlenecks, rework, or exceptions. It shows these issues in flowcharts and ranks them based on how much they affect business results. This helps you decide which problems to tackle first and take action to improve your business operations.
As you can see in the diagram below, this organization is now able to see the as-is flow of their Order to Cash process, along with the initial bottlenecks and errors.
Conformance analysis
Automation
After improving your processes, process mining can identify which ones are best suited for automation, in order of priority. By evaluating the expected ROI, you can determine which processes should be automated, and easily scale up automation efforts. In simpler terms, process mining can help you decide which processes are worth automating by looking at the potential return on investment, allowing you to prioritize automation and scale it up easily.
Reference: The business leader’s guide to process mining