Robotic Process Automation – Process Mining

Robotic Process Automation Process Mining

What is Process Mining?

  • Process Mining is a holistic approach to process optimization.
  • Process Mining provides fact-based insights into processes, based on data stored in the corporate IT systems.
  • The insights from process mining can be used to plan successful automation, monitor the impact of a change to a process and wider business goals.
Process mining flow

     Fig 1: Process Mining flow.

Why Process Mining?

Understanding your process end to end will help in

process mining

Types of Process Mining?

Discovery

Process discovery uses event log data to create a process model without outside influence. In this classification, no previous process model would exist to inform the development of a new process model. This type of process mining is the most widely used model.

Conformance

Conformance checking confirms if the intended process model is reflected in practice. This type of process mining compares a process description to an existing process model based on its event log data, identifying any deviations from the intended model.

Enhancement

This type of process mining has also been referred to as extension, organizational mining, or Performance Mining. In this type of Process Mining, additional information is used to improve an existing process model.

Types of process mining

Where does “Process Mining” fit within RPA Platform?

  • Process Mining gives you data driven insights and understanding of complex end to end processes, to continuously optimize and accelerate automation in the context of processes.
  • The product belongs to the “Discover” stage of the RPA Platform.
Process Mining fit within RPA Platform

How does Process Mining works?

Process Mining transforms the data into an event log and then creates visualizations of the end to end process, along with insightful analysis.

Step 1:Discover your process using Digital Data.

  • For ex: Enterprise system—like SAP, Salesforce or Oracle—captures event data related to your processes.
  • Process mining reads this data and transforms it into an event log.
  • Event Log contains 3 key Information I.e. Time stamp, Case ID, an Activity.

Step 2:Analysis of Event Log Data.

  • Using the Event Log data, Process mining tool creates a process graphs, that helps us understand the process.  I.e. It includes Timing of each step and all the variations in the process flows.

For ex: Ideal Process is the happy flow of the Process show in Fig1.

Fig 2. shows Process Mining graph created on the right based on Event log helps us understand the process deviations, Process exceptions, workarounds, workflow inefficiencies if any in the process.

What process mining reveals

Fig 1: Expected Process                                                         Fig 2: Actual Process

Step 3: Prioritize and Optimize

Process Mining Tools helps us to prioritize, what can be optimized, how to do it and what the return on your efforts will be on the automation solution build. 

Return on Investment (ROI) = More efficient RPA Projects + More efficient Business

More Efficient RPA Projects = Complete Processes x % Faster

Process Mining Best practices?

  • Understand the end- to – end processes -> Visualize and analyses your current processes and view automation rates.
  • Identify the best processes for RPA -> Use process insights to streamline processes.
  • Automate and monitor end to end -> Automate the most profitable processes and keep monitoring the bots.
  • Follow up and improve -> Utilize machine learning techniques that helps in predictions that are going to be late.

What are the typical “Use cases” for Process Mining?

Process Mining is beneficial for many situations in organizations, where process mining methodology has been applied actively, although other areas also can gain immediate benefits from using the same process mining models.

Some of the most common Process Mining use cases are as follows:

Robotic process automation

Understand the actual process, variations and automation opportunities in order to succeed in RPA Projects.

Process KPI Reporting

Create complete process KP I’s and dashboards for any given process.

Digital Transformation

Understand the “big picture” how organization work, what to prioritize, and what to transform

Auditing and compliance

Drive Compliance with agreed processes, rules and regulations.

Process Improvement

Identify Bottlenecks, rework and other symptoms of inefficient processes.

Note: Some of the common industries where process Mining is applied are Banking and Finance, Telecommunication, Manufacturing, Management Consulting, Retail etc. 

How does “Process Mining” help the businesses to succeed?

Process Mining enables discovery, monitoring and improvement of real processes by extracting knowledge from event logs and cane be used to speed up the Delivery.

  • Integration, Automation and Collaboration.
  • Removal of Process conflicts/Deadlocks.
  • Continuous Improvement: evaluate improvement ->identify shortcomings-> improve again
  • Cost reduction ->reduction of throughput  -> elimination of defects
  • Mitigation of Threads and Risks.
  • Enhance customer satisfaction.

Most commonly used Process Mining Tools?

Below mentioned are the TOP 4 Process Mining Tools:

  • UIPATH Process Mining
  • Celonis
  • Nintex Promapp
  • IBM Blueworks Live

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Welcome to SOAIS Newsletter of September 2021!

Continuous Testing with Remote Execution
 
The speed of innovation continues to increase, driving rapid and relentless change for today’s ever-evolving IT landscapes, creating greater risk as IT and business teams scramble to ensure timely delivery. How can your organization keep pace? Test more, worry less. With Worksoft’s Connective Automation Platform, you can easily build and maintain automated tests, accelerating testing time without losing scope or volume. You can schedule and execute remote, continuous tests to intercept defects sooner and prioritize remediation - without sacrificing your nights and weekends. Explore how continuous test automation and remote execution can empower your organization.

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Change resiliency is imperative in ever-evolving IT environments. Our patented object action framework streamlines change management by assigning object definitions to your shared assets. The same object may be used in a thousand automation steps, but it can be easily updated by making one simple change to the model definition. The change automatically propagates to every single instance where that object may have been used without a single line of code or manual human involvement. For more change readiness you can also engage our Impact Analysis for SAP to predict how changes in SAP transports will affect your business processes. 

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SOAIS Blog – Nuts and bolts of Certify Database Maintenance​

One of the key thing, which is often missed by the organizations, who have invested in using Worksoft Certify for automating their Business Process Validation initiatives, is implementing a Database Maintenance Plan. While the business and the test automation consultants get excited about the shiny new thing that they have got and start building the regression suite; planning and executing a database maintenance plan for most of the customers gets pushed down the priority list. However, since all the test assets in Certify are stored in a Database, a robust database maintenance plan is very important to maintain smooth operation of Certify with acceptable performance criteria. The customers usually start facing issues once they have built significant number of Certify processes which they have started executing on regular basis. Such executions add a lot of data to the tables storing results data and increase the overall size of the Certify database.

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Worksoft Blog – Process Intelligence: A Multi-Dimensional Approach

The ability to extract process knowledge has become easier through the years. Technology has evolved to the point where we can deploy capabilities that connect at multiple levels to extract different types of process insight. In the past, organizations were forced to spend enormous energy extracting data manually from different applications and databases. Then, they would have to use things like spreadsheets to transform the data and convert it into meaningful information. 

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