Q 350. What is process mining? How does it help in Robotic Process Automation?

 

 

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RPA practice has become a very important lever to deliver high-cost savings and reducing the dependency on humans for unskilled and repetitive tasks. RPA is successful when deployed at the appropriate process and scale. In achieving the desired outcome from RPA, Process Mining has gained a lot of relevance and has become an integral part of the RPA.

 

RPA concerns with the automation of business processes, enabling companies to strengthen cost effectiveness and quality improvements. The most critical stages of a RPA project is to pick the intended business process to be automated. However, RPA isn't the means to all or any ends and may be deployed randomly across the processes. The intended automated process must be selected carefully to profit the foremost from RPA. This is often where the critical question must be answered, where and the way do we chose the eligible process for a feasible RPA Deployment. Often the business process that's most eligible for RPA has activities that are repetitive, standardized and transactional. But how do we validate exactly which business process is that or one qualifies the minimum requirement for an RPA. Although most of the business owners and operators would have a good idea how the daily operation works, the important deal is to travel beyond a good understanding to the key stroke level details. This is often where Process Mining comes in. Use Process Mining techniques to construct the AS-IS processes by using event logs, identify and choose the processes that benefit the foremost from automation!

 

Advantage of Process Mining

Over the past few years, Business process optimization practitioners constructed the AS-IS process using qualitative methods. With Process Mining's ability to get data and supply insights into the method inputs, flow and output. We now have access to quantitative data points and trends to analyze the simplest fit process. Because the tactic model is made by data its objective and more reliable than as-is process constructed by qualitative methods. The info is extracted from IT-systems that store data and make event logs. The events range from online transactions from an e-commerce website, a business’s offering various discounts and finance schemes to adopt prepaid payment methods over post-delivery methods made through their platform. After the as-is process is made it are often extended with perspectives that are relevant to the business case or the question that possesses to be answered. Process Mining will generate data and help us to identify the frequency of repetitive activities, significance costs or resource use, slowdown time as well as waiting time, process bottlenecks, waste and barriers for a smooth process.

 

Integration of  RPA and Process Mining

Now that  we have recognize what RPA and Process Mining are, the next step it to integrate how  RPA-project can leverage Process Mining. Processes and RPA executioners simply don't only need to use Process Mining as an area of a RPA-project, it's also valuable before or after a RPA-project.

 

Here are some examples:

 

Pre RPA Deployment

Process Mining was performed before automation to optimize a business process.

Process Mining allows for locating the business process where redundancies and process inefficiencies are exposed. This is often beneficial for RPA, as for RPA to be most successful the variation within the business process should be minimized. Before RPA it's better to standardize the processes variation to make high volumes per process variation. This helps in RPA to be used as efficiently as possible.

 

During RPA Deployment

Conduct Process Mining as a sub activity of a RPA-project to supply an objective overview of business processes. It help in making the particular process transparent by a data-driven perspective whereby repetitive activities, bottlenecks and process loops are shown. By doing so we'll identify the sole processes to be automated next.

 

Post RPA Deployment

The data generated by automation enables continuous improvement in terms of further optimizing the algorithms making the tactic add the backend. Use the info for Process Mining techniques to research the tactic and determining the specified outcome, effectiveness of the automation and subsequent improvements

A defined series or steps of action, repeated in a pattern in a progression from defined “start” point to a defined standard “finish” is called a process. This ensures consistency in a commonly understood flow and thereby provides a structure for any task to be completed as effectively, efficiently and consistently, as possible.

A good process is like a checklist, which can be measured in terms of effectiveness and efficiency. This is important, as a measurable process provides for the focus to make it better to provide better results/ outcomes. The best way to determine the effect of the process is to identify trends, patterns and details of how the process runs through analysis of relevant data and improve wherever there is scope for improvement.

Process Mining is an analytical discipline, which enables the above, by discovering, monitoring and improving process as they are in their current structure, by extracting knowledge from event logs made available through the advanced information technology systems. Process Mining offers objectives, fact based insights derived from actual relevant data from within the process and it’s output. This data helps to audit, analyze and improve the existing business processes, by answering compliance related as well as performance related check points.

It is very important that process mining is data driven as the idea is to discover the map of the process in some domain. Hence, the process in focus needs to;

-          Leave some trace in our system (Log entry required)

-          Be repeated a few times, so that the data is regular for the patterns to be evident.

Based on the Event logs and the study of the pattern, Process Mining provides 3 types of information;

Discovery- Data driven approach to produce a process map, based on event logs.

Conformance- This is a method that helps to confirm if there are any breaks in the desired rules or any outliers.

Enhancement- This method helps to improve the discovery and conformance process with an improvement in the theoretical process map. You may be able to understand how the repeated processes can be done by a machine instead of a human being, thereby reducing the chances of human error.

It goes without saying that when the processes operate efficiently, the organization is agile and it is easy for it to adapt to any outside forces, allowing more time to focus on revenue and profitability.

In today’s world with so much technological opportunities in machine learning and IOT, we are seeing so many new methods from which we can take big and better business decisions through enhanced processes and generate better business values- lesser cost and more returns. Hence, Organizations want to execute maximum capacity and hence need flexibility in processes which can come only through a deep understanding of how things are working and where modifications are possible.

Many organizations leverage process mining to understand which processes are good and ready for automation. It is a pragmatic approach to select stable standardized processes which are data- centered with easy repeated tasks and deploy automation. Process Mining helps to discover the business process where redundancies and process inefficiencies are evident. This is favorable for RPA as for it to be successful, the variation in the business process needs to be minimized

RPA (Robotic Process Automation) helps to transfer the execution of such processes from humans to bots. RPA interacts with the existing IT infrastructure and helps to automate workflow of process which are labor intensive – thus eliminating the scope of any human error and reducing cost of labor in many cases.

Sundeep's answer has been selected as the best answer for the examples quoted for use of process mining at various stages of RPA. 

 

Rajesh's answer is also a must read as he has highlighted the 3 types of process mining.