Processes that make our businesses agile, responsive, innovative, and better performing than competitors – this is what all businesses want. Automating key business processes is one way to achieve process optimization and improve efficiency.
But, how do you identify weaknesses in the process and which parts to automate? The decision to automate must be backed with relevant process data. This is what business process mining does! Process mining replaces speculation with facts! Event data from business systems can be extracted by business process mining tools to build an accurate, precise, and real-time picture of the process.
This blog explores how business process mining enables integrated process discovery, its use cases, and how process mining can be put into practice.
Table of Contents
What is Business Process Mining?
Business process mining or simply process mining may be considered as the intersection of business process management and data science. Process mining is a technique adopted to discover, analyze, and improve business processes by following data mining methods. Business process mining is seen as an objective and data-driven way to evaluate the real state of processes and workflows in an organization. Analysis, improvement and tracking of processes can be effectively done with the help of process mining software.
In olden days when processes were managed manually, meetings and interviews were ways to observe and understand how processes worked. This approach paints an incomplete and one-sided view of processes. Added to this, enormous amounts of resources were spent on understanding the process and gathering information, instead of improving the process. Process mining utilizes the data already stored in systems and applications to show how processes are really executed.
With process mining, you take event data from business systems to create a precise, accurate, and real-time picture of the process. You can instantly understand where a process needs to be optimized and which processes are best candidates for automation. Processes can be monitored to assess the success of automation in achieving business goals and KPIs. Process steps and workflows that have been previously invisible, repetitive, or unnecessary can be automatically surfaced, interrogated, and improved, with process mining.
The data gathered on the “as-is” state of the process and the provision of improvement recommendations can be done through process mining. This allows you to more easily track and tackle process complexity and successfully scale your automation. Process mining brings scalability into the automation program. Process mining tools help break down silos of data about how different systems and parts of the organization work and interact. Business process mining lays the foundational step to enterprise-wide automation. The combination of process mining and automation helps you build a fully automated enterprise.
Importance of Process Mining
Why should you mine business processes? Business process analysis is not a new concept. In the past, analysis of business processes was based on time and motion surveys, process mapping or process discovery, and interviews of key personnel. Process analysis is a way of assessing the “as-is” state of business processes and a way to design and model the “to-be” state of processes. While many companies have a perfectly designed process model and standard operating procedures, the reality is that they don’t match expectations.
Process mining resolves some of the key limitations of manual analysis –
- Manual process analysis rely on subjective views of the interviews or survey analysts
- Significant time, cost, and team resources wasted on conducting analysis
- Only one-time snapshot of processes available, instead of continuous results that enable tracking and improvement
Process mining is also important for automated process discovery. It gives a data-driven way to continuously improve business processes and can be used flexibly not just to discover processes but also to model and forecast the impact of process improvements. Process mining also helps uncover inefficiencies in business operations, bottlenecks in processes, and opportunities for automation more systematically at a greater scale, compared to interview-based analysis. The Global Process Mining Software Market Insights reveals that the market was valued at USD 373.9 million in 2021 and is expected to grow at a CAGR of 49% to reach USD 557.11 million in 2022 during the forecast period 2023-2030.
Companies across industries are undergoing digital transformation with the help of automation. They are constantly on the lookout for technologies that can help optimize productivity while lowering operational costs. The rapid pace at which businesses are growing fuels the demand for robotic process automation to improve productivity and performance. Integrating process mining with BPM techniques helps identify, model, and keep track of business processes.
Process mining enhances and accelerates the overall impact and speed of process improvement and process automation. Business process mining connects to source systems for a continuous view of the process execution. When AI-driven dashboards and visualization techniques are woven into the system, a significant amount of time on analysis is saved and more time is spent on automating, improving, and tracking progress for better business outcomes. Process mining tools provide real-time updates on where your processes are and where they should be. The 3 main key performance indicators that process mining can examine include –
Time KPIs – The time taken to complete a particular process.
Cost KPIs – What is the cost for completing a particular process?
Quality KPIs – Does the outcome of the process meet established criteria?
Process mining provides a significant advantage over traditional “as-is”analysis methods in being able to access real-time event data. Taking it a step further, process mining also looks into historical data, which provides process owners with the ability to closely examine event logs that provide an in-depth understanding of what’s going on in the process. The inputs from process mining help discover the actual behavior of people, organizations, and machines and compare it with existing models. Users will be able to correlate millions of events to show how reality is different from perceptions, opinions, and beliefs. Business process mining also provides a foundation for continuous improvement and building better processes.
How does Process Mining Work?
Process mining can be viewed as a 4 step method that spans data extraction to data analysis. Let us look at each step in greater detail.
Data extraction
A process mining tool is used to extract process data from IT systems. The data extracted from various processes is useful to evaluate the performance of the process. A process mining tool or data mining algorithm extracts and collects data from event logs in different enterprise resource systems, such as ERP or CRM.
Data reconstruction
Process data that is gathered is harmonized in preparation for analysis. Data analysis is possible only when data is organized into an easily readable and understandable format. Process data from various systems is cleaned up, harmonized, and then reconstructed into graphical formats to know what exactly happened when.
Data visualization
Process mining algorithms convert data of the as-is state process into a displayable format. Users must be able to visualize the process easily with data visualization. Timestamped process data is shown in a visual format in this step. Process visualization helps build advanced mining tools that help you zero in on what needs to be optimized. Process variants view or analytical dashboards show the as-is state of the business process. Once the process improvements are finalized, you can automate and improve holistically.
Data analysis
The basis for identifying process improvement opportunities is analysis of process data. Analysis of data with the process mining tool or extraction of data helps identify opportunities to streamline, automate, or other ways to improve process performance. In-depth data analysis also helps monitor processes in real time and address issues as they arise.
All about Process Mining Algorithms
Process mining algorithms are the core of process mining software. They determine how the process model is inferred from raw event data. An algorithm is used to correlate event logs to identify trends, patterns, and aggregate metrics contained in event logs. The mined data models are then compared against the original enterprise process models to check conformity, or to discover more streamlined and efficient business process models.
There is not a clear benchmark standard for evaluating and comparing process mining algorithms that is widely accepted. This creates challenges when choosing the right algorithm for a given enterprise or application domain. A high-quality algorithm is one that can easily correlate events from completely different systems and varied data sources. Since different process mining algorithms have different qualities, enterprises will have an advantage if they are able to select an algorithm that produces mined models similar to or even better than the original models.
Process mining algorithms help discover business processes and garner insights from existing application data logs. The mined data can be used to automatically generate process models and calculate process metrics. By analyzing the sequence of events with the help of timestamps, process mining can completely reconstruct actual processes while identifying and uncovering inefficiencies, bottlenecks, and other weaknesses. Owing to the availability of data, process mining can conduct process analysis agnostically.
Getting Started with Process Mining
We have evaluated process mining, process mining algorithms, and use cases of process mining. But, how to get started with process mining? As with any new process improvement initiative, the first step is to identify the pain points that need to be resolved. The starting point for any process mining project is process analysis, which closely examines the current state of the business process. The following steps can be followed to investigate the value of process mining –
Identify the problem
Pick a problem that matters to the business and one that can be realistically tackled with process mining. The next step is to determine the business value of solving it and what metrics to be used to measure success.
Identifying data
After identifying the issue that needs to be addressed, the next step is to identify the sources of data required to comprehensively understand for addressing any glaring business process problems. You also need to identify which applications and systems must provide feeds of event data for continuous transparency into the end-to-end processes.
Conducting a pilot project
A pilot project is important for proving the potential value of a process mining solution. Choose a pilot project such that it can be accomplished relatively quickly and deliver specific and measurable outcomes.
Analyzing results
Process mining gives a clear picture based on facts, so it is important that you maintain transparency on the results. Process mining tools prove to be useful in validating the business process environment.
When used the right way, process mining contributes much more than a process tool. This requires a paradigm shift that involves skilled administrators to discover issues and remediate them. Process mining tools have the capability of opening a dialogue with the rest of the organization for comprehensively and objectively addressing ongoing, systemic process issues that impact process productivity and effectiveness.
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How can Process Mining Benefit your Business?
Process mining provides several benefits for the business. These benefits could be instant and real process automation improved productivity, or improved employee satisfaction. The data gathered by process mining can also help analyze the effectiveness of employee training and improve commonly made mistakes. Armed with input from process mining tools, businesses can spot opportunities to increase sales and identify vendors that can meet the challenging demands of projects. Some of the other benefits that businesses stand to gain from business process mining are –
Increase productivity
Elimination of bottlenecks, finding new ways of handling exceptions, and eliminating inefficiencies are some of the things that can be done with the help of inputs provided by process mining. When AI and automation technologies are supported by process mining, then you can automate redundant tasks so that higher-skilled team members can focus on tasks that matter.
Reduced risk
Systems need to have a robust exception-handling system that takes care of any steps that are forgotten or missed. Optimizing a system based on what you think is happening opens up the risk of failing to account for unforeseen circumstances. Process mining reduces the risk and allows you to make confident decisions.
Increased accuracy
Process mining provides a clear picture of the system, regardless of the circumstance. Process mining also means consistency, so that more straightforward tasks follow the same process.
Objective insights
Process mining provides fact-based insights based on actual data to help managers in audit and process analysis. Process mining also helps ensure full compliance with regulations and industry standards.
Cheaper, faster, and more accurate
Business process mining provides more accurate information faster and cheaper than process-mapping workshops and other manual input processes.
Works with existing systems
Process mining can integrate with existing software systems to help you expand on your existing technological investments without the need for investing in new software technologies.
Zero-in on bottlenecks
Identification of issues within the process, deviations, and inefficiencies that need to be rethought and automated. You can also continuously monitor processes and measure improvements with business process mining.
Types of Business Process Mining Models
Process mining is executed in 3 main formats or models – discovery, conformance, and enhancement.
Discovery
This is the most common type of process mining. A discovery process facilitates the use of event log data for creating a process model without any external influence from an existing process model. With the discovery process, no information from the existing model would inform or influence the development of a new process model.
Conformance
The conformance check verifies if an intended process is used in real practice. This type of process evaluates a process description of an existing process based on its event log data and attempts to identify any deviations from the intended process model.
Enhancement
An enhancement process (also referred to as organizational mining, performance mining, or extension process) involves improving an existing process model based on data from a conformance check process. For example, the enhancement process may use the data from a conformance check process to ease a bottleneck or an unproductive variant when discovered.
Examples of Business Process Mining
There are several process mining examples or use cases, some of which are common and include improving processes, business process management, improving auditing and compliance, validation, and analysis. Each process mining example highlights and quantifies operational efficiencies that process mining brings to the organization. Some of the common use cases for process mining include –
Finance
Process mining helps improve the working capital, increase productivity of the finance team, and ensure compliance with financial operations. As the volumes of transactions increase and more businesses become digitized, manual processes do not effectively catch all anomalous behavior. Faced with increasing regulatory and audit requirements, process mining offers companies in the financial services industry the opportunities to continuously and comprehensively discover problems within high-volume processes.
Manufacturing
Process mining helps managers in the manufacturing industry gain insights into production times for a particular product and reallocate resources.
Education
Process mining enables educational institutes to monitor and evaluate student performance and behaviors, it also helps teachers and administrators in identifying which processes work best for the curriculum.
Procurement
Business process mining helps improve the efficiency of the approval processes in the procurement cycle, reduces maverick buying, and helps identify supplier performance errors.
Customer service
Process mining tools reduce the lead time of customer response, identify root-causes of issues, and improve customer satisfaction.
Logistics
Process mining ensures reliability of supply, optimizes inventory management, and improves productivity within logistics and transportation.
Healthcare
Business process mining helps minimize the treatment processing time for each patient, and even helps provide recommendations for a quicker recovery. As data about patient experiences and outcomes continue to grow, the risks around maintaining population health and individual patient journey outcomes also increases. Healthcare organizations that face an exponential increase in data, process mining helps deliver efficient and high-quality end-to-end patient journeys. Right from initial doctor consultation to closed treatment cases, process mining takes care of all the stages.
Public works
Process mining streamlines the invoice process for several stakeholders in public works departments across industries.
E-Commerce
Business process mining can help examine online buyer behavior and recommend new strategies for maximizing ROI and sales for e-commerce retailers. Retail organizations have experienced costly customer fallout from e-commerce flows due to system or process issues. Faced with increasingly high transaction volumes, process mining helps retailers ensure that customers are able to complete orders quickly and effectively without delays or issues.
Software development
Process mining can help software developers and IT administrators reorganize their development processes into a visually documented process map.
Telecommunications
As subscriber volumes continue to grow and user activations become more automated than ever, the risk of failed activations becomes significant. Process mining helps telecommunications firms to discover expensive problems and customer fallout in their order-to-activation processes.
Conclusion
Process analysis forms the basis for continuous improvement. Process mining tools can be useful in process analysis. Process mining provides full context and end-to-end perspective that is needed to improve processes and to ensure that automation delivers results. A no-code workflow automation tool like Cflow can automate key business processes without requiring even a single line of code to be written. The visual form builder in Cflow helps build workflows that suit any type of organizational requirements. The reports and analytics feature in Cflow allows for real-time updates on process cycle times and bottlenecks. Understand and analyze your business processes with a cloud-BPM solution like Cflow. Sign up for the free trial to know more.
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