Process mining is one of the hottest areas of enterprise software investment. According to recent research by Deloitte 63%1 of global companies have started using process mining and most global business plans to at least pilot process mining in the near future.
What is process mining software?
Process mining software is any tool that allows you to discover, analyze and improve business processes using computer science and data mining methods. The goal of process mining software is to provide an X-ray into your business processes - enabling process conformance, identifying potential bottlenecks and improving efficiency.
You can see process mining at the intersection of business process management and data mining. In this way, process mining tools are any software that interacts with business software systems to extract process information, typically in the form of event logs or business objects, for the purpose of process analysis and business process improvement.
Process mining is often viewed as an enabler for continuous improvement or operational excellence. Process mining can be used in a business organization to:
- monitor the execution of processes,
- check conformance to agreed processes models,
- identify opportunities to streamline workflows,
- automate repetitive tasks,
- discover ways to reduce costs.
Process mining techniques
Much of the theoretical background of process mining has been defined in the Process Mining Manifesto - which defines three key types or techniques of process mining.
Process discovery: The most adopted of process mining, process discovery, uses event log data to create a process model without outside influence. The goal of process discovery is to get an objective "as is" view of processes within an organization.
Process conformance: Conformance checking confirms that intended process models are reflected in practice. This type of process mining compares a process to an "should-be" process model based on its event log data, identifying potential deviations.
Process enhancement: In this case additional information is used to improve an existing process model, for example, location data, costs, or timing. By enhancing process models, the aim is to allow for advanced analysis in order to improve processes. Some process mining solutions, for example, align with process modeling standards such as BPMN and allow exports of process mining data to BPM tools.
What are the benefits for using software for process analysis?
Process mining is an automated solution for process analysis. As such, it comes with a number of benefits compared to the more traditional manual form of business process analysis:
- Objective transparency. In the past, process analysis was often done based on questionnaires, surveys or workshops. Compared to these manual forms of analysis, process mining is more transparently data-focused and objective.
- Continuous insights. Once process mining software is configured, it can provide a continuous stream of insights and automatically provide updates on progress to key targets.
- Identify root causes. As process mining software provides a deep level of detail into event log data, it can be used to uncover not only inefficiencies but the underlying issues behind them that may be less visible.
- Diagnose bottlenecks intuitively. Process mining can also provide far more data on key points of failure, for example, through process variance graphs that can be sliced and diced for additional detail.
Process mining doesn't replace the need for experts to drive analysis and process improvement, but instead it equips process analysts and operational excellence professionals with the insights needed to optimize and automate digitalized work.
What to consider when choosing process mining software
When selecting process mining software, there are several key considerations that should be taken into account.
- Scope of analysis. The software should be able to provide a comprehensive analysis of the process data, making use of both current and historical data.
- Granularity of insights. The tool should also be able to provide accurate insights into inefficiencies and bottlenecks, and provide an easy-to-use interface that makes it simple to identify and assess new and existing processes.
- Integration needs. Many process mining solutions require access to event logs from different source systems. If you have a fragmented enterprise software landscape you'll need to consider how much integration effort will be required to data mine key processes.
- On-premise or cloud. While many process mining solutions are today offered as software-as-a-service (SaaS) some organizations may require on-premise solutions.
- Total cost of ownership. While every organization will have different resources to implement a process mining tool, you should consider the total cost of implementation including both the price and resources required to achieve results.
Process intelligence as an alternative
While process mining is undoubtedly popular - there is an alternative to consider. Process intelligence software, such as Workfellow, can deliver most of the use-cases of process mining without the need for data integration and data mining. Instead it uses advanced data capture technologies and AI to collect relevant business object data directly from the enterprise work stations.
Modern process intelligence software like Workfellow provide the upsides of process mining while also giving some additional benefits.
- Real-time data analysis
Workfellow analyses real-time data revealing the current performance of an organization and alerting in case of any deviations on an ongoing basis. It covers all business work-related applications, systems, and documents, leaving no space for undocumented “shadow” work that might not be covered by event logs.
- No upfront development needed
Process intelligence platform starts running and collecting data right away, without having to do multiple integrations and occupying IT peoples’ time for the data extraction.
- All prior and subsequent analysis is done automatically
Workfellow platform collects the data independently by observing all work-related activities within teams. This is the data that reveals the reality of work so no data scrubbing/cleansing is needed.
Once data insights are ready, the platform automatically analyses them and provides suggestions for further actions, taking up the role of a business analyst and data analyst.
- First results within weeks rather than months
Workfellow needs only 2 weeks before it starts generating business cases and data-backed solution recommendations for them.
Are you interested to finding out more about process intelligence? Read the Work API whitepaper!
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Process Mining Q&A
Process mining and task mining both provide insights relevant to business process management, but they work in slightly different ways. Process mining gathers data from event logs in enterprise source systems, while task mining gathers information from the user interface of workstations.
Process intelligence is the use of business intelligence strategies and technologies in business process management. Process intelligence can be used to remove bottlenecks or improve operational efficiency, and it can be used as a catalyst for business process re-design.
Process intelligence is a comprehensive approach to understanding and optimizing business processes by leveraging data and analytics. Process mining is a subset of process intelligence that focuses on analyzing event logs generated by information systems, such as ERP or CRM applications.
While process mining can be applied across various industries, it is particularly beneficial for businesses with complex processes and high volumes of data. These organizations can leverage process mining to gain valuable insights into their processes and drive significant improvements in efficiency, cost savings, and customer satisfaction.
Process mining helps organizations identify inefficiencies, redundancies, and deviations from standard procedures, enabling them to reduce resource consumption, avoid costly rework, and improve overall process efficiency, leading to significant cost savings.
Process mining provides a transparent view of business processes, allowing organizations to monitor their adherence to laws, regulations, and industry standards. By identifying and addressing deviations from standard procedures, businesses can reduce their exposure to compliance risks.
Yes, by reducing throughput time and streamlining customer-facing processes, process mining can help organizations deliver products and services more quickly, resulting in faster response times and an enhanced customer experience.
Process mining is a subset of business intelligence where you combine BI methodologies and data science techniques to business process management.
Process mining and RPA are complimentary intelligent automation technologies. Process mining finds insights by extracting and mining event logs in enterprise systems to uncover process improvement opportunities while RPA enables the automation of repetitive business processes.