Process Mining
Discover how Process Mining is transforming process insight and efficiency.
What is Process Mining?
Process Mining is a class of tools and solutions that help users monitor, improve and extract value and insight from processes in an enterprise.
Process Mining constructs and visualises processes using data extracted from the business IT system. This presents users with a representation of business processes that are based on data and truth, rather than the subjective opinions of the people involved in them.
What are the benefits of Process Mining?
Cost reductions
By identifying automation opportunities and areas of process inefficiency, Process Mining can greatly help reduce operating costs.
Process understanding
Traditional methods of process analysis are highly subjective, but Process Mining is based entirely on data. This provides an objective, detailed and accurate understanding of all structured processes in the business.
Better customer experience
By identifying process breakdown and boosting efficiency, Process Mining contributes to a more streamlined and satisfying customer experience, strengthening customer loyalty.
Happier employees
Process Mining helps to remove unnecessary bottlenecks and repetitive mundane tasks, enabling employees to focus on the work they most enjoy.
How does Process Mining work?
Modern business processes depend on data and IT systems from beginning to end.
As employees and software bots execute these processes, their actions are recorded as event data in corporate IT systems like SAP and Salesforce. Process Mining processes this information and turns it into event logs for further analysis.
Event logs usually contain a timestamp, a case ID and a relevant activity. From this information, Process Mining tools will create a process graph, which is a visual representation of a real business process. This gives users a detailed picture of the process, including all exceptions and variations that occur at any point.
From a process graph, users will be able to see inefficiencies as well as potential workarounds and automation opportunities. This gives them the insight they need to make positive interventions - whether it’s the deployment of RPA bots or the removal of unnecessary tasks - that improve the overall efficiency of the process. With Process Mining, they can also track the amended process to assess the impact of those interventions.
Why should companies use Process Mining?
Alongside automation tools like RPA, Process Mining has been critical for boosting operational efficiency in the enterprise. Process Mining allows businesses to digitise their processes, making them easier to understand, monitor and improve.
Prior to Process Mining, business and operations teams had to perform manual process mapping exercises in order to understand the processes the enterprise runs on. Process mapping could be a time-consuming and costly endeavour, pulling employees away from their work to interview them on process efficiency. For large enterprises with hundreds or even thousands of processes, the cost could be great and there was no guarantee the findings would be accurate. Employee opinions are highly subjective and they often produce results that are heavily skewed and not representative of process reality.
Process Mining puts a stop to this. By analysing only event logs and structured data in enterprise IT systems, Process Mining produces results that are unaffected by outside opinion. Instead, users can construct an objective and extremely detailed picture of all their business operations,while sidestepping the time-consuming task of process mapping. Instead, they can automatically see where inefficiency exists in the enterprise.
However, it’s important to remember that Process Mining doesn’t provide a complete picture of business operations. Process Mining needs data to build its representations, but that means that processes which can’t easily be tracked in data won’t be understood. Many business processes, like responding to emails or triaging service requests, are dependent on unstructured data which can’t be processed by Process Mining tools.
For complete insight and understanding over all processes, a business will need to supplement Process Mining with a capability like Conversational Data Intelligence. This class of solutions uses machine learning and natural language processing (NLP) to turn unstructured communications into structured data.
Where can Process Mining be used?
Process Mining has wide applicability across industries, functions and departments. Any enterprise where the number of people and processes is difficult to keep track of can benefit from Process Mining solutions. Small teams working in non-complex businesses may not need to invest in Process Mining software. However, a sizable business should invest in Process Mining as it scales its number of people and processes.
Process Mining has three primary uses:
Process discovery
Process Mining produces detailed process models using data to create event logs. From these visualisations, analysts can understand how processes operate in the business and can find opportunities for efficiencies and automations.
Process enhancement
Process Mining can be used to flesh out and improve an existing process model. For example, this could be through extending a process model with performance data.
Process monitoring
Event logs can be analysed to gain an understanding of how a process is performing. This is very useful in measuring the impact of changes to the process and when validating the process for compliance purposes.
Is Process Mining a type of AI?
Process Mining isn’t considered a form of artificial intelligence (AI). However, Process Mining can use AI technology to achieve its goals, and increasingly both technologies are being integrated in a category known as Intelligent Process Mining.
Process Mining software often leverages AI, machine learning and natural language processing technologies to automatically extract, visualise and understand operational data from the IT systems of an enterprise. AI is important, not just for detecting and suggesting root causes but also for predicting when potential problems may arise in the future.
Is Process Mining the same as Task Mining?
Process Mining and Task Mining are different solutions, though both use structured data to measure and monitor business performance.
In Process Mining, insight is extracted from event logs that are already available in an organisation’s information system. This allows users to monitor business processes in real time. Task Mining, on the other hand, captures user interaction data - such as the frequency of mouse clicks on a desktop - to help businesses understand how their people are getting work done.
Both tools are important in enhancing process understanding and improvement. But Process Mining is focused on the efficiency of structured processes while Task Mining is more concerned with the actions of employees and their efficiency.
Is Process Mining the same as Communications mining?
Process Mining and Communications Mining are distinct but complementary solutions.
Process Mining depends on structured data to give users visibility into business processes and an understanding of process efficiency. Communications Mining, meanwhile, is an application of Conversational Data Intelligence, a class of enterprise software that uses machine learning, natural language processing and human employees to drive understanding and automation in unstructured conversational data.
Communications Mining focuses on understanding and extracting value from unstructured data and communications processes. It’s the practice of converting the unstructured information these processes are built on into structured, machine-readable data that can then be used for analysis and automation.
Communications Mining is the ideal accompaniment to Process Mining. Where Process Mining analyses structured data to give you an understanding of process efficiency, Communications Mining makes sense of unstructured data to show you the root causes of process breakdown. Process Mining shows you the ‘how’, while Communications Mining explains to you the ‘why’.
When used in parallel, there is no data - structured or unstructured - that a business can’t analyse or understand. Businesses often use Communications Mining to uncover signs of friction and inefficiency, before leveraging Process Mining tools for deeper analysis to see what impact these events are having on processes.
