Process discovery is a key aspect of business process management and a significant enabler of operational excellence. In this guide, we go through what enterprise leaders need to know about process discovery - including definitions, examples, and best practices.
What is process discovery?
Process discovery is a series of techniques and tools used to define, outline, and analyze business processes. It provides a measurable understanding of how people carry out daily operations and processes in the workplace.
Discovering processes is one of the most critical steps in understanding how the organization works and, frankly speaking, is a prerequisite for any successful automation project or process transformation.
Later in this guide, we'll see how business process discovery can be done through interviews, as part of process redesign, and through automated process discovery software. Across different approaches, process discovery offers a number of key benefits:
- Process visibility
- Improved processes
- Increased cost-efficiency
- Improve digitalization
- Increase automation
Who is involved in a process discovery
Process discovery tools can be used by any business unit, function, or industry that has key processes that can be measured and improved.
It is typically conducted in enterprise businesses by a team of experts or external consultants. The people involved in a process discovery typically include:
- Process engineers - responsible for understanding and optimizing the efficiency and quality of business processes.
- Subject matter experts - the individuals or experts with specialized knowledge in a field or process.
- Data analysts - the data scientists who analyze data and create business intelligence solutions and reports.
- Business analysts - an expert in the use of data and analytics to meet business goals and objectives.
Depending on the nature of the process, additional stakeholders can include product or project managers, IT personnel, and executives. All of these stakeholders will work together to understand the current state of the business process, identify areas of improvement, and develop recommendations for optimizing it.
Common pain points revealed by process discovery
By analyzing how a process is actually carried out, organizations can uncover inefficiencies, bottlenecks, and other areas for improvement. Some common pain points uncovered by process discovery include:
- Manual and repetitive tasks: These tasks are not only time-consuming but also prone to human error. Identifying such tasks can pave the way for automation, reducing errors and improving overall efficiency.
- Process deviations: In many cases, employees may not follow the prescribed process or may use workarounds, leading to inconsistencies and inefficiencies. Business process discovery can help identify these deviations and address the underlying issues.
- Bottlenecks and delays: Some steps in a business process may take longer than expected or hold up other tasks, causing a bottleneck. Identifying these bottlenecks can help organizations restructure business processes to eliminate delays.
- Lack of visibility and transparency: It can be difficult for management to understand the current state of a process, especially if it involves multiple departments or teams. Business process discovery can provide valuable insights into the process, highlighting areas that need improvement or attention.
- Compliance issues: Process discovery can help identify steps where an organization may not be following regulatory guidelines, helping to mitigate potential risks and ensure compliance.
- Ineffective use of resources: one can uncover areas where resources, such as employees, equipment, or budget, are not being utilized effectively, and help organizations allocate resources more efficiently.
- Poor integration between systems: Many organizations use multiple software systems, which can create issues when information needs to be transferred between them. Process discovery can identify these integration issues and help organizations find ways to better connect their systems.
Process discovery interviews
Process discovery has been an established aspect of an effective process analysis strategy for decades.
Before dedicated process discovery software came into existence, companies would conduct time and motion studies, business process discovery workshops, and interviews with key stakeholders to map out current processes and manually find any inconsistencies or bottlenecks.
In-person process discovery is effective but it has its limitations. It would take a considerable amount of time and resources, yet most decisions would still be based on assumptions and intuition. Interviews by business process analysts (BPA) were time-taking but effective ways to get an understanding from subject matter experts (SMEs).
Audits still happen today, but they are increasingly being replaced by advanced software solutions.
Examples of questions asked in a process discovery interview
- What usually triggers this process or workflow? Are there other triggers that can start this process?
- What is the first process step to start the process? What output is created from starting this step?
- Who performs this step? What are the applications / IT systems used to perform this step?
- How often is this step performed every day/week/month?
- Can you identify business challenges to this step specific in the process? What is done to resolve these challenges?
- How is this process step measured? Are there key performance indicators (KPIs) for performance?
- How much time does it take to perform this step of the business process?
From process discovery to implementation
One way to view process discovery is from the perspective of continuous improvement and process optimization. In other words, the goal of process discovery is to methodologically explore the "as is" current state of processes and aim to implement an improved "to-be" model. This process discovery method can be broken down into nine concrete steps.
The 9-step method from process discovery to effective implementation
The key steps in process discovery are:
- Define objectives and scope: Clearly define the goals of the business process discovery project, such as identifying inefficiencies or preparing for automation. Determine the processes that will be examined and the scope of the analysis.
- Gather information: Collect information about the business processes under examination from various sources, such as documentation, existing process maps, system logs, and interviews with employees involved in the process. This information will help create an initial understanding of the process.
- Observe and document: Observe the business process in action to see how it is actually being executed. This can involve shadowing employees, conducting workshops, or using process mining tools to analyze system logs. Document the observed steps, participants, and flow of the process.
- Analyze process data: Analyze the collected data to identify inefficiencies, bottlenecks, deviations, and potential areas for improvement. The business process analysis should also include reviewing the use of resources, such as personnel and technology, and assessing the overall performance of the process.
- Validate findings: Validate the discovered business process with stakeholders and subject matter experts to ensure accuracy and completeness. This step might involve refining the process documentation or making adjustments based on feedback.
- Identify improvement opportunities: Based on the analysis and validation, identify areas where the processes can be improved, streamlined, or automated. Develop recommendations and prioritize them based on their potential impact and feasibility.
- Implement changes: Work with stakeholders to implement the recommended improvements. This may involve updating process documentation, adjusting workflows, reassigning resources, or implementing new technologies.
- Monitor and evaluate: After implementing changes, monitor the business processes to ensure the desired improvements have been achieved. Evaluate the results and identify any further opportunities for optimization.
- Continuous improvement: Business process discovery should be an ongoing effort, with regular reviews and updates to ensure processes remain efficient and effective as the organization evolves.
In this method, the aim is to discover and document clearly the way current processes are and how to introduce and implement improvements in a continuous cycle.
Benefits of process discovery
You can say process discovery gives a business an x-ray into the health of processes. Some of the key benefits of process discovery include:
- Process visibility. Process discovery gives transparency into the health of tasks, workflows, and end-to-end processes across a business unit or organization.
- Business process improvement. Business process discovery is often a foundation for process optimization or process redesign initiatives, providing data-driven insights into areas for improvement.
- Increased cost-efficiency. Process discovery can identify the cost and scope of wasted work - as well as identify ways to increase process efficiency.
- Advanced digitalization. Discovery can allow you to analyze how your teams are leveraging the tools and software available and can act as a catalyst for transitioning from legacy IT systems to new digital workflows.
- Increased automation. Discovery can give you a roadmap for automation as well as identify the key areas where automating business processes can bring the greatest improvement in throughput or performance.
Automated process discovery tools
Process discovery software observes all of the actions performed by humans in their daily work within different systems. It records everything users do and then analyzes it to find suitable processes for either automation, process improvement, or even process replacement.
Different process discovery tools in use
Unlike other process mapping tools, process discovery covers a whole spectrum of information systems that it can work with - from CRM/ERP tools to productivity apps such as Calendar and Slack. Collecting the data from users' digital traces, business process discovery analyses, and structures it using advanced computer vision and machine learning algorithms. These analyses help find process variations or patterns that could be a basis for finding automation potential.
Which processes qualify as automatable based on discovery? The processes need to be: repetitive or cyclical, highly manual, rule-based with little to no exceptions, and preferably have structured data.
Process discovery doesn't need any prior development before it can start working. It only requires an installation of software plug-ins that run on people's computers in the background without interrupting them or affecting their work in any way.
Process discovery vs process mining
Process mining and process discovery are the two terms that get confused a lot; they are even used interchangeably in some instances. This is reasonable if we look at the ultimate goal they aim to achieve - providing companies with insights into making work more smooth.
Demand for these two approaches has skyrocketed over the last few years and is expected to grow more with the growth of RPA. Despite such a similar position within tools facilitating digital transformation, process discovery and process mining tools have a few significant differences that shouldn't be overlooked.
Where does the data come from?
Process mining gets the data from event logs and uses different data points to re-engineer the business process and compare it to the ideal target process through conformance checking. If event logs fail to capture all the critical points or have many inaccurate records, then the created process model might not be as reliable, deviating from the real picture. In other words, process mining relies on distinct steps within the business process. Some of the systems, such as Slack or Teams, simply do not produce logs, making the use of process mining limited, and as a result, overlooking people's interactions with systems.
Process discovery, in contrast, can come from a number of sources, including interviews, surveys, or recordings of user interactions. Business process discovery records ad-hoc human work throughout the whole process and then decomposes it. Through this inverse approach, process discovery can document even the "shadow work" and "white space" that usually gets unnoticed through the event log approach. Because process discovery provides a more continuous approach to observing the work, even seemingly unimportant parts of the business process get recognition and add value to the analysis.
Development efforts before the use
Another significant difference is the need to make integrations with information systems to get started with process mining. It requires upfront back-end integrations with different software and applications that will be monitored in the mining process. Process discovery doesn't need any integrations, so users can quickly install the software agents on users' computers uninterruptedly.
That being said, process discovery and process mining can and should be used together to achieve the best results in capturing all the necessary insights.
Process discovery vs task mining
In the technology world, everything changes very rapidly, and thus, the terminology gets altered, confused, and replaced very often.
While we have discussed the differences between process mining and process discovery, task mining is another very similar term that gets confused a lot. Although underlying technology-wise these are very close relatives, the final goals and how they’re used by the end users are what sets them apart. To understand that, one could have a look at the most prominent vendors in the industry. The common pattern is that process mining companies have task mining as their complimentary service, while process discovery is used by RPA vendors.
Both technologies trace users’ digital footprints beyond event logs across IT systems and apps. While task mining does it to identify business process inefficiencies, process discovery needs the data to find automation opportunities more effectively. As a result, although they're very close to each other, they might slightly differ in terms of the outcome they bring.
Use cases for process discovery tools
With the emergence of automated process discovery tools, enterprise businesses have found a number of use cases for conducting business process discovery with dedicated software.
- Improve business processes
If the company reaches a point where it knows that something should be improved in its business-related activities, this is where process discovery can come in handy. It's a very effective first step to see the reality of work in the company and to better understand current processes before committing to multi-million automation projects.
- Automate business processes
Process discovery helps to find automation potential in a non-biased, data-driven way. Data is the new oil; valuable, high-quality data that tell a lot is a pure treasure. Process discovery's robust data collection techniques help to find better automation cases.
- Improve employee satisfaction and efficiency
Manual and repetitive tasks can be really tedious and cause decreasing job satisfaction and productivity loss. However, it's hard to identify them when integrated into a routine and interrelated between various business processes. Process discovery can be your company's eyes and really map the business processes making them more transparent.
- Facilitate RPA automation
Companies have used process discovery as an "x-ray" in their RPA initiatives. RPA is a software tool that automates repetitive, rule-based tasks by creating "bots" that mimic people's actions and execute them within a particular task. It supports identifying which processes are ideal candidates for RPA in terms of automatability and ROI. It also creates automated workflows, significantly reducing the time in RPA implementation.
Are you interest to read more about modern process discovery tools and techniques? Read the Work API whitepaper!
Additional reading
Ready to continue to more advanced topics within process discovery?
Pick the most relevant article from the list below:
-> Process discovery best practices
-> Automated process discovery explained
-> Process discovery vs process mining vs task mining
