Organizations around the world are undergoing digital transformations in response to the economic turbulence wrought by COVID-19 pandemic. Many of these transformations include automation to accelerate business processes. Process discovery is thus becoming a key step to selecting the best processes to automate and add value for the company.
What follows is a guide to process discovery, including benefits it provides users like in pursuit of identifying bottlenecks, optimizing workflows and driving success, along with methods and best practices for improving business efficiency.
What is process discovery?
Process discovery is a systematic approach to business process analysis. Because discovery is the first step in improving and automating processes, a thorough understanding of each process phase is necessary.
Process discovery includes the identification and definition of activities and tasks comprising a process; its purpose is to make all stages in a process visible in order to ensure clear responsibility for each of those phases.
Process discovery vs. process mining
Process mining and process discovery are closely related concepts for creating visibility in processes, but they also have distinct differences. Both solutions are powered by artificial intelligence (AI) and machine learning (ML) to uncover and visualize process data. Process mining, however, is a technique that has been used for longer than process discovery. It has a wider adoption across industries and far greater name recognition than process discovery.
Process mining makes greater use of event logs for creating a high-level view of a process’s operations, including quantitative insights like run times. It also includes tools like root cause analysis, which allows organizations to more easily identify bottlenecks and process issues in order to find solutions for them.
A significant performance gap of process mining is that it doesn’t capture human behavior, including the actions and steps they take when performing a process.
In contrast, process discovery captures user behavior in real time, providing a granular view of user interaction at every stage. It is extremely useful for generating the documentation needed to identify process optimization opportunities at the procedural level, including individual clicks and keystrokes by users.
This capability provides a detailed blueprint for automation, especially robotic process automation (RPA). RPA uses data from user interactions to create bots that perform the same actions on repetitive, high-volume tasks.
How does business process discovery work?
A process discovery solution installs bot software on users’ computer systems, where they record daily activities within specified applications. The bots run for two to three weeks, after which the solution uses AI to identify recurring processes.
It then generates interactive maps based on these results, allowing analysts to visualize the current processes. This also gives them the ability to explore possible task alternatives that might be more advantageous than the current ones.
Team members then define the best processes to automate, and begin documenting them in a large amount of detail. The final step is to export those process descriptions in a variety of formats, such as Process Definition Documents (PDD) and Business Process Model and Notation (BPMN).
Benefits of process discovery
Business processes don’t always run as expected due to problems like siloed data and missed activities. These inefficiencies lose hours and money that can add up to huge amounts of waste over time. Process transparency is needed to identify exactly what is hindering the process.
Businesses that don’t have access to this transparency are left guessing where in a process to make improvements. This type of process analysis is slow, tedious, and often incorrect. Process discovery takes the guesswork out of a business process improvement project, delivering empirical, data-driven answers. Let’s look at the most significant benefits of process discovery.
Organizations that understand their business processes in detail are in a far better place when faced with government regulations and industry standards. Those companies that have made full digital transitions and optimized their processes usually do so with compliance in mind and are therefore prepared for regulation updates and audits by governing bodies.
Process discovery uses the data it collects to obtain objective insights into the functioning of business processes. Analysts can avoid the biases and inherent human errors of manual analysis, resulting in more accurate conclusions and recommendations.
Improved efficiency and quality
By highlighting deviations which can subsequently be eliminated, process discovery is a great tool for standardizing production, improving the quality of a business’s products and services. Smooth, automated processes are efficient processes.
Process discovery platforms work around the clock to root out inconsistencies, which means they can pinpoint inconsistencies as soon as they appear. This ensures continuous process improvement far beyond the initial implementation.
Process discovery provides visibility into the specific steps of a process, in addition to the process’s overall role within the organization. The process maps this technique yields can be used not only for present improvements, but for pathways for future automation, as well.
Process discovery platforms improve processes by eliminating inefficiencies like unnecessary task repetition and constant IT intervention, providing significant cost savings. Businesses that choose no-code BPA platforms further reduce labor costs by eradicating the need for long employee training seminars; the software can be used out-of-the-box with no previous coding knowledge.
Which stakeholders are involved in process discovery?
Process discovery platforms typically involve two types of stakeholders:
Process analysts are responsible for breaking processes down into specific steps.
Subject matter experts have a highly specified understanding of the purpose and impact of the process in question.
6 steps of process discovery
Process discovery is a vehicle designed to continuously optimize processes, so it doesn’t have a well-defined starting or stopping point once implemented. It generally consists of analyzing processes as they currently operate, and developing improvements for them. This approach involves the following 6 steps:
- Define objectives
- Gather information
- Analyze the data and find improvement opportunities
- Implement the changes
- Monitor, evaluate and continuously improve
1. Define objectives
Define specific goals for the process discovery project. These could include objectives like preparing processes for automation or identifying inefficiencies. Analysts often use this step to identify the best candidate processes for automation. Once decided upon, they define the project’s scope.
2. Gather information
Collect information on the processes under consideration for improvement from many sources. Data sources include system documentation and logs, process maps and interviews with employees who perform these processes.
In this phase, considering data alone is short-sighted. Interview the employees who control or carry out the process, along with those who have ownership of it, for a full understanding of the operations and their pain points. Those who perform tasks each day often have keen insights into how they can and should be improved.
Observe employees performing the processes in real time, recording everything they do and the time it takes them to do it. This step may include shadowing employees, using process mining tools or conducting workshops, all of which can document a process’s steps and participants. These recorded observations often provide valuable insights into workflow optimization.
For example, seeing a process step listed among many can be useful, but watching employees perform it over a period of minutes or hours is far better information to have when looking to streamline it.
4. Analyze the data and find improvement opportunities
Analyze the data collected in the previous step to identify inefficiencies for the purpose of making improvements. Consider all sources, records, and information gathered; analysts should also review supplemental information like company resource allocation and overall performance.
5. Implement the changes
Implement the identified improvements in collaboration with stakeholders. This step can include updating documentation, learning and using new technologies, or reallocating funds and resources. Change management strategies by leadership also come into play here as employees are given new software and new objectives.
6. Monitor, evaluate and continuously improve
Monitor the updated processes for an extended period of time. Evaluate the results to assess the impact and effectiveness of the changes. This step will be continuously repeated to identify additional opportunities for improvement.
Process discovery examples
Major use cases of process discovery include procurement, HR and IT.
The complete visibility that process discovery provides makes it highly useful in procurement by allowing analysts to easily understand the value of purchases and vendor relationships. They can use data from previous sales and purchases to select preferred vendors.
Process discovery eliminates the need to complete purchase orders manually. Digital workflows also complete requests in days rather than weeks. Automated processing delivers orders on time by eliminating delays due to human error. In addition, automated customer service keeps customers happy by allowing workers to deliver better experiences.
Streamlining the hiring and employee onboarding process is one of the greatest benefits of process discovery for HR team members. Automated tasks create a seamless experience for candidates by using bots to collect and update data from multiple systems.
These bots can also accurately process data and automatically generate logs, reducing errors and ensuring compliance. This benefit allows HR to focus on more creative and personal tasks like succession planning and talent development.
Process discovery allows IT professionals to deliver value to other departments by quickly implementing intelligent process automation solutions.
These tools typically include a drag-and-drop interface that team members can use to design and implement workflows more quickly than writing code. They also provide greater control over compliance issues like managing certifications and securely scaling solutions.
Common process discovery challenges
Process discovery is never as easy as simply asking the people who perform compliance, payroll or shipping documentation how they do it. You must pursue process discovery as a formal practice to obtain the required precision, which is why you should hire an outside specialist in this discipline.
No single manager will ever have complete visibility into an individual task, which is usually handled by many employees or even departments. Furthermore, each process is usually comprised of multiple tasks, so managers only have a big-picture view of how to make a process successful. However, they rarely know the details of what employees do.
In addition, employees are unlikely to have full visibility into the process beyond the tasks they perform. While they may perform more than one task at a time that contributes to the process in a different way, it’s difficult to untangle the role of each task. Process discovery requires a comprehensive view of a process that no single individual worker can provide.
Finally, tasks performed by humans aren’t done exactly the same way each time, even when only one person is doing them. In a department with multiple people, there will be many ways of doing the same thing. Process discovery can help reduce this approach into a single procedure, but it requires compiling details from multiple sources.
Process discovery outcomes
Expected outcomes of process discovery include optimized processes, improved risk management and enhanced customer experience.
Process discovery allows organizations to optimize their processes by identifying the tasks in greatest need of improvement. Analyzing data on the way these processes are performed can identify these opportunities, which typically include reducing unnecessary steps and allocating more resources for performing a bottlenecked task.
Process discovery provides a data-driven approach to optimization that reduces costs, improves efficiency and increases customer satisfaction.
Improved risk management
The data-driven decision-making capability that process discovery provides helps organizations manage risks such as security and regulatory compliance more effectively. Analyzing process data gives them the ability to detect vulnerabilities by identifying patterns in process execution, allowing a proactive approach to risk management.
In addition, this data analysis can help develop courses of action that will mitigate risk, thus reducing the possibility of a breach.
Enhanced customer experience
Process discovery provides valuable insight into the customers’ journey towards a purchase, improving their overall experience. Analyzing data on their interactions with the company provides a deeper understanding of their preferences, needs and challenges.
This data-driven approach lets organizations make better decisions on customer issues like support, services and offerings, thus enhancing customer loyalty.
The role of BPM and BPA in process discovery
Process discovery is a must-have tool for improving business processes at scale, but other tools like BPA and BPM are also needed to complete an end-to-end solution. Pipefy offers multiple solutions for optimizing processes from a centralized interface.
For example, Pipefy’s BPA solution includes features like user tagging and alerts that reduce the hand-over time between steps.