COVID-19 has brought to light more concerns with legacy business models’ survival and business continuity. Businesses across the board are rushing to implement digital, automated, and intelligent business processes.

While many businesses have successfully launched low-complexity use cases, they are still having trouble scaling these projects to enterprise-wide operations.

Identifying and maintaining a strong pipeline of process optimization and automation opportunities remains a critical barrier to scalability and value realization as organizations embark on their automation and digital transformation journeys. 

Obstacles to establishing a robust automation pipeline

A good automation pipeline is made up of four fundamental requirements that are far more than just a set of use cases and opportunities:

1. Finding as-is processes at scale at both macro and micro levels using a fact-based approach.
2. Ability to discover and incorporate process optimization and automation opportunities.
3. While prioritizing process optimization and automation options, a holistic perspective of the ROI is required.

The ability to track the impact and return on investment of deployed initiatives and automation constantly. It allows an ongoing feedback system that aids in the agile validation and refinement of the transformation pipeline and roadmap.

Because of the large reliance on manual, interview-based procedures, we find that organizations are unable to develop a healthy transformation pipeline. This widely used method has several drawbacks and challenges, including being time and resource costly, subjective, perception-based, and potentially biased, inability to capture all process variants, and stakeholder resistance to giving critical information.

Need for process mining

Process mining assists in overcoming the constraints of manual procedures as well as the difficulty of constructing a healthy pipeline because it:

• Uses a fact-based methodology.
• Contains more information in terms of depth and breadth.
• Is more cost-effective and easy to scale than manual methods.
• Allows for continuous process and ROI monitoring.

Traditional process mining, desktop process mining (also known as task mining), and hybrid process mining are the three types of process mining technology.

The type of process data collected, the insight gained from the obtained data, and the accompanying use cases supported by the insights determine the classification of these tools.

Application of Process mining 

To expedite time-to-value realization, ROI, and scale, process mining is crucial at all stages of an organization’s digital transformation lifecycle. The following advantages can be gained by process mining:

Discover: Identifies and validates current process flows, as well as associated deviations, exceptions, variances, and key step information (such as time, cost, volume, and frequency). They can also be used to develop or update process documentation, which can be used for things like onboarding new staff and passing over procedures in outsourcing situations.

Optimize: Process mining can also be utilized to gain insight into employee collaboration, which can be used to better allocate resources and delegate tasks.

Automate: Collects detailed process data like volume, costs, duration, and frequency of process pathways and steps. The process mining tool analyses this data using relevant frameworks to uncover automation opportunities, removing the need for guesswork and opinions.

Evaluate: Models numerous process improvement and automation scenarios to forecast ROI and build or validate the business case. Configuring what-if scenarios by defining particular properties. These simulations help to reduce the risk of adopting improvements without knowing how they will affect real-time operations.

Execute: Fills in the gaps in execution by automatically activating activities based on the insights gained. Process mining is increasingly integrating with complementary technologies such as RPA workflow automation, and case management to help people act on the insights they’ve uncovered. As a result, depending on the use case, a wide range of actions may be triggered, such as:

• Email notifications and dashboard displays of events that require attention.
• Creating tickets or assigning tasks to appropriate people.
• RPA bots and automation are triggered to do certain tasks.

Monitor: Allows a business to continuously monitor process performance and develop a roadmap for process optimization and automation. Enterprises can spot bottlenecks and foresee issues in reaching important service-level agreements or potential KPI breaches by monitoring processes in near real-time, and then prepare for solutions.

Understanding of process mining journey 

Process mining can be used for ad hoc analysis of a few processes or as part of a larger transformation effort. For increased success and value realization, businesses in both scenarios can break down their process mining journeys into these five separate steps:

• Understanding the existing state: Businesses must be aware of their current process mining capabilities and outcomes, as well as the potential outcomes that can be achieved.
• Create a business case for the intended outcome: As a second stage, businesses should identify processes that are ideal for process mining, create a business case for the desired outcomes, and refine the target outcome state if the business case fails.

• Determine the capability goal state: once the desired objectives have been established, businesses should map out the necessary capabilities to accomplish them. Everest Group assesses process mining skills based on more than 25 essential aspects of companies’ process mining journeys and four maturity levels.

• Identify all determinants and map the path: given the same current and target states, different enterprises’ process mining journeys could take different paths depending on environmental factors like organizational structure, people/process-centricity, initiating stakeholders, risk appetite, change sensitivity, and technology savvy.
• Execute against the mapped path: Once the best-fit execution path has been identified, businesses can use a variety of best practice frameworks and tools to execute successfully.

Increased awareness and maturity of process mining solutions are propelling the market forward. Enterprises across geographies and industries have begun to recognize their role in driving automation and digital transformation journeys, as well as fueling continuous process monitoring, both of which are essential for guaranteeing company agility and resilience. Furthermore, its integration with automation technologies has increased its impact on fact-based and outcome-driven actions.