Maximize value through process mining and hyperautomation: strategies, synergies and the road ahead

Process mining has surged with the advent of digital technologies such as RPA, ML and AI, amplifying the significance of streamlined processes for organizational achievement.

Processes, defined as sequences of tasks from initiation to completion aimed at achieving a specific objective, are the foundation of any organization's success. Continuous process improvement is a crucial function across organizations to optimize costs and enhance customer satisfaction. Since the early '80s, organizations have leveraged lean and Six Sigma methodologies to drive continuous improvement. The rise of digital technologies like robotic process automation (RPA), machine learning (ML) and artificial intelligence (AI) has spurred unprecedented growth in process mining.

According to the Gartner 2022 Magic Quadrant for Process Mining Tools report, the global process mining market size is expected to grow from $463 million in 2021 to $2.3 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 50.1% during the forecast period. 

Additionally, Google search trends show an approximately 220% increase in the search for 'process mining' from 2015 to 2023, indicating process mining is gaining popularity (Figure 1).

Figure 1. Growth in process mining searches.

Automation-era propels growth in process mining

In the last decade the role of technology has shifted from being an enabler to an essential pillar in an organization's overall strategy. Automation is not only a technology initiative but one driven by people and processes. A well-defined automation strategy and execution approach can transform an organization's operational roadmap.

In 2019, Gartner rebranded automation as hyperautomation to emphasize the strategic amalgamation of digital levers for achieving full-scale transformative benefits for organizations. 

According to a Deloitte study conducted in 2020, hyperautomation can provide an average cost reduction of 22% and an improvement in revenue by 11% by 2023. 

Process mining is the central component in the hyperautomation universe, responsible for building knowledge about processes and identifying improvement opportunities. Application of process mining techniques can help organizations analyze existing processes, and detect inefficiencies or bottlenecks leveraging frameworks like the Japanese 5S principle.

The Japanese 5S principle provides a framework for achieving transformative benefits in each process:

• Seiri (Elimination): Remove non-value-add items/activities in a process.
• Seiton (Re-engineering): Reorganize workflow items to minimize waste, following ergonomic principles.
• Seiso (Optimization): Clean and remove all specks of dirt, optimizing operational parameters to approach perfection.
• Seiketsu (Standardization): Ensure uniformity in process outcomes.
• Shitsuke (Sustainability): Make the improved process part of the organization's culture.

Automation should be introduced to processes that have either reached the Shitsuke phase or completed the Seiketsu stage. Automating a poorly designed process will retain inefficiencies and not yield expected benefits.

Packaging process mining and intelligent automation

Process mining applies data-oriented analysis and existing process modelling approaches to discover potential improvement areas. Based on my experience in this field, I have divided process mining into four categories:

• Process Modeling: Model the current-state business process based on knowledge derived from event and user interface logs extracted from multiple information systems. Set clear expectations, analyze operational transaction volumes and apply Pareto principles to map steps responsible for 80% of volume generation.
• Process Assessment: Assess the current state of the modelled process based on industry-domain best practices and the Japanese 5S methodology. Identify and classify improvement opportunities under elimination, re-engineering, optimization standardization and automation categories. Prioritize these opportunities as immediate, short-term, medium-term or strategic for the delivery organization.
• Process Diagnostics: Identify the root causes of problems in the current state process. This can be done using process mining techniques such as conformance checking, deviation analysis and performance analysis. The output of the process diagnostics phase can be used to reprioritize opportunities identified in the process assessment phase by drawing out causal relationships between root causes and opportunity categories. Additionally, this helps to identify new improvement opportunities that were not identified in the process assessment phase.
• Process Value Proposition: Define the future state process model based on opportunities classified in the process diagnostics phase. Forecast improvements in current state process indicators and build a high-level business case to understand the costs and benefits associated with opportunity implementation. This stage concludes with a process transformation roadmap demonstrating prioritized opportunities along the journey and targeted benefits after completing each milestone.

Figure 2. Process Mining components

Once an optimized process with visible improvement in operational parameters is established, it's essential to introduce applicable elements of intelligent automation under the hyperautomation universe. The strategic application of these elements on an improved process unlocks new synergies.

Figure 3. Hyper Automation Universe

The benefits of integrating process mining and intelligent automation

Intelligent automation focuses on expanding automation coverage beyond rule-based tasks to include decision-making tasks. Integrating AI and ML capabilities with traditional rule-based automation enables the coverage of semi-structured and unstructured tasks. 

Packaging process mining and intelligent automation yields transformative benefits for businesses and organizations:

• Improved ROI and shorter payback: Organizations can realize an improved return-on-investment in a shorter time frame. According to The National Association of Software and Services Companies, RPA implementations on an optimized process can have an investment recovery period as short as 6-9 months. Forbes reports that, in a hyper-automation program, organizations can realize triple-digit ROI.
• Workforce productivity: Organizations can accomplish more operational work with fewer resources, freeing up time and energy to focus on strategic priorities. Gartner estimates that hyper-automation can boost workforce productivity by up to 40% and increase revenue between $225 billion and $400 billion.

The new disruptor: Low code/No code

In 2021, low code/no code methodology emerged as a new component in the hyper-automation landscape. Low code/no code methodology is an application development approach that utilizes a visual drag-and-drop method to build front-end interfaces, business logic layers and back-end databases in a fraction of the time required by traditional high code approaches.

Combining process mining and low code/no code approaches enable businesses to reimagine their existing landscapes. In addition to typical improvement areas (elimination, re-engineering, optimization and standardization), low code/no code can be leveraged for application modernization and rapid application development.

The future of process mining and hyper-automation

Organizations of all shapes and sizes are striving to incorporate hyper-automation as the central piece of their digital transformation and modernization roadmaps. Process mining, when adopted within the hyperautomation framework, is considered an ideal component for maximizing benefits.

In the coming decade, we are likely to see an acceleration in the adoption of process mining as part of the hyperautomation framework. Emerging approaches like predictive analytics and scenario-based analysis (digital twin) will improve process mining platform outcomes.

To ensure the success of hyperautomation programs, organizations should focus on planning. This includes defining hyperautomation strategies, prioritizing business functions and processes for initial rollouts, selecting tools, building comprehensive business cases and creating change management strategies for employees.

The future of process mining and hyperautomation is bright. By achieving synergy with hyperautomation technologies, organizations can realize transformational benefits and remain competitive in this age of technological revolution. With the continuous evolution of these technologies, we are presented with the opportunity to not only transform, but also to re-imagine business processes for the future. 

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References:

• "RPA and the mid-market organization – seven ways you stand to gain": https://www.bterrell.com/robotic-process-automation-rpa/mid-market-businesses#:~:text=According%20to%20The%20National%20Association,as%20few%20as%20six%20months.
• "Understanding Hyperautomation's Potential Impact On Your Company's Digital Systems (forbes.com)": https://www.forbes.com/sites/forbestechcouncil/2020/10/30/understanding-hyperautomations-potential-impact-on-your-companys-digital-systems/?sh=233f95d22862.
• "Benefits of Hyperautomation in Enterprises”: https://asignet.com/hyperautomation-benefits.