As businesses adapt to economic shifts, evolving workforce dynamics and the rapid adoption of artificial intelligence (AI), they enter what can be described as The Great Recalibration.
Unlike the workforce shifts of The Great Resignation or The Big Quit, this moment is characterized by strategic refinement. Enterprises are optimizing operations, reassessing cost structures and realigning technology investments to ensure long-term resilience.
Process mining and process intelligence play a central role in this transformation, providing data-driven insights that help organizations confidently navigate complexity.
From ‘growth at all costs’ to ‘smart efficiency’
For the past decade, many businesses prioritized rapid growth, often at the expense of efficiency. However, rising inflation, high interest rates and increasing investor scrutiny have shifted the focus toward profitability, operational excellence (OPEX) and long-term value creation.
The PEX Report 2025, PEX Network’s flagship industry report highlights this shift:
- 47 percent of business leaders consider OPEX and business transformation strategies mission-critical for growth and resilience.
- 43 percent prioritize improving productivity and efficiency to enhance business performance.
This new emphasis on efficiency is driving the adoption of process intelligence, which helps organizations:
- Identify operational inefficiencies that erode profit margins.
- Optimize workflows to improve productivity.
- Compare performance across teams and regions to scale best practices.
- Simulate cost-cutting strategies before implementation to minimize disruption.
A leading gas provider in Australia used Apromore’s process intelligence capabilities to analyze inefficiencies in its well intervention projects, particularly between allocation and execution where bottlenecks were costing up to $3 million per day. By identifying excessive rework and automation gaps, the company accelerated project cycle time by 15 percent with 20 percent fewer policy violations, resulting in over $7 million in cost savings per project.
Key takeaways for business leaders:
- Use data-driven insights rather than instinct to optimize costs.
- Shift performance measurement from volume-based metrics to efficiency-focused indicators such as flow efficiency and first-time-right rates.
AI adoption: from experimentation to measurable impact
Generative AI has become widely adopted, with Gartner identifying it as the most frequently deployed AI solution. However, many enterprises struggle to translate AI investments into tangible business value.
A study by Boston Consulting Group (BCG) found that only 26 percent of companies have built the necessary capabilities to move beyond proof-of-concept and achieve meaningful AI-driven outcomes.
Process mining and process intelligence provide the foundation for AI adoption by ensuring automation efforts are built on optimized, well-structured processes.
How process intelligence enhances AI adoption:
- Identifies high-impact AI use cases, such as reducing cycle time or improving compliance.
- Highlights inefficiencies that should be addressed before implementing AI.
- Monitors AI investments over time to track business impact.
- Detects automation breakdowns and AI performance drift in production environments.
A global logistics company used Apromore to assess the effectiveness of its AI-powered invoice classification system. The analysis revealed that only 60 percent of invoices were being routed correctly. By refining the AI-driven workflows, the company improved classification accuracy to 95 percent, saving two full-time employees per region.
Key takeaways for business leaders:
- AI initiatives should be built on optimized processes rather than automating inefficient workflows.
- Continuous monitoring of AI’s impact is necessary to ensure it improves business KPIs over time.
Workforce transformation: The shift to an adaptive model
The workforce landscape is evolving rapidly, with organizations managing generational shifts, hybrid and remote teams and increasing digital skill demands.
According to the World Economic Forum’s Future of Jobs Report, 63 percent of employers cite skills gaps as a major barrier to business transformation. While many organizations are investing in internal talent marketplaces and skills-based hiring, skills and talent shortages remain a challenge.
Process intelligence helps organizations optimize workforce strategies by:
- Identifying workforce-related process bottlenecks and knowledge gaps.
- Optimizing team structures based on process performance data.
- Informing workforce reskilling efforts by identifying areas where human expertise adds the most value.
Compliance, ESG and the resilience imperative
Organizations are facing increasing regulatory scrutiny, cyber security threats and environmental, social and governance (ESG) mandates. Regulations such as the European Union’s Corporate Sustainability Reporting Directive (CSRD) require companies to embed compliance and risk management into daily operations.
Process intelligence supports compliance and ESG initiatives by:
- Monitoring compliance in real-time with visual audit trails.
- Simulating risk scenarios to assess potential disruptions.
- Tracking ESG-related process metrics, such as emissions reduction, supplier risk and resource waste.
A US-based energy company used Apromore’s process simulation capabilities to evaluate the impact of CO2 emissions of failed technician visits due to “no access” events. The insights led to a 20 percent reduction in emissions for field service operations.
Key takeaways for business leaders:
- Integrate compliance monitoring into daily operations instead of relying on periodic audits.
- Use digital simulations to assess the potential impact of regulatory changes and market disruptions before they occur.
The role of process intelligence in The Great Recalibration
The Great Recalibration is not a sudden shift but a deliberate, data-driven transformation. Organizations must move from reactive decision-making to strategic recalibration, focusing on resilience, transparency and agility.
Why process intelligence is essential in this shift:
- Provides real-time visibility into how work is performed across the enterprise.
- Identifies inefficiencies, bottlenecks and compliance risks.
- Enables confident, data-backed decision-making.
Rather than chasing the latest technology trends, organizations should focus on building a stronger, more intelligent operational foundation. Process mining and process intelligence provide the necessary tools to optimize operations, enhance decision-making and drive success.