AI-led processes enhance productivity & revenue, banks face digital transformation obstacles – PEX Research & Reports News

PEX Network’s weekly news bulletin rounds up the latest research, reports and publications in operational excellence (OPEX), digital transformation, artificial intelligence (AI) and automation, business process management (BPM), process mining and process intelligence and more.

This week includes:

• Businesses with AI-led processes outperform peers
• Banks face multiple digital transformation obstacles
• Process mining optimizes emergency department efficiency
• Domain knowledge unravels business process metrics

Businesses with AI-led processes outperform peers

Three-quarters (74 percent) of businesses have seen investments in generative AI and automation meet or exceed expectations, with 63 percent planning to increase their efforts and further strengthen these capabilities by 2026. That’s according to new research from Accenture. As detailed in Reinventing Enterprise Operations with Gen AI, the number of companies that have fully modernized AI-led processes has nearly doubled from 9 percent in 2023 to 16 percent in 2024. What’s more, these organizations achieve 2.5-times higher revenue growth and 2.4-times greater productivity compared to their peers, Accenture found.

However, while the research indicates that some companies have moved to the highest level of operations maturity amid AI investment, nearly two-thirds (64 percent) still struggle to change the way they operate. For example, they lag behind on building a robust data foundation: 61 percent stated their data assets are not ready for generative AI yet and 70 percent admitted they find it difficult to scale projects that use proprietary data.

“Most executives understand the urgency of reinventing with generative AI, but in many cases their enterprise operations are not ready to support large scale transformation,” said Arundhati Chakraborty, group chief executive of Accenture Operations. “Generative AI is more than the technology. It is a driver of a mindset change that impacts the entire enterprise. It requires organizations to have a strong digital core, data strategy and a well-defined roadmap to change the way they operate. Additionally, an end-to-end perspective leveraging talent, leading practices and effective collaboration between business and technology teams is essential for intelligent operations.”

Jon Atienza, The Coca-Cola Company discusses how AI equates to better customer experience

Banks face multiple digital transformation obstacles

Banks continue to face multiple obstacles to digital transformation with budget constraints, regulatory challenges and lack of operational agility major issues, according to the Global Banking Benchmark Study conducted by consulting firm Publicis Sapient. Based on customer and operational leadership, only 11 percent of surveyed banks were classified as transformation leaders, down from 22 percent in the previous survey. The top priority for respondents is using data and analytics to better understand customers and their relationship with the bank.

This year’s study revealed that AI dominates banks’ digital transformation plans, signalling that their adoption of AI is on the brink of change. While banking leaders find digital transformation more challenging than they did when we conducted this survey two years ago, they are looking to digital to improve the bottom line.

“AI, machine learning and generative AI are both the focus and the fuel of banks’ digital transformation efforts,” commented Dave Murphy, financial services lead, international at Publicis Sapient. “The biggest question for executives isn’t about the potential of these technologies; it’s how best to move from experimenting with use cases in pockets of the business to implementing at scale across the enterprise.”

Nao Anthony, Commonwealth Bank and Tariq Munir, PepsiCo explore the complexities and challenges of digital transformation 

Process mining optimizes emergency department efficiency

Researchers demonstrated the effectiveness of using process mining and simulation models to identify bottlenecks and optimize patient flow in the emergency department of a hospital in Isfahan, Iran. The goal was to reduce patient waiting times and alleviate population density, ultimately enhancing the overall patient experience, according to the researchers.

“The results of this research demonstrate the effectiveness of using simulation techniques and process mining in making informed, data-driven decisions that align with available resources and conditions,” the academics wrote. “By leveraging these tools, unnecessary waste and additional expenses can be significantly reduced.” Notably, the process mining exercise corroborated the findings from the simulation, providing a comprehensive understanding of the inefficiencies in the emergency process, they added. The study proposed 34 potential solutions to reduce waiting times and alleviate bottlenecks.

Tony Benedict, Association of BPM Professionals International, reflects on breaking down silos in process management

Domain knowledge unravels business process metrics

A new research paper introduced a novel method for analyzing business process metrics through the integration of domain knowledge, process mining and machine learning. The Weighted Insights for Evaluating Efficiency (WISE) methodology involves defining business goals and establishing process norms with weighted constraints at the activity level, incorporating input from domain experts and process analysts.

Individual process instances were scored based on these constraints and the scores were normalized to identify features impacting process goals. Evaluation demonstrated that WISE enhances automation in business process analysis and effectively detects deviations from desired process flows. While large language models (LLMs) support the analysis, the inclusion of domain experts ensures the accuracy and relevance of the findings, the research stated.

Leona Holzbecher, psychologist, organizational developer and thought leader outlines accountability in process management

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