Data debt hampers AI investments, sustainable processes drive business value – PEX Research & Reports News

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

This week includes:

• AI investments hampered by data debt
• Machine learning and process mining enhance legal proceeding prediction times
• Sustainable business processes and green technology drive organizational value
• Operational excellence program benefits Iowa prison system

AI investments hampered by data debt

A lack of comprehensive data strategies among enterprises is curtailing use of AI tools and undermining business goals, according to a new report from HFS Research and Syniti. The pair interviewed more than 300 Global 2000 business leaders (49 percent from the US) across industries to study how organizations are navigating a complex landscape of data management challenges and how hurdles impede their ability to fully leverage operational efficiency and drive business growth. It found that enterprises perceive that over 40 percent of their organizational data is unusable and is either not trusted, lacks quality, not updated, inaccurate, duplicated or inconsistent. Improving operational data availability to integrate AI tools is therefore the biggest challenge in implementing AI technologies, it added.

“Our research proves that a data first culture means data isn't just IT’s problem; it’s a core business issue,” commented Phil Fersht, CEO and chief analyst at HFS Research. “Many business leaders still take a backseat when setting key data objectives, causing data to remain siloed across departments, and resulting in misaligned expectations across IT and business professionals. The focus for enterprise leaders must be on developing strategic talent that understands the business context behind the data.”

READ: A network approach to AI transformation

Machine learning and process mining enhance legal proceeding prediction times

A new academic research study explored the integration of machine learning and process mining techniques to enhance the accuracy of predictions in relation to the duration of legal proceedings in Brazil. Delays in legal proceedings significantly impact both corporate finances and individual livelihoods, according to the researchers from the University of Pernambuco. Traditional methods for managing these delays typically rely on subjective assessments of what constitutes a reasonable process duration.

“We applied process mining clustering techniques to over 60,000 cases from Brazilian labor courts to segment cases based on their procedural movements, creating clusters,” the researchers wrote. “These clusters, along with other procedural characteristics, such as case subject, class and digital status, were then incorporated into a feature set for regression modelling.” The researchers employed linear regression, support vector regressor and gradient boosting based methods to develop models that predicted case duration.

“The gradient boosting model demonstrated the best performance with an R2 score of 0.87. Furthermore, our analysis identifies time bands where the model performs better and employs explainable AI techniques to elucidate key features influencing case durations.” The clustering features emerged among the most significant for the task. “The proposed combined approach offers a comprehensive method for analyzing and forecasting legal case timelines and also shows the potential of process mining clustering techniques to improve the analysis.”

READ: A summary of Gartner’s 2024 Magic Quadrant™ for Process Mining Solutions

Sustainable business processes and green technology drive organizational value

Green technology can enhance overall organizational value and significantly influence sustainable business processes. That’s according to a new research study published in the Business Process Management Journal, based on data collected from more than 400 managers of IT firms. The findings implied that firms should focus on acquiring new green technologies and adopting sustainable processes, leading to enhanced profits and non-financial gains.

“Sustainable business processes, encompassing economic, social and environmental dimensions, enhance organizational value, including financial and non-financial performance,” the researchers wrote. “Consequently, a multifaceted sustainable model has been developed to optimize organizational value, providing new insights.”

READ: Why AI isn’t a green technology for data operations

Operational excellence program benefits Iowa prison system

Researchers examined how prisons can utilize effective business process, operations management and continuous improvement techniques to provide an opportunity to support the rehabilitation of inmates. The paper analyzed the Iowa Prison Industries (IPI) work training program offered for incarcerated individuals under the supervision of the Iowa Department of Corrections (IDOC). The IPI’s operational excellence apprenticeship program has worked with approximately 800 incarcerated “associates” to help them acquire skills to obtain gainful employment upon release. This includes skills and belt level assessment in Lean Six Sigma. The techniques have been deployed by 22 teams at seven locations across the state of Iowa (USA).

“Findings and success outcomes have been encouraging as those who completed the IPI apprenticeship program had lower recidivism, higher wages and more employability compared to the general prison population,” according to the researchers.

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