AI & Operational Excellence in Business

Discussion with Ilir Morina

In today’s fast-paced, competitive business environment, enterprise business process optimization, transformation, and operational excellence have become critical drivers of organizational success. Companies across industries are increasingly recognizing the need to not only streamline operations but also to ensure that they are resilient, adaptive, and future-ready. This article explores the key components of these business strategies, with insights from Ilir Morina, who has led Continuous Improvement and Transformation for companies such as Coca-Cola, Target, Jackson-Hewitt and most recently as Vice President of Enterprise Business Process Optimization & Transformation for PVH Corp. He is an expert in cross-industry process optimization and operational excellence. Additionally, we delve into how Artificial Intelligence (AI) and Machine Learning (ML) are shaping the future of these fields.

The Evolution of Enterprise Process Optimization and Operational Excellence

As Ilir Morina shared in his interview, Operational Excellence found him as much as he found it. His journey, which began in the study of psychology and criminology, ultimately led him to business transformation roles. The diverse experiences he gathered along the way shaped his understanding of teamwork, change management, and process improvement. “Earlier in my life, I spent time as a consultant for U.S. Special Forces during the Kosovo Crisis. These were formative years that shaped my understanding of teamwork, change management, training, and standardization”, he recalled​.

Morina’s journey highlights the dynamic nature of Enterprise Business Process Optimization, a field that has significantly evolved over the years. “When I entered the field, LEAN manufacturing was the cornerstone for all value creation. Subsequently, Six Sigma instilled a data-driven mindset that demanded heightened analysis and reduced variability”, he explained​. This evolution reflects how organizations have had to adapt to technological advancements and shifting market demands. The rise of big data, automation, and agile principles has further expanded the scope of Operational Excellence beyond traditional manufacturing.

The Role of AI and ML in Business Process Optimization and Operational Excellence

AI and it’s subsets such as NLP, ML RPA and robotics are at the forefront of transforming how businesses approach process optimization and operational efficiency. While traditionally, process improvements relied heavily on human intervention and analysis, AI is now providing tools that enable faster, more accurate, and more scalable solutions. According to Morina, AI is a key enabler in today’s business environment. He has become an advocate for leveraging process mining and task mining to address complex process challenges and enhance operational efficiency.

AI-driven tools such as process mining allow companies to visualize and analyze their workflows, identifying bottlenecks and inefficiencies that may not be immediately apparent. This automated approach provides a level of insight and precision that far exceeds what manual analysis can offer. Furthermore, AI can be instrumental in decision-making processes, enabling predictive analytics that help businesses forecast outcomes and optimize their strategies accordingly. “More recently, I’ve become an advocate for leveraging process mining and task mining to address complex process challenges and enhance operational efficiency”, Morina emphasized​.

However, integrating AI into business processes requires careful planning and execution. Organizations must ensure they have the right talent, infrastructure, and strategic alignment to fully leverage AI’s potential. “Assessing the organization’s readiness is critical: Do we have the capabilities and infrastructure to effectively leverage data?” Morina questioned​. Additionally “Organizations must address bias, transparency, accountability, and privacy to ensure AI systems are fair, explainable, and respectful of rights. Job displacement and autonomous decision-making also raise societal concerns. Effective management of these challenges requires strong human oversight in AI applications.”

Key Drivers for Business Process Optimization and Transformation

While Artificial Intelligence is a powerful tool, the success of any process optimization initiative still hinges on foundational business principles. Morina emphasizes that trust, respect, cooperation, and a shared commitment to delivering value to the customer are key drivers of successful business transformation. “At the core of success, you’ll find trust, respect, cooperation, and a shared commitment to delivering value for the customer. These principles are fundamental regardless of the specific factors involved”, Morina noted​.

This shared commitment is especially important in cross-functional collaborations, where various departments must align their efforts to achieve a common goal. Morina recounted a successful case where cross-functional collaboration significantly improved process performance and productivity. “Our steering committees were dynamic, entertaining, and frankly, a hot ticket. People looked forward to participating, and the environment was such that challenges were met with open debate, not defensiveness”, he shared​.

In this case, functional leaders contributed their expertise to the Operational Excellence program, while also improving their own operations. The result was a unified approach that led to substantial improvements in operating income. Such examples highlight the importance of fostering a culture of collaboration and open communication within an organization.

Balancing Innovation and Stability in Business Transformation

One of the greatest challenges organizations face during transformation initiatives is balancing the need for innovation with the requirement to maintain process stability and compliance. According to Morina, innovation is not about creating something entirely new with unlimited resources; rather, it is about generating value when resources are constrained. “Innovation is not about creativity with unlimited resources. It is about creating abundance from scarcity, variety from uniformity”, he explained​.

In practice, this balance can be achieved by maintaining flexibility within a structured framework, with a strong focus on risk management. Morina advocates for dual operating models, where “change-the-business” resources can incubate ideas in controlled environments before integrating with “run-the-business” resources. This approach allows organizations to test new ideas without compromising the stability of their core operations.

Aligning New Technologies with Business Goals

When integrating new technologies, such as AI and ML, into business processes, it is essential to ensure that these innovations align with overall business goals. Morina emphasized the importance of involving the right stakeholders, including business owners, IT, finance, and legal, to ensure that diverse perspectives are considered. “This is truly a cross-functional effort requiring collaboration across multiple departments”, he stated.

One of the strategies he recommends is starting small, with limited-scope Proof-of-Value and Proof-of-Concept exercises, to validate the feasibility of AI initiatives before progressing to larger projects. This approach not only reduces the risk of failure but also allows businesses to assess scalability and ensure they have the necessary infrastructure in place.

Challenges and Best Practices in Cross-Industry Business Transformation

When attempting to adopt cross-industry best practices, organizations often face resistance and capability gaps. As Morina pointed out, one of the most common mistakes is trying to apply a one-size-fits-all mentality. “It’s important to treat cross-industry best practices as a recipe to be adapted rather than strictly followed”, he advised​.

To overcome these challenges, businesses must strike a balance between standardization and innovation. This involves blending best practices from other industries with the organization’s unique operational needs. Morina likened this approach to a chef who adopts recipes from different cuisines but modifies them to suit their customer personas, creating new culinary delights.

Sustaining Operational Excellence and Driving Long-Term Transformation

To sustain operational excellence over the long term, businesses should leverage data analytics and continuous improvement methodologies such as Lean, Kaizen and Six-Sigma. These tools provide the framework for identifying inefficiencies and driving ongoing improvements. But they are only tools. Morina recommends that executives focus on three key criteria to ensure a smooth and effective transition during business transformations: