Human Resources Management and Services

Enterprise transformation project—AI-based manager’s profile’s selection

2025-04-23T09:23:50+00:00

The artificial intelligence (AI)-based architect’s profile’s selection (simply iSelection) uses a polymathic mathematical model and AI-subdomains’ integration for enabling automated and optimized human resources (HR) processes and activities. HR-related processes and activities in the selection, support, problem-solving, and just-in-time evaluation of a transformation manager’s or key team members’ polymathic profile (TPProfile). Where a TPProfile can be a classical business manager, transformation manager, project manager, or an enterprise architect. iSelection-related selection processes use many types of artifacts, like critical success factors (CSF), AI-subdomain’ integration environments, and an enterprise-wide decision-making system (DMS). iSelection focuses on TPProfiles for various kinds of transformation projects, like the case of the transformation of enterprises’ HRs (EHR) processes, activities, and related fields, like enterprise resources planning (ERP) environments, financial systems, human factors (HF) evolution, and AI-subdomains. The iSelection tries to offer a well-defined (or specific) TPProfile, which includes HF’s original-authentic capabilities, education, affinities, and possible polymathical characteristics. Such a profile can also be influenced by educational or training curriculum (ETC), which also takes into account transformation projects’ acquired experiences. Knowing that selected TPProfiles are supported by an internal (or external) transformation framework (TF), which can support standard transformation activities, and solving various types of iSelection’s problems. Enterprise transformation projects (simply projects) face extremely high failure rates (XHFR) of about 95%, which makes EHR selection processes very complex.

Leading with excellence: Critical leadership dimensions in Lean Six Sigma for business excellence

2025-05-07T08:16:17+00:00

In today’s competitive and complex business environment, achieving business excellence requires a combination of effective methodologies and strong leadership to drive and sustain organizational transformation. Lean Six Sigma (LSS), a proven methodology for improving operational efficiency, relies on effective leadership for successful implementation and lasting impact. This study examines how the integration of Lean, Six Sigma, and Total Quality Management (TQM) shapes leadership strategies that enhance organizational agility, resilience, and responsiveness to market dynamics. It highlights the crucial role of leadership in fostering collaboration, optimizing resource utilization, and cultivating a culture of continuous improvement. The study introduces the Structured Lean Leadership Framework as a strategic tool to develop the leadership capabilities essential for LSS success, addressing challenges such as weak leadership commitment, resistance to change, and communication barriers. Through the application of the DMAIC framework, Key Performance Indicators (KPIs), and Voice of Customer (VOC) analysis, the research aligns LSS with business objectives, customer needs, and sustainability goals. Additionally, it explores how combining LSS with Agile methodologies can improve operational efficiency, governance, and innovation, helping organizations better navigate future challenges. This research offers valuable insights for executives, practitioners, and researchers, supporting leadership development, data-driven decision-making, and long-term value creation. Future studies should focus on validating the Structured Lean Leadership Framework, exploring Agile-LSS integration in regulated industries, and examining the impact of Industry 4.0 technologies on LSS and leadership.