In the context of my research on digital transformation in municipalities and small-to-medium-sized enterprises (SMEs), I’ve come to understand continuous improvement (CI) as a complex, systemic process that goes far beyond toolsets and methodologies. While classical drivers such as strategic alignment, leadership commitment, employee engagement, and data-informed decision-making are essential (Bhuiyan & Baghel, 2005; Bessant et al., 2001), their effectiveness depends largely on how they are embedded within broader institutional and technological environments.

In rural municipalities, for example, the potential for continuous improvement is strongly influenced by institutional actors, regional norms, and inter-organizational dynamics. Here, CI often emerges through adaptive governance structures, stakeholder involvement, and the replication of perceived “best practices” in response to normative, coercive, and mimetic pressures—an institutional isomorphism that shapes how digital tools are adopted and sustained (Patalon & Wyczisk, 2024).

In SMEs, particularly those pursuing technology-driven business model innovations, continuous improvement is closely linked to external knowledge partnerships—especially with higher education institutions. These partnerships support firms in overcoming internal capacity limits and enable more robust experimentation with technologies such as predictive analytics, AI, and additive manufacturing. This is evident in sectors like retail and healthcare, where digital innovation must be accompanied by cultural change and the redesign of operational processes.

From a socio-technical perspective, continuous improvement should be understood not merely as operational fine-tuning, but as a dynamic capability—one that enables organizations to strategically adapt to change, embed learning, and realign resources in response to both internal inefficiencies and external pressures (Teece, 2007). This means aligning digital infrastructures with institutional logics and fostering data literacy, participatory leadership, and feedback-oriented organizational cultures.

Ultimately, in both public and private sector settings, CI becomes most impactful when it is treated not as a stand-alone initiative but as a systemic capability—deeply embedded in the organization’s strategic orientation, technological trajectory, and institutional context.

Refs:

Bhuiyan, N., & Baghel, A. (2005). An overview of continuous improvement: from the past to the present. Management Decision, 43(5), 761–771. https://doi.org/10.1108/00251740510597761

Bessant, J., Caffyn, S., & Gallagher, M. (2001). An evolutionary model of continuous improvement behaviour. Technovation, 21(2), 67–77. https://doi.org/10.1016/S0166-4972(00)00023-7

Patalon, M., & Wyczisk, A. (2024). Mapping Digital Transformation of Municipalities through the Lens of Institutional Isomorphism. International Journal on Social and Education Sciences, 6(1), 58–72.

Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640

Continuous improvement in organizations is driven by a combination of mindset, systems, and leadership commitment. At its foundation, it requires a culture of learning where employees are encouraged to question processes, experiment with solutions, and view mistakes as opportunities for growth rather than failures.

Key drivers include:

• Leadership Commitment: Leaders who model continuous learning and improvement set the tone for the entire organization.
• Employee Empowerment: Frontline employees often have the best insights into inefficiencies; giving them ownership over improvements fuels engagement and innovation.
• Customer Feedback: Listening closely to customer needs and expectations pushes organizations to evolve products, services, and processes.
• Data-Driven Decision-Making: Using real-time data and performance metrics helps identify areas needing enhancement and measures the impact of changes.
• Agile Methodologies and Lean Thinking: Frameworks like Agile, Lean, and Six Sigma institutionalize small, frequent improvements rather than waiting for large overhauls.
• Psychological Safety: Teams need to feel safe to propose changes, challenge assumptions, and share new ideas without fear of reprisal.

Ultimately, continuous improvement is not a one-time project but a mindset embedded into the organization's DNA, ensuring it remains resilient, innovative, and competitive over time.

I agree with Tan Kwan Hong that leadership commitment is a must for continuous improvement. However, I believe that has to be backed up by good data collection and ongoing analyses. How do you know if you have improved if you do not know where you started. Identifying the right metrics and tracking them is what any good leader should insist upon to have continuous improvement.