From Multi-Skilling Mindset to Lean Operations and AI Adoption. 

In the context where service companies are facing increasing pressure from rising operational costs, shortages of qualified talent, and ever-higher customer experience expectations, labor productivity has become a critical survival factor. However, productivity in service organizations cannot be improved merely by “working faster” or “pushing KPIs harder.”

Based on applied research and real-world implementation across service operations consulting and training programs, this article proposes a systemic approach to productivity optimization. The approach integrates: restructuring the multi-skilling and multi-tasking mindset, standardizing processes and cross-functional collaboration through a Lean Service operating model, and developing a practical roadmap for technology and AI adoption tailored to the realities of service enterprises in Vietnam.

1. Productivity Challenges in Service Enterprises: Where Do the Real Issues Lie?

Through operational assessments and field observations across various service companies, several recurring productivity bottlenecks can be identified:

• Employees are required to handle multiple tasks simultaneously but lack clearly defined competency standards, leading to overload or inefficient performance.
• Operational processes are experience-driven and highly dependent on individuals, with limited standardization and low scalability.
• Coordination among service, sales, operations, and support functions remains fragmented, resulting in errors caused by poor communication, unclear handovers, and ambiguous accountability.
• Technology investments exist but are not embedded into daily work behaviors, creating situations where “systems are in place, but productivity does not improve.”

These issues highlight a common reality: productivity in service enterprises is fundamentally a system-level challenge, not merely an individual capability issue.

2. Multi-Skilling and Multi-Tasking: A Necessary but Insufficient Condition

In many service organizations, “multi-skilling” and “multi-tasking” are often treated as short-term solutions to talent shortages. Practical research, however, shows that:

Multi-skilling without proper management quickly leads to overload, errors, and declining service quality.

An effective approach must be built on three core pillars:

• Developing a Skill Matrix for each service function, clearly defining core competencies, supporting skills, and proficiency levels for each role.
• Assigning, coordinating, and rotating personnel based on competency data rather than intuition or the mindset of “whoever is available does the job.”
• Designing multi-skilling training programs that are closely tied to real operational scenarios such as peak periods, staff shortages, unexpected incidents, and difficult customers.

This enables organizations to shift from reactive multi-tasking to controlled and strategic multi-skilling.

3. Process Standardization and Cross-Functional Collaboration in Lean Operations

A key insight from service operations consulting projects is that:

The greatest sources of waste in service companies do not lie within individual tasks, but at the “handover points” between departments.

To optimize productivity, organizations need to:

• Review and redesign core processes using Lean Service thinking, eliminating unnecessary steps, reducing waiting time, and minimizing rework loops.
• Standardize SOPs based on the principles of being fit-for-purpose, easy to understand, and easy to apply, rather than creating lengthy procedures that no one follows.
• Establish clear standards for cross-functional collaboration: responsibility ownership, information-sharing requirements, handover timing, and completion criteria.
• Integrate typical coordination failure scenarios into training programs through discussions, simulations, and case-based exercises.

This approach significantly reduces operational errors, improves processing speed, and enhances service quality in a sustainable manner.

4. Technology and AI: Productivity Levers for Service Enterprises

Technology delivers real value only when it enables organizations to: Reduce manual work – increase transparency – support fast and accurate decision-making.

Within the service productivity optimization model, technology and AI are applied across three layers:

• Digitalization of daily work: Checklists, reporting, task assignment, shift scheduling, and progress tracking—reducing reliance on paperwork and individual memory.
• Operational support and monitoring: SLA tracking, delay alerts, incident logging, and bottleneck analysis within service processes.
• AI-enabled decision support and training: Resource allocation recommendations, recurring error analysis, SOP development support, scenario-based response design, and on-the-job training assistance.

The critical success factor lies in building a technology and AI adoption roadmap aligned with organizational maturity, rather than chasing trends without driving real behavioral change.

5. Managerial Implications and R&D Directions for Service Enterprises

From an R&D perspective in service management, several key implications emerge:

• Productivity optimization must go hand in hand with a reframing of managerial thinking, integrating people, processes, and technology as a unified system.
• Training delivers real value only when linked to competency assessment, action planning, and post-training follow-up mechanisms.
• AI in service enterprises is not an end goal, but a tool to enhance decision quality and operational effectiveness.
• Future research should focus on measuring the relationships between operational productivity, customer experience (CX), and employee experience (EX).

Optimizing productivity in service company operations is not about doing more with fewer people, but about doing the right work, in the right way, at the right time, based on a well-designed operating system that aligns with real-world business conditions.

This philosophy also lies at the core of Lead-UP Academy’s R&D, consulting, and practice-based training programs: measurable outcomes, behavioral transformation, and sustainable performance improvement for service enterprises navigating today’s volatile and fast-changing environment.

Lead-UP Academy | Learn to Act – Act to Lead