Enhancing Efficiency, Completeness, and Data Quality
Introduction
The rapid development of Artificial Intelligence (AI), particularly Generative AI (GenAI), has significantly changed the way people work. AI is no longer merely a technical support tool; it has evolved into a thinking partner that helps professionals work more systematically, efficiently, and comprehensively. In line with my Objective and Key Results (OKR), “Implement GenAI in work tasks and document outcomes on Ecolabs,” one of the first and most impactful implementations I undertook was in the process of creating employee satisfaction surveys.
This article documents that experience, explains how GenAI is integrated into daily work, and highlights the tangible value it brings—especially in terms of efficiency, survey completeness, and the quality of insights generated.
Background of the Work
One of my routine responsibilities is designing employee satisfaction surveys, whether they are topic-specific (such as benefits, health programs, or vendor performance) or more general surveys covering overall employee experience.
Creating an effective survey is not a simple task. It requires:
- A clear understanding of the survey objectives
- Identification of relevant satisfaction dimensions
- Well-structured, unbiased questions
- Ensuring that no critical topics are overlooked
When done manually, this process can be time-consuming. It usually starts with listing survey topics based on past experience and existing references. However, in practice, one or two important aspects are often unintentionally missed, especially when surveys must be prepared within tight timelines.
Challenges of Manual Survey Design
Despite professional experience, manual survey creation has inherent limitations, including:
- Heavy reliance on personal memory and perspective
- Risk of unconscious bias in defining focus areas
- Potential gaps in coverage, such as user experience, service quality, or long-term impact
- Additional time required to validate completeness
As a result, surveys may not fully capture the data needed for strategic decision-making.
The Role of GenAI in Workflow Transformation
Since the introduction of GenAI, this process has become significantly more efficient and reliable. In practice, I use GenAI platforms such as ChatGPT and Gemini AI to support survey creation.
The approach is straightforward but highly effective. I provide specific and structured prompts, typically including:
- The topic of the survey
- The scope or areas to be evaluated
- The objectives or goals of the survey
- The target audience (e.g., all employees or specific groups)
Based on this input, GenAI generates:
- A well-organized survey structure
- Relevant evaluation dimensions
- Comprehensive question sets
- Appropriate rating scales and formats
AI as a Preventive Tool, Not an Instant Solution
It is important to emphasize that AI is not an instant or standalone solution. In this implementation, GenAI serves as a preventive tool—ensuring that each survey:
- Covers all critical dimensions
- Minimizes the risk of missing important topics
- Aligns closely with the intended data objectives
After the AI generates the initial draft, I review, refine, and contextualize the content to align with organizational culture and practical needs. In other words, AI accelerates and enriches the thinking process, while final judgment and responsibility remain human-driven.
Impact on Efficiency and Data Quality
From an efficiency perspective, the impact of GenAI is substantial. Tasks that previously required extended brainstorming and validation can now be completed in a much shorter time. More importantly, the overall quality of the surveys improves because:
- Questions are more structured and consistent
- Evaluation dimensions are more comprehensive
- The resulting data is more relevant and actionable
This directly enhances the quality of analysis and recommendations provided to management.
Conclusion
The implementation of GenAI in survey creation is a clear example of how AI can deliver real value in everyday work. Within the context of the OKR “Implement GenAI in work tasks and document outcomes on Ecolabs,” this experience demonstrates that GenAI is not merely a technological trend but a practical tool that improves both efficiency and output quality.
By using AI as a preventive and complementary resource, I am able to ensure that every survey is more complete, structured, and capable of generating meaningful insights. Looking ahead, this approach can be extended to other work processes, further embedding AI as an integral component of modern, effective, and sustainable ways of working.