In all conducted surveys, one should strive for as high validity and reliability as possible.
Validity refers to whether we measure what is relevant in the context. That is, does our empirical data answer the question we have asked, are the questions valid in the context? It's really about using the right thing, the right question, at the right time.
Reliability refers to whether we measure in a reliable manner. Have we measured what we intend to measure reliably, accurately, and meticulously? If we ask the wrong questions but do so carefully, meticulously, and thoughtfully, our survey has low validity but high reliability.
If we use very well-tested and carefully crafted questions but ask them in a stressful environment without a chance for reflection or contemplation for the informant, then we get a survey with both low validity and reliability because high validity also requires high reliability.
We have considered our questions to the extent that we believe they are valid for the purpose we intend to use them for. That is, collectively they should give us an image of how the employee perceives themselves, their team, their manager, and their employer. How does the employee perceive the context they are part of? We believe, based on what we have learned from research in the field, that this will help us find keys, factors, or ideas on how to stimulate and motivate the staff and thus be able to convey factors that promote job satisfaction to the management within the Company and others interested in the subject.
Concrete examples of our work to ensure reliability and validity include:
• Reflections on the placement of questions in the survey, studied and compared the results when making changes during the development of our NMI model.
• Comparing results over time from a large number of employee surveys.
• Formulated questions so that they are 1. clear 2. in simple language, 3. easily understandable, 4. with clear definitions, 5. avoiding being leading or value-laden, 6. avoiding being hypothetical 7. avoiding being negating (negative questioning, e.g., I do not think)
• Qualitative studies in connection with the development of the survey, e.g., interviews with respondents from various industries and backgrounds on how they interpret questions and what has been the basis for their answers.
Quicksearch always strives to find statistical methods that minimize the number of questions and the methods that develop the survey industry.
We also believe that through information and the ways in which the surveys were conducted, we have ensured that a high reliability for the survey has been obtained.