# Resilience Analysis Grid-Rasch Rating Scale Model for Measuring Organizational Resilience Potential
## 4 Discussion and Conclusions  
This paper demonstrates the practical feasibility of the proposed method in the context of OHS through the use of a dedicated questionnaire and summary data. The standard RAG provides a snapshot of the state of an organization's resilience potential in the absence of a normative sample. It can be employed as a longitudinal  
Figure 4: Organization ability estimates for learning (error bars represent standard error). Figure 5: Organization ability estimates for anticipating (error bars represent standard error). analysis tool to examine the changes in an organization's resilience potential over time. When a questionnaire is distributed to multiple organizations, direct comparison on a defined scale is inherently limited by the absence of a common standard against which the datasets can be evaluated. The integration of the Rasch model into resilience measurement has several advantages in terms of reduced complexity and increased objectivity. The simplification achieved with the Rasch model is largely due to its unidimensional structure, where all items on a rating scale measure a single latent trait, i.e., the potential of the corresponding ability possessed by each organization. The Rasch model estimates both the item difficulty and organizational resilience potential for each of the four pillar abilities on the same scale, allowing organizations to be differentiated according to their responses to the individual items for each ability. This change in methodology allows practitioners to derive a direct, quantifiable measure on an objective relative scale of resilience potential based solely on questionnaire responses from a group of organizations, dispensing with a normative group. Because the Rasch model produces estimates on a common, unidimensional scale, it provides a standardized measure of resilience that facilitates comparisons of potential between different groups, such as departments, professional teams, or demographics. The potential for the RAG-Rasch scale model to be a valuable tool in OHS field is significant, and it offers a means of overcoming the limitations of its predecessor. The method permits a single cross-sectional measurement campaign to evaluate the resilience potential of a set of comparable organizations, providing an objective scale that does not require a normative sample. This work presented here, although based on synthetic data, delineates a methodology suitable for assessing organizational resilience in OHS. As is, this methodology could be applied in real organizational contexts to compare the resilience of different organizations operating under the same conditions. Depending on the extent of the sociotechnical system being analyzed, several factories operating in the same domain can be assessed at once, and it is possible to compare different teams in the same organization. Moreover, an organization that has demonstrated resilience in the past could be in principle used as a benchmark, which simplifies the assessment process for managers and provides them with a more reliable measure. This study has several limitations that require further exploration. Firstly, while the RAG-Rasch model demonstrates scalability in handling multiple organizations simultaneously, its application to larger datasets or diverse sectors remains untested. Future research should explore the model's performance with real-world organizational data and assess its scalability in more complex sociotechnical systems. Secondly, the integration of this framework with real-time monitoring tools could enhance its practical applicability by enabling continuous data collection and immediate feedback, facilitating dynamic resilience assessment and adaptation. Investigating these avenues will be critical for validating and extending the utility of the RAG-Rasch approach in operational contexts. The RAG-Rasch model inherits the assumptions of the Rasch RSM, but without implying operational changes in the administration of the RAG instrument.