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@article{207831,
        author = {Pratiksha Pramod Gujale and Dr. Suraj R. Nalawade and Prof. Tapase A.D. and Prof. Sanas A.D},
        title = {THE FUTURE :- DATA DRIVEN DECISION MAKING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {3321-3325},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207831},
        abstract = {Abstract for Data Driven Decision Making:-This empirical study on Industry 5.0 provides verifiable evidence of the transformational potential of data-driven decision making. The validation of data-driven choices as one of the essential elements that Industry 5.0 would use in performance was presented by an impressive increase in decision outcomes of a 46.15%. This fact about choice criteria aligning with pertinent data sources is a manifestation of how much data is significant in the establishment of well-informed processes for decision making. Moreover, the methodical execution and oversight of choices showcase the pragmatic significance of data-driven methodologies.This empirical evidence positions data-driven decision making as a cornerstone for improving operational efficiency, customer happiness, and market share, solidifying its essential role as the industrial environment changes. These results herald in an age when data's revolutionary potential drives industrial progress by providing a compass for companies trying to navigate the complexity of Industry 5.0. This study proposes a model to assess data-driven decision-making (DDDM) readiness in organizations.
We present the results from investigating the DDDM readiness of a Sweetdish organization in the food industry. We designed and developed a questionnaire to collect data about the organization's decision-making and IT systems. We conducted eleven interviews at the case study organization: ten with various functional decision makers and one with the IT Manager about IT systems. The interview data were then analyzed against known decision theories and state-of-the-art DDDM. Based on the interview outcomes, we analyze the data according to the assessment model and recommend changes to the organization's readiness for data-driven decisions. The findings show that while the organization was assessed as ready in the decision-making process and decision-maker pillars, it was not ready in the data or analytics pillars. Accordingly, we offer a set of actions, including reviewing integration and decision systems further, developing dashboards further, increasing data and analytics resources with an enterprise data warehouse, big data management tools, data lake environment, and data analytics algorithms, and defining key roles needed for digitalization and DDDM, such as Data Engineer, Data Scientist, Business Intelligence Specialist, Chief Data Officer, and Data Warehouse Designer/Administrator. The contribution of this study is the DDDM readiness assessment model, which is accompanied by a questionnaire for determining the readiness level in organizations.},
        keywords = {},
        month = {August},
        }