A Framework for Investigating Influence of Organizational Decision Makers on Data Mining Process Achievement

Currently, few studies deal with evaluation of data mining plans in context of solvng organizational problems. A successful data miner is searching to solve a fully defined business problem. To make the data mining (DM) results actionable, the data miner must explain them to the business insider. The interaction process between the business insiders and data miners is actually a knowledge-sharing process. In this study through representing a framwork, influence of organizational decision makers on data mining process and results investigated. By investigating research literature, the critical success factors of data mining plans was identified and the role of organizational decision makers in each step of data mining was investigated.‌ Then, the conceptual framework of influence of organizational decision makers on data mining process achievement was designed. By getting expert opinions, the proposed framework was analyzed and evantually designed the final framework of influence of organizational decision makers on data mining process achievement. Analysis of experts opinions showed that by knowledge sharing of data ming results with decision makers, "learning", "action or internalization" and "enforcing/unlearning" will become as critical success factors. Also, results of examining importance of decision maker's feedback on data mining steps showed that getting feedback from decision makers could have most influence on "knowledge extraction and representing model" step and least on "data cleaning and preprocessing" step.