Decision-Making Framework Using a Growth Hacking Model for Computerized Decision Support

Abstract

Strategic decisions positively drive organizational performance and could have a measurable impact on any enterprise. Proper management and resource allocation are relevant to the growth of any organization, and there is an accelerated progression towards a complete overhaul of manual systems leading to the increased proliferation of digital systems. Businesses with less or no computerization create a bridge between users and data, in turn, causes poor decision making, loss of data on transit, time wastage in data extraction, poor data management, improper use of data and erroneous application of organizational data for decision making. This study utilizes information modeling method aimed at studying a decision-making framework and how growth hacking plays a critical role in the implementation of a decision support system for organizational growth. Supporting decision making in a traditional platform consumes time, taking note of the data collection phase, analysis and the choice of alternatives phases but a decision support system digitizes the whole process of data input or extraction, data processing, and the output mechanisms. The paper models the decision-making steps and also suggests that decision-making will take less time in contrast to the use of traditional methods using this growth hacking model. The end product of the implementation of the suggestions from the output stage of this model is growth.