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Data driven decision making a literature review

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In business, you constantly have to make decisions — from how much raw material to order to how to optimize retail traffic for changing weather. In days gone by, you might have consulted the person who had been around the longest for their best guess; for a more scientific approach, you might have also looked at sales records. Today, companies are finding that the best answers to these questions come from another source entirely: large amounts of data and computer-driven analysis that you rigorously leverage to make predictions. This is called data-driven decision making DDDM. Data-driven decision making DDDM is the practice of collecting data, analyzing it, and basing decisions on insights derived from the information.
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Wisdom within: unlocking the potential of big data for nursing regulators

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Data-Driven Decisions Start with These 4 Questions

Big data is consistently cited by business leaders as a central driver of business innovation. Data-driven decision-making DDDM is defined as making decisions based on hard data as opposed to intuition, observation, or guesswork. The value of data-driven decisions is dependent on the quality of the data and its analysis and interpretation. DDDM is generally used to gain a competitive advantage but can be used to help organizations reduce costs and run more efficiently.
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Why Data Driven Decision Making is Your Path To Business Success

We read about it everywhere. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. Of course, this sounds incredible in theory.
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Aim: This paper explores the potential for incorporating big data in nursing regulators' decision-making and policy development. Big data, commonly described as the extensive volume of information that individuals and agencies generate daily, is a concept familiar to the business community but is only beginning to be explored by the public sector. Background: Using insights gained from a recent research project, the College and Association of Registered Nurses of Alberta, in Canada is creating an organizational culture of data-driven decision-making throughout its regulatory and professional functions. The goal is to enable the organization to respond quickly and profoundly to nursing issues in a rapidly changing healthcare environment. Sources of evidence: The evidence includes a review of the Learning from Experience: Improving the Process of Internationally Educated Nurses' Applications for Registration LFE research project , combined with a literature review on data-driven decision-making within nursing and healthcare settings, and the incorporation of big data in the private and public sectors, primarily in North America.
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