Using Data Driven Decision Making

Data driven decision-making is the analytical gathering and dissecting of a variety of data (test scores, course grades, teacher observation, discipline, free and reduced lunch, and other demographic

Data consists of the descriptions that can be used to summarize the raw facts of everyday happenings and objects. These raw facts can be anything from customer count to average sale per ring. PayPal co-founder Max Levchin said once said that “The world is now awash in data and we can see consumers in a lot clearer ways.” To a business owner like Max, data is important because it provides the means to make better decisions for the customer.

Not including alphabetic characters in a Social Security Number field is an example of _____.

This report finds that data-driven decision making involves the collection, combining and crunching of data received from multiple sources throughout the organization. The technique can contribute to the improvement of Acme’s decision making process as a whole. Acme gathers

In the past, leaders often relied on their intuition and pursued a hypothesis driven approach to strategic decision making. Field of data science has entirely shifted this paradigm. The advent of machine learning and pattern recognition techniques, in conjunction with the growth of cloud storage and parallelized computational capabilities has given business leaders enormous flexibility to boil the ocean and make decisions entirely based on data.

The word "data" may seem to be facts or numbers collected for future references and analysis of a subject that is being carefully examined, but data are pretty much used in all aspects of our lives. With these important facts and statistics, we can help an individual or a company reduce a significant amount of cost. These data can help companies such as Apple realized future growth potentials and where it can better maximize its income.

“Every truth has two sides; it is as well to look at both, before we commit ourselves to either” - Aesop

There are several different types of systems like Customer Relationship Management (CRM), and Enterprise Resource Planning (ERP), which are being used by organizations to make decision processes. These systems have progressed tremendously in the last few years by making large amounts of information accessible using data marts and data warehouses (Wixom & Watson, 2001). The above mentioned systems and many more that are not mentioned above allow managers to analyse data depending on the business requirements, to make better informed decisions. These systems have made the decision-making processes easy to a certain point, when used properly. If this system are not used effectively, they can prevent optimization of the decision making process. Humans are the once who make decisions in any organisation/industry and not

decisions made at this level are likely to have a large impact on the organisation as a

A good methodology to organizations such as the PRC is the practice of evidence-base data driven decision making. In fact, evidence-based decision making is a directional approach to organizations when creating or making decisions supported by the collection of data (Power, 2014). Unfortunately, this is a tool which is not practice at the PRC and it is necessary for Mrs. Lewis and her future partners to have in place. According to research, practicing evidence-based data decision making is a lifelong commitment, which keeps on making positive transformations and improvements to organizations (Mandinach & Jackson 2012). Additionally, the importance of adopting such a practice can benefit executive directors like Mrs. Lewis and provides a greater

Today, new organizations are being formed continuously and, as a result, competition is fierce. It is key that organizations should use be able to make well-informed decision in order to be successful in business. However, most of these organizations are not able to make decisions effectively due to business data are not kept appropriately. Furthermore, if organizations do not provide strategic information for making decisions, the organizations will not gain competitive advantages, nor predict future outcomes. Thus, revenues and profits of organizations will be affected. Therefore, by considering this issue, it might be possible to offer solutions for organizations to develop effective decision making strategies.

Bethel University (2010) refers to the need to make the best decisions based on the data you have. This is evidence-based decision making (EBDM). Kreitner and Kinicki (2013) define EBDM as a process of conscientiously using the best available data and evidence when making decisions. There is a five step model to evidence-based decision making that includes identifying the problem or opportunity, gaither internal data or evidence about the problem and evaluate its relevance and validity, gather external evidence about the problem from published research, gather views from the stakeholders affected by the decisions and consider ethical implications, and integrate and critically appraise all data and then make a decision (Kreitner and Kinicki,

As an administrator I intend to use data from not only students to help improve student learning, but I intend to use data to monitor teachers and instruction. An example would be using data to monitor and see if technology is used in a classroom for instruction and if that technology implementation supports the student learning. I would look at data from standardized testing to see areas of weakness or strength and see if I can tap into teachers’ strengths and support areas of weakness that appears in the data. Data is essential to monitoring and improving student learning. According to Kowalski et al. (2008) data-based decision making is “the process of compiling, reviewing, sharing, and using data to assist in improving schools, particularly, enhancing student achievement” (Owen & Valesky, p. 312).

New organizations can leverage Big Data in such a way that it provides benefits that can prove valuable especially to an organization seeking to establish itself and grow. One of these benefits is faster and better decision making. Particularly with the analytics of Big Data, organizations have access to real-time data

In continuation, Duncan’s framework for assessing environmental uncertainty, which examines the environment from environmental change and complexity perspective, will be used to further analyze the type of external environment and thus methods to overcome and adapt to it. All resources from external environment will be adopted to Fayol’s 4 management functions starting from planning, organizing, leading and controlling. The aftermath of this adoption would result in completing best performance for the organization and thus compete effectively. The model is shown at the figure below: