Data driven decision making (DDDM)
As it is rightly said by Plato, â€œNecessity is the mother of inventionâ€; it comfortably fits in the life and business perspective. In today competitive world, we cannot even think of succeeding over others if we are not better than them. It is applicable in both day to day lives as well as in Businesses. In day to day life, we have numerous examples of us competing with our colleagues for ranks, posts or various other things. But it is the candidate which has better skills and qualities will always succeed. This thing is also applicable to a larger extent to businesses where every day lakhs and crores of transactions are performed. Any organization should use all its data available judiciously and all the decisions should be based on these data instead of personal beliefs. This process of making decisions based on data is called Data-Driven Decision Making.
In a recently published article, â€œData Science and its Relationship to Big Data and Data-Driven Decision Making,â€ Foster Provost and Tom Fawcett define Data-Driven Decision Making as â€œthe practice of basing decisions on the analysis of data rather than purely on intuition.â€ Equally succinctly, they view data science â€œas the connective tissue between data-processing technologies (including those for big data) and data-driven decision making.â€ This DDDM is being viewed as a tool to help people make smarter, more effective decisions.
Also according to Electronic Learning Assessment Resources (ELAR), a DDDM focus uses student assessment data and relevant background information, to inform decisions related to planning and implementing instructional strategies at the district, school, classroom, and individual student levels. Even the concept of Data literacy meaning â€œa person possesses a basic understanding of how data can be used to inform instructionâ€ is closely inter-weaved with DDDM. We can say Data Literacy as an underlying technique of use of DDDM.
Considering the reference from the research paper â€œStrength in Numbers: How Does Data-Driven Decision making Affect Firm Performance?â€ by Erik Brynjolfsson, MIT & NBER Lorin Hitt, University of Pennsylvania and Heekyung Kim, MIT. A detailed survey data on the business practices and information technology investments of 179 large publicly traded firms, it was found that firms that adopt DDD have output and productivity that is 5-6% higher than what would be expected given their other investments and information technology usage. Such surveys and studies have every now and then showed the importance of data in taking important managerial decisions.
Even the share-market is not luck or belief based. It is based on various complex logics which have to interpreted using different other factors. So it is the need of the hour to work on the data analysis for having better forecasts, demands and market scenarios. If we see all the prospering companies of the world, they go by numbers. It is the challenge on the part of the management to lead the organization towards data-driven decision making. This DDDM is important because of the following reasons:
Keeping in mind these important factors, it become necessary for any company to take decisions very precisely as each and every decision has very long term effects on the company and its revenues. Recently, so many technologies have evolved including Big Data which have made the analysis of data far easier as it was earlier. Now even small information which is sort out of crap data is very useful for the organizations in taking future decisions. In last few year many new organizations had come up which provide services in the field of data analysis which indirectly helps the companies hiring them. Lots of social networking sites provide some data which are used by these analysts to provide related advertisements to the people. This explosion of decision making from personal instincts to data driven can be largely attached to Big Data.
With the advent of Big Data, this has come out even more drastically and most of the companies shifting towards it. Lot of money is being invested in getting meaningful data out of bulk of data available in the companies. Itâ€™s not surprising that data-driven decision making is one of the most promising applications in the emerging discipline of data science. It has an explosive growth.
There are large numbers of characteristics of Data which have to study before taking certain decision. These include variety, volume, velocity, veracity, variables and sources. In finding meaningful information from the raw data the following steps are to be followed:
This complete procedure is a basic process of DDDM. It has to be followed if the accurate analysis is required.
In a nutshell, we can conclude that this data driven decision making is the need of the hour and each and every company should move towards it as soon as possible. It may be looking a tedious and unnecessary at the present moment but its long term effects are very soothing and beneficial for the entire company.
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