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Data driven decision making (DDDM) As it is rightly said by Plato, “Necessity 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, “Data Science and its Relationship to Big Data and Data-Driven Decision Making,†Foster Provost and Tom Fawcett define Data-Driven Decision Making as “the practice of basing decisions on the analysis of data rather than purely on intuition.†Equally succinctly, they view data science “as the connective tissue between data-processing technologies (including those for big data) and data-driven decision making.†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 “a person possesses a basic understanding of how data can be used to inform instruction†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 “Strength in Numbers: How Does Data-Driven Decision making Affect Firm Performance?†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: 1. Commodity priced computing 2. Massive file system storage and retrieval technology 3. Bandwidth 4. Smart devices: Records are everywhere 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. It’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: 1) Collect all data from various sources 2) Create a file of raw data and arrange properly 3) According to predefined index, interpret the data to make a data file 4) Analyze this data file generated 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. References: · http://blogs.wsj.com/cio/2013/09/27/data-driven-decision-making-promises-and-limits/ · http://online.liebertpub.com/doi/full/10.1089/big.2013.1508 · www.a51.nl/storage/pdf/SSRN_id1819486.pdf‎ · https://www.950.ibm.com/events/wwe/grp/grp017.nsf/vLookupPDFs/Michael%20Kowolenko%20Presentation/$file/Michael%20Kowolenko%20Presentation.pdf Note - Visitors shall not be able to comment on this article until they are logged in.

You have been making decisions on the basis of your gut; it has never led you astray. Undoubtedly, you have been hearing this buzz about using data to make decisions around you. Can Data Driven Decision Making (D3M) be trusted? Is it worth all the hoopla surrounding it? Let us find out. As the name suggests, D3M is literally making decisions based on the analysis of data or information. Primarily, the information that must be analysed has to be relevant and there has to be a sufficient amount to help you make your decision. We shall discuss more about the nitty-gritties later as we dissect this term further. The concept of D3M was born out of necessity. Today, any action by a human causes data to be generated. According to an article on TechnologyReview, in the year 2012, 2.8 zettabytes of data was generated. That is almost equal to 3 billion hard disks of 1 terabyte each. A one terabyte hard disk can store 250,000 songs. Mind boggling, is it not? Even if you were to deal with the smallest fraction of the human race, there is still too much data for a mere mortal to handle. Enter the concepts of Big Data and D3M; these concepts have perhaps single-handedly revolutionized the way we make decisions. Surprisingly, the concept of D3M has been around for a really long time; organisations started using it as early as the 1980s. It is just the scale and corresponding technology that has evolved. It is best stated in an article by Pamela Wheaton Shorr back in 2003 where she states that making a decision without data is similar to flying a plane in the dark without any radar. She also states that using D3M makes sure that everyone is held accountable; in her words-“ there is nowhere to hide†because the analysis of collected data can find out the most minute of discrepancies ensuring you do not lose any money to such irregularities. Contrary to what many people believe, D3M is not that different from the methods that we have been using to make decisions. For starters, it is used all across the organization in different capacities as stated by Irving Wladawsky-Berger in this article on the Wall Street Journal. Henceforth, I aim to make it clear that D3M is an extension to the current intuition based decision making and not a replacement. As mentioned by several experts, every decision is made two times- a.) Intuition: We make a decision on the basis of our intuition and past knowledge b.) Data driven: Once data is available, we decide to continue with or forego the decision altogether. The benefit of D3M is that you can combine these steps into one and get better value for the time spent in making that decision. Even though it is not apparent, what we call intuition and belief are often a sum total of data. Our belief is born out of our past experiences; that too is data evaluated by our brain. So in essence when we talk about D3M, we have brought out the workings of our brain into the real world. Just like our brain, the D3M too has points which if not watched out for may cause incorrect decisions to be made. i.) Time consistency : Any decision that we make is of use to us only within a limited time frame. Similarly, for any decision made through the D3M system, every decision is good as long as it is made on time. What causes a delay in decision making? The answer is rather simple when you think about it. Just like in life, here too, you cannot have the perfect answer. It is important to draw the line somewhere. Before making any decision using the D3M, you have to ask yourself- “Whether you want the correct answers – quickly if possible or do you want the answers quickly – correct if possible?†Something we must do in life as well. ii.) How much data is enough data ? : While making decisions conventionally, it is quite possible for us to overthink things and in trying to account for everything, we fail to make an apt decision in time. The equivalent of this in terms of D3M is the above mentioned question. Here, experts advise us to use our instinct and decide the bare minimum amount of data that we need to make our decision. Most experts give a fairly simple mantra to highlight the importance of this concept- “ Garbage in, garbage out â€; this phrase highlights that the better the quality of data you put in for analysis, the better the results. It is here that your formidable intuitive skills will be useful the most. iii.) Confirmation : More often than not, we tend to pre-formulate an opinion or decision in our minds and instead of arriving at that decision through analysis; we use that analysis to verify our decision. Most of the times, we tend to ignore any discrepancies between the suggested decision and our pre-decided decision. This causes us to make the wrong decisions. An easy way out is to be ready to make changes to our initial assumptions. This is similar to the way we streamline our decisions in real life based upon feedback. In the discussion so far, I have tried to cover all the important details about D3M. The purpose of presenting even the possible issues above is to show you that this system is just an extension of what you have been doing till now. The benefit of D3M is that it gives you the ability to quantify your decision and you have absolute control over the decision making process. You do not have to take my word for it; just refer to the links provided within the article and make sure for yourself. References: 1. Decision-Driven Data Management: A Strategy for Better Decisions with Better Data (SAS White paper) 2. 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