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  • Data Driven Decision Making (Dddm)


     

    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

     

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    Nice one.. but don't you think sometimes Data is a false God, there is possibility of generating fake data and also no matter how deep you go, you’re only looking at one piece of the puzzle. What do you think of this or in short, what are the problems with DDDM


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    @Anita Naikwadi- Thank you for showing interest in this article. As far as your question is concerned, there are a few problems associated with DDDM as it is by nature that everything has both positive and negative aspects. Some of the problems with data-driven decision making is that:
    - it is difficult to gather data and then analyze
    - the time required for decision making is generally higher as compared to by gut feeling
    - experts in the field has to be hired which imposes extra cost on the organization

     

    But in spite of all these problems, the pros of DDDM are much more thereby making it lucrative for company to indulge in these activities. Also the possibility of fake data is always there, but it is the task of analyst to identify the relevant information and use it for the benefit of the organization.

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    Hello Aakash,


     


    A very nicely written article. But I have a question regarding your topic. You have talked about data-driven decision making but how is this useful in day to day operations of any company? 


    As we all know that the demand pattern is varying daily and just focusing on data to make future decisions in my sense is not a correct answer to the problem.


     


    Your view to the point please.


     


    Thank you.


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    Hi,


     


    Thank you very much for the details about Data-Driven Decision Making. I was searching for any report on this topic to present it to my boss to use my concept of using data in taking decisions. Now I can show your (which I felt was very wisely written) as well as other articles in the website to show her the importance of data. 


     


    I work as a salesperson in a company. We have to go to various types of customers and persuade them to take our product. In recent few year we have been noticing that our competitor company is progressing well. After some initial research I got that they are using some data analytics tools to go to only specific type of customers thereby have more effective selling as compared to our organization. I need to know how should we improve our revenues. Can you please help me in this regard, so that I can persuade my boss to use DDDM ?


     


    Thank you,


    Sameera


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    Hiii Aryan Verma,


     


    Thank you for your comments and perspection.


     


    Talking about your question, I totally agree that we don't see much use of DDDM in day to day operations of a company. But in reality it is not so that they don't exist. It is just that it is the back-end which does the analysis work and only the simple report is presented to the management. So we feel that it is not useful. But as I have stated earlier also that DDDM helps in making proper and accurate decisions in our operations.


     


    Coming to your second part of query, it is true that demand varies daily. But if we use the concept of agility for fulfilling the demand then only data can help in getting the proper results. For example, consider "Godrej Consumers" is a company which uses Agile supply chain and all demand-supply calculation is done in very short span of time as compared to previous techniques of quarterly fore castings. So it is not that data varies daily, but how we process data is more important.


     


    I hope I answered you well.


     


    Thank you


    Aakash


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    Hi Sameera,


     


    Thank you for showing interest in the article.


     


    It is true that data-driven decision making is very helpful in every sector whether it is marketing, operations or retailing. But the most important is to use it in a proper way as required. For example, let us consider your company's case only if your company uses the previous records to identify the more perspective target consumers then it will certainly help you to improve your revenues. Also company can carry out some survey for the class for people preferring your product so that you can sell only to those people. This will not only reduce the efforts but also reduce the requirement of company's resources.


     


    I hope I satisfied your query with full justification.


     


    Thanks,


    Aakash


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    Hi Deepti,


     


    Thank you for your interest in the article. That is a very good question, because in the entire article and discussion so far I have only focused on industrial aspect, but you came up with question about day to day life. In our day to day activities we also use DDDM, but the thing is that we do that in sub-conscious mind and not intentionally. For example, if you want to go to your relatives place on a holiday and you have numerous routes to follow. Then you will certainly look at all the aspects like traffic density on a particular route, length of route and if you have some other work in the way. So, this is also one of the application of data-driven decision making. There can be many other similar examples.


     


    I hope I answered your query well.


     


    Thank you


    Aakash


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    Hiii Aryan Verma,

     

    Thank you for your comments and perspection.

     

    Talking about your question, I totally agree that we don't see much use of DDDM in day to day operations of a company. But in reality it is not so that they don't exist. It is just that it is the back-end which does the analysis work and only the simple report is presented to the management. So we feel that it is not useful. But as I have stated earlier also that DDDM helps in making proper and accurate decisions in our operations.

     

    Coming to your second part of query, it is true that demand varies daily. But if we use the concept of agility for fulfilling the demand then only data can help in getting the proper results. For example, consider "Godrej Consumers" is a company which uses Agile supply chain and all demand-supply calculation is done in very short span of time as compared to previous techniques of quarterly fore castings. So it is not that data varies daily, but how we process data is more important.

     

    I hope I answered you well.

     

    Thank you

    Aakash

     

    Thank you Aakash for that nice reply. All the best !!!

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    Nice post

    Will see if this can be more thorough with lots of examples.

     

    @Amit Kumar- Thank you very much for your perspective.

    Yes there may be few shortcomings and I should have given more examples but due to work constraint I have to cut short my article. But surely if you want to know more about it, you are free to ask.

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