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  • My Experiments With Data Driven Decision Making (D3M)


    As a Computer Illiterate growing up in the new millennium, I had tremendous difficulty making sense of how to do most of my stuff. Most of my decisions were snap, on-the-moment and intuitive ones. By the time I was in my teens, I had learnt my way around the big computer problem. My experiences and the Great Indian “Jugaad†mind-set had provided me with a sufficient enough method wherein I only worked on the computer when absolutely necessary. If there was any other way to do the task, any escape route, I gladly followed it.

    By now you must have realised that I was and am sceptic and data-averse. Data to me was always those unreadable files that eat a hell lot of my storage space. I was gaining proficiency in getting around this data problem and along came Big Data. Everyone from Google to Barrack Obama was using it.[1] As a student at one of the most prestigious B-Schools in the knowledge market, not only was I supposed to know what it was, but was expected to be able to tune in and utilise it to make a difference. Life has strange ways of getting back at us, mere mortals, and here was my customised gut wrenching sucker punch. The fighter in me knew I had to do this, but I did not find a way I could.


    A 3 month long research in the field led me to Data Driven Decision Making or D3M. Simply put, it is the pleasure of sipping a coffee in your office chair while you watch your computer work up some algorithms and provide you invaluable decision making tips to face some of your most frequently encountered problems.


    Immediately after, I experimented with the different sorts of decisions that can be made with D3M. The results were a true eye-opener. If we think of decision making as a broad spectrum from operational decisions at one end to strategic decisions at the other. Operational decisions can be characterized as highly structured, routine, short-term oriented and increasingly embodied in sophisticated software applications. On the other hand strategic decisions are taken by the top management and serve to set the long-term directions, policies and procedures of an organization. They tend to be complex and unstructured because of the uncertainty and risks that generally accompany longer term decisions. In between these two extremes, we can have varied decisions including non-routine ones in response to new or unforeseen circumstances beyond the scope of operational processes, and tactical decisions dealing with the necessary adjustments required to implement longer term strategies. [2]



    Half a decade ago, D3M could have only helped you with the more structured forms of decision making but no more. With the advent of Big Data, machines know much more about humans and human behaviour than humans themselves. Sample this, personal analytics can actually allowed me to analyse my Whatsapp chat history and find why most of the girls I chatted with refused me a date. The word cloud usage showed me that my texting skills were uninspiring to say the least with the most common words being “ok†and “yaâ€. I realised I needed to be more creative and engage better. What did not help was that most girls chatted in the window of 8-12pm whereas I had the habit of taking a short nap at the time. Also it helped me identify my most productive work hours and helped me plan out my work better.


    Thus far, all seemed well with D3M but on further research most early moving corporates into the field were still undecided on its benefits. A closer look exposed a distinctly similar pattern in them. Most early moving managers thought that D3M will help them save money or time or both. Research shows that they are misguided to say the least. D3M does neither, atleast not in the short term. What D3M does allow though is discovering solutions you never knew existed. What it will do though is finding needles in the haystack consistently. Another interesting insight was that D3M depends a lot on the data collection. Great collection leads to great results. All we are required to do is ensure data cleanliness, variety and velocity.

    In his book, Data Driven: Profiting from Your Most Important Business Asset, Prof. Thomas Redman summarizes the whole decision making via data as “Good decision makers follow at least three Bayesian principles. First, they bring as much of their prior experience as possible to bear in formulating their initial decision spaces and determining the sorts of data they will consider in making the decision. Second, for big, important decisions, they adopt decision criteria that minimize the maximum risk. Third, they constantly evaluate new data to determine how well a decision is working out, and they do not hesitate to modify the decision as needed.â€


    After months of thorough investigation and experimentation, I have arrived at this conclusion, “To stay a step ahead in this ever competitive world, using Data Driven Decision making is a must. So let D3M take care of all the external data that you need to work with and let your mind focus on understanding “the data from insideâ€. That will surely lead you to not just success but contentment.



    1. http://swampland.time.com/2012/11/07/inside-the-secret-world-of-quants-and-data-crunchers-who-helped-obama-win/

    2. http://blogs.wsj.com/cio/2013/09/27/data-driven-decision-making-promises-and-limits/


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    Nice article


    As  an HR student I want to know D3M use in HR.? 



    One of the most successful uses of Data Driven Decision making has been in the field by Human resources by various HR consultancies and Government Institutions in the US. Some of the Key areas that they have identified are:


    1. Using HR Analytics to diagnose key drivers of organization/business performance

    2. Rigorously evaluating the effects of HR interventions

    3. Assessing costs and consequences of important employee behaviors (e.g., turnover)

    4. Strategic Workforce Planning 

    5. Predictive Analytics about their workforce. (Understanding the drivers of performance and retention, using statistics to decide who to hire, analyzing how pay correlates to performance, etc.)



    I'd suggest that you go through the following link for more information regarding the same.

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    Its a suprise how from 0, your comment count went up to 50 in less than a day.


    Havent seen that happening on forums usually. This D3M thingy is sure creating a buzz.

    I'll take it as compliment towards my marketing skills, Sir. But that just illustrates the power of Data and Networking in today's world. I received information of my selection a few days back. Shared the Link for the same across all my Social Networking Accounts and my blog, and here we are at 50 comments in a day with lots of interesting queries still to be answered and time running out. 


    Credit goes to the Benchmark Six Sigma Team for highlighting such an important issue that people of all ages flocked to read the article and clarify their doubts regarding the same. And It isn't restricted to just my article. Almost all articles have similar number of likes and it only serves to remove all doubts about the importance of this discussion.

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    Really well crafted and well written Nachiketa....you really gave some good insights into an area of which I had very minimalistic knowledge till now..!!!!

    Thanks Kaustabh, Glad that I was able to shed some light on this matter and help you in whatever little way I could.

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    A good write-up.. but isn't it too early to say that D3M is 'THE' thing for the future. I mean, we still don't know the reliability of the information. The information might be as good as predicting the next movement of stock market. Moreover, it will be available to almost all the companies. So, how do we then use it to gain competitive advantage?

    Integrity and Reliability of the data in the knowledge base is one of the cornerstones of D3M. 

    With the advent of Big data and easy availability of data the need for credible information has grown all the more. Therein lies the great chance. the chance to fulfill the huge potential of being a credible source of information. Many firms will strive to achieve that in the near future. A few days ago, Apple bought the Twitter Analytics company Topsy for 200 Million. This shows the importance that analytics will play in the near future. 


    A DSS not only depends on a lot of external data that would be similar and available to everyone but also a lot of internal data which would differ from company to company. It also depends on the customer perceptions of the company and how the customers place the particular brand more than anything else.  


    Thus it is safe to say that the DSS provides us customized solutions that satisfy all our needs, but at the same time provide unique and optimal solutions.

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    I knew that every decision is made by my mind, but now I wonder whether it is backed by intuition or data. I feel that each of my decision is backed by data which comes as a result of intuitive thoughts.

    I look forward for an even strong merger of data of my mind with my intuitive powers.


    Thanks Nishant. It is indeed a great time for us humans. To be able to synergize our intuitive thinking with newer and richer Data Driven Approach, is a win win situation for all stakeholders.

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    good work nachiketha..


    good study :) hope we can have a session to explore more on this Data driven

    Thanks Sasi Msb, glad that you found the article informative and I do recognize the need of more time to explore this hidden gem properly. Lets try and work out something together.

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    Nice work Nachiketa!


    Just one question haunting my mind is that how will D3M help me in unpredictable, unordered and complex context where right decision cannot be made through persistent investigation or understanding of available data/information?

    Thanks Deepika for the effervescent praise.


    As I have already stated that one of the main features of a DSS is that it is able to solve complex and unstructured problems. It is designed in a way that allows queries of any type so on that front your concerns will be minimal.


    In the second case though, where there isn't enough data or data understanding is low, These systems may take an incomplete/inaccurate decision. But even in such cases, the decision of the D3M system will be much more accurate than the decision of a human who's placed in the same situation.

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