NACHIKETA .

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.

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.

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.

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.

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

Thanks Abhishek, glad that you liked the article.

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.

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. http://www.forbes.com/sites/joshbersin/2013/10/07/big-data-in-human-resources-a-world-of-haves-and-have-nots/

Thanks Aayush. I will always remember that Mu-Sigma incident.

Nice Nachi!!!! ...very well written, wat are the techniques ideas are their for data collection, at least to the level to make decisions. Thanks for the appreciation Stacy Angom and Karan Kamra. Since both of you have asked a similar question I'd like to answer both of them together. I concur with you on the importance of data collection and it's truly a wonderful question. As I have stated repeatedly in the comments Data in the Knowledge Base is basically from three sources. 1. Legacy System/Core Transaction Processing System - The data from these sources is saved in the form of a core dataset and incremental snapshots of the data at fixed intervals of time. 2. Customer Relationship Management system - The data from the CRM system is cleansed for inconsistencies and added to the data from Stage 1 wherever needed. 3. Market, Industry and Environment data - The Market, Industry and environment data is obtained by evaluating the environment variables and internal and external reports and market analysis. In addition to the aforementioned types historical data, expert opinion and industry specific models may also be a part of the knowledge base.

Thanks Himanshu Lohani.. Your question is multi-fold and I would like to answer it byte-by-byte. I agree with you to the extent that yes in times when we don't have sufficient data at hand we have to take wild guesses. But taking such wild guesses repeatedly bequeath logic. We have so much data nowadays. The world today is home to 5 zetta bytes of data. Facebook alone collects upto 15 TB of data each day. Needless to say, we now need to come out of our hollow cocoons of intuitive decision making and face the brave new world of data. Today Data is everywhere. We have enough data to find solutions to most of our problems however structured or unstructured they may be. One of the key features of a DSS is the ability to solve arbitrary and unstructured problems and that will be the key to success in the future. This feature will also help us seek newer problems and apply all our pre-obtained knowledge on them to solve the, This is the power of Data Driven Decision Making.

Thanks Swati for the compliments. I totally agree with you on the fact that Decision making has been based on reasoning and logic since time immemorial. Intuitive decision making has always been a smaller set. And in the age of Big Data, we realize that we have the golden opportunity to tune into this data and utilize it to make better and more sound decisions...

Thanks Chahat, I hope this article was of some help to you and thanks for your motivational words.

Thanks Aditya. Glad the article could help you get an insight into this intriguing world.

Dear Sakshi, thanks for the praise. now moving on to your question. Humans make decisions on the basis of their perceptions of reality and not reality itself. These perceptions are based on their sensory organs, experiences, emotions and motivation amongst other factors. These perceptions also suffer from camouflage, recency effect, contrast effect and grouping along with a host of arbitrary errors. These perceptions differ from the reality in varying degrees and in worst case scenario it can be unrecognizably different from the reality. Thus the question that really comes to all our minds is whether it is safe to take decisions on such false premises??? The answer is no. Human Decision making is blinded by our perception which acts a screen between the outside world. This perception is riddled with biases and errors. There have been cases where the best possible solution to a given problem has been ignored completely by the human mind or camouflaged or grouped along with irrational solutions. Also human decision making stops when we arrive at an optimal solution. What we fail to recognize is that there maybe more than one optimal solutions to a problem. On the other hand DSS systems start with an exhaustive list of possible solutions and evaluate each of them on their merits and demerits. Thus they can arrive at multiple optimal solutions and never miss the best solution.