Murphy Choy

The surest way to corrupt a youth is to instruct him to hold in higher esteem those who think alike than those who think differently.

In Uncategorized on November 7, 2011 at 3:21 pm

While being a college kid, I have the privilege of studying Philosophy under two great teachers who taught us the fundamentals of the field. It was a refreshing experience which has no direct influence on my future career but my future choice of wife. It was interesting in the sense that the title is a quote by Nietzsche who is considered some of the most oddball character of all time. Why the above statement?

A few days ago, I have the opportunity of interviewing a candidate who is trying to enter a Masters program. She was lamenting about the problems that she faced at work especially dealing with Business Analytics. I find the conversation interesting and thus I am blogging about it. She is from the Marketing Analytics department of a reputable company and the most frustrating issue she faced is the huge amount of abuse of business analytics to support all the the hypothesis which the bosses want. Very often, the data is tortured and contorted to fit the beliefs of the senior management team and not the reality.

Personally, I find it extremely amusing that companies who are talking about using analytics to improve their business are just digging their own graves. They are ignoring the reality and warping their world to what they believe. This is reinforced by the problem of organizational hierarchy which the superior has a lot of power over the subordinates. If someone believes in something else, they are asked to leave even if the belief is the reality. This promotes herd mentality which has led to catastrophic disaster for our economies.

At the end of the interview, Nietzsche’s statement came into my mind and I hope people will learn to accommodate analytics into their organization.

Business Analytic Opportunity Identification Process: Ontological Approach

In Uncategorized on October 23, 2011 at 6:18 am

A few days ago, we were having a meeting and discussing about the aspects of coming out with a procedure to identify processes or functional area groups where analytics can be applied vigorously and regularly in order to optimize the business. Now this is a very good idea in theory, but it is very difficult practice in reality. One of the key issue that one will face in trying to come out with such a process is that one can never truly understand all the underlying processes that governs an organization. This is particularly the case for companies that are very big all or multi-national in nature.

However this does not mean that we cannot identify processes in order to improve them. The simplest thing that one can actually do is to actually map out the entire process or the entire operational model or aspect of the organization. However, this is not without its difficulties. Many organizations because of the long established history of operation, they have actually forgotten about the origins of the many existing processes and could not give satisfactory explanation as to why this processes were placed or implemented. This resulted in many confusing meetings in which many senior managements will have difficulty communicating with the middle managers.

In order to identify processes, there are a few approaches to doing so and the approach given above is just one of the many processes possible used to identify potential areas. Now the above process is actually an empirical process which relies on the ability to map out the processes of the company. However in this case, I propose an ontological approach towards the identification of potential areas where business analytics can be applied easily. In in my proposal, suppose that any processes or any functional area in which it can be measured quantitatively – they can be optimized further through the use of analytic. Why do I use quantifiable measures? The reason behind is only quantifiable measures in our organization can be optimized by understanding the constituent components, modeling them and in turn improving the overall results. This is far more difficult to achieve using qualitative information. While this is something that I have not experimented with existing data, because this is an ontological approach this is after all a theoretical move.

A dangerous aspect of analytic: dark side of the force

In Uncategorized on October 14, 2011 at 5:10 pm

I was having some discussion with fellow colleagues about the applications of analytic in public sector. We did appreciate some of the great improvements that have occurred as a result of the various analytic initiatives. However, there were some very interesting observations about how analytic can be abused when money is concerned.

We were having a discussion about public amenities and some one in the crowd mentioned that some public services have stopped offering services to people who cannot pay. Now it is useful to understand that public services are not designed to be profitable business and thus non-paying customers are serious problem for them. To prevent this, they have adopted some kind of analytics to prevent this from occurring through rejection of people who are deemed to be unable to pay.


Public services existed to serve the greater public and ensure that the public has access to these amenities. It is almost unthinkable that they actually abuse analytic to deny public access to amenities. Analytic as with all sciences was developed in hope of helping business make better decisions and achieve higher performance but never at the expense of public interest.The other issue is that analytic works on the basis of probability. What if you classified someone wrongly and thus denied that individual of rightful access to amenities?

I sincerely hope that public sectors will look to it as their duties to serve the public and not abuse analytics to deny people of their amenities.