By Richard L. Parcia
Here’s a typical Filipino exchange. “Can I ask you a question?” says Pedro. “Sure, huwag lang math,” Juan replied. Such is the tale of the common Filipino’s aversion to anything with numbers.
But don?t get me wrong. We have brilliant mathematicians. We have kids who win math Olympiads with hardly have any support from our society. We have statisticians who man the information systems of the most complex industries. At the basic level, we have math teachers who are masters with equations, armed only with three pieces of chalk and an old rag for an eraser.
For sure, our aversion to anything with decimals is not genetic. Just like the rest of humanity, we are built to reason. We are not incapable of it; we are just averse to it. But if the things that we love tell us what we are, as Thomas Aquinas once quipped, then the same can be said of us for the things that we hate.
All the above were my thoughts as I made my way to a conference some weeks ago on data analytics. SAS Institute’s Marianne Decena sent me an invitation to see their new module that deals with data graphics.
Let me say that I have been a SAS user for almost my entire career. But that’s the thing: I don?t know a lot of SAS users because the product, in my early professional life, was known only to hardcore statisticians and researchers.
As a graduate student who struggled financially, I was forced to learn it from my graduate research adviser, Dr. Santiago M. Alviar, who was then a full-professor of computer science in UP Los Banos (thank you so much sir, wherever you are).
Because it was only known to a few people then — and majority of them were academics — I did not know a lot of people who used it for decision-making with practical applications.
It was the same case with other products like Statistica and SPSS. Of course, SPSS became very popular in schools because of its portability. However, beyond the mandatory thesis writing rudiments, it was hardly considered as a business tool; it is just a tool that most graduates were so eager to dispose of and forget after seeing their names in the list of graduates.
This is even true in graduate research in business. An MBA is the preferred graduate degree of professionals and executives for good reason. However, there aren?t a lot of MBA schools left in the country that still requires their graduates to write a thesis or a research output as a prerequisite for graduation. Most schools have tweaked their programs with ?soft skills? and ?leadership? courses.
The argument for it (or against it) is that research — data analytical work in general — is impractical for professional workers or executives as they don?t do such things while in the work place. I always found that argument wanting because it is within the business setting that decisions are driven by data analysis.
Applied research is a comprehensive data analytics exercise. If a person cannot write the simplest applied research paper (aka position paper), how can we be sure that his or her decision is based on sound analytical thinking? Some will protest, “We?ll just pay for a good analytics person,” but how would you know you are getting what you paid for?
Having said that, I don?t think that the problem are the tools. I suspect that the problem is the basic demand for it. If it?s not a way of life for our people to solve problems with numbers, then there is no need for the tools at all. These tools, as we all know, only make the processing faster. The fundamentals should be solid and demand for it, inevitable.
So, I was quite surprised with the turnout of the conference. The universities were well represented. I was also surprising to see educational institutions which are not exactly known for research, much less advanced analytics, as participants in paper competitions. It is good to know that more and more people are driven to data analytics and just not the statistician themselves.
Data analytics is not entirely new but its importance to business has been recently amplified. Our connected world has ushered in the era of Big Data. Thus, there is a need for approaches that can make this data work for business, health, and even defense.
In fact, the battle for markets are waged, won, and lost daily not by big percentages but the tiniest of margins brought about high velocity number crunching.
The term real-time data has never been so true. Analytics professionals are scampering for data points and sources to provide better pictures (models) to decision-makers. And analytics professionals are the only ones equipped to do this, thus the cost for their services has skyrocketed in recent years ? and it will not change in the near future. It will be this way moving forward.
For the ordinary person, as we get more and more dependent with things that provide data, our lifestyles will be shaped by these analytics professionals. They may not exactly be the ones who will show the world the picture of tomorrow. But it is their brush that will paint it.
Richard L. Parcia, Ph.D., is an associate professor of information systems at the Graduate School of the University of Santo Tomas. He has held various technology positions at Intel, TriQuint Semiconductor, and BayanTrade. Currently, he is the senior manager for IT Infrastructure Services and Incubation at the United Health Group