The new Blade Runner movie will hit theaters next month. If the new film is anything like the first, I expect a lot of existential topics to permeate both formal and casual discourse. Pop culture’s renewed interest in self-actualization is particularly interesting to me because I see data, specifically the processing of data, as a means of improving ourselves. Cogito ergo sum. I crunch data, therefore I am.
I head the new Data Science Lab of the Asian Institute of Management, which we have christened “ACCeSs@AIM” (Analytics, Computing, and Complex Systems). While not as cool as Tyrell Corporation’s headquarters, the lab is also concerned with commerce, and how data analytics can improve the flow of business and government.
Data science can be an arcane concept to most lay people, so I’ll use a recent (albeit somewhat unfortunate) business development to demonstrate in concrete terms how analytics could have made things better.
Recently, I read that a number of Korean manufacturing businesses, mostly from the garment and electronics industries, were moving operations from the Philippines to Vietnam. This is especially disheartening since, just five years ago, many Korean companies were looking forward to setting up shop in our country. But it seems times have changed.
In a newspaper interview, Korean Chamber of Commerce of the Philippines president Ho Ik Lee provided several reasons for the move, including the lack of incentives to invest in the country, and the high cost of doing business here ― which he said was almost three times higher than Vietnam’s.
What stood out was his assertion that the Philippines needed to ramp up its manufacturing capabilities. I believe one way to maximize our manufacturing potential is by providing smarter, analytics-driven operations. Now, physical manufacturing may seem separate from intangible Data Science, but the two are closely linked.
In 2013, Travis Korte, research analyst at Washington DC-based think tank Center for Data Innovation, declared that data scientists should be the new factory workers. In his piece, Korte asserted that “increased automation and more sophisticated robotics, driven by data science and fed with sufficient volumes of high-quality sensor data, could increase productivity dramatically and help regions with high labor costs stay competitive.”
Let’s say you own a contract manufacturing facility for producing children’s clothing. With “smart manufacturing” (as Korte calls it) you should be able to track every aspect of your operations along each step of the manufacturing process. You would be able to make better purchasing decisions by comparing the quality of raw materials from multiple suppliers, factoring in any potential losses from downtime.
Backed by data science, you could analyze demand for your products across different timelines, even factoring in minute variables such as economic fluctuations abroad and shipping fleet operations.
This can form the basis for a predictive model of anticipating future seasonal demand. With that, you can better manage the hiring of line workers. Managing your factories’ energy consumption will also be more efficient and streamlined. You can schedule production times around electricity peak times.
Now, imagine what it would have been like had we had full smart manufacturing facilities in place for our Korean partners. Data science is all about possibility. I believe embracing data-driven manufacturing would have increased the chances of retaining our accounts with those Korean companies.
This is just the tip of the iceberg. We face a major upheaval in the way we mass-produce goods. We refer to this disruption as the Fourth Industrial Revolution.
The First Industrial Revolution utilized steam power to boost manufacturing. The second used electric power to enable mass production. The third, information technology and electronics. The Fourth Industrial Revolution combines facets of the previous two, while placing emphasis on automating operations. (Yes, robots. No, not SkyNet.)
Worker paranoia over losing jobs to machines has loomed over us for centuries. But the Fourth Industrial Revolution really does require a recalibration of our skill sets and ability to contribute to a society where machines and data-driven operations are fast becoming the norm.
Our goal at ACCeSs@AIM, in synergy with the upcoming MSc Data Science program, is to enable professionals, particularly managers, to engage this brave new world. The word “brave” is key. We want our students to be fearless, not only when they take business risks, but also when they take on technological risks.
A noble task, if I may say so myself, as I find it hard to imagine that modern Luddites torching data centers as a means to reclaim the labor market would be very productive.
Big data doesn’t just measure a website’s traffic or your online search and shopping history. Big data is the story of your business told through, well, data. It is a story that is continuously being written. I can’t wait to see where this tale takes us.
Dr. Christopher P. Monterola heads the School of Innovation, Technology, and Entrepreneurship at the Asian Institute of Management. Chris recently returned to the Philippines from Singapore, where he worked as an expert in Complexity Science, Neural Networks, Computational and Statistical Physics, Social Networks, Biological Physics, and Predictive Analytics. E-mail CMonterolaMT@AIM.edu for more information or visit AIM.edu.