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6 years ago

Data-driven economy for sustainable development

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Back in 2006, out of top five most valuable public companies three were from Oil sector and Microsoft was the only in that list from tech domain. By 2016, in course of just 10 years, only one oil company (ExxonMobil) could somehow retain its position in that list while rest of them are from technology domain. Facebook, Apple, Amazon, Alphabet (Google's parent company) and the big elephant 'Microsoft'!

Besides bringing social and behavioural changes in our daily life, oil-rich countries had been very much influential in shaping world politics during the pick time of Industrial revolution - and that prevails till date. In absence of the components of oil, the world we experience today would have been much different. And now the presence and manipulation of tons of data, is about to bring in the most prolific changes in the domain of our behaviour and thus in the business pattern too. Realising the robust impact of data on business, UK mathematician and architect of Tesco's Clubcard Clive Humby duly coined the phrase 'data is the new oil' back in 2006. The phrase was vividly explained farther by PieroScaruffi, a cognitive scientist and the writer of the book The History of Silicon Valley, with the hint that the difference between oil and data is that the product of oil does not generate more oil (sadly!) while data can be cured, same data can be reused for different purposes and most importantly, data is logically nonperishable. Its reusability and nonperishable characteristics enable data to be the most persuasive driver in shaping business and market behaviour.

Data is playing some mysterious 'upside down' role in decision making. New startups are increasingly creating pressure and outplaying their old giant peers. In the realm of heavily data-driven business world, enterprises are so much equipped with precise customers' data that it seems enterprises know their customers better than the customers know themselves. By developing a unique database of customer profile, Zillow, a data analytics company operating in real estate, has gained super competitive advantage over its rivals in the market. Crafty utilisation of data has given birth to a hefty number of young under-30 billionaires in last decade or so. Just think of 'Dollar Shave Cub' that delivered shaving razors blades to its customers on a monthly basis, was acquired by Unilever for a reported $1.0 billion in cash. It is thought to be the rich database of 'Dollar Shave Club' that actually made Unilever interested to acquire this small startup on its sixth year of launching.

The wind of change is leaving its impact on employment and recruiting pattern to. It is getting extremely classified when it comes to utilisation of chunk of data and drawing actionable and meaningful decisions out of it. McKinsey calculates that big data initiatives of the US healthcare system "could account for $300 billion to $450 billion in reduced healthcare spending". So, how do we deal with these changes having the limitless opportunities? A recent trend tells us that the average machine-learning trained machine will need as many as 10,000 to 100,000 times more data than single human workers will generate during the course of their professional life. This is beyond the capacity of any company.

The economy of Bangladesh is yet to reach data sophistication level. But surely we can exploit the available data. Our economy is heavily dependent on remittance and ready-made garment (RMG) sector. There are sufficient employment data of those countries where we send our manpower. We can gather and analyse those data and predict the skill set they will need in coming days. A skilled person can earn two to five times more than an unskilled person depending on the nature of job. So if we can predict the upcoming skill set requirement in those countries and undertake necessary initiative through private-public partnership, then the employability opportunity will increase and the flow of remittance will be sustainable and get momentum.

Similarly in RMG sector, we are mostly fulfilling the orders from the buyers. Our value addition in the cognitive domain in RMG is insignificant. It does not have any common repository of data bank that can assist in predicting new wave of fashion and trend; thereby we lag behind in developing our required skill set. Merely setting up the institution 'BGMEA Institute of Fashion & Technology' will not adequately support a sector that accounts for about $25 billion of export. In addition to that, our RMG employee base is mostly unskilled. Just to compare, to produce 1.0 million equivalent RMG product India and China need 69 and 45 persons respectively whereas Bangladesh need 145 persons. We cannot endlessly canvass 'cheap labour' as our competitive advantage; it is an eroding one.

We need to embrace the ever-changing information availability pattern and the relationship with technology, keeping the cons aside. It took more than 350 years to 'reach' the printing press from Gutenberg, Germany to this subcontinent but we cannot afford to behave in the same manner while building a data-driven economy. It will be a question of our existence if we fail to match the pace of trend in the era of 4th Industrial Revolution.

Shamim Sahani (John) is a Visiting Faculty at the Jahangirnagar University.

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