In today’s information age where almost any bit of information is accessible, data-driven management has revolutionized decision making among corporate leaders. Managers and executives can now depend on reliable information systems capable of presenting data specifically organized to their decision needs. Over the years, statistical and basic mathematical models have been developed to increase ease of interpreting the numbers being yielded in a business operation. This is why big data is considered to be the future of business analytics, but this technology is everywhere. It has trickled into your shopping platforms, your social media, your cryptocurrency stocks trading, and even your smart-home technology. Anything that can be harvested into data that predicts your behavior, is harvested, stored, and sold.
Big data is a concept which first started in a report presented by McKinsey, a US-based advisory firm. It refers to the development of new methods, software, and technology which is capable of presenting and interpreting data in newer ways. The goal of big data is to increase the ways in which data can be used, thereby creating more specialized mathematical methods from which different industries can base their decisions. The way it works is that when a data object – which can be as simple as a line of text Is Pepperstone stone regulated? – is transmitted, it is broken down into smaller data chunks, and these chunks are then encrypted and distributed across the network. With data being highly accessible these days, it became a widely accepted concept in the business community. This is why large companies would invest in supercomputers with high-level security clearances and high processing power. The ability to process information as it is needed became one of the driving forces of the economy. A good example in this situation is Zara, the multinational fashion company. They utilized their information to know about their customers per region to predict what kind of fashion trends would be more appropriate in those areas. From there, they were able to increase their sales revenues and reduce spoilage and obsolescence costs related to their industry.
McKinsey expected to increase overall productivity and pacing in the economy through big data. Apart from speed in processing, the discovery of newer data sets is bound to create more solutions for daily business problems. If a business maintains identity records like customer name, gender, preferences, address, and business phone number, big data algorithms could process these bits of information and organize them geographically, making it easier for managers and leaders to make decisions regarding supply chain, distribution, and other pertinent factors. What’s really interesting here is that the use of computational models for decisions may not be limited to data-driven managers anymore, but would extend to corporate leaders as well. The implications related to this prediction would be immense. Normally, computations are used by managers to determine the viability of business transactions, and would not usually involve long-term decisions like overall supply chain management or distribution schemes. With big data, decisions which may be subjective, and are mostly passed on to higher authority, may have an objective basis, making it easier to make these decisions bureaucratically. Apart from this, existing computational models related to business would be revolutionized. For instance, the subjective selection between the use of net present value and economic value added formulas to determine the financial feasibility of long-term projects might be lessened. All of these could add up to one common result, which is the expedited business decision-making process. As decision making and deliberation becomes easier, more and more operations could be handled, leading to higher turnovers in every sector driven by big data.
Despite all of this, there are still those who question the success of the concept. Others claim that while there are firms which benefit from information at big data’s level, most small and medium entities may not be as benefitted. For instance, nations with smaller economies who depend on small and medium enterprises like bar stools shop and smaller businesses may not need sophisticated data sets to run business. It has also been perceived by counter-proponents as a waste of resources, as some of the computational models introduced by big data are left unused. Their argument lies under the assumption that an overload of information may lead to unnecessary expenses when being processed.
While the concerns related to big data are valid, it cannot be denied that the pace of the markets and the opportunity costs associated with it will require the aid of faster solutions. The only way to keep up with these growing demands is to create new ways which may not have been thought of in the past. Big data proposes a new generation of data processing involving both technology and human intervention. The responsibility to keep up with the needs of society has fallen on businesses to make their operations more efficient. Improving business decision-making is now needed more than ever, as the market develops. Even if the impacts of big data have yet to be felt, it cannot be denied that its implications would still be big in the coming years as it is applied.
