More and more of what happens in the real world these days generates a vast, ongoing flow of digital information, a kind of parallel universe made of data. Now this data has become a valuable new resource for business, thanks to "Big Data" analytics.
The data are "big" in the sense that they comprise a large, complex mass of raw datasets that lack any single defined structure or format. In our new digital age, Big Data proliferate from a wide variety of Internet technologies, data-sharing smart devices and everyday platforms such as call centers, text messages and social media. Through intensive use and constant connectivity, new contents are continually generated in all textual, visual and audio formats. This huge variegation, breadth and continuity is how Big Data is so different from traditional data types that rely on single datasets collected at a given time, such as sales statistics or a customer database.
Analysis of Big Data can boost a company's potential by uncovering hidden patterns and relationships in behaviors and events. Big Data is thus predictive and diagnostic. By contrast, traditional datasets are constrained by their structure and therefore of relatively limited usefulness in forecasting. For example, a customer survey only represents the customers’ attitudes and intentions, not their actual behavior. With Big Data, a company can tap not only its own internal data but also a vast universe of online data about factors like customer lifestyle, weather and competition data. This helps analyze existing relationships, generate new insights and make accurate predictions. Big Data illuminates consumer preferences and tastes to enable new marketing strategies and sales tactics.
EIC's survey of over 60 top firms in Thailand found that more than half have begun to employ Big Data, a trend that began within the past three years. Both the service sector and manufacturing sector use this tool especially to maximize their sales and marketing potential, e.g., to optimize prices and personalize campaigns and promotions. In businesses characterized by high competition and relatively similar products, such as telecommunications and real estate, companies can deploy Big Data to differentiate their offerings. In manufacturing, makers of electronics, appliances, autos and auto parts utilize Big Data to improve productivity.
Big Data are likely to play much bigger role in the Thai private sector during the next three years, in line with the global trend for companies to get smarter about consumers, on the one hand, and their own operations, on the other. The "smart consumer" concept is about catering to today's demanding, digitally immersed consumer. The "smart company" model is about using Big Data and other advanced technologies to enhance manufacturing, service and administrative operations. Our survey finds that among the Thai firms that do not already use Big Data, some 70% plan to do so in the near future. Gearing up to use this process takes about one to three years, however. On the sales and marketing side, companies should develop Big Data analytics to cope with complex consumer behavior, high expectations and minimal brand loyalty, as social media ramp up these pressures in the marketplace. To improve internal operations, companies should use Big Data to save costs, improve productivity and enhance human resources.
Formerly easy to please, Thai customers have become highly sophisticated and demanding. EIC found that over 80% of Thai consumers now expect that products and services will fit their preferences in an optimal way, and they prioritize quality. Yet they have little brand loyalty. Fortunately, Big Data can help. Data analytics on signals like images and comments posted on social media, search engine keywords, and Internet of things (IoT) data can lead toward strategies that meet individual customer needs via personalized marketing, price optimization, cross-selling and so on.
Thai corporates now face pressures from higher operating costs, shrinking productivity, and high staff turnover. Once again, data analytics can help. It starts with switching to digital storage of relevant data. One example is installing sensors in the assembly in order to collect a large data set, which can help prevent defects and enhance productivity. Analyzing data on employees' behavior and interests can help identify the best candidates and prolong their tenure.
EIC believes that the business sectors that are best positioned to take advantage of Big Data are retail, transportation & logistics, and telecommunication & media, since they already possess an abundance of relevant data and can easily access more. Other companies can get started by digitizing their existing data. EIC studied how various Thai business sectors differ in their Big Data potential in terms of readiness and benefits. The study examined three indicators: data preparedness, potential business benefits, and preparation time. Retail, transport & logistics, and telecom & media are in a superior position because they are service-oriented businesses that interact extensively with customers. As a result, all the customer data they already collect every day -- e.g., for online purchases, GPS, voice calls and mobile internet use -- can be harnessed in sales and marketing strategies that constantly refashion products and services to suit emerging needs. Companies that believe they should move toward adopting Big Data should embrace digital platforms in order to collect real-time data, e.g., by developing the company website, establishing a social-media presence, installing sensors in the assembly line, and incorporating external data into internal data for analytical purposes. These digital platforms help a company deploy relevant data to stay competitive and grow.
Businesses are becoming ever more data-driven. But applying Big Data successfully requires clear objectives, appropriate data sources and knowledgeable analysts. Entrepreneurs and executives often rely on their own experience and instinct when making decisions. But now the abundant availability of useful data together with effective analytic tools help minimize personal bias. The key is to select the right data, adopt the right thinking process, and use the right analytical tools. But Big Data is not a short cut to success. Companies need to aim for long-term sustainable growth, which requires keeping ahead of fast-changing trends and adapting strategy proactively.