How Big Data Can Transform Outcomes and Opportunities

The increasing use of “big data” -large, multi-dimensional and quicklychanging datasets -prompted this research, depth interviews that explore how big data affect organizations or even society at large. Examples include one firm now selling data on oil well flow to the well owners, but considering giving it away instead and selling analytics that flag danger signs using 18 years of archival data. The authors conclude that even small firms will find opportunities in big data, likely using consultants rather than employing specialists, and that business as usual will – and should – shift to more creative data usage. “We close loans more quickly now,” says a data analysis manager at a major U. S. bank. “Our Internet of Things (IoT) solutions help us track the records of all supplier parts that are assembled together, so that we can take a deeper look at the supply chain for safety issues,” says a global business line manager for a European-based industrial tool making organization. From a U.S. consultant: “Our work allows residents to know about dangerous releases of chemicals in their neighborhood.” How Big Data Can Transform Outcomes and Opportunities Rutgers Business Review Vol. 4, No. 1 47 From an online sales and e-commerce specialist at an African based airline: “We can now target microsegments of customers with targeted offers and deliver an end-to-end customer experience owing to all the data we have and can analyze.” The study described here investigates specifically how organizations are using big data and what changes occur when they do so. Its focus is how usage transforms “business as usual” in a range of organizations located on three continents, to help any manager assess the value of big data in his or her own organization. Examining the “big data” concept Commonly, the term “big data” is associated with volume (scale and quantity of data), velocity (complexity in data structure) and variety (different format of unstructured and structured data).1 In addition, characteristics such as value (extracting knowledge of data), veracity (data assurance, accuracy of data), variability (constantly changing meaning of data) and visualization (presenting the data in a readable manner) are commonly associated with the term.2,3,4 However, from a management perspective, what matters is how big data are used. Big data analytics refers to extracting unapparent insights from data5 to create valuable business knowledge: enhanced information and understanding about business processes and the business environment.6 In other words, big data alone do not represent a solution to a problem faced by an organization [or by society], but rather can be considered fuel, while analytics represents the engine for business insights.7 The significance of big data for managers varies, of course. Some managers work in an organization where the term is just a concept; some work with such data routinely; most may be in between. All, however, might reasonably ask how its use can be transformative. Such insights can provide clues to what competitors are or will be doing, also suppliers, also customers – and also non-governmental organizations and governmental bodies. In addition, insights concerning how big data can lead to change can provide justification for pushing one’s own organization forward in this realm. Eighty-two percent of executives say their organizations are increasingly using data to drive critical and automated decision-making.8 Also, recent research suggests that big data utilization can lead to an increased profitability and productivity.9,10 Quoting Davenport, whose focus is artificial intelligence: “It is dangerous to do nothing in this area, or to move too slowly.”11 Nevertheless, Merendino et al. see business decision-makers as deficient in knowing how to deal with big data.12 Furthermore, because big data extend How Big Data Can Transform Outcomes and Opportunities 48 Rutgers Business Review Spring 2019 into so many facets of organizational life, it is easy for an organization with some utilization to overlook other utilization opportunities. Such an organization may find big data analytics effective in marketing, as suggested by several authors 13, 14 and/or in supply chain management15 and/or customer relationship management.16 Yet because the data come from and are utilized by different areas within an organization,17 opportunities may be overlooked in other areas of operations or in human resources, for example. The chance to bring such opportunities to light justifies this study, which used depth interviews with managers in Europe, the U.S. and in one case Africa to probe how big data are used and with what payoff. Big data usage: spanning categories of users and functional areas Our qualitative study was undertaken to gain deeper insights into the results of a quantitative survey of 551 Finnish CEOs and other high-level decision makers that we conducted. Based on categorizations derived from Schmarzo,18 that study measured big data use in 10 different company functions: Procurement. In procurement, big data analytics can provide information about supplier performance and assist in predicting and managing supply chain risks. Such analytics can assist in supplier selection and strategic sourcing, but may be helpful also in tracking material availability and detecting quality problems.19, 20 Product development. Big data can accelerate the launch of new products and help to determine product weaknesses earlier in the development cycle. Additionally, big data analytics can provide information about which functionalities and product features customers are willing to pay a premium for and which they are not.21 Manufacturing. Big data analytics enable a company to forecast product demand and thereby predict optimal levels of labor force and personnel allocation.22 Also management can collect real-time performance attributes and parameters. Distribution and supply chain management. In these areas, benefits come from supply chain efficiencies; also data from such sources as RFID tags, EDI transactions and mobile applications24 can be utilized to optimize logistic arrangements. Marketing. Big data consumer analytics can extract hidden insights about consumer behavior.25 Fan, Lau & Zhao26 recommend applying insights from data to such decisions as customer segmentation and customer profiling, product reputation management, promotional marketing analysis and competitor analysis, while Sprigg27 offers an example from a hotel chain of using big data to test the relative success of promotions. How Big Data Can Transform Outcomes and Opportunities Rutgers Business Review Vol. 4, No. 1 49 Pricing and yield management. Big data allow firms to compare quoted prices with those actually paid under varying conditions. For example, in the semiconductor industry, analysis of data for meaningful patterns can influence pricing to increase the likelihood of matching supply to future demand. 28 Merchandising prompts such ideas as an example of a retailer who monitors customers’ abandoned online shopping carts.29 The retailer then targets these customers with a special promotion at the location closest to them, thus combining location data with the store’s inventory levels. Sales. Sales operations utilize orders, customer data, inventory data and supplier data. Additionally, the sales function benefits from information about customers’ preferences, locations and other information to improve product design, production, logistics and sales processes.30 Store operations. Fisher and Raman31 report on optimizing store assortments using sales data from existing products to estimate the demand for relevant attributes, and estimating the demand for a potential new product from the demand for its constituent attributes. Retailers can also use novel technologies such as eye-tracking technology and RFID chips to monitor customers’ in-store behavior,32 while mobile apps add additional opportunities.33 Human resource management. With big data analytics, HR departments can predict personnel allocation requirements more accurately, reduce labor costs34 and better understand employees’ attitudes and behavior toward the company.35 These ten areas, probed in on online survey, led to finding broad usage of big data across firm sizes and across functional areas, although usage in general was only about half of what respondents deemed to be the maximum. The 551 Finnish managers surveyed were asked to scale on a 1 to 5 range their organization’s usage of big data in each area. The results of the survey, shown in Table 1, show no significant differences between the b-to-b and b-to-c marketing organizations in usage. The table does show big data usage spanning all 10 functional areas probed, even though to a lesser extent among small firms. How Big Data Can Transform Outcomes and Opportunities 50 Rutgers Business Review Spring 2019 Table 1. Usage of big data among Finnish managers by function and firm size* Company size All (n=551) Small (n=378) Medium (n=132) Large (n=41) Overall 2.36 2.26 2.52 2.88 Procurement 2.04 1.93 2.20 2.44 Product Development 2.15 2.02 2.36 2.73 Manufacturing 2.22 2.04 2.51 2.95 Distribution 2.13 2.04 2.23 2.63 Marketing 2.41 2.30 2.58 2.93 Pricing and Yield Management 1.90 1.83 1.98 2.27 Merchandising 1.89 1.85 1.89 2.24 Sales 2.14 1.96 2.49 2.61 Store Operations 1.80 1.79 1.65 2.41 Human Resources 2.14 2.05 2.20 2.83 * Average scores shown in the table. The range was from 1 for no usage to 5 for maximum usage. Interviews to gain more specific insights Based on these insights concerning potential transformations possible with big data analytics, we conducted a qualitative study to highlight actual applications. Our study consisted of in-depth interviews with managers and consultants in Africa, Europe, and the U.S., seeking anecdotal or illustrative descriptions of how 18 organizations use big data. Our goal was to identify disrupti