Big Data Analytics Adoption
Big Data is an emerging phenomenon. Nowadays, many organizations have adopted information technology (IT) and information systems (IS) in business to handle huge amounts of data and gain better insights into their business.
Many scholars believe that Business Intelligence (BI), solutions with Analytics capabilities, offer benefits to companies to achieve competitive advantage towards their competitors. According to Adelman et al. (2002), “Business Intelligence is a term that encompasses a broad range of analytical software and solutions for gathering, consolidating, analyzing and providing access to information in a way that is supposed to let an enterprise’s users make better business decisions”.
A report by Gartner (2010) lists data analytics as one of the top 10 strategic technologies. In fact, “Analytics facilitates realization of business objectives through reporting of data to analyze trends, creating predictive models for forecasting, and optimizing business processes for enhanced performance.”
The Institute for Operations Research and Management Science ( INFORMS) identifies three main categories of analytics: Descriptive Analytics (The representation of a set of data is used to understand and analyze business performance); Predictive Analytics (extensive use of data and statistical techniques to explain and predict models of business performance); and Prescriptive Analytics (It comprises a set of mathematical techniques that can be used to generate high-value decisions for actions to improve business performance). Selecting the most appropriate statistical techniques depends on research objectives and nature of data.
MIT and IBM (2011) conducted a study on 3000 executives, managers and analysts across 30 different industries and 100 countries to identify the relationship between the company’s performance and its Analytics ability. They found that Analytics-leading organizations are three times more successful than Analytics-starter organizations. Top performing organizations prefer to use analytics five times more than lower performers. It is clear that the adoption of advanced analytic approaches guide organization’s future strategies and help them to make smarter decisions.
The IBM study, “Big data, Analytics and the Path from Insights to Value” has categorized organizations based on their level of analytic adoption in three levels: Aspirational (Aspirational organizations have few people, processes or tools to collect, understand, incorporate or act on analytic insights);Experienced (Experienced organizations develop better ways to collect, incorporate and act on analytics effectively so they can begin to optimize their organizations); and Transformed (These organizations have substantial experience using analytics across a broad range of functions) . Therefore, identifying the level of organizations’ analytics capability helps them to be better prepared to turn challenges into opportunities.
In addition, there are several factors that directly affect adoption of analytics approaches. A primary obstacle is data quality. Accurate data should be collected and structured in order to extract useful insights out of those data. Lack of understanding of how to use analytics to improve the business is another obstacle in analytics adoption. According to Davenport and Patil (2012), the shortage of data scientists is becoming a serious constraint in many companies. In fact, “data scientist” is considered as a high-ranking professional. “Data analysts are creative; have analytical skills, ability to bring structure to large quantities of formless data; and make analysis possible”. Furthermore, they are able to advise managers on the implications of the data for products, process, and decisions. They also have a solid foundation in math, statistics, probability, computer science, and business. Furthermore, studies indicated that managerial and cultural factors are important in the adoption of analytics. Unfortunately, some organizations do not encourage sharing information and do not intend to apply analytics. They make decisions based on intuition and personal experience instead of fact-based. Therefore, managers, decision makers should realize the importance of big data analytics in improving their business. Changes should be created in organizations for successful adoption of business analytics.
(Image Source: IBM)
By Mojgan Afshari