Analytics 3.0 discussion
The business environment is characterized by wide range of activities that necessitate the use of complex analytical techniques to analyze data. The globalization of business operations and emerging competition also require business organizations to continuously adopt analytical techniques that place them in ideal competitive positions. Tom Davenport characterized various stages of data analytics with different features to show the need for business organizations to understand the necessity for advancing their analytical techniques to keep pace with ever -changing the role of data in their organizations.
The first stage in the development of analytics is analytics 1.0, which characterizes the era where business managers use data to get intuitions on how business decisions ought to be. The second stage, known as analytics 2.0 was characterized by the use of increasingly large quantities of data. The role of data also began to become more diverse during this stage. The third stage, referred to as analytics 3.0, was mainly marked by new investments by various organizations in analytical tools that could support the changing business needs. However, the three eras have some features that overlap. For example, all the three stages outline how analytical tools developed. Nevertheless, each stage has some unique features that distinguish it from others. Considering the trends in the applicability and diversity of the analytical techniques, I tend to agree with the way Tom Davenport characterized the three phases of analytics.
The role of data has become more diverse compared to the past whereby managers required few data to make decisions (Davenport, 2009). Additionally, it is evident from the current level of globalization that the sources of data have become more diverse. These new developments call for continuous advancement in the analytical methods. Sophisticated tools that allows for the collection of large amounts of data from diverse sources and continuous staff training to equip them with modern analytical and computational skills support Tom’s intuition in distinguishing the three phases of data analytics.
The level of business competition is evidence that can be used to support Tom Davenport’s characterization of the emergence of the three eras of data analytics. Business organizations use data to design competitive model that enable them to control significant market shares (Davenport, 2009). Some organizations are continuously investing in analytics that allows them to meet the changing needs of the global market. As such, there is an irresistible need to embrace changes in the analytical tools to keep business organizations at the desired competitive edges. The efficiency of data analysis ensures high-quality decisions are made. Besides, most of the online organizations like Google have been able to exploit new business opportunities because of their ability to utilize data efficiently. Thus, the characterization of the three eras of the development of analytics is instrumental in the study of the progress in the business development.
References
Davenport T.H. (2009).Analytics 3.0: Spotlight on Making Your Company Data-Friendly. Harvard Business Review.
