Essay

Since the publication of Tom Davenport's Competing On Analytic article in 2006 analytics has rapidly emerged as a strategic priority for businesses. The increased focus on analytics as a value driver has improved business performance and unlocked new revenue streams, but it has also raised new management challenges. Underlying those challenges is the fundamental difficulty in defining "analytics." What definition of analytics best frames the various management implications of this new capability? Specifically, consider the following: a. How has the growth in data volumes, variety, and velocity driven the evolution of analytics? How is analytics an extension of traditional data management practices? How is the analytics practice distinct from traditional data management practices? b. How have businesses changed in the way they view analytics as a strategic asset? How does the recent emphasis on analytics change the way companies think about the traditional people-process-technology model? Can a business in today's economy be successful without investing in analytics? c. In class we discussed "formalism" as an important characteristic of the new analytics - i.e., basing decisions on data that is managed and analyzed externally (in business data systems, eg) instead of relying on the data we carry around in our brains. What are some of the challenges that a business might face in the adoption of more formal analytic methods? What does the Tversky and Kahneman paper tell us about human decision-making might pose a challenge to the adoption of formal analytics? Using Davenport's DELTA model, discuss ways that a business might overcome some of the challenges to the use of more formal analytics.

Reference: https://hbr.org/2006/01/competing-on-analytics