Analytics as Decision Science

We acknowledged in our previous post that just like in Accounting, Analytics projects, having data science professionals working with data and human ingenuity, need checks and balances through an independent validation of those projects, aka an Analytics Audit!

We consider Analytics as Data Driven Decision (D3) making in the business world, which is the empirical application of Decision Theory. The science in Decision Sciences comes from the “body of knowledge and related analytical techniques of different degrees of formality designed to help a decision maker choose among a set of alternatives in light of their possible consequences.

As per INSEAD, “the area of Decision Sciences includes risk management, decision making under uncertainty, statistics and forecasting, operations research, negotiation and auction analysis, and behavioural decision theory.” Interestingly, even at my own Alma Mater, Indian Institute of Management Bangalore (IIMB), my area of Quantitative Methods and Information Systems (QMIS) in which I did my Fellowship, has been renamed as Decision Sciences and Information Systems (DSIS)! By the way, my first Analytics job was in the Decision Sciences group in a corporate setting!

The Decision Sciences Journal is in publication since 1970, well before anyone would have heard or used the term ‘Analytics’. This Journalseeks research papers which address contemporary business problems primarily focused on operations, supply chain and information systems and simultaneously provide novel managerial and/or theoretical insights.

The research papers in academic journals are always double-blind peer-reviewed, before they are accepted for publications, even when they are written by established and renowned researchers and scientists. Then, why do we not follow similar practice in a scientific realm of Analytics! Should not we have an independent review of Analytics projects, aka an Analytics Audit?

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