Insights - Big Data, Analytics, Actionable Business Intelligence.

Big Data, Analytics, Actionable Business Intelligence.

by Dr. Thomas Papanikolaou on July 19, 2013

In the search for evidence to enable informed business decisions Big Data, Analytics and Actionable Business Intelligence are frequently used terms. In this article we look behind the terminology and what it actually means for your business.

According to Wikipedia, the term Big Data refers to a collection of data sets so large and complex that it requires specialised tools in order to capture, curate, store, search, share, transfer, analyze, and visualize. We prefer this definition over the “Volume, Velocity, Variety, Veracity” definition by Gartner and others, as it better describes the operational aspects of Big Data. Diverging from it, we prefer to categorize analysis and visualisation as part of Analytics.

Big Data and Big Data Analytics have become part of the CIO vocabulary and, when the projected financial returns justify it, the CIO agenda. The reasoning is simple: being able to rapidly answer critical questions and / or statistically predict answers to such questions based on analysis of a vast amount business data can create an unfair advantage over competition. Think, for example, the benefits a supermarket could reap by predicting what customers would buy at particular point in time based on analysis of historical purchasing data.

This brings us to the creation of Actionable Business Intelligence which is the main reason for considering the employment of Big Data and Analytics. Actionable Business Intelligence is about deriving insights from the answers delivered by Analytics on Big Data, to enable the creation of executable plans to deliver new or improved business benefits. The key phrases here are “deriving insights”, “executable plans” and “delivering business benefits”. You will note that all these activities encompass organisational work beyond the automatic data processing and analytical number crunching.

Let us dive deeper into two key areas:

  1. Human Intelligence
    Even after Big Data and Analytics have performed the processing, it is absolutely crucial to employ common sense and a critical view on the delivered results. In our supermarket example, even if the Analytics would say that customers would be buying product X, it could very well be that, because of a recent event Y, the preferred product for customers is now Z. With our current technology, it is only humans that can prevent such misleading conclusions and it could be perilous for a business to think otherwise. The very insightful article Being Digital Demands You Be More Human explains why.
  2. Execution Timeliness
    With our lives, businesses, and social fabric being in constant transformation the lifetime and validity of business insights has been dramatically reduced i.e. uncovered insights need to be applied directly if they are to create competitive advantage. This raises the question if today's organisations are able to operate in such a real-time mode. Is the yearly frequency of a strategy development process adequate to ensure agility? Can a sourcing model based on 6-months pre-order cycle capture world-market opportunities? We believe and would advise that introducing Big Data and Analytics capabilities must go hand-in-hand with an organisational review to optimize the company's ability to execute on insights.

Summarising

  1. having a Big Data and Analytics Infrastructure in place is a necessary but not sufficient condition towards acquiring Actionable Business Intelligence. Human Intelligence i.e. common sense and a critical view are still mandatory components.
  2. Big Data and Analytics alone cannot deliver business agility. To secure Timeliness from insights generation to execution, it is advisable to review, determine and implement an appropriate organisational structure.

CREDITS & REFERENCES

  1. Big Data Definitions: Wikipedia, Gartner.
  2. Analytics Definitions: Wikipedia, Gartner.
  3. HBR: Being Digital Demands You Be More Human.

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