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Freakonomics, Big Data and Thinking Beyond Assumptions

Published On: February 19, 2013

Most of us who work in a data-related field are familiar with the universal themes and controversy surrounding Freakonomics.

Freakonomics, the brainchild of two economists who use economic principles to explain and explore just about every aspect of society, was introduced to us in the mid-2000s as a book, and then made into a documentary.  It has now evolved into a blog and discussion platform for all things relating to numbers, statistics and what we can deduce from data, using data sets to debunk, disprove and uncover startling reasons for why things may be they are.

To this day, Freakonomics is one of the finest examples in using data to make people sit up and pay attention. One of the best examples of this in the documentary was the explanation of an equation that was applied to uncover corruption in Sumo Wrestling. This two-minute video sums it up – The Numbers in Sumo Cheating.

Through a series of calculations, based on the data of match results, a simple equation was able to reinforce something that many people suspected, but could not necessarily prove: widespread corruption in a sport.

Freakonomics also deals with a range of controversial data-driven analysis of cause and effect, along with debunked assumptions based on data interpretation – each discovered in its own special way.

What Freakonomics does prove is that in many cases, when people often stumble across ‘freak findings’ of data, it’s by accident. What I mean ‘by accident’ is that in the pursuit of a single finding, many other findings are often uncovered in the process. Therefore, it’s only through carrying out the process of analysing data that true intelligence can be gleaned from it over an ongoing basis.

The same thing can be said about ERP and BI. While ERP and BI tools give more and more people access to powerful information about a business, it’s still almost always open to the interpretation of the decision maker to make use of it and constantly assess which elements should require attention.

The intelligence gained through data, can change behaviour and provide better visibility of how the business is tracking. With the rise of ‘big data’ and greater access to volumes of information,  being able to make sense of data and uncovering causes for why things occur will certainly have a positive impact on the bottomline. While instinct alone may get you a long way in business, maximising success relies on making informed and timely decisions backed by the right data.

But in order to deliver immediate insight into business performance for end users, some technical aspects need to be considered. Systems that come with the ERP data dictionary fully mapped for BI usage, out-of-the-box, is advantageous both from time and cost perspectives. This means that you can start building your reports, dashboards and analytics instantly without having to understand the ERP database structure. The ongoing cost of interfacing two systems with different upgrade cycles is also avoided.

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