“Big Data, you say?”

As the internet continues to grow from strength to strength, the data available online is becoming too large and complex for traditional methods of analysing. Consequently, Big Data is the term for this phenomenon and is measured in varying ways, one of which being analytics.  An example of how analytics can help a organization is to better understand the business and social environment and improve real time decision making which is a crucial element of an organizations orientation. With increased awareness of big data and knowledge of how to measure and manipulate this for a greater benefit, could this previously named ‘phenomenon’ prove to be a necessary element for managers and ultimately revolutionse management? McAfee, A., & Brynjolfsson, E. (2012) certainly seem to think so! The article read detailed how big data has the potential to revolutionise management and can prove to be a helpful and useful tool.

McAfee, A., & Brynjolfsson, E. (2012) detail how with the additional element of managers being able to measure data allows them to know a radical amount more about a business and translate this into improved decision making and performance. An example of this is the ability of online book retailers such as Amazon to have algorithms that can predict which book consumers could potentially want based on prior purchases and how other consumers who had similar buying behaviour purchased thereafter. Also, the article mentions how location data allowed inferring of how many people were on their phone outside Macy’s around the christmas period. This provided data of how many potential consumers were out and prepared for christmas shopping which was helpful, relevant data for Wall Street Analysts. This is just an example of how much data there is to be explored and manipulated and also an example of how we are all walking data generators without even realising our contributions!

A further detailed case study is mentioned within the article in regards to airlines. Airlines following other previous methods, now use RightETA which calculates times by combining publicly available data about weather, flight schedule and other factors with propreitary data the company collected with information from stations to gather data about every plane in the local sky. Every single 4.6 seconds, RightETA collects relevant information that proves handy for the management of delays and informing consumers about this if necessary. Research undertaken throughout the article depicts how if businesses were to adapt a more data-driven style of management that they would gain a competitive edge against competitors and perhaps perform better if given access to unlocking their knowledge management. A predominant amount of the article is focused around knowledge management. This is associated with capturing, sharing, developing and efficiently utilising organisational knowledge. Contrary to this, big data usage does not remove the value of human insight and relevant leadership skills necessary to specifically outline company objectives and goals – this must not be overlooked and managers should not become idle.

In conclusion, I have gained a lot of information from the article. It was highly descriptive and I have displayed varying reasons why I believe that big data is highly useful for an organization and could potentially revolutionize management. This is ideal in terms of marketing as it can heighten customer engagement as access to the right type of data can allow insight into who the consumers are, what they want and what is the best median for consumers to be reached out to from (for example, the case study of Amazon and their online algorithims). Also big data can help us realise what influences customer loyalty and help us to keep maintaining this. Finally, the recurrent theme throughout this blog post, the best decisions can be made for the organization optimizing the marketing performance as a whole.

Until next time.


McAfee, A., & Brynjolfsson, E. (2012). Big data: the management revolution. Harvard business review, 90 (10), 60-66




Skip to toolbar