Data analytics is a method used by organizations to gain competitive advantage over other companies in their specific market. It is a scientific process of mining and analyzing the database gathered by organizations about their customers and their products in order to generate more profit or to build the marketing strategy of the company (Loveman, 2003). For example, a travel agency may be able to use the information they gather about customer characteristics and correlate it with their traveling destinations and be able to use that information to market new packages or destinations.
Data analytics is a combination of programming, statistics and intuition, although majority of it is based on actual data or evidence and gut feeling is only used to point to the right direction of analysis and utilization. Data analytics is more than just having a large database of customer characteristics and behaviors but it also takes a skilled statistician with an eye for marketing and consumer psychology to be able to make use of relevant information.
For example, an organization may have access to the electric consumption of individual households but it cannot be useful if it does not affect the consumer behavior the company is targeting. In order to compete on analytics, an organization must have a rich source of data about their customers and their market. This would give the company a huge breadth of data that would paint an accurate picture of the kind of customers and market the company has as well as forecast its standing in the business. Data analytics is data mining and analysis and before this could be carried out, the organization has to have access to these data.
Next, the organization must have a trained employee to manage and mine the database as this kind of job requires a highly specialized and trained individual who has a very good concept of statistics and analytics. Some organizations have set up a special team or even a whole unit or department that is in charge of data management and mining while key individuals in each aspect of the business could ask the said team to work on different ideas and angles to test whether their ideas are feasible or not.
In this way, the organization need not spend its finances and workforce in something that is not profitable. Third, the organization must have the right equipment for job, a super computer to manage the database, software or programs that would dissect the database and to come up with more creative and innovative ways of using the said information. Lastly, there should be a team who will have the responsibility to put into good use what has been found and to monitor whether it has met its objectives or not (Davenport, 2006).
Aside from those mentioned, the most important thing to be able to compete with analytics is to have the desire to know and learn more about the customers and how that knowledge can be used to develop new strategies which does not only work but will help place the company on top.
Davenport, T. (2006). Competing on analytics. Harvard Business Review, 84, 98-107 Loveman, G. (2003). Diamonds in the data mine. Harvard Business Review, vol. 81; 5, 109-113.