Data-driven decision making is defined as the practice of making decisions based on the analysis of data rather than on intuition. Decision-making has remained a focal point in the rising growth of Big Data over the past few years. It comes as no surprise that data-driven decision making is one of the most budding applications in the rising discipline of data science. Several businesses to date struggle with the ability to successfully incorporate analytics and data to drive decision-making. Even though, our modern era has introduced intuitive analytic software that aid businesses, there remains considerate challenges regarding the use of analytics and data to make productive decision-making.
If used properly, analytics can provide fruitful insights into past performance of a product or service. It can help determine risk, quantify costs and weigh outcomes thereby, allowing businesses to make lucrative decisions in the long run. Determining whether your analytic efforts are being targeted to places where they'll do the best can be a daunting task and requires a professional analytic technician. For companies that have just embarked on the analytical journey might face problems with finding a good target size. As you progress through this journey, your analytical experience grows and target size becomes wider and more strategic to optimise key business goals. You should focus your analytic investments towards distinctive capabilities in order to drive business success.
Data and analytics are two different things and it is important to establish a sound difference between both before using them to drive decision-making. Data focuses more upon statistics and probability whereas analytics display meaningful patterns in the data. Both data and analytics work hand-in-hand to generate effective decisions because put simply, without a firm analytics foundation, data is useless. In order to draw behavioural patterns, it is important that businesses gather data, which will provide helpful information, clear conclusions and support decisions. There is an abundance of data over the internet and everywhere else, but to extract useful data upon which analytics can be performed can be quite a challenge. That's why businesses are turning their attention towards specialists who can extract this useful data and assist them in making fruitful decisions.
The internet and the business press is splashed with case studies and anecdotes that highlight the value of being data-driven however what these case studies and anecdotes fail to do is address the issue of businesses performing well due to the use of data and analytics. According to a survey conducted by Harvard Business Review, businesses across a broad spectrum have mixed attitudes towards this phenomenon. But one factor was observed throughout this broad spectrum that businesses performed financially and operationally better when they performed data-driven decision making. Although businesses have become technologically empowered through analytics and data when it comes to decision-making however, they shouldn't discount the importance of human insight and vision which still remains a vital component of decision-making.