February 5, 2016
PETER Sondergaard, Senior Vice President at Gartner, said, “Information is the oil of the 21st century, and analytics is the combustion engine.” In today’s severely competitive global environment, organizations need to rapidly turn terabytes of raw data into insights about their customers and their industry to make sound marketing and investment strategies. Few organizations are able to make the most of data and drive business decisions. The current analytics field has enormous potential to tap into and explore possible opportunities to boost business. According to a study by Forbes Insights and E&Y conducted in November 2015, 54% percent of executives heading large organizations report that analytics is key to their overall business strategy.
Here are three key points about data analytics:
Analytics involves deep diving into the data to find hidden trends and discover hidden customer patterns that could serve in strategic planning. This includes the use of statistics, computer coding and analytical skills. The insights from data can be visualized and communicated to support managerial decisions. Organizations need to get the most out of data by mining it. This will produce bits of information which when collated can turn into a full-fledged model to drive business decisions.
This deep diving can help organizations gain early trends and insights, work on focusing on new customers, increase efficiency in organizational processes and drive improvements. More importantly, organizations need to use analytics to gain competitive advantage and stay ahead in the market by understanding customers and trends. According to an article by Networkworld, UPS used predictive modeling for their package delivery and reduced 85 million miles driven a year, which means 8.5 million gallons of fuel.
Organizations can collate disparate data sources to focus and improve on their growth. Saving on operational costs and increasing revenue are two key benefits of using analytics-driven decision making. Bill Palace at UCLA writes, for example, “One Midwest grocery chain used data analytics to get an insight into local buying patterns. By analyzing the data, they understood that when men bought diapers on Thursdays and Saturdays, they were inclined to buy beer. Diving deep showed that these customers typically did their weekly grocery shopping on Saturdays. The retailer concluded that they purchased beer to stock up for the weekend. Grocery stores can make use of this data analytics information, and they can place beer and diapers side by side to increase sales.”
Organizations need to get deeply involved in data analytics and have internal strategic conversations to come up with the best ways they can leverage analytics to drive their strategy. This is the time for organizations that have not explored data analytics to dive in. If data analytics remains low on their priority lists, it will likely come to haunt them with lost market share and revenue.