What is Operational Analytics?

Operational analytics is the use of data, analytics, and visualization techniques to support and improve the day-to-day operations of a business. This typically involves the collection and analysis of real-time or near real-time data from operational systems, such as transactional systems, manufacturing systems, or supply chain systems, in order to identify trends, patterns, and opportunities for improvement.

Operational analytics can help businesses to make more informed and timely decisions, by providing insights and recommendations that are derived from data and analysis, rather than relying on intuition or past experience. This can help to improve efficiency, reduce costs, and increase the agility and responsiveness of the business.

Examples of applications of operational analytics include:

• Monitoring and analyzing real-time data from manufacturing systems to identify bottlenecks or inefficiencies in the production process, and to optimize the use of resources.
• Analyzing customer behavior data from transactional systems to identify trends and patterns, and to make recommendations for targeted marketing or personalized offers.
• Monitoring and analyzing data from supply chain systems to identify potential disruptions or delays, and to take proactive measures to mitigate the impact on the business.

Overall, operational analytics is a powerful tool for businesses that want to make better use of their data to drive improved performance and competitive advantage.