Utilizing Cognitive Analytics for Optimized Business Results
In today's data-driven world, cognitive analytics is emerging as a game-changer for organisations seeking a competitive edge. Early adopters find cognitive technology essential for their strategic success, with 65% of them considering it crucial for sustainable growth.
Cognitive analytics is a sophisticated form of data analysis that combines technologies like Semantics, artificial intelligence, machine learning, deep learning, and natural language processing. Unlike traditional AI, which primarily automates processes, cognitive analytics enhances human capabilities by imitating human brains to draw inferences and insights from data patterns, helping businesses make critical decisions.
Businesses are increasingly turning to cognitive analytics to tap unstructured data sources such as images, emails, text documents, and social posts, enabling them to find real-time answers. Examples of cognitive analytics in use today include Microsoft's Cortana, Apple's Siri, and IBM's Watson.
The global cognitive computing market, valued at $8.87 billion in 2018, is projected to reach $87.39 billion by 2026, growing at a CAGR of 31.6% from 2019 to 2026. This growth can be attributed to the broader trends in AI, digitization, and advanced computing technologies.
The approach of data analytics has evolved over the years from Descriptive to Diagnostic to Predictive to Prescriptive analytics, and is now shifting towards cognitive analytics. As a result, businesses are improving their business outcomes by providing accurate data analysis, leaner and more efficient business processes, and improved customer service and interaction.
Industries most likely to benefit from cognitive computing include healthcare, finance, and education. In the healthcare industry, cognitive computing can manage unstructured data from various sources to make recommendations to medical practitioners, helping doctors in making better treatment decisions and providing better patient care. In finance, it can improve risk management and predictive analytics, offering better decision-making tools. In education, cognitive computing can personalize learning experiences through adaptive learning systems.
In the retail sector, cognitive analytics can provide personalized suggestions based on the consumer's information and product preferences, gathered from various sources like social media, past purchases, and customer reviews. In the finance sector, cognitive analytics can help banks analyse customers' questions, sentiments, etc. to create a database for loan management, suggesting the category and type of loan based on their financial transactions, needs, and queries.
Moreover, cognitive analytics can enhance customer service by automating routine customer care operations and improving operational efficiency. For instance, USAA financial services company has been an early adopter of cognitive analytics, checking policy applications for approvals and disapprovals. The Lark app leverages AI and health IoT devices to cognitively gather data and provides personalized health advice for treatments and fitness.
Cognitive analytics can also help businesses improve customer acquisition by refining product pricing based on purchase records and market trends. Additionally, it can help financial services industries mitigate risk while adding value, better customer experience, and improved security and compliance.
Furthermore, cognitive computing can empower patients by enhancing their health in the form of devices that will capture information and provide recommendations from customized exercises to diet plans. For example, researchers at the University of California, Los Angeles were able to identify people with diabetes changes by mining patient records.
In conclusion, while specific data on the cognitive computing market is lacking, related markets and technologies suggest that cognitive computing could benefit from the broader trends in AI, digitization, and advanced computing technologies. As businesses continue to embrace cognitive analytics, we can expect to see a transformation in various industries, leading to improved efficiency, personalized experiences, and better decision-making capabilities.
- The finance industry can utilize cognitive analytics to improve risk management and predictive analytics, offering better decision-making tools.
- In the retail sector, cognitive analytics can provide personalized suggestions based on consumer information and product preferences.
- In the finance sector, cognitive analytics can help banks analyze customers' data to create a database for loan management, suggesting the category and type of loan based on their financial transactions, needs, and queries.
- Cognitive analytics can also enhance customer service by automating routine operations and improving efficiency.
- Cognitive computing can empower patients by enhancing their health through devices that capture information and provide recommendations, such as customized exercise plans and diet plans.
