How AI Can Assist Data-Driven Organizations to Drive Efficiency?

AI

AI

Redefining decision-making in data-powered businesses using AI.

Artificial intelligence is revolutionizing businesses at a blistering pace. As almost every organization today strives to become data-driven, AI assists leaders to make informed and effective decisions based on the information they have to create a lasting impact. The right data flow to every member of a company and to information supply chains can fuel R&D, as well as improve the skills base of the current and future workforce, and enable new services. While AI guides decisions on everything, it works best as a collaborative function across organizations, using reliable data and processes to complement a business strategy that aligns with organizational culture and values.

 

The Data-Driven Organization

Becoming data-driven is all about making data and analytics part of the business strategy, systems, processes and culture within a company. A data-driven organization fosters and creates a mindset to use data and business intelligence to make all decisions. Such organizations are committed to gleaning data concerning all aspects of the business. They intend to reach a stage where they can make each decision through germane data. Data-driven organizations must make the usage of data a more natural part of the workflow of all the employees and departments.

The data businesses collect can power conclusive decision-making and becomes part of the companies’ competitive advantage by enabling employees at every level to use the right data at the right time. Moreover, a data-driven culture within an organization improves situational awareness and drives performance at individual, team, and department level. According to McKinsey & Company, data-driven organizations are 23 times more likely to acquire new customers, six times more likely to retain them, and 19 times more likely to be highly profitable.

 

Unlocking the Value of Data

Undoubtedly, data is oil to improve business productivity. As the affordability of technology continues to rise, both individuals and companies will have more opportunities to access and process data, and use and monetize that data to gain a competitive edge. As noted by Capgemini, most organizations still rely on making decisions based on information that is at best dated, and at worst is unreliable or inconsistent. This rear-view mirror approach to analysis and decision making will never let an organization to stimulate with confidence or create the value data promises. Thus, to drive effective analytics and derive accurate insights, enterprises must start making operational improvements to how data is ingested, cataloged, governed, and shared.

Since companies collect data from various sources, shifting to a data-driven culture is an incessant endeavor that allows organizations to bring the customer at the center stage, drive for operational excellence, and find new routes.

The rate at which data is being generated and collected is incredible. Artificial Intelligence techniques that automatically scan and index data assets can be used to catalog all disparate data. They can also be utilized to improve data management in areas such as data ingestion and query performance, enabling data professionals to speed up data management and analytics projects and database administrators to focus on higher-impact tasks. One of the significant advances of AI is it can bridge the previously vast gap between the data and insights with those who need to understand it.