POV on Augmented Analytics: From Decision Support To Intelligent Decision-Making
Panoramic VP of Product Max Cobert discusses his take on Ilya Gandzeichuk’s recent article on the value of Augmented Analytics. Read more on Forbes.
As companies develop the infrastructure to get the right data in the hands of decision makers, they must also take steps to ensure that data is fresh, accurate, and easy to understand. A great data analytics team with the right tools can assemble this ‘single source of truth’, but it requires more than just AI for insights and recommendations. A superior data team must be able to capture the context – what was the business team trying to accomplish, what problems are they facing, and what decisions are they making to address them. Only when this context is added to the system can a company really create reliable, trustworthy AI systems to improve data-driven decision making.
- Companies can now absorb data from a multitude of different business systems, and these systems are getting faster and more robust about providing data. If companies aren’t taking advantage of all of this data to improve their decision making systems, they won’t be able to live up to consumer expectations.
- AI/ML usage is expanding through organizations from front-office features to back-office features. Teams that are spending a lot of time on repetitive tasks, like fetching and cleaning data, can now be augmented by analytic solutions that can do these tasks faster and more reliably.
- The need to make data more transparent across an organization will continue to grow. Storing all of this value within a single analytics team is no longer enough. It needs to be exposed to all teams so the entire organization can benefit.