The Evolution of Decision Making: Embracing 2.0 with Generative AI

In today’s evolving technological advancements, companies need tools that give them the ability to rapidly analyze the nearly endless streams of data produced across their business divisions. Finding ways to instantly harness this information for a comprehensive analysis and a quick understanding of relationships among metrics has long been solved through the use of data dashboards.

These valuable tools have been the method of choice for democratizing data, providing an at-a-glance snapshot of company functions. For more than a decade, dashboards have empowered individuals at all company levels to quickly grasp the overall business environment, enabling them to make intelligent data-backed decisions that drive growth, innovation and profit.

Today though, companies are finding dashboards alone are not enough to stay ahead of the competition. It’s here that Generative Artificial Intelligence has been making a difference, transforming how companies see data and its myriad relationships, leading to what has been dubbed Decision Making 2.0.

To make it all come together with real impact though, companies need to find the right partner with extensive experience to guide them skillfully through the challenges of this new technology transition.

Improved Data Dynamics With AI: Without constant improvements and updates, existing technology can only be so effective. This is particularly true in today's dynamic business environment, where data and related processes are constantly evolving. This has led to a tenuous situation where businesses are discovering their analytics dashboards no longer function as effectively as they did even in the recent past, resulting in costly wasted efforts. The highly fraught and time-consuming process of adjusting business metrics while racing to try to stay ahead of data quality and integration means the true effectiveness of most current dashboards lags severely behind.

Consequently, data specialists frequently find themselves requiring tedious processes such as filtering, downloading data and conducting in-depth analyses on a manual basis. They often do this offline from the dashboards and data product, uncovering valuable insights only after a lengthy, time-consuming search.

Without the ability to adapt quickly, analysts are overwhelmed by the streams of data fed through dashboards today, resulting in a sheer inability to provide rapid answers to critical questions. In some cases, an individual company will use more than 100 dashboards, tailored for individual business divisions, making it nearly impossible to coordinate analysis and find immediate insights staff can utilize for important data reports. What’s more, costs skyrocket as systems proliferate to accommodate technology gaps and time lags.

That’s where the transformative union of Generative AI and machine learning capabilities marks a strategic revolution for analytics dashboards. They are no longer the static at-a-glance snapshots of data they once were, going beyond the merely pure Predictive. Instead, through the power of AI, they have developed into intelligent platforms imbued with cognitive prescriptive capabilities.

The Three Component Process: How does it all work so harmoniously? There are three main features to using AI to transform the data dashboard process, giving companies the ability to find answers they need at breathtaking speed.

·       Smart Insights: This agile feature leverages several machine learning techniques as the underlying model to parse out trends, find unusual patterns and discover unique insights within the streams of data, those dazzling golden nuggets data analysts strive for. These insights are then processed by LLM (Large Language Model) to devise an end-user narrative accompanied by compellingly produced adaptive visuals. This saves time and effort as insights that usually take a dedicated human effort to detect quickly glitter through the data. Smart Insights is the versatile tool that every organization can integrate into their dashboards to enhance overall intelligence.

·       Predefined Questions: By focusing on a targeted set of 5 to 12 prompts, the Predefined Questions tool generates instant insight and easy-to-understand data visuals. Just a few swift key taps will allow users to access updated views and Smart Insights, allowing for rapid data-driven decision-making. The limited array of questions allows for a quicker, more efficient intelligent response versus longer, open-ended questions.

·       Copilot Prompts: This complex feature allows users to interact with data through suggested questions and prompts. The process generates detailed text, visuals and insights based on the dataset. Extensive prompt engineering design combined with data mapped into sophisticated semantic layers ensure accurate and meaningful responses robustly tailored to an organization’s needs.

Companies have found that by elevating and refining their insights, AI reduces both the number of dashboards needed and their related maintenance, overhead and labor costs. The process frees data analysts from the tedious time-consuming aspects of their jobs, letting them focus on valuable business information waiting to be gleaned and interpreted from the data streams.

Streamlining the Dashboard Experience: In addition to elevating insights and promoting a more proactive data analysis approach, the Generative AI powered Decision Making 2.0 platform provides significant advantages when integrated into intelligent dashboards for your daily business operations. By incorporating these AI capabilities and related functionality, the need to overwhelm dashboards with information is significantly reduced, allowing for exceedingly accurate data analysis.

Discover more about NEORIS and how we can assist you in leveraging Generative Artificial Intelligence to optimize your company’s data dashboards and enhance your Decision Making 2.0 framework.

Visit the link to explore instances where we've empowered companies to analyze their data with AI in cost-effective, streamlined approaches.