“A practical domain framing a wide range of decision-making techniques bringing multiple traditional and advanced disciplines together to design, model, align, execute, monitor and tune decision models and processes. Those disciplines include decision management (including advanced nondeterministic techniques such as agent-based systems) and decision support as well as techniques such as descriptive, diagnostics, and predictive analytics.”
While the Gartner definition is quite exhaustive, it essentially boils down to using data science and analytics to make better decisions. Decision Intelligence software solutions are now a critical part of the modern business cycle.
For us at Lumin, Decision intelligence empowers business users to make better and faster decisions every day by allowing business users to quickly ask and get insights that not only explain the “What” but also the “Why,” “What will be,” and “What-if.”
At its core, DI uses a set of advanced capabilities such as Machine Learning (ML) and Artificial Intelligence (AI) to transform the organization's data into intelligent insights. When it comes to applications for business users, Decision Intelligence software solutions systems allow these leaders to get insights as quickly as asking their favorite search engine for recommendations for their evening dinner plans.
Of course, one of the key questions that IT and analytics teams are grappling with is what is the difference between Business Intelligence and Decision Intelligence?
The difference between Decision Intelligence and Business Intelligence
Let's take a step back and think about BI in our organizations. Most organizations that have BI teams are still struggling to keep up with the constant need for business leaders and decision-makers to understand “why has this happened?” While BI regularly makes business users aware of their KPIs, every time there is a need to understand the “Why,” the business needs to go back to the BI and Decision Support teams. This cycle can be cumbersome and makes decision-making challenging because business intelligence users cannot extract insights quickly and across different datasets.
Another major challenge with BI is that the core users for BI tends to be analysts or IT teams comfortable working with products that require a basic understanding of data and data structures. In contrast, DI is meant for consumers and analysts and generally has a very intuitive question-and-answer capability that enables business users to ask plain-language questions and get insights.
Regardless of their pitfall, it is crucial to have business intelligence and Decision Intelligence tools working together holistically. The combination gives you a better understanding of the history and current state of your business, allows you to dig into interesting trends and anomalies, and explore future scenarios easily.
