The pandemic has completely transformed the way we live life and do business. Over the last two years, we have learned how important it is to be flexible and agile in our decision-making. According to a recent survey by Gartner, “65% of respondents said the decisions they make are more complex than just two years ago, and 53% said they face more pressure to explain or justify their decisions.” Workplaces have become more agile, and if the previous two years have taught us anything, it’s that business leaders, stakeholders, and associates must use data systems to advise their decisions.
Nearly three billion business decisions are made annually, and research by Bain shows “a 95% correlation between decision effectiveness and financial performance.” This new method, fortified by recent technological advances, has led to a new class of Decision Intelligence products designed to augment and amplify business users’ decision-making capabilities.
These automated decision intelligence tools and technologies transform how decisions are made in a business and are quickly becoming accepted. By 2023, Gartner projects that “more than one-third of large organizations will have analysts practicing Decision Intelligence, including decision modeling.”
What is Decision Intelligence?
According to Gartner, Decision Intelligence is:
“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.
Can Decision Intelligence help if you already have DSML and AI Tools?
Another question that organizations are also grappling with is with managing their Directory Services Markup Language (DSML) tools. Business leaders often ask, “We also have DSML and AI products. They were brought in to help us make better decisions, so do we need decision intelligence technology?
The simple answer is yes.
Directory Services Markup Language (DSML) and AI tools are standard in stakeholder decision-making. However, many businesses wonder if they need Decision Intelligence tools if they already have these other technologies in place. While DSML and AI tools focus on taking data and getting insights, they do so in a raw format. Similar to BI tools, data scientists are necessary to get the most out of these tools. DI tools, however, are much more user-friendly.
Overall, Decision Intelligence tools focus on C-suite-friendly technology to give you the most intuitive tools imaginable. DI tools enable you to be more productive without needing the technical skills of ML or AI engineers. Even still, the truth is that all of these technologies have a place in the whole decision-making ecosystem. An appropriate decision intelligence platform bring some unique benefits to the table when it comes to helping businesses use data to make better decisions.