As every company strives to become data-driven, Decision Intelligence has emerged as one of the most strategic technology imperatives today. And for good reason. Today there’s more data than ever before, and decision-making is becoming more challenging. Decision Intelligence democratizes AI-enabled analytics and enables anyone within an organization to make better decisions faster and more consistently. In this article, Omri Kohl, co-founder and CEO of Pyramid Analytics, explores the emerging practice of decision intelligence, what’s driving its demand, and what the future holds.
The idea that “data is the new oil” is a mantra that companies have rallied behind for decades, and yet data alone creates little to no value if it’s not analyzed and acted upon. Business intelligence (BI) and analytics tools – many of which were first introduced more than 20 years ago (one is even 30 years old) – promised a future where Business users could easily access and transform huge volumes of enterprise data to make timely and reliable decisions.
But the reality is that these tools remain highly technical. They are often built on older data models/structures and legacy architecture and require data scientists to conceptualize and transform the data into dashboards, reports and usable insight by others.
Ironically, many lack augmented analytics capabilities and AI, which are critical to achieving two critical outcomes: 1. Moving beyond BI dashboards and basic descriptive analytics; and 2. Putting the power of actionable information – which is what decision intelligence provides – into the hands of everyone in an organization who would benefit from data-driven insights. And isn’t that pretty much everyone?
As businesses of all sizes strive to become data-driven, decision intelligence has emerged as one of the most strategic technology imperatives today. Decision intelligence aims to democratize analytics and enable anyone within an organization to make better decisions faster and more consistently.
Let’s explore what we mean by decision intelligence (DI), what’s driving its demand, and what the future holds.
The term “decision intelligence” was co-invented by Mark Zangari, CEO of Quantellia and Lorien Pratt, Ph.D., Chief Scientist at Quantellia and became more popular thanks in part to Dr. Pratt’s 2019 book,How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World. Despite technological advances, organizations have traditionally had difficulty applying data science to solve the most critical problems facing businesses today. Why? Simply put: a gap has existed between data scientists and everyday users — employees, stakeholders, and organizational leaders that get the work done.
The gap is now closing. Thanks to advances in AI, ML, and augmented analytics capabilities, decision intelligence is a new emerging discipline that helps organizations move beyond the limitations of traditional business intelligence.
Gartner defines decision intelligence as “a practical approach to improving organizational decision making,” which “models each decision as a set of processes, using intelligence and analytics to inform, learn from, and refine decisions.” Accordingly, new decision intelligence software platforms are coming to market that help everyday users make, more intelligent decisions, even if they don’t have a technical background in analytics or data science.
Today there is more data than ever before. With an incredible 2.5 quintillion bytes of data being created every day, 90% of the world’s data has been created in the last two years alone.