Analytics

Decoding decision intelligence: What it means for businesses today

By Brynne Henn - June 30, 2021

With more data available to organizations than ever before, the question many organizations struggle with is how to more efficiently and effectively use that data to drive decisions for the business. This challenge is precisely the problem that decision intelligence is solving.

To better understand the rise of decision intelligence and the implication this new framework and technology can have on businesses, Eric Topham of The BI Report recently hosted a conversation between experts in decision intelligence. This panel featured Peter Bailis, CEO and Founder of Sisu, Bipin Chadha, VP of Data Science at CSAA Insurance Group, and Pragyan Nayak, Chief Data Scientist at Hitachi Vantara Federal.

Take a look at a few of their insights on decision intelligence and how to apply decision intelligence in the excerpts below. Or, if you prefer, watch the entire conversation on-demand.

What is decision intelligence?

Setting the stage for the conversation, Eric asked the experts to clarify what decisions are for a business and, with that in mind, what decision intelligence is. The panel agreed, decisions are what modern knowledge work is all about. Whether someone is in marketing, sales, business, operations, product development, engineering, or another team, every part of a company is making critical choices on performing their job and, by extension, impacting the business.

However, Peter Bailis, CEO of Sisu, explained we’re seeing a shift in how we monitor and measure these decisions, saying,

“Increasingly, the output of our job is measured according to KPIs and metrics that are informed by analytics. In an organization of hundreds of thousands or tens of thousands of people, each making five to 15 consequential decisions per day, these decisions add up to that final metric. It used to be that businesses only focused on larger metrics like profit and loss, but today we see businesses focusing on more and more fine-grained metrics.”

Decision intelligence addresses these fine-grain metrics and stands in contrast to the approaches of legacy business intelligence tools. Peter clarified, “No one would say business intelligence is a bad idea; in fact, it’s forced all of us to aspire to make more data-driven decisions.”

Instead, the problem with business intelligence tools is that they’re not designed to keep up with the changing pace of data. With more data available to businesses than ever and every part of the businesses keeping a close eye on their metrics, data analytics teams and BI cannot scale with the number of questions being asked by the business. Because of this, there’s a new wave of technology classified as decision intelligence, which Peter defined as:

“Decision intelligence focuses on enabling everyday decision-makers to inform their actions with data. Decision intelligence is not full-blown AI because we still need the context and expertise for decision-making that only humans can do. Rather it augments people’s ability to use their data to effectively make decisions based on the metrics they already track.”

Pragyan Nayak, Chief Data Scientist at Hitachi Vantara Federal, expanded on this definition, adding, “As someone who started as a C++ developer, I think the simplest definition of decision intelligence is BI ++. It’s about how an organization brings in automation to decisions that make it more stable and more resilient to changes.”

Why is decision intelligence on the rise now?

Peter kicked it off, explaining that while decision-making isn’t new, the way data is stored and accessed has changed. There is now a massive amount of data collection and consolidation happening, especially when we compare it to 10-15 years ago when data was still in on-premises data silos. Today, most businesses consolidate their data in a single cloud warehouse where the cost of ownership is cheap, and storage is seemingly infinite.

As Peter said, “This consolidation means there’s more and more data available to really anyone in the company. You no longer have to worry about query interference or query performance. Instead, the problem has actually shifted to what query do we want to run?”

Consolidation of data shifts the bottleneck in analytics, from the tools used to store data to the sheer amount of questions any data team could answer. And yet, despite more data available, most businesses aren’t actually answering more questions. Peter gave an example, sharing,

“I know general financial institutions that have 100,000 BI licenses and 80,000 employees. They have more than one of each tool, but they’re stuck realizing they’re not using all that data they’ve collected. They finally have the data consolidated, but the question now is how do we go and operationalize that. It’s a huge problem you can’t solve by just throwing people at the problem.”

Decision intelligence is on the rise because it aims to solve this exact problem. Peter drove this need home, saying, “Analytics teams need to learn to do more with what they’ve got, and the business has to learn how to do more with the data they have access to.”

Bipin Chadha, VP of Data Science at CSAA Insurance Group, added to this explanation by pointing out,

“The fundamental assumption used to be that if only you could give me all the data I wanted, I could make a decision. With this, analysts spend a lot of time and effort putting together dashboards and reports to take to senior leaders. Leaders are initially impressed by the fancy-looking reports and dashboards, but they ask for a new one only two months later because it’s not helping. What decision-makers really mean to ask is, ‘Tell me something actionable.’ That’s the biggest disconnect between what we have with BI and what we need in the future. We’re moving from simply reporting to empowering people to make a decision in a more prescriptive manner.”

What is a decision intelligence framework, and how should it be applied?

Finally, the participants got a little more practical and shared their tips for leveraging decision intelligence in an organization.

According to the panelists, intelligence frameworks are critical for responding to and dealing with uncertainty. While it’s helpful to know and analyze historical data to understand multiple scenarios and what’s come before, you don’t have a way of knowing what’s coming. Decision intelligence is that forward-looking framework that helps stakeholders make informed decisions.

“Where the decision intelligence framework today can actually make an impact is in reducing uncertainty, and you reduce uncertainty by presenting the right data to the right people at the right times to inform the decisions and lower those error bars. You can think of decision intelligence as almost nudging the decision in one way or the other, and sometimes challenging people’s assumptions of what’s really going on in the data,” Peter stated.

Want to hear more? Listen to the webinar to learn more about the rise of decision intelligence and how to leverage it in your business.


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