Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In this edition, we’ll learn what decision intelligence is, how it could help businesses, and much more.
Illustrated by Derrick Roy
We covered the basics of decision intelligence (DI) in an earlier Five worthy reads blog. In this blog, we’ll take a look at how it is going to help businesses flourish in 2022.
Living in an era where the technology landscape keeps changing at breakneck speed, it is especially challenging for businesses to keep up. Be it a billion-dollar company or a small-scale operation, any organization is required to make snap decisions to ensure it stays competitive in the market.
With the rate at which data stores are growing, it is almost impossible for humans to make a quick decision considering all the information that is available. Here comes DI to help businesses with what they’ve been struggling with in regards to decision-making. While this approach has been making the rounds for more than a couple of years now, many organizations are yet to step into the world of DI completely.
Business decisions carry significant weight, and decision fatigue is rampant in organizations; both make corporate decision-making a daunting task. It is high time for businesses to evolve their decision-making process given that the onus is to make decisions swiftly, precisely, and taking into consideration the huge amount of data involved. Now, before we jump into the depths of DI, let’s quickly recap what it is in simple terms.
DI is a realistic approach to improving corporate decision-making by using several techniques to make more precise decisions. Each decision is modeled as a series of processes, and the organization then uses artificial intelligence and analytics to refine the decision and learn from past ones.
Technologies such as analytics, machine learning, natural language queries, and AI can quickly uncover correlations and patterns in large amounts of data. DI can take such data and apply it to more intangible human characteristics like intuition, creativity, feeling, and the ability to handle complexities successfully.
Here are a few quick reads to help you understand everything about DI.
1. Decision Intelligence: The Trending Tool in the Data Scientist’s Kit Â
 “Make more out of less”—this might be the goal of many companies, and DI provides a platform for it by combining data and analytics with emerging technologies for better decision-making. It bridges the gap between data and effective decision-making for organizations seeking to stay anchored in a sea of data. DI, according to some researchers, might be the next step in the progression of AI.
2. 10 tips for getting started with decision intelligence
With an idea of what DI is and how it benefits organizations, let’s jump into how to get started with it. DI gives organizations the ability to mix large quantities of data with emerging technologies to transform data analytics dashboards into decision support platforms. This involves tweaking algorithms, using tabletop exercises to simulate several outcomes, and more.
3. Decision Intelligence in 2022: In-Depth guide for businesses
DI driven by AI can help in determining eligibility for certain financial services by using a user’s CIBIL score, salary details, and other such information. Similarly, DI can aid various other businesses in making more rapid and accurate decisions by eliminating biases and accommodating intuition.
4. How Decision Intelligence Will Finally Change Decision-Making From Mystical To Mundane
While digitization has been changing each area of a business, like finance, marketing, and sales, managerial decision-making is one area that has been left untraversed. There is no system set up for executives to check their past decisions and the associated outcomes, such as how a decision impacted business unit performance. DI could turn this situation around, helping leaders make effective decisions.
5. Why decision intelligence is the future of underwriting
Due to the various issues in traditional underwriting, it is time that insurers started evaluating if they are set up for intelligent underwriting to avoid preset data models. With the holistic view DI provides by using network graph analytics and predictive modeling, automated decision accuracy is enhanced and operational efficiency is increased.
With digital disruption and the complexity of globally connected businesses, an element of uncertainty has been added to straightforward decisions. The amount of data is growing exponentially across all industries, and it’s about time the world came together to utilize the data available through AI-driven DI to meet market demands.
