Five worthy reads is a regular column on five noteworthy items we have discovered while researching trending and timeless topics. This week, we explore decision intelligence.
Illustration: Dorathe Victor
AI and analytics are playing critical roles in driving innovation among many businesses riding the digital transformation wave during this pandemic. Many business leaders realize that people are not wired to think exponentially, but incrementally in a linear world, unable to see the ripple effects of their actions. The pandemic has highlighted the enormous impact this has on the quality of decisions made, especially in the context of business.
Organizations across the globe are modernizing the way they think about making decisions, looking for automation wherever possible. While AI models help with creating predictions and labels, they still leave behind questions like “So what?” and “What should I do about it?” Here’s where decision intelligence (DI) comes into play.
DI is an emerging discipline of creating strong decision models in a wide range of processes, helping users map actions to outcomes. It provides a framework to help data and analytics leaders design, model, align, execute, monitor, and tune decision models and processes in the context of business outcomes and behavior.
DI models are capable of producing faster and more accurate decisions that provide better outcomes. DI models bring the skills from applied data science, social science, and managerial science together, thereby bringing human elements into the modeling and decision-making processes. This way, it’s possible to leverage the benefits of human intuition while eliminating errors like biases when making a decision.
Gartner indicates that we will have 800 percent more data by the end of 2020, and 80 percent of this is unstructured data that consists of images, emails, voice records, and more. Since the human workforce won’t be able to process all this data manually, organizations can use decision intelligence combined with improved machine learning algorithms to handle this increase.
Now that we know what decision intelligence means and does, here are five interesting reads that further discuss decision intelligence.
1. Decision intelligence vs. business intelligence: what is your company running on?
Businesses are looking for next-generation business intelligence tools and platforms that are faster and more modern to solve problems based around a specific domain. Decision intelligence could be the solution to making better decisions for better outcomes.
2. Improved decisions through decision intelligence
Decision intelligence focuses on business decisions and corresponding outcomes rather than machine learning algorithms. It places focus on involving humans in the decision-making process along with data and algorithms, thereby improving the quality of decisions.
3. The missing link in many data science projects: Decision intelligence
Decision intelligence is the application of data science within the context of a business problem. It augments data science with social science and managerial science. Only by combining the principles and skills from these disciplines can business decisions be unlocked.
4. Decision intelligence vs business intelligence
Decision intelligence uses a modern data architecture and massively parallel processing to take all of a company’s data into account. It provides deeper insights compared to legacy business intelligence applications that are built around older data structures, featuring static dashboards.
5. When artificial intelligence isn’t enough: the new discipline of decision intelligence
The basics of decision intelligence can be understood in three steps: understanding what a decision is, understanding how to map actions leading to outcomes, and learning how to brainstorm outcomes and actions. Following these steps will help any practitioner get started.
The predictive power of AI backed by data science is playing a prominent role in leading organizations towards the new normal. Gartner says by 2023, more than 33 percent of large organizations will have analysts practicing decision intelligence, including decision modeling. It is predicted that in future, AI agents can make decisions on their own, with the attributes and capabilities of a person running a department.
