Part 1: What is Decision Intelligence and why does it matter?
Part 2: Three keys to applying Decision Intelligence in your organization.
A decision is a choice that you make about something after thinking about several possibilities.
– Cambridge Dictionary
Understanding Decision Making
Each of us make decisions every day. This is done instantly in some cases or can be a more considered exercise involving making a choice based on a range of options. Making the right choice or the best decision is important to a good life and a strong business. This is particularly true when the decision involves critical strategic or even tactical choices with a measurable impact on growth or even business survival.
There are many factors that go into making the right choice. Key among them, is analyzing and leveraging the increasing volume of business and customer data that drive a modern organization. The good news is that the advent of new technologies allows us to analyze these decision components more rapidly and more clearly define options. For example, the integration of AI and machine learning and advanced analytic techniques help to unearth key insights, model best approaches, and create transparent roadmaps more rapidly.
What is Decision Intelligence?
There are disciplined processes for most business managerial functions like sales forecasting, lead optimization, acquisition targeting, etc. But making decisions based on a holistic view of an enterprise, requires a structured approach to understanding how various actions lead to specific outcomes.
Enter Decision Intelligence. With origins going back a decade, Decision Intelligence is an idea that has become both a new technology and a scientific discipline. It is the answer to a simple question first asked by Dr. Lorien Pratt, who, along with Mark Zangari, who are recognized as the founders of the field:
“If technology should do one thing that it is not doing today, what would that be?”
Gartner includes Decision Intelligence in its Top Strategic Technology Trends for 2022 and defines it as:
…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.
Advantages of Decision Intelligence
The hallmark of decision intelligence is that it allows you to understand how a decision flows across each area of the organization. It should not be thought of as another tool or even an alternative to current processes. Rather, it is a single point of truth that brings together business intelligence, analytics, machine learning, and AI into a framework where the decision is the primary driver.
Much has been written about the benefits of decision intelligence with the core benefits being:
- Ability to make data-driven decisions. Most organizations believe data-driven decision making is the key to growth. But most admit they are not there yet. Data must be correctly analyzed, models produced, and the best option chosen. AI can take a better look at the data and find invisible patterns and possible anomalies that can significantly influence the outcome.
- Make faster decisions. Few organizations are happy with their decision-making speed. Decision making is cumbersome in most cases and much time is spent without much assurance that the decision is the correct one. AI decision-making systems speed up the process since they can process huge amounts of data almost instantly.
- Leverage multiple problem-solving options. AI-powered decision-making algorithms often prove very flexible, yielding several outcomes for a particular decision as parameters are changed. This helps organizations make the best choice from a multitude of options, that are in alignment with business goals and objectives.
- Eliminate mistakes and biases. Decision intelligence helps avoid key biases that influence outcomes as algorithms take objective looks at available data.
Decision intelligence is the discipline of turning information into better actions at any scale.
Cassie Kozyrkov, Chief Decision Scientist, Google
Decision Intelligence in Action
Some of the most visible examples of Decision Intelligence in action are recommendation engines, which use analytics to predict which products consumers would find most appropriate, or which movies they should watch next. Tools such as these provide context and pertinent options to help people make better decisions.
Here are a few industry use cases:
- Financial Services: Decision Intelligence is being used by financial services organizations to assess credit applications for mortgages, car loans, etc. Powered by AI that can assess credit scores, income or other customer data, financial organizations can rapidly confirm eligibility and recommend products and options.
- Retail: Business owners leverage Decision Intelligence applications to anticipate ideal pricing for merchandise based on external data, such as customer demand, trends, and even emotions.
- Environment: One advantage of Decision Intelligence is its ability to identify potential environmental hazards based on past and current data and offer reaction, mitigation and risk management solutions using AI.
Part 2: Three keys to applying Decision Intelligence in your organization.
For more on how Decision Intelligence helps accelerate data-driven decision making, check out this article.
