How to derive value from your AI investments with Decision Intelligence
Ultimately, a company’s value is measured by the sum of its decisions. In order to succeed, the organization must make and execute decisions—across all levels of the business—better and faster than its competitors. This sounds so simple, and yet it’s the single most elusive challenge that operational decision makers face every day.
And, it’s why so many companies have been successfully built to help solve this very challenge. Think back to the early days of Business Intelligence giving way to Advanced and Predictive Analytics then to Big Data and now to Artificial Intelligence solutions.
There’s no disputing that analytical advances have augmented our ability to understand data and predict outcomes. However, innovation has simultaneously left operational decision makers asking even more questions from more data and constantly demanding more from their AI investments.
Today, operational decisions sit on a spectrum of risk and complexity, and depending where on the spectrum they’re found, AI can help improve them through depth of insight or augmentation. However, AI is not designed to engage with decision makers or actually decide and act on anything. This has become a bottleneck and places even more pressure on operational leaders to derive insight from more data, faster and act.
Enter Decision Intelligence. Decision Intelligence is the engine that transforms AI outcomes into quantifiable business decision opportunities.
To put this in context, here are several examples of the types of operational decisions companies are facing.
First, there are the types of singular decisions need to be made instantly and repeatedly, such as high-speed sorting and online-shopping product recommendations in retail or loan approvals in banking. The stakes are low, speed is the priority, and the decision situation is generally well-understood. None of these decisions carries much value on its own, but cumulatively, they can mean the difference between success and failure. These fixed repeated questions are great candidates for AI models and optimizations. However, when it comes time to decide and act, narrow AI solutions need support.
Second, there are high-level, strategic decisions that are characterized by a high level of uncertainty. They include corporate acquisitions, large capital investments, or major product launches. These decisions heavily influence the growth and development of a business and carry a much higher degree of risk, and are generally made by humans, whose holistic thinking, intuition ability to reason have not yet been matched by machines. We’re unlikely to apply Decision Intelligence anytime soon; what we need is decision augmentation.
Finally, the place where most business decisions fall, there are many semi-structured situations where decisions can’t be fully automated, but may also get bogged down by the limits of human cognition. Where these decisions are made is an important part of a business’s structure; delegating more decisions to various operational levels speeds up decisions and contributes to agility, but the trade-off is reduced control and possible misalignment with the company’s overall goals. Another challenge of many-layered decisions is their complexity. Some decisions, such as hiring, mainly affect a single division of a company. Others, such as pricing or product decisions, tend to involve complex trade-offs, and need to be considered from both an internal and external perspective.
Decision Intelligence combines human and AI-driven decision-making capabilities and works with decision makers to apply context to the infinite raw materials that are a product of AI investments and makes rapid decisions a reality. The result is optimized AI investments that deliver quantifiable value to the business.
This is where diwo, the AI-powered Intelligent Advisor really makes a difference. Operational leaders can make the best decisions, faster with diwo’s AI-powered Intelligent Advisor. diwo is a Decision Intelligence application that allows users to rapidly explore, iterate, decide and act on opportunities for growth. Unlike AI, ML and BI-based reporting applications, diwo focuses on solving operational problems, not simply diagnosing them. diwo identifies trends, provides real-time recommendations and automates the decision-making process.
The potential of AI is tremendous if it’s being used to drive valuable business outcomes. Decision Intelligence leverages AI to create more opportunities to make better operational decisions, faster.
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