The core focus of analytics has been to enable data-informed decisions, but siloed data and analytics without an enterprise-wide view can limit effectiveness. Modern decision intelligence is all about driving better decisions, faster and at scale with the help of AI.
Time is an important factor because some decisions happen in real time or near real time, and the right data needs to be accessible at all times. This is why decision intelligence platforms are becoming increasingly autonomous.
Automation also helps organizations deal with the tremendous amount of data from internal systems and the outside world they're trying to process, said Stephen DeAngelis, chairman, founder, CEO and president of AI and data science company Enterra Solutions.
"A lot of Fortune 100 companies are making certain parts of the value chain autonomous -- from consumer insights on the front end to revenue growth applications, how to price and promote and [display] your product on a shelf," he said. "[They're] using it to shape demand and manage supply chain complexity during times of uncertainty."
Enterra Solutions created a category called autonomous decision science to enable autonomous decision-making. That's not to say that every decision should be automatic; it means decisions that should be automated are and humans make the decisions that require human knowledge.
Prior to major world events such as COVID-19, supply chain disruptions and the war in Ukraine, businesses used decision intelligence to become more competitive. While that goal still stands, the heightened level of uncertainty has necessitated an extreme form of agility and faster decision making.
While at Carnegie Mellon University, DeAngelis built a methodology called enterprise resilience management. DeAngelis and his team began by building resilience into government systems that made critical applications and infrastructure resilient to cyber attacks and natural disasters.
"You need to analyze data and then make a decision within a decision cycle so you can take an action when it matters," DeAngelis said. "Often times, having humans do this is too late. By the time humans analyze the data [and] decide to take an action executed within a system, the opportunity to mitigate that risk or exploit that opportunity [has passed]."
Decision intelligence is changing operations for organizations across many different industries. Retailers have been trying to optimize pricing and promotion for years. These efforts have had to adapt to the increasingly unstable global economic environment.
Retailers plan their promotions for an entire year, but shifting geo-economic and geopolitical unrest, a lingering pandemic and changing customer expectations require them to adapt and respond to change much faster.
For example, one company used an Enterra Solutions system to automate trade promotion and pricing processes in year one. In year two, the company delegated decision rights to the platform so it could create a base promotional campaign.
This approach has evolved into "business war gaming," a strategy that enables users to understand how to use a game theoretic framework to understand competition in the marketplace. The strategy also makes decisions so users can beat their competitors and makes the organization resilient to changes they're facing in the marketplace. In 2023, organizations are bracing to deal with a possible recession.
"The only way to minimize risks and exploit opportunities at scale is to have a system that has decision-making built into the technological platform," DeAngelis said.
Healthcare uses decision intelligence to address new markets
Healthcare providers are trying to uncover the right opportunities by understanding which physicians they should contact, the addressable market size and how the market dynamics are changing around them.
For example, there's a shift to ambulatory and outpatient care, so providers must understand how to measure and observe that in their own market. They need to discover which facilities care is shifting to, identify how that should be monitored over time, how to develop their territories, how to do patient journey mapping and understand referral networks.
"The shift to ambulatory care is making things more complex, especially as we get more complex types of procedures, more complex types of care [and] telehealth enters the mix," said Amanda Robison, vice president of provider growth strategy at decision intelligence software firm Definitive Healthcare. "You want to have the intelligence and insight to understand where those different types of care are happening and how you fit into that ecosystem."
Trucking is becoming more efficient
Trucking company and decision intelligence solution provider Aifleet has been using decision intelligence to reduce the number of trucks it uses to haul freight. Software and smart algorithms making repeatable, traceable and measurable decisions govern its entire order-to-cash pipeline. The goal is better asset utilization and performance.
For example, the average trucking company has an asset utilization of 50%, which means the truck and driver are only used 50% of the time. Aifleet has a 70% utilization rate, according to company representatives, which reduces the number of trucks needed to haul the same amount of freight. This also results in an average of 30% higher revenue per truck.
Mark FarkasCTO, Aifleet
"We use decision intelligence to select the orders that fit our fleet the best at the right price," said Mark Farkas, CTO of Aifleet. "We also use historical data and intelligent algorithms to come up with predictions that help our tactical and operational decision-making in all aspects of our operations from maintenance to refueling."
Decision intelligence software lets organizations make more precise decisions at an enterprise level to enable faster and more informed decision-making. Achieving this broader view takes time because organizations must first prioritize use cases and ensure they have the data needed.
"DI [Decision intelligence] transforms human knowledge into corporate knowledge, which allows organizations to detach their scaling from the ability to attract, motivate and integrate a large pool of experts," Farkas said. "DI, and software in general, will completely transform how we humans work and deliver value in organizations."