Decision intelligence is a relatively new discipline that’s gaining more industry attention lately, particularly as the COVID-19 pandemic and digital disruption continue to magnify the complexity of both business problems and decision-making processes.
With the rapidly increasing urgency to digitize and gain competitive value from new technologies like artificial intelligence (AI) and machine learning (ML), decision intelligence is emerging as a solution that can connect decision support, decision management, and complicated systems applications.
Organizations are trying to stay afloat in a sea of data, and decision intelligence acts as the missing link between data and improved decision making. Fields like financial services, healthcare, and supply chain are in acute need of reliable decision-making today, and decision intelligence can enable them to make the most of their data and optimize the potential of AI.
What is Decision Intelligence?
Gartner forecasts that more than 33 percent of large organizations are going to have analysts who will practice decision intelligence by 2023. This discipline offers a framework to assist data and analytics practitioners develop, model, align, implement, track, and modify decision models and processes related to business results and performance.
Decision intelligence applies data science within the frame of business problems, and is attained by taking stakeholder behaviors into account to affect adoption and decision making. Frequently, it’s a fusion of business intelligence, data science, management, and decision modeling.
Some other definitive characteristics of decision intelligence include:
- The core pillar is that decisions hinge on our notion of how actions lead to outcomes
- Incorporates different decision-making methods like rules-based approaches to ML and AI
- It can be used as a solution for business problems across numerous diverse industries
- Helps reduce the time and effort associated with creating, developing, and deploying complex business logic
- Aids in resolving discrepancies between decision-making practices and the complicated nature of the circumstances in which those decisions occur
Why Decision Intelligence is Having a Moment Now
One of the top priorities for today’s organizations is to become an analytics and AI-driven company to meet changing customer demands, succeed amidst new digital competitors, and become more resilient and responsive to change.
Emerging technologies can empower an organization’s ability to make data-driven decisions in real-time, a critical capability in numerous scenarios and resource-intensive industries. But achieving operational AI success is no easy feat. Decision intelligence helps address the business need instead of the ML algorithms, which helps to accelerate AI or ML operationalization to support quality, trusted decision making.
Current decision models are often unpredictable because of the inability to identify potential vulnerabilities associated with model behaviors in a business environment. Decision models can be strengthened by connecting decision-making and processes with ML algorithms.
Companies using AI to augment their day-to-day operational decision-making need to be able to trust in AI outcomes, and decision intelligence can also eliminate bias while still accommodating the value of human intuition, knowledge, and judgment.
Applications & Use Cases
Though adoption is still in the early stages, decision intelligence platforms are being used by organizations to help automate and accelerate decision-making in a variety of industries and use cases.
- Financial services: Processing credit, mortgage, and car loan credit applications based on the client’s income, credit score, and other data.
- Retail: Inventory and fulfillment optimization and warehouse management according to demand forecast.
- Logistics: Real-time truck and freight optimization to reduce superfluous transportation and costs.
Some experts believe that decision intelligence is the next phase in AI’s evolution. Moving into the future, organizations may be impacted by decision intelligence in a couple of ways. More robust computational power means that AI systems can provide the most lucrative options to enable business leaders to make quick, accurate, and dependable decisions. Also, AI agents can autonomously make decisions utilizing the capabilities and characteristics of a department manager.
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Decision intelligence is key to helping business accomplish more with less, and data scientists can help ensure that organizations achieve this goal by maximizing data and analytics and new technologies for better decision making.
Data scientists need every tool available in their arsenal in order to help them ask the right questions about their data. Decision intelligence can assist practitioners in establishing meaningful, actionable business insights and recommendations.
For more information about this growing new discipline, and other data science, analytics, and AI resources, check out Simplilearn.