What is decision intelligence?

What is decision intelligence?

Decision intelligence (DI) refers to the human, organizational, or technological capabilities that enable timely and effective decision-making. When organizations provide broad access to DI technologies, decision-making becomes faster and more effective at scale.

DI allows nontechnical businesspeople to access data-driven insights more easily. This access helps both business and technical professionals improve their decision-making. Unlike traditional business analytics, which often relies on technical experts and limits access to insights, DI democratizes data access.

Augmented analytics is a key differentiator between DI and traditional business analytics. DI offers self-service capabilities, enabling users to find relevant data and optimize decisions based on their unique preferences and goals. This empowers business professionals to leverage analytics without needing data experts as intermediaries.

How does decision intelligence relate to business intelligence (BI)?

Decision intelligence is the next evolutionary stage of business intelligence (BI), which traditionally turns data into insights to support better business decisions. While BI relies on data experts to curate insights, DI makes analytics processes accessible to virtually anyone in an organization, regardless of data expertise. This democratizes data access across the organization.

What is a decision intelligence platform?

A decision intelligence platform empowers users with augmented, automated, and collaborative insights, simplifying and guiding data use in decision-making.

DI platforms are designed for organizations with significant data infrastructure investments and broad capability needs. They are built for scale and automate many manual configuration tasks required by traditional BI tools, freeing up human resources and expanding access to meaningful data.

Compared to traditional BI, DI platforms offer more powerful analytics, including automation, augmentation, machine learning (ML), and artificial intelligence (AI) for advanced data exploration and decision-making.

DI platforms also streamline data governance, making it easier for data leaders to provide direct access to critical data without handling individual requests. This supports any analytics use case and eliminates the need for multiple analytics tools across departments.

How does it work?

Decision intelligence unlocks the strategic value of enterprise data for everyone in the workforce. DI processes align data insights with human decision-making in streamlined, practical, and flexible ways, redefining the purpose of business data.

In practice, DI platforms help businesspeople make more accurate predictions (predictive analytics), recommend specific actions (prescriptive analytics), and collaborate and share insights within a single environment.

DI platforms achieve this by integrating data preparation, data analytics, and data science into a single environment and automating many of these processes.

Critical features of DI platforms

• ​Automated data preparation: Automatically prepares and cleanses various types of enterprise data, identifying sources, parsing unstructured data, and performing tasks that would otherwise require extensive manual effort.
• ​Self-service interfaces: Provides user-friendly data visualization and analytics tools for anyone in the organization. These tools promote interactivity and may include dashboards, visual decision trees, and predictive analytics capabilities.
• ​Machine learning algorithms: Offers advanced analytics through machine learning, enabling users to explore and analyze data interactively and gain predictive insights.
• ​AI-driven capabilities: Utilizes artificial intelligence technologies such as natural language processing (NLP) and text analytics, allowing users to interact with data using simple questions and receive results in an accessible format. AI capabilities also support publishing informative reports and visualizations.
• ​Collaboration tools: Includes features that enable decision-makers to share insights with colleagues, such as decision-support dashboards and decision communities, facilitating faster and more informed actions.

What are the benefits?

Decision intelligence helps organizations become more agile, collaborative, and data-driven by eliminating common pain points in traditional BI, such as data bottlenecks, silos, and ill-informed decisions. Key benefits include:

• ​Faster and better decision-making at scale: Enables quick access to and analysis of data, supporting real-time, high-quality decisions.
• ​Improved team collaboration around data: Centralizes data access, making it easier to share insights across teams and departments, and supports advanced analytics capabilities.
• ​Reduced backlogs and consistent reporting: Automates data preparation, allowing business users to access and analyze data without waiting for IT or data experts.
• ​Simplified configuration for future roles and use cases: Uses automation and augmentation to reduce the time, cost, and labor of configuring analytics environments, making DI more scalable than traditional BI.
• ​Comprehensive analytics support: DI platforms continually expand their capabilities, making them suitable for organizations of all sizes and industries, and can be implemented on-premises, in the cloud, or in hybrid environments.

How can Pyramid Analytics help?

Pyramid Analytics offers a leading decision intelligence platform that empowers users to optimize decision-making and derive critical insights from their data. The platform supports democratized data access, self-service features, collaboration tools, and data governance capabilities to maximize the value of organizational data assets.