Decision Intelligence

What is decision intelligence?

Decision intelligence (DI) is the human, organizational, or technological capabilities used to enable timely and effective decision-making. Broad organizational access to technologies used for DI leads to faster, more effective decision-making at scale.

DI gives nontechnical businesspeople easier access to data-driven insights. Access to those insights helps all professionals in business and technical roles improve their decision-making. This contrasts with common business analytics approaches, which rely on technical experts and often leave data-driven insights out of reach for the business.

Augmented analytics differentiates DI from traditional business analytics. Specifically, DI provides users with self-service capabilities to help them find the most relevant data and optimize their decision-making with augmented capabilities based on their unique preferences and goals. In this way, business professionals of all kinds can leverage the power of business analytics without data experts as intermediaries.

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

Decision intelligence represents the next evolutionary stage of business intelligence (BI), the traditional process of turning data into insights to help organizations make better business decisions. Traditional BI relies on data experts to curate these insights through their analytics processes. In contrast, decision intelligence makes analytics processes available to virtually anyone in an organization—even those without data expertise. In this way, DI “democratizes” data access.

What is a decision intelligence platform?

A decision intelligence platform empowers people with augmented, automated, and collaborative insights that simplify and guide the use of data in decision-making.

DI platforms are purpose-built for organizations with significant data infrastructure investments that require broad capabilities for any number of roles within a modern enterprise. DI platforms are built for scale and can reduce the manual efforts required to configure data and analytics environments and workflows that are often heavily manual-based with BI tools and technologies. Specifically, DI platforms automate traditionally labor-intensive configuration tasks, freeing up human resources and expanding possibilities regarding who can achieve meaningful data access.

DI platforms often have more powerful analytics capabilities than traditional BI tools. Where traditional BI focuses on descriptive analytics, DI platforms use automation, augmentation, machine learning (ML), and artificial intelligence (AI) to help people explore and analyze data for more advanced functions and decision-making.

DI platforms also streamline data governance, which can be difficult at scale with traditional BI tools. Data leaders can provide anyone with direct access to critical data without getting involved in individual requests for data analysis. This makes it easier to provide for any analytics use case, now and in the future.

This “platform approach” to decision intelligence collectively supports DI at scale. Further, it eliminates the need to use different analytics tools, in other departments, with varying capabilities in terms of sophistication and access.

How does it work?

In principle, decision intelligence can unlock the strategic value of enterprise data for everyone in our modern workforce. Decision intelligence processes align insights from data 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 (i.e., predictive analytics), recommend specific actions (i.e., prescriptive analytics), and proactively collaborate and share their insights within a single intelligence environment.

DI platforms deliver these outcomes 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: DI platforms automatically prepare and cleanse different types of enterprise data by identifying potential sources, parsing unstructured data into structured formats, and performing other tasks that otherwise require extensive manual effort from technical users.
• Self-service interfaces: DI platforms provide powerful, user-friendly data visualization and analytics tools that anyone in an organization can use to explore and analyze data. These tools promote interactivity and can include dashboards, visual decision trees that help people without technical expertise navigate data for insights, and predictive analytics capabilities that provide decision-makers with forecasts, among other useful functions.
• Machine learning algorithms: DI platforms provide powerful, user-friendly data visualization and analytics tools that anyone in an organization can use to explore and analyze data. These tools promote interactivity and can include dashboards, visual decision trees that help people without technical expertise navigate data for insights, and predictive analytics capabilities that provide decision-makers with forecasts, among other useful functions.
• AI-driven capabilities: In addition to machine learning algorithms, DI platforms leverage artificial intelligence technologies, such as natural language processing (NLP) and text analytics, to help anyone more easily explore and interact with their data. NLP uses AI, allowing people with little or no technical experience to ask simple questions and have the platform display the data and results in a more consumable format. With AI capabilities, business people can publish informative reports and visualizations to corroborate any decisions they make.
• Collaboration tools: DI platforms may include collaborative tools that enable decision-makers to share their insights with colleagues and decision-making partners. These tools can consist of decision-support dashboards, decision communities, and other innovations that help decision-makers uncover valuable insights and take action faster.

What are the benefits?

With decision intelligence, organizations can become more agile, collaborative, and data-driven because they can eliminate common pain points within traditional BI processes, such as data bottlenecks, data silos, and ill-informed decision-making. Here is a closer look at the organizational benefits DI can provide:

• Support faster and better decision-making at scale. DI can help decision-makers access, analyze, and derive insights from data more quickly and efficiently than traditional BI tools. As a result, it enables decision-makers to make data-driven decisions in real-time and improve decision quality.
• Improve team collaboration around data. Team members can access data from a centralized location, share insights more easily across teams and departments, and use advanced analytics capabilities that traditional BI often does not support.
• Reduce backlogs and ensure consistent reporting. With the support of a DI platform, decision intelligence can automate data preparation tasks, allowing businesspeople to access and analyze data without waiting on IT teams or other data experts. Importantly, this helps decision-makers get the data they need, when they need it, to make more informed decisions.
• Simplify the configuration of analytics environments for future roles and use cases. DI platforms use automation and augmentation to reduce the time, cost, and labor involved when configuring traditional BI technologies. This makes decision intelligence more scalable than conventional BI, enabling decision-makers to add new people or use cases without spending time and money manually configuring their analytics environments.
• Provide for virtually all of an organization’s analytics needs. In principle, decision intelligence is a process that provides universal decision support. DI platforms are continually expanding the scope and sophistication of their capabilities, making decision intelligence a viable tool for users in organizations of all sizes and any industry. Leading DI platforms can be implemented in various environments, including on-premises, in the cloud, or in hybrid environments.

How can Pyramid Analytics help?

Pyramid Analytics provides organizations with the world’s leading decision intelligence platform, empowering users to optimize decision-making and derive critical insights from their data. Pyramid Analytics makes the democratization of data access more accessible, safer, and more practical, with powerful self-service features, collaboration tools, and data governance capabilities that maximize the value of organizations’ data assets.

Contact us today to learn more about how we can help your business with decision intelligence.