What’s in a decision?: Four components needed to operationalize your analytics

Every organization collects data, but collecting it isn’t enough.

For companies that want to make personalized offers, detect fraud and optimize supply chains, decision-making is the ultimate measure of analytics success. But despite massive investments in data infrastructure and AI, many companies still struggle to bridge the gap between insight and action.

That’s where enterprise decisioning solutions, automated, repeatable, rules-based decisions powered by data and analytics, combined with business processes, protocols and policies come into play. Everyone wants to know how to streamline the use of those insights that make sense for the business.

Enter SAS® Viya®, the all-in-one AI platform that helps you build, manage and deploy reliable AI decisions by humans and AI agents. SAS® Intelligent Decisioning, part of the unified stack of applications on SAS Viya, enables customers in retail, financial services, manufacturing and beyond to make trustworthy, agile decisions at scale.

However, one might ask: What goes into a decision? Some might say magic, but it’s the integration of data prep, model management, decision flows/rules and governance into a unified platform.

And while platforms like SAS Viya can help operationalize these processes, the real story is how these building blocks transform analytics into action.

Let’s explore each piece of the decisioning puzzle in more detail.

Puzzle piece #1: Data – the foundation of every decision

At its core, every decision starts with data. But raw data alone isn’t enough – you need clean, governed and accessible data pipelines that fuel your decisioning process.

Without reliable data, models can produce misleading insights, governance can fail to catch issues and business rules may trigger the wrong actions.

Effective data management ensures that the right information is available to the right people at the right time.

Read more about data in this insights article.

Puzzle piece #2: Models – analytics that drive intelligence

Once you have the data, the next step is interpretation. Predictive models and analytics transform raw information into insights you can act on. They help decision makers spot patterns, predict outcomes and simulate alternatives before committing resources.

But models aren’t a magic wand. They need to be monitored, updated and aligned with business goals to ensure they are accurate, fair and effective.

Puzzle piece #3: Governance – the guardrails for responsible AI

Fast decisions are great – as long as they’re right. That’s why governance is essential. Governance ensures that the framework of policies, processes, roles and controls that ensure decisions are transparent, compliant, consistent, auditable and aligned with organizational strategy and risk tolerance.

Good governance ensures that teams can validate, document and monitor decisions throughout their life cycle.

Puzzle piece #4: Business rules – the logic behind the action

Finally, business rules are essential to decisions. Business rules support the processes and protocols that align with specific business contexts, allowing them to function. They can be simple (“approve this transaction”) or complex (“adjust pricing dynamically based on inventory, demand and competitor activity”) and are often part of larger decision flows.

Make decisions you can trust

When data, models, governance and business rules come together in a single environment, decision-making becomes faster, smarter and far more reliable. It’s the difference between insights sitting on a dashboard and insights guiding action.

That’s what SAS Viya and SAS Intelligent Decisioning are designed to deliver. With these, teams can:

• Manage and govern data end-to-end: With SAS Viya, you can manage your data in one system, with end-to-end support for data access, preparation and governance. Everyone from business users to data scientists can contribute to managing data and understanding how it impacts their organization.
• Build, manage and deploy models at scale: SAS Viya can help your team build, manage and deploy models at scale. It tracks models for fairness and performance, ensuring reliable and confident data-driven decisions by humans and AI agents.
• Embed governance and transparency: SAS Viya provides numerous governance capabilities that are reflected in our enterprise decisioning solutions. Teams can collaborate, validate and test their decisions throughout the entire development and deployment process in a low-code, no-code environment.
• Automate and orchestrate business rules: Business rules also follow specific standards. They follow conditional logic, trigger an action or outcome, and can be dynamic (meaning they can adapt as organizations or markets evolve). They can also be part of a larger decision flow (such as those with decision trees or complex rule sets). Business rules are a centerpiece of SAS’ enterprise decisioning capabilities.