6 Critical Features of Enterprise Intelligence Solutions

Data is the lifeblood of businesses. But the vast amount of data businesses accumulate makes it difficult to turn that data into actionable insights. 

Enterprise intelligence solutions offer a system for collecting, managing, analyzing, and monitoring your process and business data. A good enterprise intelligence solution empowers organizations to make informed, data-driven decisions, enhance operational efficiency, and maintain a competitive advantage. 

This post will cover six essential components of strong enterprise intelligence systems and how they can help businesses influence future outcomes. 

Organizations generate a lot of data. In theory, this should result in better data-driven decisions. But, too often, data’s walled off in silos. Each department deploys separate systems. Customer service has their own software for ticketing. Sales has their CRM. Back-office departments have project management tools. Beyond this, there’s no guarantee of uniformity within a department. Sometimes, teams use multiple systems performing the same function to supplement features (such as using several ERP systems in manufacturing organizations). These data silos make it hard to unify, manage, and analyze data. 

A data fabric centralizes data across multiple sources within a single, virtualized layer. There’s no migration from old systems or extensive data programming necessary. When you update data, the data fabric synchronizes other software solutions and data repositories. Centralizing this information sets up analysts to make smarter decisions.

Operational efficiency gives organizations an advantage. And enterprise intelligence can help. It starts with a powerful tool called process mining. Process mining uses event logs from software and IT systems—or your data fabric—to create a visual representation of a process or workflow in the real world. Using this information, low-code developers and analysts can discover and eliminate operational bottlenecks or slowdowns across their critical enterprise applications. 

Additionally, when you undertake process improvement projects, process mining tools can measure improvements through before-and-after snapshots. Plus, process mining enables you to monitor workflows in real time, allowing for quick corrections when things go off course.

The best enterprise intelligence tools take process mining a step further by providing dashboards, collaboration tools, and intelligent recommendations for where and how to take action.

Artificial intelligence (AI) is transforming all aspects of business. Enterprise intelligence is no exception. The proliferation of natural language processing (NLP), large language models (LLM), and generative AI models have made it easy to gain deep insights. Employees can ask questions about data, then receive instant, actionable answers without the need for complex queries or deep technical expertise. 

These AI tools have a wide range of potential applications across business scenarios. For example, an insurance team lead could use conversational AI to analyze the performance of their claims processing team. The lead could ask, “Which agents have the highest claims resolution rates this quarter?” and receive instant answers. From this, they can identify top performers and others needing coaching or improvement. They could also ask about historical data patterns to determine whether performance issues are consistent trends or anomalies.

Additionally, organizations can use predictive AI and predictive analytics to anticipate future events and generate optimal outcomes. This type of AI applies to a wide range of use cases such as financial forecasting, demand forecasting for retail and purchases, or analyzing market trends.

Strong visual charts and robust data visualizations are essential for modern enterprise intelligence solutions. A good solution can transform complex datasets and processes into easily digestible visual representations. The right visualizations can give you deep insights across industries, whether analyzing demand for supply chain operations or risk management in financial institutions. 

Effective visualizations must be based on real-time data from a variety of sources. This is where the foundation of data fabric and AI comes into play. First, data fabric ensures you have the right information in a single place for easy review. Second, AI amplifies data visualization. When conversing with AI, you can use the latest data models to generate graphs or visualizations on the fly. This can often allow you to identify patterns, outliers, and correlations missed in traditional reports. For instance, a sales analyst might check a dashboard to review the deals in the pipeline with an estimate on closing dates. But they can use AI to dig deeper by asking questions like, “Show me all of the deals among life sciences companies.” This allows them to get more granular with their reports.

Top solutions scale across the business as the organization grows. As organizations continue generating data, the system must not only scale for performance but also allow for expansions of types of data. The enterprise intelligence solution must accommodate larger datasets, more users, and more complex analytical requirements without compromising performance. For example, an expanding retail organization can use scalable solutions to integrate new stores’ data, analyze customer behaviors across regions, and adjust inventory levels in real time.

As mentioned, your data is your organization’s lifeblood. You need to protect it. That’s why it’s critical to choose enterprise intelligence solutions that have strong security. Before you choose a solution—or a platform that can help you build these solutions—check out their trust center to ensure they follow best practices. 

For example, a good data fabric will include role-based permissions and security. This prevents unauthorized access to data and ensures critical intelligence is kept on a need-to-know basis. This also reduces your attack surface by minimizing the amount of information an individual employee has access to. This offers added protection against widespread leaks in the unlikely event of a breach. 

Lastly, check compliance certifications. Even if your industry isn’t heavily regulated, an organization that has passed stringent compliance requirements takes security seriously. While security and compliance aren’t the same thing, they’re good proxies. In other words, while security and compliance aren’t twins, they are siblings.