Systems of Intelligence

What are Systems of Intelligence? 

Systems of intelligence help organizations extract value from their tech stack by creating a highly accessible single source of data-driven insights from their systems of record to support strategic decision-making. The data can be analyzed or modeled to provide insights that reflect what has happened, what is happening, and what could happen. 

They comprise many different business applications, including data warehouses, systems of record, machine learning, data science, artificial intelligence (AI), ERPs, internet of things (IoT), and more. Systems of intelligence incorporate all the data and information available to them to help organizations make decisions.  

Systems of Intelligence Components  

Systems of intelligence are comprised of multiple elements all working together to deliver intelligence. Although there is no required number of components for systems of intelligence, they operate best when they include a variety of components. The better the quality and features of the components, the better the system of intelligence. 

 Components include:  

• Databases, data centers, data warehouses, and third-party applications 
• Data prep, reporting, analytics, and advanced analytics  
• Predictive and prescriptive analytics; machine learning, data science, and AI 
• Natural language processing (NLP) and computer vision 
• Data mining, statistical modeling, sentiment analysis 
• Visualizations, interactive dashboards, and reporting 
• Decision intelligence and decision automation 

Most systems of intelligence are hybrid systems, with a mix of cloud, on-prem, and SaaS solutions. What’s important is that they contain a range of abilities to extract insight from the available data. Systems of intelligence that contain all these components will be able to provide organizations with better, faster insights that translate into business value.  

The Business Value of Systems of Intelligence  

Systems of intelligence enable organizations to respond quickly to market changes, identify opportunities, and mitigate risks. A few examples of the business value they provide include the following. 

• Data and Analytics Democratization: Systems of intelligence naturally allow for the centralization of all data assets and create a single source of truth for an organization.  
• Streamlined Processes: Automating repetitive tasks and data processing frees up valuable time and resources for employees, allowing them to explore more options and focus on making the best decision.  
• Improved Decision-Making: Real-time insights and recommendations enable organizations to ensure they look at all possible decisions and select the choices with the highest probability of success. This decision-making process includes augmented decision-making and automated decision-making.  
• Increased Revenue and Cost Savings: Systems of intelligence use machine learning and AI to uncover trends and patterns, plus identify growth opportunities, helping organizations optimize operations, reduce costs, and drive revenue growth.   
• Improved Customer Experience: Systems of Intelligence can help businesses analyze customer data, identify patterns, and anticipate customer needs, resulting in tailored products, services, and marketing efforts that boost satisfaction and loyalty.  
• Competitive Advantages: Faster decision-making, better decisions, improved processes, and better customer experiences all lead to innovation and capitalizing on market trends—which leads to your organization having the upper hand over your competition. 

The Difference Between a System of Record and Systems of Intelligence

Although a system of record can be included in systems of intelligence, they are not the same thing. A system of record is used to store and manage an organization’s data. This storage system usually includes cloud and on-prem data warehouses, data lakes, local files, and more.  

System of Record Examples

• Customer relationship management (CRM) systems 
• Enterprise resource planning (ERP) systems 
• Human resource information systems (HRIS) 
• Enterprise systems 
• Enterprise applications 

A system of record provides financial data, inventory records, patient records, and more to systems of intelligence for data analysis. Insights and assets created from a system of intelligence may then be exported back into a system of record.  

The Difference Between a System of Engagement and Systems of Intelligence

A system of engagement and a system of intelligence are similar in that both facilitate interaction. The difference is that systems of engagement facilitate interaction between customers and an organization, whereas systems of intelligence facilitate interaction between data sources and data analysis. 

Components of a System of Engagement

• Email 
• Chatbots 
• Social media 
• Mobile apps 
• Customer portals 

 Although data and analytics can be used as part of a system of engagement (for example, patients accessing financial services that project potential earnings), their primary purpose is to provide a platform for people to interact with an organization. Systems of intelligence leverage systems of engagement to capture data and feed it into the business processes that drive decision-making. 

Systems of Intelligence Use Case Examples

Systems of intelligence can tackle any analytical business initiatives you throw at them. Here are a few use cases displaying their benefits.  

• Sales and Operations Increases: Applying AI to sales and operations reports helps organizations see whether KPIs increased or decreased and, more importantly, what drove those increases or decreases.  
• Fraud Detection: Machine learning algorithms analyze historical and real-time transaction data to identify patterns and anomalies that signal potentially fraudulent activity, such as unusual spending behaviors and purchases made in multiple locations.  
• Customer Experience Enhancement: Systems of intelligence grab customer data, such as spending habits, locations visited, canceled purchases, and saved items, and feed it to machine learning to identify customer preferences. These insights are used to provide personalized recommendations and offer promotions.  
• Supply Chain Optimization: Systems of intelligence examine inventory levels, shipping and transportation routes, and transaction data to identify inefficiencies. Machine learning algorithms help optimize routes and processes while reducing costs.  
• Healthcare Outcome Improvement: Healthcare providers use patient data to predict risks and outcomes. The insights gained from this analysis lead to personalized treatment plans that improve patient outcomes. They can also reduce costs for the provider and the customer. 

Conclusion

Systems of intelligence serve as powerful tools for organizations. By centralizing data and insights from all sources, systems of intelligence can leverage data science, machine learning, and AI to explore and understand data at deeper levels. This deeper level of understanding enables organizations to make better, faster decisions. Not only that, but they provide a competitive advantage that can help organizations create defensible moats.