What is operational intelligence?
Operational intelligence (OI) is part of the broader family of data analytics focused on making business processes run smoother, faster, and better. Operational intelligence gives you a front-row seat to what’s happening inside your operations. Like an operational watchdog, OI technology is constantly on the prowl, sniffing out what's happening inside critical business processes. However, it doesn’t just collect process data—it lives in, breathes, and analyzes it instantly.
Operational intelligence tools come in various forms, each designed to harness real-time data for enhanced decision-making and operational efficiency. For example, real-time data analytics platforms collect and analyze data from various sources, such as IT infrastructure, IoT devices, and applications, providing instant operational insights and visualizations.
Another type of OI tool is the cloud-native process intelligence platform. These platforms offer scalable and secure real-time analytics, integrating machine learning-based anomaly detection and predictive analytics to anticipate potential issues. By leveraging these leading-edge technologies, digital leaders achieve real-time visibility into their operations to optimize workflows and drive smoother, faster, and more efficient business processes.
[ Looking to improve your processes? Get The Ultimate Guide to Continuous Process Improvement. ]
How operational intelligence works
Operational intelligence systems pull information from IT infrastructure, such as servers, databases, and networks. Data from desktops, mobile devices, IoT devices like sensors and smart meters, security platforms, and applications also feed into OI systems.
All of this data gets scrutinized, analyzed, and turned into actionable insights faster than you can say “efficiency.” This comprehensive approach is often called “operational process intelligence,” emphasizing the focus on understanding and optimizing business processes in real time.
When something’s off, operational intelligence jumps into action, firing off alerts before you even realize there’s a problem. A slowdown on the production line? OI knows it. A glitch in your supply chain? OI’s on it. Moreover, operational intelligence doesn’t just point out problems; it shows how to fix them and optimize mission-critical workflows.
Pairing OI and business intelligence for maximum impact
Business intelligence (BI) refers to the processes, technologies, and tools that transform raw data into meaningful and useful information for business analysis. BI focuses on enabling better business decision-making through data visualization, reporting, and querying. Large organizations often integrate OI and BI tools into unified dashboards to create a seamless operational information flow.
For example, business intelligence applications in manufacturing allow companies to analyze production data from the past year, capturing trends in machine performance, maintenance needs, and production output. Manufacturers use these BI insights to help plan future production schedules and budget for maintenance.
Meanwhile, OI applications excel at monitoring the factory floor, immediately detecting equipment malfunctions or deviations from your production schedule. If a machine starts to underperform, operational intelligence tools alert your maintenance team for immediate intervention to prevent operational downtime. This combination of historical analysis and real-time monitoring ensures that your business runs efficiently and operational issues are addressed promptly.
While OI and BI tools are complementary, it's essential to understand how operational intelligence compares with other process optimization tools. One such tool is process mining, which, like OI, aims to improve efficiency but approaches it from a different angle.
Operational intelligence vs. process mining
Process mining and operational intelligence share the common goal of improving efficiency.
Process mining uses event data from Enterprise Resource Planning (ERP) or Customer Relationship Management (CRM) systems to create a model of your process. AI algorithms then analyze this model, surfacing valuable insights about where and how the process can be improved.
How process mining works:
Operational Intelligence takes this a step further, providing a comprehensive view of how your organization operates. It focuses on real-time business and process data analysis, offering immediate visibility into current operations and enabling quick, informed decision-making. This real-time aspect of OI is also called “operational process intelligence,” highlighting its capability to continuously monitor and optimize processes. By leveraging both tools, you gain holistic visibility into your processes, from historical trends to real-time performance.
This synergistic approach optimizes existing workflows while providing the agility your organization needs to adapt to unforeseen operational challenges as they arise.
Operational intelligence and process mining: A dynamic duo
Operational Intelligence: Offers real-time insights using business and process data to manage and optimize ongoing operations. It helps in maintaining operational efficiency and continuous improvement
Process Mining: Looks at event data to understand and improve process flows. It helps you identify long-term trends and structural inefficiencies.
Combining the capabilities of process mining and operational intelligence gives IT leaders a comprehensive view of process performance. Process mining offers a wide-angle view of process data, identifying trends and inefficiencies. Conversely, operational intelligence combines day-to-day operational data with real-time visibility.
This dynamic duo ensures IT leaders can make informed decisions based on historical insights and current performance data. By leveraging both tools or a platform that combines them, IT leaders can optimize enterprise processes more effectively and respond swiftly to operational challenges. Now, let's explore the 7 essential benefits of operational intelligence.
7 essential benefits of operational intelligence
1. Real-time monitoring and alerts:
Operational intelligence systems continuously monitor data streams from various sources, such as IoT devices, transactional databases, and enterprise applications. They provide instant alerts when anomalies or deviations occur, enabling organizations to address issues promptly before they escalate into significant problems.
2. Improved decision-making:
With real-time data at their fingertips, decision-makers can respond quickly to dynamic conditions. This agility allows for more informed and timely decisions, whether reallocating resources, adjusting production schedules, or addressing customer service issues.
3. Enhanced customer experience:
Operational intelligence tools help organizations monitor and improve customer interactions by providing real-time insights into customer behavior and service performance. Organizations can quickly identify and resolve issues and enhance customer satisfaction and loyalty.
4. Operational efficiency:
Operational intelligence systems analyze real-time data to identify inefficiencies and bottlenecks in processes. This continuous feedback loop allows organizations to streamline operations, reduce waste, and improve overall productivity.
5. Risk management:
OI systems enhance an organization’s ability to manage risks by providing early warnings of potential issues. Whether predicting equipment failure, identifying security threats, or monitoring compliance, OI tools help organizations mitigate risks proactively.
6. Predictive insights:
Leveraging machine learning and advanced analytics, OI systems can predict future trends and behaviors based on current data. This predictive capability allows organizations to anticipate market trends, customer needs, and operational demands, staying ahead of disruption.
7. Resource optimization:
Real-time visibility into operations enables better resource allocation and utilization. Organizations can ensure that their human or material assets are used most effectively, reducing costs and optimizing performance.
Understanding the essential benefits of operational intelligence highlights its impact on business efficiency and decision-making. However, integrating automation and orchestration tools takes OI capabilities to the next level. Let’s delve into how these tools optimize OI for even greater effectiveness.
Optimizing OI with automation and orchestration
Automation Tools
Automation tools are the muscle behind operational intelligence, jumping into action when a problem flares up. Picture this: OI spots a bottleneck or an inefficiency in your back-office operations, and without missing a beat, it fires off an automation script to tackle the issue head-on. Automation tools are proactive like that. They get things done immediately. Integrated into OI systems, automation tools help smooth out workflows before problems hit the proverbial fan.
[ Download the Process Automation Guide and discover how to unlock the full potential of end-to-end process automation.]
Orchestration Tools
Orchestration tools manage and coordinate multiple automated tasks, ensuring they work together seamlessly to achieve operational goals. When an OI system detects a delay in one part of a process, orchestration tools can adjust subsequent tasks to mitigate the impact, maintaining overall process efficiency. Integrating automation and orchestration tools into your operations ensures that your core business processes are monitored, actively managed, and instantly optimized.
Integrating automation and orchestration tools with operational intelligence (OI) drives substantial improvements across operations. However, implementing OI systems is not without its challenges. It’s hard to fully leverage the power of OI without understanding the potential roadblocks you may encounter along the way.
[Learn how to enable end-to-end process optimization with process mining. Get the Process Mining Guide.]
Navigating roadblocks to operational excellence
A variety of challenges hinder the adoption of OI systems. For example, inconsistent or poor-quality data can derail effective operational decision-making, making data governance an essential component of successful OI systems.
Let’s dive into the biggest barriers to OI implementation and explore solutions for navigating them. Integrating data from diverse sources like IoT devices, servers, databases, applications, and security platforms is a major stumbling block for many organizations.
Data integration
The fix? Develop a robust data integration strategy. Use standardized protocols, data formats, and APIs to ensure seamless data flow into the OI system. Traditional data management practices like data warehouses, data lakes, and data mesh try to tackle these challenges but fall short.
They bring increased technical debt, costly migrations, and security concerns. Enter data fabric. It integrates and manages data across disparate sources, boosting data integrity and security. It's essential for modern process automation platforms to optimize complex business processes end to end and enable scalable improvements.
For example, The Appian Platform offers end-to-end process automation powered by enterprise data and AI. One of its key features, data fabric insights, addresses common challenges such as security concerns, data availability, and real-time access issues. This capability extends the value of your data and processes, ensuring secure, accessible, and up-to-date information across the organization.
Scalability
Scalability is crucial for OI systems to grow with your organization. Choose solutions that can handle large data volumes and seamlessly expand for mission-critical work. Opt for cloud-based OI platforms that offer the flexibility and scalability required to accommodate growth.
Prioritize platforms that can scale horizontally and vertically, allowing for adding more resources or upgrading existing ones without disrupting operations. This level of control and adaptability is key to staying ahead in a rapidly changing business environment.
Assess your system's performance and scalability regularly to anticipate future needs and avoid bottlenecks. Incorporate automated scaling features to adjust resources based on demand dynamically. By prioritizing scalability, you can ensure that your OI systems support your organization’s growth over time, giving you the power to shape your future.
[Automate mission-critical processes at scale. Expand capacity as needed without sacrificing performance. View the Appian Cloud Whitepaper]
Security and compliance
Security and compliance are critical when implementing OI systems. Start by implementing robust security measures, including encryption, to protect data in transit and at rest. Establish strict access controls to ensure only authorized personnel can access sensitive information.
Conduct regular security audits to identify and address vulnerabilities, ensuring your system remains secure against emerging threats. Stay up-to-date with industry regulations such as the General Data Protection Regulation (GDPR), the Health Insurance Portability and Accountability Act (HIPAA), or the California Consumer Privacy Act (CCPA), and ensure your OI systems comply with industry standards. Prioritize training staff on compliance requirements and best practices for data protection.
Additionally, consider integrating automated compliance monitoring tools that can continuously check your systems for adherence to regulatory requirements. Develop incident response plans to address security breaches or compliance issues that arise quickly. By prioritizing security and compliance, you can protect your organization’s data integrity and build trust with customers and stakeholders.
Change management
Change is hard. Adopting new OI systems can be difficult for employees accustomed to old processes. To overcome this, develop a comprehensive change management plan. Start by clearly communicating the new system's benefit to all stakeholders, highlighting how it will improve efficiency and support their roles.
Engage stakeholders early and often, seeking their input and addressing feedback throughout the transition process.
Create a phased implementation schedule that allows for gradual adoption, reducing the shock of sudden changes. Provide regular updates on progress and celebrate small wins to build momentum and stakeholder buy-in. By fostering an environment of open communication, continuous learning, and active participation, you can ease the transition and ensure the successful adoption of your new OI system.
ROI framework
Let's talk about cost. The initial investment and ongoing maintenance of OI systems can be substantial. To justify the expense, develop a clear ROI framework that outlines the expected benefits and savings. Begin with a pilot project to demonstrate the system's value and effectiveness in a controlled environment. Regularly review and adjust the ROI framework, as needed, to ensure it aligns with your evolving business goals and operational needs. By starting small and scaling strategically, you can manage costs effectively while maximizing the benefits of your OI system.
Lead your organization to operational excellence
In today's hyper-competitive digital economy, IT leaders are expected to extract greater value from technology investments. Leveraging operational intelligence (OI) drives business growth, even in financially constrained times. By implementing robust OI systems, you position your organization for future success.
Prioritize scalability, ensure security and compliance, manage change effectively, and justify costs with a clear ROI framework. These steps will help you exceed stakeholder expectations and fully reap the benefits of operational intelligence.
[See why companies choose Appian for end-to-end process automation.]
