Processes form the foundation of any business and power day-to-day operations. However, for business operations to run smoothly, processes require constant monitoring to ensure they remain optimized and streamlined.
This guide discusses benefits, challenges, and solutions for driving operational excellence through process monitoring. It also covers the major steps in implementing these solutions.
Learn how to improve process monitoring functions with the Definitive Guide to Business Process Automation
Business process monitoring: definition and purpose
Business process monitoring is the observation of application-related functions needed for smooth and reliable core, support, and long-tail business processes.
It is also helpful for tracking key performance indicators (KPIs) to assess factors like bottlenecks, improvements, program scheduling management, and background tasks. These solutions require detailed procedures for identifying and resolving problems, including escalation paths and points of contact.
The early detection of problems is a key goal of business process monitoring, as this capability allows organizations to solve problems before they cause critical damage.
Process monitoring also includes all activities related to the review and analysis of process performance, generally for the purpose of identifying successes and failures. This monitoring is part of the business process management (BPM) lifecycle, which a variety of software tools may perform.
Benefits of process monitoring
The specific benefits of process monitoring include the ability to establish baselines and targets, proactively identify and resolve problems, and continuously improve processes. Keep reading to learn how and why.
Establishing baselines and targets
A type of process monitoring known as performance monitoring focuses on establishing baselines for current performance and setting goals for future performance. Baseline performance is essential for measuring progress because it shows the performance and outcome indicators before implementing an IT project.
These indicators are known as KAP (Knowledge, Attitude, and Practices) studies, which are based on systematic processes and methodologies.
Once the project analysis team collects baseline data, it inserts the resulting values into a Monitoring and Evaluation (M&E) plan. This team can then set realistic targets by collaborating with the implementation staff.
The next step in M&E is to identify the data sources and collection methods so staff can conduct proper sampling of those sources. An M&E plan should also provide information on KPI assessments, such as their scheduling.
Proactive issue identification and resolution
A process-oriented alert monitoring system allows stakeholders to proactively monitor the status of processes. Managers receive alerts and other notifications, so they can review and approve tasks to keep processes on schedule. Real-time process monitoring also allows IT teams to resolve process problems quickly and efficiently.
Process monitoring solutions should be able to create alerts for specific conditions related to data point thresholds or other metrics. They can also make exceptions for anomalies to account for expected daily, weekly, or seasonal fluctuations. These capabilities help prevent errors and system outages without the need for direct monitoring by staff members.
In addition, proactive monitoring allows an organization to track metrics in real time, which is especially useful for monitoring KPIs like availability, error rates, reliability, response times, and throughput.
At the same time, proper configuration and AI capabilities enable intelligent monitoring, so managers only receive notifications for critical issues by eliminating false positives.
Continuous improvement and optimization
Organizations must focus on continuously improving their processes if they’re to remain competitive in today’s dynamic business environment.
This paradigm ensures that methods, practices, and processes remain accurate, effective, and efficient; all of this despite the inevitable changes that routinely occur in business. Continuous process improvement (CPI) provides long-term benefits by making incremental changes to processes.
CPI consists of examining and improving processes, often by identifying and eliminating process bottlenecks. Performing this practice effectively requires the right software solution and management methodology, but it also assumes that the process already meets its specified objectives.
Business process monitoring challenges and how to solve them
Challenges in business process monitoring often relate to one or a combination of the following issues: data quality, data integrity, integration, and automation.
Data quality and integrity
Data quality and integrity problems result from bad data or changes to the data pipelines.
Resolving these problems generally involves monitoring the data before it arrives at its destination, based on certain metrics. This approach allows the monitoring solution to send an alert to the data owner and flag data that doesn’t look as it’s expected.
Data pipelines typically accept data from multiple sources, making it easy for a change in a data source to break the pipeline in the pre-processing step. In other cases, changes to the data schema can result in valid changes to the data, although the monitoring software may not be trained on the new input.
Assume, for this example, that a database administrator renames a column or adds another column to store new data. This change would require an update to the pipeline to map the relationship between the changed column and other columns in the table.
Another common problem with data integrity occurs when data is lost or corrupted at the source. Missing data can be the result of changes to the data source upstream or failure to record the data at all.
In other cases, the upstream data source may have missing features or corrupted data. Data processing requires close monitoring to prevent these issues, as they can affect the system’s overall performance.
Possible solutions to detecting problems with data quality include issuing alerts for schema changes. Owners of the pipeline and other data services should always be aware of changes to data sources, which requires frequent and effective communication among them.
Database administrators should also ensure that data owners implement proper data validation practices. In addition, they should ensure that stakeholders in these processes are aware of their role in moving data through the pipeline.
Safe integration and automation
A process monitoring solution usually sits directly on top of a platform product, requiring close integration between the two applications. This architecture appeals to users because implementation doesn’t require the existing processes to be customized. However, building the monitoring functionality on top of the platform rather than the processes can create some challenges.
For example, users can only monitor the parts of a process that’s executed on the platform. However, processes in a modern business are often distributed throughout its IT infrastructure, with some in the cloud and others on on-premise servers.
In this scenario, processes may be executed in multiple phases, making it difficult to obtain a unified view of the process. In addition, data that’s transferred within a process typically can’t be used to make monitoring decisions such as alerts.
Unified monitoring is the general solution to these problems. This approach requires an organization to achieve a clear understanding of its business processes, allowing it to create accurate models.
For example, a company must be able to define all of the steps needed to execute a process, after which it can assign a subset of those steps to each user group. Since it only needs to send events with the correct identifiers, this approach eliminates the need for the integration solution to have knowledge about processes.
How to create an effective business process monitoring strategy
In addition to defining objectives and metrics, collecting and analyzing data, and visualizing and reporting that data, an effective strategy also uses a variety of tools and technologies, including process automation software.
1. Define objectives and metrics
You must clearly define your objective before implementing a process monitoring solution. For example, simply saying that you want to support order processing during a busy time isn’t sufficient. You need a more precise goal, such as automating the approval process of purchases requests that comply with the purchase policy and are under a certain amount.
It’s also important to define the appropriate KPIs to help you understand the goals of process monitoring and identify any problems with its implementation. Keeping with the example above, appropriate KPIs for this improvement include whether approval times improved (or worsened) or rogue spending decreased (or increased).
Organizations can also use these metrics to establish objectives for individual employees and track their progress. Both quantitative and qualitative KPIs are essential for obtaining balanced insights into process performance.
2. Data collection and analysis
Implementing a process monitoring solution requires organizations to collect and aggregate data from many sources, including applications, customer interactions, databases. This data is vital for providing valuable insights into process performance and identifying areas to improve.
3. Visualization and reporting
Process visualization tools provide a visual representation of a workflow, allowing users to more easily understand critical factors such as dependencies and bottlenecks. These tools also let organizations obtain data-driven insights into optimizing these processes. Process visualization tools include technologies such as process intelligence, process mining, and task mining.
Monitor business processes effectively with Pipefy
Key processes require constant monitoring based on appropriate KPIs, making it easy to track process improvement. To effectively keep up with risks, changes, or improvements, a process monitoring system is essential for maintaining the health of business processes.
Pipefy’s business process automation platform simplifies process monitoring by centralizing communication, alerts, processes, data, and people in one place. Its no-code visual interface lets process owners build, modify, automate, and integrate workflows with a set of IT-sanctioned tools.
With customizable templates, create any workflow you can imagine without the fear of not knowing where or how to start. Pipefy also offers innovative tools like Pipefy AI to automate repetitive, labor-intensive tasks to improve process efficiency and provide process monitors a real-time glance into process performance.
Take the guesswork out of process monitoring. Integrate Pipefy with your existing workflows and tech stack for end-to-end process control and visibility.
