Guide
Real-Time Process Monitoring as a Service for Mid-Market
Real-time process monitoring as a service provides mid-market operations with immediate, actionable intelligence to prevent issues and boost efficiency without the high cost and complexity of enterprise platforms. It continuously observes business processes, detecting anomalies and triggering alerts within seconds, so teams can address problems like SLA breaches or production bottlenecks before they escalate.
The True Cost of Lagging Data
Traditional process mining, while valuable, often operates on historical data. It analyses event logs in batches, typically nightly or weekly, producing insights into inefficiencies and bottlenecks that have already occurred. This is like looking in the rearview mirror: you know where you’ve been, but it doesn’t help you avoid the collision happening right now. For time-sensitive sectors like manufacturing, healthcare, hospitality, and logistics, this delay is more than an inconvenience. It’s a direct hit to the bottom line.
Key shift
Real-time process monitoring closes this gap, shifting from retrospective analysis to continuous observation, alerting teams to deviations within seconds or minutes.
When deviations from expected process behaviour aren’t flagged immediately, the consequences compound. A delayed patient discharge in healthcare can ripple through bed availability and staff workload. A missed delivery window in logistics can incur penalties and damage reputation. In manufacturing, a quality issue undetected for hours can lead to entire batches being scrapped.
Delivering Live Insights as a Service
Mid-market operations leaders need Celonis-grade results without Celonis-scale tools or budgets. Zenotris delivers real-time process monitoring as a service, not a product: our experts handle the technical integration, data streaming, model configuration, and dashboard setup, so your team can focus on action, not administration. The service continuously observes your business processes as they execute, capturing events from your ERP, CRM, MES, or a custom application. When behaviour deviates from your defined patterns or SLAs, the detection engine triggers automated alerts within seconds, catching:
In logistics, this can mean pre-breach detection across a carrier network, flagging a potential delay before it becomes a customer complaint. See Real-Time Monitoring for Logistics and Supply Chain for how this applies to supply chain operations specifically. Engagements begin by identifying the 1-3 processes with the highest operational value, for a focused approach with a faster time-to-value.
We integrate with your ERP, CRM, MES, or custom applications to capture live event data.
Your SLAs and expected process patterns are modelled so deviations are meaningful, not noise.
The detection engine watches process execution in real time, around the clock.
Automated alerts and a live dashboard put deviations in front of the right people within seconds.
Choosing Your Path: Platform vs. Service for Live Operations
When deciding between a real-time process monitoring platform and a service, the trade-off usually comes down to budget, complexity, and internal resource availability. Here’s how the common approaches compare:
| If you are… | Use | Because | But |
|---|---|---|---|
| A large enterprise with a dedicated process mining team | Celonis EMS | Market leader with broad capabilities for deep, complex analysis. | High cost, often tied to data volume, and complex implementation. |
| Heavily invested in SAP systems | SAP Signavio | Native integration with SAP source systems for process insights. | Less suitable for diverse, multi-vendor technology stacks. |
| Needing to link insights to automation execution | UiPath Process Mining | Strong integration with the UiPath RPA system. | Primarily focused on automation candidates, not standalone process analytics. |
| Seeking rigorous process mining without enterprise pricing | Apromore | Open-source entry point, accessible pricing for mid-market. | May require more technical expertise to get full value from modern features. |
| Monitoring IT infrastructure or application performance | Datadog / Splunk APM | Excellent for system health and application-driven workflows. | Built for IT systems, not natively designed for business process conformance. |
| Building a custom solution with internal data engineers | Kafka + Flink | Maximum flexibility and control over the entire stack. | Requires significant data engineering investment and ongoing maintenance. |
| Needing Celonis-grade results as a service | Zenotris | Predictable, service-based model with expert delivery and automated detection. | Requires initial data integration support from your IT team. |
The service model shifts capital expenditure to operational expenditure, lowering the barrier to entry and shortening time-to-value. You get specialist expertise without the overhead of building an internal team. To see how this works in more depth, visit our Real-Time Process Monitoring solutions page.
Your Live Dashboard: Key Metrics for Operational Excellence
With real-time process monitoring in place, the value shows up in a live dashboard that reflects the pulse of your business. These are the KPIs operations leaders should be tracking. The right target depends on your own baseline, so each row says how to set it:
| Metric | What it means | How to set your target |
|---|---|---|
| On-time delivery | Actual delivery vs. promised date, not ship-confirm date. | Use your last 90 days as the baseline, and raise the target once the cause of late orders is fixed. |
| Cycle time variance | Deviation from average process completion time. | Measure the normal spread first, then alert when a case runs well outside it. |
| SLA compliance | Percentage of instances meeting agreed service level agreements. | Take the level from your customer or carrier contracts, and alert before a breach, not after. |
| Exception rate | Frequency of business exceptions: rework, escalation, rejection. | Track it weekly; a rise matters more than the absolute level. |
| Throughput | Number of process instances completing per hour or day. | Compare with the same weekday in previous weeks, so normal weekly swings do not trigger alerts. |
| First-pass yield | Percentage of instances completing without rework. | Set it from your best recent month and look into any week that falls below it. |
Where to start
Pick one process that lacks real-time visibility today, document its current cycle time and exception rate, then set an alert for a 10% deviation. That single process is usually where the first return shows up.
Monitoring a process that runs across several systems
Most processes worth watching live do not sit in one system. An order starts in the ERP, moves through a warehouse system and a carrier portal, and ends in finance. Live monitoring needs three things to work across them.
1. Capture events as they happen. The usual methods, fastest first:
| Method | How it works | Delay | Best when |
|---|---|---|---|
| Change data capture | Reads the database’s change log (for example with Debezium) | Seconds | The system has no event feed and cannot be changed |
| Webhooks or platform events | The system pushes each change (for example Salesforce Platform Events) | Seconds | The system offers them |
| Message streams | Events already flow through Kafka or a similar bus | Seconds | Your IT team already streams events |
| Orchestration logs | Reads the history of a workflow engine such as Camunda, Temporal or UiPath Orchestrator | Seconds to minutes | The process is already automated |
| Scheduled polling | Asks each system for changes on a timer | Minutes | Nothing else is available |
2. Join everything on one case ID. Every event needs the same case reference, or a mapping between references: the order number links to the shipment ID, which links to the invoice. Record timestamps in one time zone (UTC). The IEEE 1849 (XES) event log standard names the three fields every event needs: the case, the activity and the timestamp.
3. Keep orchestration and monitoring separate. An orchestration engine knows the steps it runs. It does not see the manual work and the other systems around them. Monitoring reads all of them, so it shows where a case is waiting, not only where the automation is.
What the live dashboard should show
- Live queue: every open case by step and age, oldest first.
- Flow: where cases are waiting now, compared with a normal day.
- Alerts: breaches and cases about to breach, each with an owner.
- Trend: a daily roll-up, to check that a fix held.
A team lead works the queue and the alerts; a director watches flow and trend.
Gain real-time visibility into your operations, today
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Exception rate