Process Automation: 12 Ways to Save Time with Approval Workflows

What is Process Automation?

Modern process automation consolidates all workflows into a single platform

Process automation is the execution of repetitive business processes through software and systems with minimal or no human intervention. When a trigger event occurs, the system takes actions based on predefined rules, sends notifications, and advances the process.

The core components of process automation are:

• Triggers: Events that initiate the process—form submissions, date/time, or system events
• Conditions: Rules that determine process branching—amount thresholds, department, or priority
• Actions: Automatically executed operations—notifications, data updates, or integrations
• Approvals: Steps requiring human decision—multi-level approvals, parallel/serial flows

Automation Maturity Levels

Every business is at a different point in its automation journey:

Level 1: Manual Processes

All operations are conducted via email, paper, or verbal communication. Tracking and reporting are challenging.

Level 2: Digitized Processes

Processes have moved to a digital environment, but still require manual triggering and tracking. ERP/CRM systems exist but are not integrated.

Level 3: Rule-Based Automation

Automated flows based on defined rules. Exceptions require manual intervention. This is the target level for most corporate firms.

Level 4: Intelligent Automation

AI-powered decision-making, predictive analytics, and continuous learning. A ten-year vision with pilot applications.

You can review the relevant pages for detailed information on industry-specific applications.

Automation Types and Layers

Different automation layers work together to create an integrated structure

Process automation is not a single technology, but a collection of components working across different layers:

1. Workflow Automation

The most fundamental automation layer. It defines the steps, conditions, and transitions of a workflow:

• Approval flows (procurement, expenses, leave)
• Document management flows (review, revision, publishing)
• Customer request management (ticketing, assignment, resolution)

2. Integration Automation

Automates data flow between different systems:

• API-based integrations (REST, SOAP)
• Middleware and ESB (Enterprise Service Bus) solutions
• iPaaS (Integration Platform as a Service) tools

3. Robotic Process Automation (RPA)

Software robots that mimic human behavior in existing applications:

• Screen scraping
• Form filling and data entry
• Legacy system integration

4. Intelligent Automation

Automation enriched with AI and machine learning:

• Document classification and data extraction (OCR + AI)
• Predictive routing
• Email/chat analysis with Natural Language Processing (NLP)

Trigger-Based Actions

Proper trigger design is the heart of automation

Trigger-based actions are the foundation of process automation. When an event occurs, a series of actions is automatically initiated.

Trigger Types

1. Event-Based Triggers

• Form submission: Web form, mobile app, ERP screen
• Record creation: New customer, order, inventory movement
• Status change: Order status, project stage, approval result
• Integration event: E-invoice receipt, bank transaction, email

2. Time-Based Triggers

• Calendar trigger: Every day at 09:00, the 1st of every month
• Delay trigger: 24 hours after creation, 3 days before the due date
• Periodic trigger: Every 15 minutes, once a week

3. Condition-Based Triggers

• Threshold value: When inventory falls below the minimum level
• Combination: VIP customer AND high amount AND urgent priority
• Negative condition: If no action is taken within 48 hours

Action Design

Actions to be performed after a trigger:

• Notification: Email, SMS, push notification, system alert
• Data processing: Record creation, update, calculation
• Routing: Assigning the task to a specific person/group
• Integration: Sending data to an external system, API call
• Document: PDF generation, email attachment, archiving

RPA Fundamentals and Application Areas

RPA delegates repetitive manual tasks to software robots

Robotic Process Automation (RPA) consists of software robots that automate tasks performed by human users by using the interfaces of existing applications. It is particularly valuable for legacy systems where API integration is not feasible.

When to Use RPA?

• If APIs are unavailable or costly in legacy systems
• If there are high-volume, repetitive data entry tasks
• If manual copy-pasting is performed between multiple applications
• For rule-based tasks that can be defined with decision trees

Process Characteristics Suitable for RPA

Not every process is suitable for RPA. Ideal RPA candidates:

• High volume: Hundreds or thousands of transactions daily/weekly
• Low exception rate: 80%+ of transactions follow standard rules
• Stable interface: The application interface does not change frequently
• Digital input: Data is already in a digital format (Excel, email, system)
• Rule-based decision: Can be defined with IF-THEN-ELSE logic

Common RPA Application Areas

Finance and Accounting

• Invoice processing and matching
• Bank reconciliation
• Month-end closing processes

Human Resources

• Data entry during the recruitment process
• Payroll data preparation
• Leave and attendance tracking

Procurement and Supply Chain

• Supplier price comparison
• Order creation and tracking
• Inventory level monitoring

Customer Service

• Ticket categorization and routing
• Customer data updates
• Automated responses to standard queries

Notification and Escalation Systems

Effective notification systems reach the right person at the right time

In process automation, notification and escalation systems ensure timely action is taken where human intervention is required.

Notification Channel Strategy

Choosing the right channel for each notification is critical:

• Email: Detailed information, document attachments, situations requiring archiving
• SMS: Urgent and critical alerts, field team notifications
• Push notification: Instant alerts for mobile app users
• In-system notification: Task box within the ERP/CRM, dashboard alert
• Integrated messaging: Corporate chat applications

Escalation Mechanism

Automatic forwarding to higher levels if no action is taken within the specified time:

Level 1: Initial Reminder

First reminder to the task owner (e.g., after 4 hours)

Level 2: Manager Notification

Cc notification to the unit manager (e.g., after 8 hours)

Level 3: Senior Management

Escalation to the department/general manager (e.g., after 24 hours)

Level 4: Automatic Action

Application of a predefined default decision or process suspension

Notification Best Practices

• Prevent notification fatigue—eliminate unnecessary alerts
• Send actionable notifications
• Implement priority levels (low/medium/high/critical)
• Offer one-click action capability (mobile approval)
• Allow personalization of notification preferences

SLA Monitoring and Performance Management

SLA dashboards monitor process performance in real-time

Service Level Agreement (SLA) monitoring is critical for measuring process performance and tracking compliance with goals.

SLA Design

1. Time Metrics

• Total process time: Total time from start to finish
• Step-based time: Completion time for each step
• Waiting time: Time spent waiting for approval/decision
• Processing time: Active working time

2. Thresholds

• Target: Ideal completion time
• Warning: Threshold requiring attention
• Critical: Threshold requiring escalation
• Breach: Threshold considered an SLA violation

SLA Monitoring Architecture

Technical infrastructure for effective SLA monitoring:

• Timestamp: Creation/update time at every process step
• Status history: Log of process status changes
• Calculation engine: Real-time or periodic SLA calculation
• Alert mechanism: Automatic notification upon threshold breach
• Dashboard: Real-time visibility and reporting

SLA Reporting

• Compliance rate: Percentage of transactions completed in accordance with SLA
• Average time: Average completion time
• Distribution analysis: Time distribution via histogram
• Trend analysis: Performance change over time
• Bottleneck analysis: Steps causing the most delays

Process Discovery with Process Mining

Process mining reveals actual process flows based on data

Process mining is an analytical method that automatically extracts and analyzes actual process flows from system logs (event logs). It reveals the gap between the theoretical process map and actual usage.

Process Mining Core Concepts

Event Log

For every transaction: Case ID, activity name, timestamp, resource (who did it), additional data.

Process Discovery

Automatic creation of a process model from event logs. Shows how it actually works.

Conformance Checking

Detecting deviations between the actual flow and the target model.

Performance Analysis

Bottlenecks, delay points, and resource utilization analysis.

Process Mining Implementation Steps

1. Data extraction: Collecting event logs from ERP, CRM, and custom applications
2. Data preparation: Merging different sources, cleaning
3. Process discovery: Creating an automatic process model
4. Analysis: Variants, bottlenecks, deviations
5. Improvement: Process optimization based on findings

What Can Be Detected with Process Mining

• Process variants: How many different ways the same process is executed
• Rework: Returns and repeated steps
• Bottlenecks: Steps with the longest waiting times
• Rule violations: Execution of undefined process steps
• Automation opportunities: Repetitive, rule-based steps

Field Example: Procurement Approval Automation

Real Case (Unbranded)

Situation

A manufacturing firm with 180 employees. Procurement requests were sent via email, and approvals were tracked by phone. The average approval time was 3-5 business days. Even for urgent needs, the time did not decrease. An average of 250 procurement requests were processed monthly.

Steps Taken

1. Weeks 1-2: The current process was mapped, and the actual flow was extracted using process mining. 12 different process variants were identified.
2. Weeks 3-4: The standard process was defined, and an approval matrix was created (based on amount + category).
3. Weeks 5-6: Workflow automation was set up, and mobile approval was activated.
4. Weeks 7-8: The SLA monitoring dashboard was launched, and escalation rules were defined.
5. Weeks 9-12: Pilot application, feedback collection, fine-tuning.

Result (Representative)

• Average approval time: Dropped from 3-5 business days to 4-8 hours
• Approval time for urgent requests: 2-4 hours
• Email traffic regarding procurement decreased by 70%
• SLA compliance rate: 92% (requests completed within target)
• Time spent by the procurement team on reporting: From 8 hours per week to 1 hour

7 Most Common Mistakes in Process Automation

1. Automating a Bad Process

Automating an inefficient process only accelerates inefficiency. First, the process itself must be optimized, then automation should be considered. The “garbage in, garbage out” principle applies.

2. Forgetting Exception Management

Not every process is 100% standard. Building automation without defining exceptions (edge cases) makes the system “brittle.” The minimum exception rate is between 5-15%; there must be a manual path for these.

3. Designing Overly Complex Flows

Flows with 10+ steps and 20+ conditions become unmanageable. Start simple and expand as needed. It is recommended to have a maximum of 7-8 steps in a flow; break them into sub-processes if necessary.

4. Ignoring User Experience

Automation that works perfectly technically will fail if not adopted by the user. Mobile compatibility, one-click approval, and an intuitive interface are critical.

5. Insufficient Testing

Test all scenarios before going live. Positive flow, negative flow, threshold values, timeouts, parallel approvals… Test each one separately. Start with a pilot user group.

6. Neglecting Monitoring and Measurement

Assuming “the job is done” once automation is live is a mistake. You cannot improve without SLA monitoring, error logs, and performance metrics. Automation without a dashboard is a black box.

7. Lack of Change Management

Even the best automation can fail in the face of user resistance. Do not launch without a training, communication, and support plan. The first 30 days are the critical period.

Identifying automation mistakes in advance is the key to success

Success Metrics

Track the following metrics to measure the return on investment of process automation (representative values):

Continuously improve automation performance by monitoring these metrics regularly (weekly/monthly).

Process Automation Checklist

Frequently Asked Questions (FAQ)