Process identification and analysis
In the first step, we work with the specialist department to identify suitable processes for automation. We analyze the status quo: How does the process currently work? Which systems are involved? How much time does it take? Where do errors occur?
RPA in practice: examples, successes, best practices
After looking at the basics of robotic process automation (RPA) in the first part of our blog series, it's now time to get practical. Because theory is good - but what counts is the added value in reality.
What does an RPA implementation actually look like? Which processes can be automated really efficiently? And what are the final benefits - in terms of figures, time and quality?
In this article, we take you on a tour of real RPA projects: From the first analysis meeting to ongoing optimization, we show you typical project phases, successful use cases and tried-and-tested best practices. This will not only give you a clear insight into the life cycle of an RPA bot, but also inspiration for your own automation projects.
The life cycle of an RPA project
Before we get to the practical examples, let's take a look at the typical process of a successful RPA project:
Process design and optimization
Before we automate, we optimize: Not every existing process should be transferred 1:1 into a bot. Process steps can often be simplified or eliminated, resulting in more efficient automation solutions.
Bot development
Now the actual development of the RPA bot begins. Using modern low-code platforms such as UiPath, Automation Anywhere or Microsoft Power Automate, we can quickly create functional prototypes. The bot is programmed to carry out the necessary steps, handle exceptions and use escalation paths if necessary.
Tests and quality assurance
We rigorously test the bot in various scenarios: How does it behave with correct inputs? What happens if data is missing or incorrect? Is the error handling robust? Only when all test cases have been successfully completed does the bot go live.
Deployment and monitoring
After commissioning, we continuously monitor performance: Is the bot running as planned? What throughput times is it achieving? Are there any errors or exceptions? Detailed dashboards provide information on the efficiency and reliability of the automation.
Continuous improvement
An RPA project is never really finished. We regularly analyze the results and continue to optimize the bot - be it by expanding functionality, speeding up processes or improving error handling.
Practical examples: RPA bots in use
Let's now look at some concrete examples of how RPA bots are creating efficiency in different industries and departments:
Example 1: Automated sales order entry for one-off customers
Initial situation:
An online store or retailer processes numerous orders every day from new customers who often only make one-off purchases. The manual order entry process comprises an average of 6 process steps per customer, including entering data into the ERP system, creating deliveries and invoices and posting the outgoing goods. This requires around 10 minutes of manual processing time per customer and regularly leads to errors due to manual entries.
RPA solution:
A bot automatically performs the following tasks:
Reading order data from Excel files received as e-mail attachments
Automatic logon to the SAP system
Creation of sales documents
Creation of deliveries
Implementation of order picking
Posting the goods issue
Creation of the invoice
Result:
The processing time was reduced to 3 minutes per order. The error rate fell from around 10% to almost 0%. The automated process saved resources and significantly increased the efficiency of processing one-off customer orders.
Example 2: Automated report generation in sales
Initial situation:
A sales manager of a wholesaler spends 2-3 hours every Monday morning generating reports from various systems, consolidating them in Excel and sending them to the management team.
RPA solution:
A bot that automatically performs the following tasks every Monday at 5:00 am:
Registration in the various source systems (CRM, ERP, Business Intelligence)
Export of the required data in a standardized format
Consolidation in an Excel template with predefined formulas and charts
Creation of a PowerPoint presentation with the most important KPIs
Sending reports by e-mail to the sales management and the management team
Result:
The reports are available punctually at 7:00 a.m., before the first employee arrives at the office. The quality is consistently high and human errors in data transmission have been eliminated. The sales manager can now use his Monday morning for strategic planning and team meetings.
Example 3: Automated onboarding of new employees
Initial situation:
The HR department of a service company with a high fluctuation rate needs an average of 4 hours per person to set up all the necessary systems for the onboarding of new employees.
RPA solution:
A bot takes over the following steps after approval by HR:
Creation of the employee in the personnel management system
Creation of e-mail account and access to relevant applications
Setting up standard authorizations based on the job description
Ordering the necessary hardware and software
Sending automated welcome emails with relevant information
Registration in standard training courses and induction programs
Result:
The processing time has been reduced to 45 minutes, of which only 15 minutes is manual work. New employees have access to all the required systems from day one, which significantly increases productivity during the induction phase.
Best practices for successful RPA implementations
Based on our experience from numerous customer projects, we have identified the following best practices for successful RPA implementations:
Start with the right process
For your first project, choose a process that has high volumes, is rule-based and stable, promises measurable savings and is not too complex. Early success creates trust and acceptance for further automation projects.
Actively involve the specialist departments
The experts from the specialist departments know their processes best. Their involvement is crucial for:
- Correct recording of all process steps and exceptions
- Acceptance of the automation solution
- The continuous improvement of bots
Document meticulously
Detailed documentation is the be-all and end-all. It should include process flows with all variants and exceptions, the bot logic and decision rules, all system access and authorizations as well as all test and validation procedures. This not only facilitates maintenance, but also knowledge transfer and scaling.
Establish robust exception handling mechanisms
No process always runs 100% according to plan. Therefore, make sure that your bots recognize unexpected situations, create meaningful error logs and involve a human processor if necessary. They should also be able to restart as independently as possible after errors or interruptions.
Think about scaling right from the start
A sustainable RPA strategy takes into account reusable components for frequently occurring tasks, standardized development guidelines and clear governance structures. Centralized control and monitoring of the bots is just as important.
Plan the operation
Bots also need regular maintenance. This includes regular performance checks, adjustments in the event of changes to the underlying systems and regular updates to the RPA platform. Equally important is the continuous optimization of processes to ensure high efficiency in the long term.
The path to your customized RPA solution
Have you identified processes that could be suitable for automation? Our experienced RPA team will be happy to support you on the way to your individual solution:
- In a free initial consultation, we evaluate the automation potential in your company together.
- In a proof of concept, we demonstrate the practical feasibility and the concrete benefits for a selected process.
- With our RPA starter package, we accompany you from the conception to the productive use of your first bots.
Outlook for part 3: Intelligent automation - when RPA meets AI
In the next part of our blog series, we will show how the limits of classic RPA solutions can be overcome by integrating AI components. Find out how intelligent document processing and machine learning are revolutionizing automation options - especially for unstructured data and complex decision-making processes.
We will shed light on how modern RPA bots can be supported by AI technologies such as:
- Optical Character Recognition (OCR)
- Natural Language Processing (NLP)
- Machine Learning (ML)
- Computer Vision
become intelligent assistants that can do far more than their rule-based predecessors.
Are you ready to take your process automation to the next level? Contact us today for a no-obligation consultation and discover the potential of modern RPA solutions for your company.
FAQs
1. What is the typical course of an RPA project?
An RPA project usually goes through six phases: Process Identification, Process Optimization, Bot Development, Testing, Deployment & Monitoring and Continuous Improvement.
2. Which processes are particularly suitable for RPA?
3. Which tools are used for RPA development?
4. How quickly can measurable success be achieved with RPA?
5. What are best practices for a successful RPA implementation?
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