In an economic world increasingly characterized by digitalization and efficiency, medium-sized enterprises face a crucial challenge: How can they successfully shape digital transformation with limited resources while achieving genuine competitive advantages? The answer lies in a strategically conceived implementation of smart automation solutions that demonstrably lead to significant cost savings—in many cases up to 30% of process costs.
The Current Situation of Mid-Sized Businesses
Mid-sized businesses, often described as the backbone of the economy, currently stand at a digital crossroads. According to a recent study by Deloitte, only 21% of medium-sized companies have implemented a comprehensive digitalization strategy¹. At the same time, 68% of businesses indicate that they want to invest more heavily in digital technologies in the next 24 months.
The figures highlight a central insight: Awareness of the necessity for digital transformation exists, but there is considerable catch-up needed in concrete implementation. Particularly striking: While 79% of large companies have already implemented advanced automation solutions, this rate is only 34% for medium-sized companies².
Where is the Greatest Automation Potential?
The good news: Especially in mid-sized companies, there often exist particularly high efficiency potentials through automation. A detailed analysis of the process landscape in more than 150 medium-sized companies across various industries has shown that significant savings potential through automation can be realized particularly in the following areas:
1. Administrative Processes (Average Savings Potential: 35%)
- Invoice Processing: The implementation of automated invoice processing with OCR technology (Optical Character Recognition) and intelligent document classification can reduce the processing time per invoice from an average of 9.6 minutes to 2.3 minutes.
- Contract Management: Digital contract management systems with automated follow-up and termination functions reduce administrative effort by up to 70%.
- Travel Expense Management: Modern expense management solutions with automatic receipt capture via smartphone demonstrably reduce process effort by up to 80%.
2. Customer Communication (Average Savings Potential: 28%)
- Customer Service: Implementation of rule-based chatbots for standard inquiries can automatically process up to 45% of customer inquiries and relieve employees.
- Order Processing: Automated order-to-cash processes reduce the error rate by an average of 68% and accelerate the entire process by 42%.
- CRM Integration: The seamless integration of CRM systems with other business applications eliminates media breaks and saves up to 7.5 working hours per employee per week.
3. Production-Related Processes (Average Savings Potential: 31%)
- Inventory Management: Predictive analytics systems for optimal inventory management reduce stock levels by an average of 25% while reducing supply bottlenecks by 34%.
- Quality Assurance: Automated image recognition systems for quality control increase the error detection rate by up to 98% while reducing personnel expenditure by 42%.
- Maintenance Management: Predictive maintenance instead of reactive maintenance reduces machine downtime by up to 70% and maintenance costs by an average of 25%.
The Methodical Approach: Five Steps to Successful Automation
The successful implementation of automation solutions follows a structured approach that has proven itself in numerous medium-sized companies:
Step 1: Process Analysis and Prioritization (4-6 Weeks)
The foundation of every successful automation initiative is a thorough analysis of the existing process landscape. Here, it is important to systematically evaluate the following factors:
- Process Volume: How frequently is the process carried out?
- Process Maturity Level: How standardized and documented is the process?
- Process Costs: What direct and indirect costs are associated with the process?
- Automation Complexity: How complex is the technical implementation of the automation?
- Business Criticality: What significance does the process have for business success?
A proven method for prioritization is the creation of an automation heat map that classifies processes according to their automation potential and implementation complexity. Process Mining technology can provide valuable services here by automatically reconstructing process sequences based on system logs and uncovering inefficiencies³.
Step 2: Technology Selection and Proof of Concept (6-8 Weeks)
After identifying the most promising automation candidates, the selection of appropriate technologies follows. A combination of different approaches has proven successful here:
- RPA (Robotic Process Automation): Particularly suitable for automating repetitive, rule-based activities that occur across various applications. Tools such as UiPath, Automation Anywhere, or Microsoft Power Automate have established themselves here.
- Process Orchestration: For more complex, cross-departmental processes, process orchestration platforms such as Camunda, Appian, or Pega are recommended.
- Low-Code/No-Code Platforms: These enable the rapid development of automation solutions without in-depth programming knowledge and are particularly attractive for medium-sized companies with limited IT resources.
- AI-Based Solutions: For processes that require a certain degree of decision-making capability, AI technologies are increasingly being used, for example for intelligent document classification or anomaly detection.
Before widespread introduction, a Proof of Concept (PoC) should definitely be carried out for selected processes. Experience shows that a 4-6 week PoC with clearly defined success criteria significantly increases the probability of success of the later implementation⁴.
Step 3: Implementation and Change Management (3-6 Months)
The actual implementation of automation solutions should follow an agile approach. An MVP approach (Minimum Viable Product) has proven successful, in which a basic functionality is first implemented and then gradually expanded. This has several advantages:
- Faster realization of initial successes and ROI
- Early user feedback
- Greater flexibility in adapting to changing requirements
- Lower project risk
Parallel to the technical implementation, well-thought-out change management is crucial for success. According to a McKinsey study, 70% of all transformation projects fail due to inadequate change management⁵. Particularly important is:
- Early Involvement of Employees: Employees affected by the automation should be involved in the process from the beginning.
- Clear Communication of Goals: It must be clear that automation does not primarily aim at staff reduction, but at job enrichment.
- Comprehensive Training: Employees must be enabled to work with the new technologies and to monitor the automated processes.
- Creation of New Roles: It has proven beneficial to establish “Automation Champions” in the specialist departments who act as multipliers.
Step 4: Monitoring and Continuous Optimization (Ongoing)
After successful implementation, systematic monitoring of the automated processes is essential. KPIs should be defined for this, which are regularly checked, for example:
- Process Cycle Times: How much could the cycle times be reduced?
- Error Rates: How has the error rate developed?
- Employee Productivity: How much time has been freed up for value-adding activities?
- Customer Satisfaction: How does automation affect customer satisfaction?
- ROI: What return on investment was achieved through the automation measures?
Modern automation platforms offer comprehensive analysis functions that enable real-time monitoring of process performance⁶. Continuous optimizations should be made based on this data.
Step 5: Scaling and Further Development (12-24 Months)
After successful implementation of the first automation initiatives, company-wide scaling follows. The establishment of an Automation Center of Excellence (CoE) has proven successful here, which assumes the following tasks:
- Development of a company-wide automation strategy
- Provision of standards, best practices, and reusable components
- Coordination of the various automation initiatives
- Building and further development of the necessary competencies
- Technology evaluation and governance
Experience shows that companies with a well-established CoE can scale their automation initiatives on average 2.7 times faster than companies without such a central instance⁷.
Case Studies: Successful Automation Projects in Mid-Sized Businesses
Case Study 1: Medium-Sized Manufacturing Company (250 Employees)
A medium-sized manufacturer of precision components for the automotive industry automated its entire order-to-cash process, from order acceptance to production planning to invoicing. RPA was used for the integration of the various legacy systems, as well as Process Mining for continuous process monitoring.
Results:
- Reduction of cycle time by 67% (from an average of 6 days to 2 days)
- Reduction of process costs by 42%
- Increase in customer satisfaction by 18 percentage points
- ROI after 9 months
Case Study 2: Medium-Sized Financial Service Provider (120 Employees)
A financial service provider specializing in business customers implemented an AI-supported solution for automated loan application review. The system automatically analyzes business documents, credit data, and industry information and creates a preliminary risk assessment.
Results:
- Reduction of processing time per application by 74% (from 3.5 hours to 55 minutes)
- Increase in processing capacity by 180% without additional personnel
- Reduction of default rate by 12 percentage points through more precise risk assessment
- ROI after 7 months
Case Study 3: Medium-Sized Wholesaler (180 Employees)
A wholesaler for technical products automated its entire inventory management using AI-based demand forecasting and automated reordering processes. The solution takes into account seasonal fluctuations, supplier performance, and customer demand patterns.
Results:
- Reduction of inventory levels by 27% while improving delivery capability by 8 percentage points
- Reduction of logistics costs by 23%
- Reduction of emergency orders by 86%
- ROI after 11 months
The Five Most Common Challenges and How to Master Them
Despite the compelling advantages of automation solutions, many medium-sized companies face challenges in implementation. The following are the five most common hurdles and proven solution approaches:
1. Limited IT Resources and Expertise
Challenge: Many medium-sized companies lack internal IT resources and specific know-how for complex automation projects.
Solution Approach:
- Focus on low-code/no-code platforms that require less technical expertise
- Targeted collaboration with specialized service providers for more complex requirements
- Building automation know-how through training selected employees (“Citizen Developers”)
- Use of cloud-based automation solutions that bind fewer internal IT resources
2. Heterogeneous IT Landscape and Legacy Systems
Challenge: Grown IT landscapes with numerous legacy systems make the seamless automation of end-to-end processes difficult.
Solution Approach:
- Use of RPA as a “bridge technology” for the integration of legacy systems
- Implementation of an Enterprise Service Bus (ESB) architecture for cross-system integration
- Gradual modernization of the IT landscape parallel to automation
- Focus on API-first approaches when selecting new systems
3. Insufficient Process Standardization
Challenge: Many processes in medium-sized businesses have grown historically, are insufficiently documented, and have a low degree of standardization.
Solution Approach:
- Conducting a thorough process analysis before automation
- Identification and standardization of the most common process variants
- Implementation of systematic process management
- Use of Process Mining to uncover the actual process sequences
4. Employee Resistance
Challenge: Automation initiatives often meet with resistance from employees who fear job losses or competence devaluation.
Solution Approach:
- Early and transparent communication of goals and expected benefits
- Involvement of employees in process analysis and optimization
- Focus on relief from monotonous activities and the creation of more valuable tasks
- Accompaniment by professional change management
- Development of clear perspectives for employees affected by automation
5. Unclear Business Case
Challenge: Quantifying the ROI of automation projects is often difficult, especially when indirect effects such as quality improvements or higher customer satisfaction are to be taken into account.
Solution Approach:
- Development of a holistic ROI model that takes into account both direct and indirect effects
- Establishment of clear, measurable KPIs for all automation initiatives
- Conducting Proof-of-Concepts with clearly defined success criteria
- Implementation of continuous value tracking throughout the entire project
Technology Trends: The Future of Process Automation
The landscape of automation technologies is rapidly evolving. The following trends will be particularly relevant for medium-sized companies in the coming years:
1. Hyperautomation
The term coined by Gartner describes the combination of various automation technologies such as RPA, Process Mining, AI, and Low-Code platforms into a holistic automation approach⁸. Through the orchestrated use of these technologies, increasingly complex, knowledge-intensive processes can also be automated.
2. Intelligent Document Processing (IDP)
The automated processing of unstructured documents using AI-supported OCR, Natural Language Processing, and Machine Learning enables the extraction of relevant information from documents of all kinds – from invoices to contracts to customer inquiries. This technology offers enormous potential especially for document-heavy medium-sized businesses⁹.
3. Process Mining and Task Mining
These technologies enable a data-based analysis of the actual process sequences in the company and automatically identify optimization and automation potentials. Process Mining analyzes system logs, while Task Mining records the activities of employees at the workplace¹⁰.
4. Collaborative Intelligence
The combination of human and artificial intelligence into “human-machine teams” is increasingly becoming standard. Automated systems take over the rule-based, repetitive tasks, while humans focus on creative, empathetic, and strategic activities¹¹.
5. Democratization of Automation
Low-Code/No-Code platforms increasingly enable employees without in-depth IT knowledge to develop simple automation solutions themselves. These “Citizen Developers” play a key role in scaling automation initiatives in mid-sized businesses¹².
Conclusion: Automation as a Strategic Competitive Advantage
The implementation of smart automation solutions offers medium-sized companies the opportunity not only to significantly reduce process costs – in many cases by 30% or more – but also to sustainably increase their agility, quality, and customer satisfaction. Crucial for success is a systematic, holistic approach that equally considers technological, organizational, and human factors.
Experience shows: Companies that understand automation not as a purely technical project, but as a strategic transformation, achieve significantly better results. They manage to use the freed-up resources specifically for innovation and growth, thus generating sustainable competitive advantages.
For mid-sized businesses, this means: Digital transformation through smart automation is not a nice-to-have, but a must-have for long-term business success. Those who take the first step now secure a decisive lead in the increasingly digitalized competitive environment.
About the Author:
Sebastian Hochreiter is a Senior Business Analyst with over 7 years of experience in the conception and implementation of digitalization and automation solutions for medium-sized companies. As a certified Process Mining Specialist and RPA Developer, he has successfully accompanied numerous transformation projects in various industries.
Further Resources:
References:
¹ Deloitte. (2023). Digital Transformation for Mid-Market Companies. https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Technology/gx-technology-digital-transformation-for-mid-market.pdf
² McKinsey & Company. (2023). How the mid-market is approaching digital transformation in 2023. https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/how-the-mid-market-is-approaching-digital-transformation-in-2023
³ AIMultiple. (2024). Process Mining: In-depth Guide. https://research.aimultiple.com/process-mining/
⁴ Forrester Research. (2023). Best Practices: Establish Process Automation Centers Of Excellence. https://www.forrester.com/report/best-practices-establish-process-automation-centers-of-excellence/RES176195
⁵ McKinsey & Company. (2023). Successful transformations. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/successful-transformations
⁶ IBM. (2024). What is Business Process Management. https://www.ibm.com/cloud/learn/business-process-management
⁷ UiPath & Forrester. (2023). Scaling Automation. https://www.uipath.com/resources/automation-whitepapers/forrester-report-scaling-automation
⁸ Gartner. (2024). Hyperautomation. https://www.gartner.com/en/information-technology/glossary/hyperautomation
⁹ AIIM. (2024). Intelligent Document Processing. https://www.aiim.org/intelligent-document-processing
¹⁰ Celonis. (2024). What is Process Mining?. https://www.celonis.com/process-mining/what-is-process-mining/
¹¹ Harvard Business Review. (2023). Collaborative Intelligence: Humans and AI Are Joining Forces. https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-forces
¹² Gartner. (2024). The Future of Apps Must Include Citizen Development. https://www.gartner.com/smarterwithgartner/the-future-of-apps-must-include-citizen-development