DEV Community: Thomas Delfing

Intellectual Property Management for SMEs: Turning Innovation into Business Value

Thomas Delfing — Wed, 28 Oct 2026 08:13:21 +0000

Why Intellectual Property Matters for SMEs

Small and medium-sized enterprises (SMEs) are often highly innovative. Technical solutions, specialised processes, distinctive brands, product designs, software, and valuable business know-how frequently emerge from their day-to-day operations. Yet, many companies only consider intellectual property (IP) when a competitor copies an idea, a deadline approaches, or investors request reliable information about their IP portfolio.

According to the German Patent and Trade Mark Office (DPMA), only around 10% of SMEs in the European Union have registered industrial property rights. At the same time, companies holding patents, trademarks, or designs generate, on average, 44% higher revenue per employee than companies without these rights. Although this correlation does not prove that IP rights alone cause business success, it highlights the importance of professionally managing intellectual property.

IP Is More Than Patents

Intellectual property encompasses patents, utility models, trademarks, registered designs, copyrights, trade secrets, software, data, and operational know-how.

For SMEs, the first step is not to register as many rights as possible. Instead, companies should identify the intellectual assets they already own and determine which ones support their business objectives. A structured IP audit can reveal existing rights, protection gaps, third-party rights, contractual issues, and potential funding opportunities.

Clear agreements with employees, development partners, and external collaborators are equally important. Companies must also manage confidential information carefully, as not every idea automatically belongs to the business, and public disclosure can compromise certain protection options.

Align IP Strategy with Business Goals

With limited budgets, SMEs must prioritize their investments in intellectual property. The key question is not simply what can be protected, but which rights will strengthen the company's competitive position and future growth.

An effective IP strategy considers:

Which technologies, brands, or designs contribute most to revenue and profit margins.
Which innovations differentiate the company from competitors.
Which countries are strategically important for sales, production, licensing, or competition.
Whether formal registration or confidential know-how offers better protection.
Whether the company can realistically enforce its rights if infringement occurs.
Which IP assets support future products and business opportunities.

Thorough research is essential to reduce infringement risks and avoid spending money on rights with limited legal strength or commercial value.

Manage IP Costs and Portfolio Value

Registering intellectual property is only the beginning. Over its lifecycle, an IP right may generate costs for legal advice, applications, translations, international filings, renewal fees, monitoring, and enforcement.

These expenses should be assessed against both direct and indirect business benefits. IP rights may generate licensing revenue, protect product margins, discourage imitation, strengthen negotiations, or support partnerships and financing.

A sound IP portfolio review should therefore evaluate:

Current and projected protection costs.
Direct income, including licensing revenue.
Contributions to products, markets, profitability, and competitive advantage.
Strategic value for future innovation and business development.

Every significant IP right should have a clear business rationale. Companies should regularly decide whether to maintain, expand geographically, license, sell, enforce, or discontinue individual rights. These decisions should be reviewed at important milestones, particularly before major international filing expenses or renewal payments.

Funding Helps, but Strategy Comes First

Funding programs can reduce the initial cost of IP protection. For 2026, the DPMA highlights the EU-funded SME Fund, administered by the European Union Intellectual Property Office (EUIPO), which supports eligible IP-related activities depending on the available voucher scheme.

Applicants must follow the applicable process, including submitting an application and waiting for the funding decision before beginning the funded activity. However, financial support does not replace a long-term IP strategy. Businesses must still determine which rights are worth protecting and maintaining.

Professional IP Management with Genese

As an IP portfolio grows, spreadsheets, calendars, and scattered document folders become increasingly difficult to manage. They may track deadlines, but they rarely provide a complete overview of which innovations are protected, which products depend on those rights, or how future costs compare with expected business value.

An IP management system (IPMS) centralizes information about IP rights, patent families, deadlines, tasks, documents, responsibilities, contracts, and costs. When combined with product, market, licensing, and valuation data, it transforms administrative record keeping into strategic portfolio management.

Solutions such as Genese and Gweb Workspace support this process. Genese provides capabilities for file and document management, deadline tracking, reporting, planned and actual cost analysis, and cost forecasting. Gweb Workspace supports web-based access to files, patent families, deadlines, and tasks, with role-based access controls for structured collaboration.

For SMEs, the main advantage is transparency. Management teams, developers, IP professionals, and external advisers can work with consistent information, assess costs against commercial objectives, identify protection gaps, and make better-informed portfolio decisions. An IPMS does not replace legal advice or business judgement; it provides the reliable information needed to support both.

Conclusion: Turn Intellectual Property into a Strategic Asset

Intellectual property does not automatically become a business asset simply because it is registered. Its value emerges through systematic identification, appropriate protection, commercial prioritization, ongoing monitoring, and regular portfolio reviews.

For SMEs, where a small number of innovations may underpin a significant competitive advantage, professional IP management is particularly important. An IP management system such as Genese helps companies maintain visibility over critical rights, control deadlines and costs, and evaluate how their IP portfolio supports current performance and future growth.

The objective is clear: move beyond managing IP records and start managing intellectual property as a strategic driver of innovation, competitiveness, and long-term business value.

Sources and Further Reading

AI Agent Security in Law Firms: Key Lessons for Secure MCP Integrations

Thomas Delfing — Tue, 27 Oct 2026 07:16:19 +0000

AI agents and Model Context Protocol (MCP) servers offer new opportunities for law firms and IP management—but they also introduce significant cybersecurity risks.

Artificial intelligence is evolving beyond answering questions and generating text. Today, AI agents can search databases, retrieve documents, process emails, call APIs, and execute actions across enterprise systems. The Model Context Protocol (MCP) provides a standardized way for AI models to interact with external tools and applications.

For law firms and intellectual property (IP) departments, these capabilities can streamline patent research, document analysis, deadline tracking, and administrative workflows. However, once AI can take action rather than simply generate text, security risks change fundamentally. An incorrect answer may become an unauthorized action with real-world consequences.

What Recent AI Security Incidents Teach Us

In May 2026, AI security company Irregular tested the cybersecurity capabilities of advanced AI models in simulated corporate environments. According to the source article, Google's Gemini inadvertently gained access to the public internet during a test and interacted with systems belonging to three real companies.

The incident highlighted a critical security weakness: insufficient isolation between a simulated environment and real-world systems.

The lesson for businesses is clear. The primary concern is not necessarily that an AI model develops malicious intentions. It is that an AI agent may execute a task using technical permissions that exceed its intended scope.

This distinction is particularly important when AI agents connect to business applications through MCP servers.

Why AI Agents Create New Cybersecurity Risks

Traditional enterprise software generally follows predefined rules. AI agents, by contrast, dynamically select tools and actions based on their objectives, context, and available capabilities.

An MCP server might expose functions such as searching case files, downloading documents, creating notes, sending emails, deleting deadlines, or submitting applications.

If an agent has excessive permissions, a single mistake can trigger unauthorized data access, disclosure of confidential information, or unintended changes to business records.

One major threat is indirect prompt injection. A seemingly ordinary PDF, email, or webpage may contain malicious instructions designed to influence an AI agent. If the agent can access confidential documents, export files, and communicate externally, manipulated content could initiate a damaging sequence of actions.

Instructions such as “never access another client's confidential files” are not sufficient security controls. Actual access restrictions must be enforced by the underlying software.

The Principle of “Assume Agent Compromise”

Organizations should design AI systems around the principle of Assume Agent Compromise. Instead of assuming that an AI model will always behave correctly, security architecture should anticipate mistakes, misunderstood instructions, prompt injection, and unexpected tool usage.

The key question is:

What is the maximum damage an AI agent could cause if it made the wrong decision?

The answer depends on how its access to data, networks, credentials, and executable functions is restricted.

10 Best Practices for Secure AI and MCP Deployments

Start with read-only access. Separate document search and analysis from functions that modify records, send emails, or delete information.
Avoid unrestricted service accounts. Whenever possible, execute requests within the authenticated user's security context. Check permissions on the server for every tool call.
Enforce authorization outside the AI model. Application-level access controls, role checks, and client separation must never depend solely on system prompts.
Require human approval for critical actions. Confirm actions such as sending external communications, exporting large datasets, changing deadlines, deleting documents, or submitting official applications.
Restrict internet access. Allow connections only to explicitly approved services and APIs required for the task.
Keep credentials separate from the model. API keys, passwords, database credentials, and OAuth tokens should remain in secure server-side systems. Use narrowly scoped, short-lived credentials where possible.
Treat external content as untrusted data. Emails, PDFs, websites, attachments, and tool outputs may contain malicious instructions and must not automatically be treated as authorized commands.
Enforce client separation before data reaches the AI. Search results, document retrieval, and API requests must respect existing permissions and confidentiality barriers.
Log and monitor agent activity. Record relevant users, sessions, tools, actions, affected records, timestamps, and outcomes. Detect suspicious patterns such as mass exports or unusual access volumes.
Approve and manage MCP servers centrally. Prevent unauthorized extensions from entering production environments and review approved tools for changes and vulnerabilities.

Secure AI Integration for IP Management Systems

For IP management systems (IPMS), one of the most important architectural decisions is how an AI agent accesses confidential business data.

Giving an agent direct access to a database or document repository can create a parallel access layer that bypasses existing application permissions and business rules.

A safer approach is to connect the AI through the application's established interfaces, such as the GeneseConnect REST API offered by Genese.

With this architecture, an MCP server acts as an intermediary between the AI agent and the IP management system. Requests pass through the application's existing authentication, authorization, and business logic rather than accessing the database directly.

The architecture follows this pattern:

User → AI Agent → MCP Server → GeneseConnect REST API → Genese Business Logic and Access Controls → Data

For example, when a user asks an AI agent to summarize current patent files for a client, the agent can initiate a search through MCP. GeneseConnect then applies the user's existing permissions and returns only the records that the user is authorized to access.

Even if the AI attempts to retrieve additional files because of a misunderstanding or malicious prompt injection, the application should deny unauthorized requests.

This approach preserves the IP management system as the authoritative source for access control.

Apply Different Security Levels to Different Actions

Not every operation carries the same level of risk. Searching for a case reference is fundamentally different from exporting an entire file archive or submitting a legally significant application.

A secure integration should distinguish between:

Read operations: Searching files, viewing case information, and retrieving document lists.
Internal changes: Creating notes or updating permitted records.
External actions: Sending emails, exporting documents, or transmitting data to third parties.
Critical actions: Deleting deadlines, submitting IP applications, or sending legally binding communications.

The greater the potential impact, the stronger the required safeguards should be. These may include additional authentication, explicit human approval, detailed audit logs, and technical restrictions.

The governing principle is straightforward: user permissions define what is allowed, the API defines which functions are available, the MCP server limits which tools the AI can use, and human approval protects particularly sensitive actions.

Conclusion: Control the AI Agent's Capabilities, Not Just Its Instructions

AI agents and MCP integrations can deliver substantial productivity benefits to law firms and IP professionals. Avoiding the technology entirely is not necessarily the answer. The priority should be to establish clear, enforceable security boundaries.

An AI agent should be treated as a powerful software component—not as a trusted user with unrestricted access.

For IP management, integrating AI through a controlled interface such as the GeneseConnect REST API helps preserve existing permissions and business rules while enabling AI-assisted workflows.

Access controls, client confidentiality, credential management, network restrictions, activity monitoring, and human approvals must be enforced by the surrounding technical architecture.

The most important security principle is this: AI may decide how to complete an authorized task, but it must never decide what it is authorized to do.

As AI agents become more autonomous, secure MCP integrations will depend less on trusting the model and more on limiting what it can do when something goes wrong.

Why We Need to Read More, Not Less, in the Age of AI

Thomas Delfing — Mon, 26 Oct 2026 06:13:53 +0000

Deep reading, cognitive performance, and time management are becoming essential skills in an AI-driven world.

Artificial intelligence can summarize texts, analyze research papers, organize information, and explain complex concepts in seconds. What once required 30 minutes of reading can sometimes be understood in five. This is a significant advancement, but it also presents a challenge: as AI takes over more of our intellectual work, we must consciously maintain the cognitive skills we still need ourselves.

One of the most important is deep reading — the ability to engage with longer, more demanding texts with sustained attention and critical thought.

Reading Is a Complex Cognitive Process

Reading may feel effortless to experienced adults, but it requires several brain systems to work together, including visual processing, attention, language comprehension, memory, and prior knowledge.

A 2025 meta-analysis of 163 neuroimaging studies highlights the complexity of the brain networks involved in reading. Additional research into digital reading suggests that distractions can negatively affect text comprehension.

Reading is therefore more than simply absorbing information. It is an active cognitive process that requires concentration, interpretation, and the ability to connect ideas.

When we read longer articles, books, or research papers, we retain information across paragraphs, evaluate arguments, identify contradictions, and integrate new insights with existing knowledge. By contrast, rapidly scrolling through short posts and fragmented information encourages us to move quickly from one topic to another.

How AI Is Changing the Way We Think

AI makes accessing information easier than ever. We can ask it to summarize a lengthy report, extract the findings of a scientific paper, or compare several sources without reading each one in full.

These capabilities are valuable. The problem arises when assistance becomes permanent delegation.

If we rely exclusively on AI-generated summaries, we may miss important parts of the thinking process. We receive the conclusions without necessarily working through the reasoning ourselves.

The key distinction is whether AI supports learning or replaces the cognitive steps required for it.

AI should accelerate our thinking, not replace it.

For simple factual questions, a quick summary may be all we need. But when learning a new subject, developing professional expertise, or making complex decisions, reading the original material can be essential.

Taking time to reread a difficult paragraph, question an argument, or compare competing explanations is not wasted time. It is part of learning.

Deep Reading as a Professional Skill

For business leaders, developers, researchers, consultants, and other knowledge workers, access to information is no longer the primary challenge. The real advantage lies in evaluating information, understanding context, and exercising sound judgment.

Deep reading helps create the conditions for this kind of critical thinking. It should therefore be treated as a deliberate professional practice, not merely a leisure activity.

This does not mean reading every document from beginning to end. AI can efficiently identify relevant information and reduce unnecessary research. However, we should reserve time for activities that demand deeper engagement, such as reading specialist books, examining research beyond its abstract, studying detailed analyses, and following complex arguments without constant interruptions.

Just as physical exercise requires deliberate effort, sustained reading requires us to make room for concentration.

Time Management: Making Space for Deep Work

In today's information-rich environment, attention has become one of our most valuable resources. AI makes information increasingly accessible, but our capacity to focus remains limited.

This changes the questions we should ask about productivity. Instead of measuring success solely by how much work we complete, we should also consider how we spend our attention and whether our time supports meaningful learning.

This is where TimeSpin can help.

With TimeSpin, users can track and categorize their activities and reflect on how satisfied they feel with the time spent on them. For example, recording “Professional Reading” as a separate activity makes it possible to see how much time is actually dedicated to books, specialist literature, and continuous learning.

That information can reveal a simple but important pattern: are we deliberately making time for deep reading, or are urgent tasks continually pushing it aside?

While TimeSpin does not measure reading comprehension or cognitive effort, it helps make time allocation more visible. Activities such as professional reading, research, training, and deep work can be tracked alongside meetings, emails, and project work.

What we do not consciously schedule is often displaced by whatever feels most urgent.

A Better Way to Work With AI

The future of productive work is not about consuming more information as quickly as possible. It is about using technology intelligently while protecting the time needed for deeper understanding.

A practical principle is simple: use AI when speed matters, and read for yourself when understanding matters.

By combining AI-assisted efficiency with deliberate deep reading, we can make better use of technology without neglecting the cognitive skills that support learning, sound judgment, and professional growth.

At the end of the week, it may be worth asking not only how many hours we worked, but also how much time we invested in reading, thinking, and understanding something new.

In the age of AI, that time may become one of our most valuable investments.

By Oliver Otto | Bremen | September 14, 2026

Germany’s STEM Education Problem Starts Before University

Thomas Delfing — Sun, 25 Oct 2026 08:54:47 +0000

How declining school performance, critical thinking, and AI skills could shape Germany’s future competitiveness

Germany faces a growing challenge: while businesses grapple with skilled labor shortages, digital transformation, and the rapid adoption of artificial intelligence (AI), student performance in mathematics, reading, and science continues to raise concerns. These issues are closely connected. The skills developed in school form the foundation for technological innovation, workforce readiness, and long-term economic growth.

The OECD’s PISA assessments offer important insights into the abilities that underpin a competitive, technology-driven economy. Mathematical reasoning, scientific literacy, and reading comprehension are essential for analyzing data, developing software, understanding technical documentation, and solving complex problems.

When these foundational skills weaken, the consequences extend beyond schools and universities. Businesses eventually feel the impact through increased training requirements and a smaller pool of suitably prepared talent.

Why STEM Skills Matter for Germany’s Workforce

Technical training cannot begin entirely from scratch. Companies can teach programming languages, databases, software architecture, and development tools. However, it becomes more difficult when trainees lack fundamental mathematical knowledge, structured thinking, reading comprehension, and the persistence needed to solve unfamiliar problems.

For Bremen-based software company Genese.de GmbH, which develops software for managing patents, trademarks, and other intellectual property rights, these challenges are part of the practical realities of vocational training.

Managing Director Oliver Otto emphasizes the importance of curiosity in software development.

“Curiosity is one of the most important qualities for an application developer. They need to understand why something works, why it fails elsewhere, and whether a better solution exists,” Otto explains.

Developers who accept the first available answer without questioning it may struggle to produce consistently reliable results, particularly as AI becomes more integrated into software development.

Curiosity and Academic Achievement Must Work Together

Children naturally ask questions, experiment, and explore how things work. Yet this curiosity can diminish when education focuses too heavily on producing correct answers quickly and avoiding mistakes.

In mathematics, science, and technology, progress rarely comes from knowing the solution immediately. Software developers test code, identify errors, and refine their approach. Engineers simulate designs, assess failures, and improve their work. Scientific discoveries often begin with recognizing that something remains unexplained.

Germany therefore needs both academic achievement and intellectual curiosity. Curiosity encourages exploration, while discipline and sustained effort turn questions into knowledge and practical skills.

An effective education system should maintain high expectations without discouraging students from questioning assumptions, learning from mistakes, and exploring alternative solutions.

Artificial Intelligence Makes Foundational Knowledge More Important

AI tools can now generate code, analyses data, draft content, and explain complex subjects in seconds. This may create the impression that foundational knowledge is becoming less important. In reality, the opposite is increasingly true.

Professionals must be able to evaluate AI-generated results, identify incorrect assumptions, check sources, and recognize missing information. Producing an answer is not the same as producing a reliable answer.

An experienced software developer can use AI to generate code quickly, but their expertise remains essential for assessing architecture, security, edge cases, and long-term maintainability. A beginner may generate similar-looking code without recognizing its weaknesses.

The same principle applies to business analysis, technical assessments, calculations, and written communication. AI can produce convincing results that are nevertheless inaccurate or incomplete.

Consequently, AI literacy requires more than writing effective prompts. It demands subject knowledge, critical thinking, analytical skills, and the confidence to challenge a machine's conclusions.

What AI Skills Mean for Education and Business

Students and employees should learn to use AI as a tool for investigation rather than simply accepting its first response. Effective AI use involves asking follow-up questions, comparing alternatives, verifying evidence, and reconsidering the original problem when necessary.

These habits closely resemble scientific reasoning. They also help businesses make better decisions and use technology more productively.

For companies such as Genese.de, which trains future application developers, the distinction is particularly relevant. Programming tools and AI systems can accelerate development, but they cannot eliminate the need for people who understand what they are building and why.

The challenge for Germany is to prepare a workforce that combines technical competence with independent judgement. As AI automates more routine tasks, employees who can understand complex systems, evaluate outputs, and make informed decisions will become increasingly valuable.

Why Companies Cannot Solve the Education Problem Alone

Businesses can support young talent through apprenticeships, internships, structured training, and practical experience. However, they cannot permanently compensate for weaknesses that develop throughout a student's school years.

Improving education also requires investment in teachers, modern learning environments, digital infrastructure, and effective teaching methods. Just as importantly, students must have opportunities to practice, make mistakes, and develop confidence in tackling difficult problems.

Learning requires effort. Watching tutorials or copying existing solutions is not enough to become a capable software developer. Real competence develops through experimentation, problem-solving, and the willingness to try again after failure.

Academic achievement and curiosity are not opposing goals. When combined, they create the conditions for deeper understanding and sustained innovation.

Germany's Economic Competitiveness Starts in the Classroom

Germany cannot rely on low labor costs to compete internationally. Its economic success depends on productivity, technological expertise, quality, and innovation. All require a workforce with strong foundational skills.

The country's STEM education challenge is therefore more than a school policy issue. It is a long-term economic concern that affects businesses, technical training, and Germany's ability to remain competitive in an increasingly AI-driven world.

Schools must teach knowledge and demand achievement while preserving students' desire to understand how things work. Businesses must continue developing talent, and employees must learn to use AI critically rather than unquestioningly.

Ultimately, Germany's future will depend not simply on how many people can operate AI tools, but on how many have the knowledge and judgement to evaluate their results, challenge their assumptions, and turn them into meaningful innovation.

The foundation of Germany's technological future is built in the classroom, long before the first line of code is written.

By Oliver Otto | Bremen | 23 September 2026

Daylight Saving Time 2026: How the Winter Time Change Affects Workplace Productivity

Thomas Delfing — Sun, 18 Oct 2026 14:25:08 +0000

Discover how the October 2026 time change may affect concentration and productivity, and how TimeSpin helps analyze work patterns.

How the October Time Change Can Influence Productivity

On October 25, 2026, clocks in Germany will move back one hour, marking the transition from daylight saving time to winter time. Although employees technically gain an extra hour, the body's internal clock still needs time to adjust to changing sleep patterns, daylight, and daily routines.

But does gaining an hour automatically make us more productive? Not necessarily.

The time change offers businesses and employees an opportunity to examine how their working habits, concentration, and daily routines influence productivity. The key question is not simply how many hours we work, but how effectively we use those hours.

Why Working Hours Don't Tell the Whole Story

Two employees may work eight hours and achieve very different results. One might spend the day in focused work sessions, with a few meetings and phone calls. Another might constantly switch between emails, administrative tasks, meetings, and interruptions.

Their recorded working hours may be identical, but their working patterns are not.

Research into circadian rhythms suggests that changes to our internal body clock can influence alertness, attention, and reaction times. Although the autumn time change is generally considered less disruptive than the spring transition, its effects can still vary from person to person.

Some employees may find it easier to concentrate in the morning, while others may experience changes in energy levels or focus throughout the day.

Rather than relying on subjective impressions, businesses can use activity-based time tracking to understand whether the time change affects their actual work patterns.

Measure Productivity Before and After the Time Change

The weeks surrounding the October 25 transition provide a practical opportunity to compare working habits.

For example, employees can compare the working week of October 19–23 with the week of October 26–30, 2026.

Instead of asking, "How long did I work?", a more revealing question is:

"What did I spend my working time doing?"

With TimeSpin, users can track different activities and analyze how their working time is distributed. The TimeSpin dodecahedron allows users to assign individual sides to activities such as:

Focused project work
Meetings and internal communication
Customer communication and sales
Administration and organization
Training and professional development

When switching tasks, users simply turn the device to the corresponding side. Time entries synchronize automatically, providing data that can be reviewed later.

This approach helps reveal patterns that conventional timesheets may overlook. For instance, employees might discover that focused work begins later in the morning after the time change, administrative tasks take up more time, or longer concentration periods become easier to maintain.

The results will differ between individuals. The objective is to identify actual patterns rather than assume that the time change affects everyone in the same way.

Why Activity-Based Time Tracking Matters

For knowledge-intensive professions, the structure of the working day can significantly influence the ability to complete complex tasks.

In law firms and patent practices, uninterrupted time can be essential for drafting legal documents or preparing patent applications. Software developers need sustained concentration to solve complex technical problems. Agencies and consulting firms also rely on focused work to deliver creative solutions and manage client projects.

Frequent task switching can interrupt these concentration periods, making it harder to maintain momentum.

By using TimeSpin, employees can examine how much time they spend on individual activities, how frequently they switch tasks, and when longer periods of focused work occur.

The physical design of the TimeSpin tracker also helps reduce the effort required to record activities. Instead of repeatedly opening software, selecting a project, and starting a timer, users simply turn the device when their activity changes.

Recorded time can support personal productivity analysis, project billing, and business reporting. Through its REST API, TimeSpin can also integrate with existing software environments, including project management and ERP systems, as well as compatible solutions such as DATEV and Sage.

Productivity Analysis Should Create Insights, Not Surveillance

Activity-based time tracking should not be treated primarily as a tool for monitoring employees. Its greater value lies in understanding the conditions that support effective work.

Useful questions include:

When do employees typically begin their most focused work?
Which activities cause the most interruptions?
How frequently do employees switch between tasks?
Are important tasks regularly postponed?
How do flexible working hours and daily routines influence concentration?

These insights can help individuals organize their schedules more effectively and enable businesses to improve workflows, especially in hybrid and project-based working environments.

As modern work becomes less dependent on fixed schedules and physical office attendance, recorded presence alone provides an increasingly incomplete picture of productivity.

Frequently Asked Questions

Does the autumn time change affect productivity?

It can. Changes in sleep patterns, daylight, and circadian rhythms may temporarily influence alertness and concentration. Individual experiences vary.

When does Germany switch to winter time in 2026?

Germany switches to winter time on October 25, 2026. At 3:00 a.m., clocks move back to 2:00 a.m.

How can I measure the impact of the time change on my work?

Compare activity-tracking data from the weeks before and after the transition. Look at focused work periods, task switching, administrative work, and the distribution of activities throughout the day.

How does TimeSpin help measure productivity?

TimeSpin enables users to record time by activity using a physical tracking device. The resulting data helps identify work patterns beyond total hours worked.

One Hour Can Change How We Understand Work

The debate over abolishing the twice-yearly clock change in the European Union continues, but the October 2026 transition provides a practical opportunity to reflect on everyday working habits.

By comparing activity data before and after the time change, employees can identify shifts in concentration, task distribution, and working routines.

Ultimately, productivity is not determined simply by the number of hours spent at work. It depends on what we accomplish during those hours, how effectively we concentrate, and how we manage transitions between tasks.

The winter time change moves the clock by just one hour. With the right insights from TimeSpin, that small shift can become an opportunity to better understand how we work—and how we can work more effectively.

Time Tracking for School Leaders: How Transparency Improves Workload Management

Thomas Delfing — Sun, 18 Oct 2026 14:05:39 +0000

Why School Leaders Need Greater Transparency in Their Workload

School leaders face a wide range of responsibilities, from organizing substitute teachers and supporting staff to communicating with parents and managing administrative tasks. Much of this work happens behind the scenes, making it difficult to demonstrate how limited working hours are being used.

Activity-based time tracking can help school leaders understand their workload, identify organizational bottlenecks, and make more informed decisions about priorities and resources. TimeSpin offers a practical approach to documenting these activities and making otherwise invisible work more transparent.

The Legal Context: Understanding Excessive Workloads

On September 17, 2026, Germany’s Federal Administrative Court (Bundesverwaltungsgericht) rejected a former primary school principal’s claim for financial compensation for additional working hours (Case No. 2 C 19.25).

According to the court’s press release, the additional hours resulted from the principal’s own decisions rather than a corresponding instruction from the employer. The court indicated that when the allocated time for non-teaching duties is insufficient, school leaders should report the excessive workload and, where necessary, postpone certain tasks.

Importantly, the court left open the question of whether European Union law requires working-time recording. The ruling does not establish that teachers can never receive compensation for additional work.

The case highlights the importance of documenting workload and communicating capacity constraints. However, as reported by News4teachers, documentation alone may not be enough if it does not lead to meaningful relief.

For school leaders, the key question is therefore not simply how many hours they work, but which activities consume their time and what changes could improve the way their schools operate.

Sources: Federal Administrative Court press release | News4teachers report

Why Total Working Hours Do Not Tell the Whole Story

A weekly total provides an overview of working time, but it does not explain why that time is needed. Two school principals may work the same number of hours while facing very different challenges.

At one school, staff shortages and substitute-teacher scheduling may dominate the workload. At another, parent communication, staff development, or new administrative procedures may require considerable attention.

Connecting tasks, activities, and time provides a more meaningful picture. It helps school leaders investigate whether responsibilities are clearly assigned, information is available when needed, and administrative processes are organized efficiently.

Time tracking does not automatically explain the cause of a heavy workload. It provides evidence that can support further investigation and better decisions.

How TimeSpin Supports Activity-Based Time Tracking

TimeSpin provides a practical way to record time spent on different activities. Its physical time-tracking cube allows users to assign activities to its twelve sides and select a category by turning the cube. Digital tracking options are also available.

For school leadership, relevant categories could include:

Staff management and personnel matters
Lesson planning and substitute-teacher coordination
Parent communication
Administrative duties
School development and strategic planning

Over time, these records can reveal how leadership time is distributed across different responsibilities.

The greatest benefit comes from consistent tracking. School leaders should record activity changes reliably, correct entries when necessary, and review data across representative periods rather than drawing conclusions from a single unusually busy week.

Turning Time Tracking Data into Practical Improvements

Regular analysis can help school leaders identify recurring interruptions, tasks that take longer than expected, and important projects that continually lose priority.

Consider a principal who discovers that coordinating substitute teachers consumes a significant portion of their working week. The data alone cannot establish whether the problem stems from staff shortages, unclear responsibilities, or missing information.

By reviewing the process with colleagues, the principal may discover that the same information is repeatedly requested from different people. Introducing a standardized reporting procedure could reduce unnecessary coordination. Subsequent tracking would then help determine whether the change reduces administrative effort without compromising the reliability of lesson coverage.

This illustrates the real purpose of time tracking: using documented activities to test improvements, rather than simply collecting more data.

Making Workloads More Transparent to Education Authorities

Activity-based time records can also support conversations with school supervisors and education authorities. A summarized activity profile can make the practical responsibilities of school leadership more visible and show how much capacity specific duties require.

When requesting additional support or discussing excessive workloads, school leaders can use this information to explain which responsibilities have increased and which other tasks are being displaced as a result.

However, TimeSpin does not guarantee legal recognition of overtime, compensation, or the effectiveness of a formal workload notification. The value of the data depends on its quality, its context, and how decision-makers use it.

It is equally important to distinguish time spent from work quality. A longer meeting does not necessarily produce a better outcome, just as a shorter conversation does not automatically indicate greater efficiency. Meaningful evaluation must consider the task, the circumstances, and the results.

Implementing Time Tracking Responsibly

To obtain useful results, schools should establish clear categories, maintain consistent recording practices, and review data across different phases of the school year, including particularly demanding periods.

They should also agree on the purpose of tracking, who can access the records, and how the results will be evaluated. For organizational analysis, broad categories such as parent communication are generally sufficient; children’s names and confidential conversation details should not be included in activity summaries.

Most importantly, every tracking period should lead to a defined next step. School leaders and relevant stakeholders should review the findings, agree on a practical improvement, and establish when its impact will be assessed.

There is currently no empirical evidence presented here demonstrating that TimeSpin directly improves efficiency in schools. Its potential value lies in providing a structured basis for examining workloads and testing organizational improvements in practice.

Conclusion: Better Workload Management Starts with Transparency

Effective school leadership requires a clear understanding of how limited time is allocated across competing responsibilities. Activity-based time tracking helps make hidden work visible, supports more structured workload discussions, and provides a basis for improving administrative processes.

With consistent documentation and meaningful follow-up, TimeSpin can support school leaders in reviewing their working practices, communicating resource needs, and making informed decisions about priorities.

Ultimately, transparency creates value when it leads to action: more reliable processes, sufficient time for essential responsibilities, and tangible improvements in the conditions required for effective school leadership.

Rethinking Work Ethics: Productivity Is About What We Do, Not How Long We Work

Thomas Delfing — Thu, 15 Oct 2026 03:47:31 +0000

Are longer working hours a sign of greater productivity? As AI transforms the workplace, businesses need to focus less on time spent and more on how working hours are used, which activities create value, and where processes can be improved.

An American living in Germany once described the cultural difference in a simple way: in the United States, people live to work, while in Germany, people work to live well. This observation highlights a fundamental question for modern business management: Should employee performance be measured by hours worked or by the activities and results those hours produce?

David Valdes, who moved from San Francisco to Munich and works at Google, described these contrasting attitudes toward work in an interview with Süddeutsche Zeitung. While work often plays a central role in professional identity and social status in the United States, employees in Germany tend to place greater emphasis on integrating work into a balanced life.

Working-hour statistics may appear to support this distinction. According to the OECD figures cited in the original article, annual working hours averaged 1,332 per employed person in Germany and 1,800 in the United States in 2025. However, longer working hours do not automatically indicate greater productivity, just as shorter hours do not necessarily mean lower performance.

An hour is simply a unit of time. It tells us how long someone worked, not what they accomplished.

Why Tracking Activities Matters More Than Tracking Hours

Businesses have long recorded attendance, working hours, breaks, holidays, and overtime. Yet many still struggle to understand how employees actually spend their time.

How much time goes into client projects, administration, meetings, research, development, or support? Which activities create value, and which consume resources without delivering proportional benefits? Where could automation eliminate repetitive tasks, and which projects consistently exceed their budgets?

Without answers to these questions, companies may know their employees' working hours without truly understanding their work.

Consider a developer who automates a process that previously required ten hours every week, completing the automation in just five hours. This is not a sign of reduced effort. It is a measurable productivity improvement.

The same principle applies to consultants who solve problems faster through experience, professional firms that streamline administration, and teams using artificial intelligence (AI) to accelerate research and documentation.

True productivity comes from creating greater value with the time available—not from consuming more hours.

How AI Is Changing Employee Productivity Measurement

Artificial intelligence makes this distinction increasingly important. Tasks such as drafting content, summarizing documents, analyzing data, generating code, and researching information can now be completed significantly faster.

However, businesses that measure performance primarily by hours worked risk penalizing their most efficient employees. If someone completes a task in two hours with AI instead of four hours without it, traditional time-based metrics may make that employee appear less busy, even though productivity has improved.

The time saved could instead be invested in customer service, innovation, quality improvements, professional development, or additional projects.

To realize these benefits, companies need visibility into which activities consume time, where efficiency gains occur, and how saved capacity can be used effectively.

From Time Tracking to Activity Tracking

Modern time tracking should go beyond recording how many hours employees work. It should help businesses understand which activities fill those hours, which are necessary, which create value, and which could be simplified or automated.

This is where activity tracking becomes a practical management tool.

With timespin, employees can track their activities using a physical dodecahedron-shaped timer. Each side can represent a specific project, client, or task. When employees switch activities, they simply turn the cube to the corresponding side, allowing them to record their work without repeatedly opening software windows or entering times manually.

The recorded data is automatically synchronized and can be used for reporting, project billing, and controlling project costs.

This straightforward approach makes activity changes easier to capture as they happen, providing businesses with a clearer picture of how working time is distributed.

Activity Tracking Should Improve Processes, Not Monitor Employees

Detailed activity tracking must not become a tool for judging every minute of an employee's day. Its real value lies in identifying patterns and opportunities for organizational improvement.

If a developer spends too much time on administration, the problem may be inefficient internal processes rather than individual performance. If a project repeatedly exceeds its estimated development hours, the cause could be inaccurate budgeting, incomplete specifications, or underestimated coordination requirements.

Similarly, if consultants spend excessive time documenting their work, automating documentation may be more effective than simply asking them to work faster.

Activity data should be treated primarily as process data. Used responsibly, it helps employees and managers identify bottlenecks, improve workflows, and make better-informed decisions.

Why Project-Based Businesses Need Greater Transparency

Activity tracking is particularly valuable for agencies, law firms, software companies, consultancies, engineering firms, and technical service providers, where employee capacity is a significant business resource.

If a project budgeted for 200 hours ultimately requires 320 hours, the additional effort creates a financial challenge regardless of how hard the team worked. In fixed-price projects, every additional hour can reduce profit margins rather than generate additional revenue.

Accurate activity data supports project cost analysis, budget-versus-actual comparisons, and more reliable future estimates. Through integrations such as REST APIs and data exports, these records can also be transferred to existing ERP systems, accounting platforms, and industry-specific software.

The result is a stronger foundation for project management, cost control, and operational planning.

The Future of Work Is About Value, Not Hours

As businesses navigate AI adoption, skills shortages, remote work, and changing expectations around working hours, focusing exclusively on whether employees work 35, 40, or 45 hours a week is no longer sufficient.

Companies first need to understand what happens during those hours.

The most productive organizations will not necessarily be those that encourage employees to work longer. They will be those that understand where resources are being used, which activities create value, and where better processes or technology can eliminate unnecessary effort.

Ultimately, work ethic should not be measured by how long someone sits at a desk. It should be reflected in how responsibly and effectively people use their time.

The question businesses should ask is no longer simply, How long did we work?

It is: What did we work on, what did we achieve, and was the time invested worth it?

In an economy increasingly shaped by artificial intelligence and productivity pressures, answering that question will be far more valuable than measuring who arrives at the office first or leaves last.

Beyond Time Tracking: Why Activity Transparency Matters for Workplace Productivity

Thomas Delfing — Tue, 13 Oct 2026 15:14:22 +0000

Time Tracking Shows When We Work—Not What We Do

Working hours are relatively easy to measure. An employee starts at 8 a.m., takes a break, and finishes at 5 p.m. The time record shows eight hours. But an important question remains: What actually happened during those eight hours?

A pilot project in Bremen, Germany, brings this question into focus. During the 2026–2027 school year, teachers at nine schools are recording not only their working hours but also the activities that fill them. These include lesson preparation, grading, supervising breaks, advising parents, attending conferences, organizing class trips, and resolving conflicts—all essential tasks that can remain invisible when workload is measured mainly by teaching hours.

The lesson extends far beyond education: Is time tracking enough to understand how work gets done today? In many workplaces, it is not.

Time Tracking vs. Activity Tracking

In industrial settings, time was once a useful indicator of work. Today’s knowledge work is more complex. A software developer may spend a day coding, investigating bugs, attending meetings, documenting systems, helping colleagues, and responding to messages. A patent attorney may review files, advise clients, check deadlines, draft legal documents, and handle administrative communication.

Both employees might record eight hours, yet their days—and the implications for planning and productivity—could be very different.

Time tracking records when work starts and ends and how long it lasts. Activity tracking adds context by showing how that time is spent. Combining the two creates a clearer picture of workloads, processes, and how work is distributed.

The Bremen Teachers’ Pilot Shows Why Context Matters

For teachers, the distinction is particularly clear. Teaching hours are only one part of the job; preparation, grading, administration, parent communication, and conflict resolution also take time.

Bremen’s education senator, Mark Rackles, has argued in connection with the pilot that the focus should move beyond scheduled teaching hours toward total working time. But total hours are only the starting point. If a teacher works 50 hours in a week, it also matters how those hours are divided among teaching, preparation, grading, administration, and communication.

One teacher involved in the pilot reportedly found that the workload reached around 50 hours a week at the start of the school year. Recording activities also encouraged a more deliberate approach to organizing the working day. This illustrates an important effect of activity transparency: measurement can change awareness. Patterns that were previously only a vague impression become visible.

Transparency Should Improve Work—not Become Surveillance

Detailed activity tracking can raise concerns about employee surveillance. That is why the purpose of collecting data must be clear from the start.

Activity records should not become a tool for continuously ranking individuals or comparing how many minutes different employees need for the same task. That approach can undermine trust rather than improve work.

The real value lies in understanding how work is distributed, which processes consume disproportionate time, how often interruptions occur, and which tasks take up more of the day than expected. The useful question is not, “What did this employee do for eight hours?” but “Which activities shape our working day, and does that distribution support our goals?”

Activity Transparency Helps Explain Overload

Knowing that someone regularly works ten hours a day signals a problem, but it does not explain its cause. The workload may come from too many operational tasks, excessive meetings, growing documentation requirements, administrative work, or repetitive manual processes.

Without insight into activities, conversations about overload remain abstract. With it, organizations can identify where pressure originates and decide whether to add staff, redistribute tasks, redesign workflows, automate repetitive steps, or stop doing work that no longer adds value.

Why Activity Data Matters for AI and Automation

As organizations invest in artificial intelligence, activity transparency becomes even more important. Businesses want to know whether AI tools are improving productivity—but that is difficult to assess without understanding how employees spend their time.

Imagine that an AI tool reduces the time needed to produce a document from two hours to 30 minutes. That appears to save 90 minutes. But are those minutes genuinely freed up, redirected to higher-value work, or absorbed by other tasks? Time records alone cannot answer that question. Activity data can help organizations evaluate where the time goes and whether the expected productivity gains materialize.

From Compliance to Better Organizational Decisions

Working-time recording has also gained legal importance in Germany. In 2022, the Federal Labour Court (Bundesarbeitsgericht) held that employers are generally required to establish a system for recording the beginning and end of daily working time. Organizations should not treat time recording solely as a compliance exercise, however.

Existing records can become more useful when time is also categorized by activity. This does not necessarily require minute-by-minute project accounting. Even broad categories can reveal patterns—for example, how much time a manager spends on strategy, people leadership, customer contact, administration, and operational problem-solving.

Developers might distinguish between development, debugging, meetings, support, and documentation. Law firms could track client work, communication, deadline management, research, and internal administration.

Tools such as TimeSpin follow this principle: the goal is not simply to count hours, but to understand the activities to which those hours are allocated. Instead of seeing only a 45-hour workweek, an organization can build a clearer picture of what that week actually involved.

The Key Metric Is How Time Is Used

Debates about whether a 35-, 38-, or 40-hour workweek is ideal are legitimate, but hours alone tell only part of the story. Two people can each work 40 hours and experience very different workloads. Two companies can invest the same number of working hours and achieve very different results.

Organizations need to understand how much time goes to core work, coordination, administration, tasks created by inefficient processes, and activities that could be automated or organized differently. That insight supports better decisions than knowing only that employees worked an average of 8.2 hours a day.

Conclusion: Move from Time Tracking to Activity Transparency

The Bremen teachers’ pilot may offer lessons that reach well beyond education. Organizations need to look at working time as more than a number. They understand work more fully when they can see which activities fill that time.

Time tracking answers: How long did we work?

Activity transparency answers: What did we work on—and was that the best use of our time?

Sending XML E-Invoices and Readable Invoice Copies Together: Legal Requirements and Best Practices

Thomas Delfing — Sun, 11 Oct 2026 07:22:03 +0000

An XML e-invoice may be sent together with a readable representation of the same invoice. For an additional PDF, the German tax authorities explicitly confirm that this is permitted. An accompanying Word document is also generally possible, although it does not independently meet the requirements for an e-invoice.

The decisive factor is that both files represent the same invoice and contain no contradictory information relevant to tax law. The number of files alone does not create an additional VAT liability. [1, 2, 3]

For businesses and professional practices, this distinction has immediate practical implications. Accounting departments require structured data, while invoice approval is often carried out using an easily readable document. Both workflows can be combined, provided that invoice creation, transmission, and archiving rely on a single, consistent set of invoice data.

What Qualifies as an E-Invoice Under German Law?

Section 14(1) of the German VAT Act (Umsatzsteuergesetz, UStG) requires an e-invoice to use a structured electronic format that enables electronic processing. An ordinary PDF or Word document, by contrast, falls into the category of other invoices.

The XML file extension alone is not sufficient. The data record must satisfy the statutory requirements for the applicable format. [1]

XRechnung and suitable ZUGFeRD formats are widely used implementations. ZUGFeRD combines the readable invoice representation and the structured data record in a single file.

By contrast, sending two separate attachments — for example, an XRechnung file and an ordinary PDF — does not turn them into a hybrid ZUGFeRD invoice. This distinction should be considered when selecting the invoice transmission method. [4]

Why Sending an Additional PDF Is Permitted

The German Federal Ministry of Finance (Bundesministerium der Finanzen, BMF), in its letter dated 15 October 2024, states in paragraph 6 that an additional human-readable document may optionally be transmitted. The guidance expressly mentions both hybrid formats and an additional PDF. The tax authorities therefore do not require an XML file to be transmitted exclusively. [2]

The second file must be understood as an alternative representation of the same invoice. The invoice number, issue date, parties involved, supply or service, consideration, and VAT details must be substantively consistent. Differences in layout, page breaks, or graphic design do not create a separate invoice.

The cited passage does not establish an explicit special rule for Word documents. The general permissibility of an additional Word representation instead follows from the treatment of multiple identical copies and the fact that German VAT law does not prescribe a specific format for an additional readable representation.

As a practical recommendation, PDF is preferable. It provides a more stable presentation and reduces the risk of unintended changes. However, a PDF is not automatically immutable either. [1, 2, 3]

Invoice Copies Versus Separate Invoices

Section 14c.1(4), sentence 6, of the German VAT Application Decree (Umsatzsteuer-Anwendungserlass, UStAE) excludes substantively identical multiple copies of the same invoice from the consequences associated with issuing multiple invoices. Explicitly marking a document as a copy is not a prerequisite for this exception.

The BMF letter dated 15 October 2025 adds in sentence 7 that repeatedly transmitting an e-invoice file is also harmless where the file is merely sent more than once as a substantively identical copy of the same invoice. [3, 5]

The situation may be different when several separate invoices are issued for the same supply or service. In such cases, any additional tax liability under Section 14c of the German VAT Act must be examined.

Neither the number of attachments nor the word “invoice” in a filename determines the outcome. The decisive factor is the actual content of the billing documents. [3, 6]

A note such as “Readable representation of the attached e-invoice. No additional payment request” is therefore a useful administrative measure. It helps the recipient associate both files with a single transaction. However, such a note does not compensate for inconsistencies between their contents.

Discrepancies Between XML Data and the Invoice Image

For hybrid invoices, Section 14c.1(4a) of the UStAE expressly provides that a visual representation containing different invoice details relevant to tax law may constitute an additional invoice in another format. In that case, the requirements of Section 14c of the German VAT Act must be examined.

Minor technical discrepancies or supplementary information are not challenged under the conditions specified in that provision, provided that the document retains its character as an identical copy. This rule directly concerns hybrid formats. Separate XML and PDF files are subject to the general rules governing multiple copies. [5]

In practice, both representations should be generated from the same approved data set. For example, if the invoice amount is changed in Word after the XML file has been generated, both files must be reconciled again before transmission.

Labeling a document as a copy does not make an inconsistent representation legally harmless.

Mandatory Invoice Information and Supplementary Service Records

As a general rule, all mandatory information required under VAT law must be included in the structured part of the e-invoice. A missing description of the supply or service cannot be remedied merely by including that information in the accompanying PDF.

The structured data must identify the invoiced supply or service clearly and in a manner that allows it to be readily verified. Additional details, such as comprehensive time sheets, may be included in an attachment incorporated into the e-invoice. Specific rules for particular situations must also be observed, such as the deduction of advance payments already received in final invoices. [4, 5]

For example, a patent law firm could identify the patent application concerned, the specific work performed, and the service period in the structured service description. An attachment could then explain the individual work steps in greater detail.

This example is a recommendation for invoice design. Whether the description is sufficient in a particular case depends on the actual supply or service being invoiced.

Technical validation helps identify format errors and business-rule violations. According to the BMF FAQ, however, validation is not itself a direct prerequisite for tax recognition, nor does it replace a substantive review of the invoice. [4]

Invoice Transmission and Archiving in Daily Law Firm Operations

The tax-law permissibility of an additional PDF does not resolve every question concerning the transmission method. A recipient portal may impose technical restrictions on the number and type of attachments.

Invoices issued to public-sector contracting authorities are also subject to the applicable rules governing electronic invoicing in public procurement. If a submission is rejected for technical reasons, it should therefore be re transmitted through an appropriate channel. [4]

As an organizational recommendation, law firms should store both representations under the same invoice number, record the invoice only once in their accounts, and approve it for payment only once. Proof of transmission, the approved invoice version, and any subsequent corrections should be associated with the same transaction.

A subsequent change to the visual representation alone does not create a consistent set of invoice records.

Section 14b of the German VAT Act generally provides for an eight-year retention period, calculated from the end of the year in which the invoice was issued. Any additional retention obligations must also be observed.

For e-invoices, at least the structured component must be preserved intact in its original form. A printout or ordinary PDF does not replace the XML file. If attachments contain other information subject to retention requirements, that information must also be preserved. [7, 4]

Law firm management software should therefore manage the structured invoice and its readable representation as related documents. Generating both files from a central data set, maintaining a traceable approval process, and linking the documents permanently to the corresponding accounting entry help prevent errors caused by separate processing.

Sending both representations together is therefore a permissible and practical process, provided that both consistently represent the same invoice.

Creating Individual and Consolidated Invoices with Genese

With Genese, e-invoices can be created easily as individual invoices or consolidated invoices. This allows a law firm to process a single billing transaction or combine multiple services for the same invoice recipient into one invoice.

The appropriate option depends on the agreed billing arrangement and the client’s requirements. E-invoicing thus becomes an integrated part of the firm’s day-to-day workflow.

An individual invoice may be suitable for a specific completed task in an intellectual property matter. A consolidated invoice can group several billable services for the same client, such as work performed during a billing period across multiple intellectual property rights.

Even in a consolidated invoice, the services, relevant service dates or periods, consideration, and VAT details must remain clearly identifiable and verifiable. Different invoice recipients do not become a single invoice recipient merely because they belong to the same corporate group. [1]

A consolidated invoice must be distinguished from the collective transmission of invoices.

When several separate invoices are transmitted together, each retains its own invoice number and remains a separate billing transaction. A consolidated invoice, by contrast, combines several services into one invoice.

This distinction is important for accounting and payment allocation. A PDF that summarizes several individual invoices does not turn the associated XML files into a single structured consolidated invoice.

Genese supports the delivery of generated e-invoices through customer portals, Gweb, or email. The appropriate method depends on the agreed process and the technical requirements of the invoice recipient.

The actual e-invoice file must be transmitted or made available for retrieval. Merely displaying a visual invoice representation in a portal is not sufficient for this purpose. An identical readable representation may be provided in addition.

XRechnung and the Leitweg-ID for Public-Sector Invoices

For XRechnung invoices addressed to public-sector contracting authorities, the Leitweg-ID supplied by the recipient enables unique addressing and routing within the designated invoice-receipt platform. It is included in the structured invoice data as the buyer reference.

The Leitweg-ID is not itself a transmission channel and does not initiate the sending process. The invoice must also be transmitted through an approved route, such as uploading it to a designated portal or sending it to the appropriate platform email address.

Making an invoice available through Gweb does not automatically replace a mandatory public-sector submission channel. [8]

For ordinary business-to-business invoicing, a Leitweg-ID is not required, even when the XRechnung format is used.

Genese’s supported creation and delivery of individual and consolidated invoices can therefore accommodate the different receipt processes used by clients. As an organizational recommendation, the matter-file reference, selected transmission method, and exact version sent should remain traceable within each invoice transaction. [4]

Legal Disclaimer

The statements concerning administrative practice are based on the German VAT Application Decree and the relevant BMF letters. These documents are administrative guidance rather than independent legislation; they do not bind the courts in the same way as statutory provisions.

This article addresses general VAT requirements and does not replace an assessment of specific circumstances.

The statutory and administrative sources cited in this article have been reviewed for the purposes of its preparation.

Sources and Legal References

[1] German VAT Act (Umsatzsteuergesetz), Section 14 — Invoicing, particularly paragraphs 1, 3 and 4

https://www.gesetze-im-internet.de/ustg_1980/__14.html

[2] BMF letter dated 15 October 2024, reference III C 2 — S 7287-a/23/10001:007, particularly paragraph 6. Official text reproduced by NWB.

https://datenbank.nwb.de/Dokument/1046425/

[3] German VAT Application Decree (UStAE), Section 14c.1(4), sentences 5 and 6. Official 2024 German VAT Handbook; see source [5] for the 2025 amendment.

https://usth.bundesfinanzministerium.de/usth/2024/A-Umsatzsteuergesetz/IV-Steuer-und-Vorsteuer/Paragraf-14c/ae-14c-1.html

[4] BMF FAQ on mandatory e-invoicing, as of March 2026, particularly questions 4a, 7, 7a, 7b, 8 and 13.

https://www.bundesfinanzministerium.de/Content/DE/FAQ/e-rechnung.html

[5] BMF letter dated 15 October 2025, reference III C 2 — S 7287-a/00019/007/243, particularly the amendments to Section 14c.1(4), sentence 7, and paragraph 4a. Official text reproduced by NWB.

https://datenbank.nwb.de/Dokument/1072024/

[6] German VAT Act, Section 14c — Unlawful or incorrect VAT disclosure

https://www.gesetze-im-internet.de/ustg_1980/__14c.html

[7] German VAT Act, Section 14b — Retention of invoices

https://www.gesetze-im-internet.de/ustg_1980/__14b.html

[8] Procurement Office of the Federal Ministry of the Interior (BMI), information for federal administration invoice issuers, particularly the Leitweg-ID and transmission via OZG-RE.

https://e-rechnung-bund.de/rechnungssteller/

German Working Time Act Reform: Flexibility vs. Employee Protection

Thomas Delfing — Fri, 09 Oct 2026 07:40:31 +0000

Debate over reform of Germany’s Working Time Act (Arbeitszeitgesetz, ArbZG) gathered momentum in early 2026. Saxony’s Minister-President Michael Kretschmer argued that existing rules belong to “another era” and should better reflect a digital, global workplace. The central question is whether Germany should retain its daily working-time limits or place greater emphasis on weekly hours.

What Germany’s Working Time Act Currently Requires

The current framework generally limits the working day to eight hours, with an extension to ten hours possible when the statutory average is maintained over the applicable reference period. It also provides for at least 11 consecutive hours of rest in most cases and sets specific restrictions on Sunday and public-holiday work. Critics say this daily structure does not always match project-based work, knowledge work, mobile working and international collaboration.

The Case for More Flexible Working Hours

Supporters of reform argue that fixed daily limits can be difficult to reconcile with work that fluctuates by project, workload or time zone. A stronger focus on weekly hours could let employees work longer on busy days and finish earlier on quieter ones. Businesses could respond more easily to demand peaks, while internationally distributed teams could coordinate across time zones with fewer scheduling constraints. For some employees, that flexibility could also help accommodate family commitments or personal productivity patterns.
Competitiveness is another part of the argument. Kretschmer has warned that rigid rules could discourage investment or encourage companies to move projects to countries with more flexible working-time arrangements. Reform advocates therefore see weekly or annual working-time models as one way to modernise Germany’s approach.

The Risks: Health, Fairness and Family Life

Trade unions, social organisations and occupational-health experts caution that longer working days carry real risks. Fatigue, reduced concentration, cardiovascular strain and psychological stress can rise as the day extends. Keeping the same weekly total does not necessarily offset the impact of repeatedly working very long days.
There is also a power imbalance to consider. Flexibility may be presented as a mutual benefit, but employees could feel pressured to stay longer to meet expectations or protect career prospects. In highly competitive workplaces, this can become an informal expectation to overwork. Variable schedules can also make childcare, caring responsibilities and family planning harder, reducing predictability rather than increasing employees’ control over their time.

How Digital Time Tracking Can Help

Whatever form future legislation takes, accurate and transparent working-time records will remain important. Digital tools can make work patterns easier to understand and help connect flexibility with safeguards.

TimeSpin is one example: it helps document activities over the course of a day or week and presents the distribution of work in a clear weekly overview. Employees and managers can see how time is allocated, identify workload peaks and quieter periods, and discuss actual patterns rather than relying on assumptions. In flexible weekly-hour models, this visibility can help teams recognize potential overload and plan compensatory time off. Time tracking supports better decisions, though it does not replace legal limits or health protections.

A Balanced Path to Reform

The debate is not simply a choice between flexibility and protection. A sustainable reform could give organizations and employees more room to arrange work while preserving clear rest periods, documentation requirements and safeguards against excessive workloads. Digital transparency can support that balance by showing how work is actually distributed across the week.

What Happens When beA Fails? BGH Clarifies Lawyers’ Duties and Emergency Filing Rules

Thomas Delfing — Tue, 06 Oct 2026 06:12:55 +0000

The German Federal Court of Justice (BGH) has clarified an important issue for modern law firms: when the mandatory electronic legal communication system fails shortly before a deadline, lawyers are not automatically required to revive technical methods they no longer routinely use.

In its decision of July 30, 2026 (I ZB 85/25), the BGH addressed the consequences of a temporary failure of the special electronic lawyers’ mailbox (beA). While the Court maintained strict requirements for substitute filings, it also placed limits on how far a lawyer’s duty of care can extend in an emergency.

The decision is particularly relevant for firms that have moved their workflows almost entirely to electronic communication.

The Case: A beA Failure on the Final Day

The underlying case concerned a deadline for filing grounds of appeal, which had been extended until May 14, 2025.

On the evening of the deadline, the responsible lawyer and two colleagues repeatedly attempted to submit the appeal grounds through beA to the Higher Regional Court of Munich. According to their account, the attempts failed because of technical problems.

At around 11 p.m., the lawyer looked for an alternative. Working from home and apparently without access to a conventional fax machine, he attempted to send the document through several internet-based fax services. He had never used these services before.

The document eventually reached the court by fax before midnight. It was also submitted through beA the following morning, once the system was functioning again.

That, however, did not resolve the legal problem.

The Computer Fax Was Not Formally Valid

Under Section 130d of the German Code of Civil Procedure (ZPO), lawyers must generally submit pleadings and other procedural documents electronically. An alternative filing is permitted when electronic submission is temporarily impossible for technical reasons.

A fax can, in principle, qualify as such a substitute. But the substitute method must still satisfy its own formal requirements.

The BGH found that the computer fax in this case did not meet those requirements. Unlike a conventional fax, a computer fax generally does not involve a physical original bearing an original handwritten signature. Depending on the circumstances, formal requirements may instead be met through an appropriate scanned signature or a statement indicating why a handwritten signature cannot be provided.

That was missing here.

The document contained references such as “via ERV” and “electronically signed,” which were consistent with an intended electronic filing through beA, but did not adequately establish compliance with the requirements applicable to the computer fax.

The BGH therefore maintained that the fax itself did not effectively preserve the deadline.

A Technical Failure Must Also Be Properly Documented

The Court highlighted a second issue with major practical consequences.

Under Section 130d sentence 3 ZPO, a lawyer relying on a temporary technical impossibility must substantiate that failure when making the substitute filing or immediately afterward.

A general statement that beA was experiencing problems is not necessarily enough.

In this case, the lawyers referred the following day to the previous day’s “beA outage in Bavaria” and submitted a screenshot showing a system disruption. The BGH considered that insufficient.

The Court emphasized that the circumstances must be presented in a coherent and understandable way. The record should make it possible to determine that a technical problem actually prevented the specific filing—not, for example, an operating error or a problem on the sender’s side.

For law firms, the practical lesson is straightforward: technical failures should be documented immediately.

Relevant evidence can include the time of each transmission attempt, error messages, screenshots, official outage notifications and the names of the employees involved. The closer the documentation is created to the actual incident, the easier it becomes to demonstrate what happened.

The Key Question: Must Every Lawyer Still Be Able to Fax?

This is where the decision becomes particularly significant.

Although the computer fax was invalid and the initial evidence of the beA outage was insufficient, the BGH overturned the decision of the lower court and sent the matter back for further examination.

The central issue was reasonable diligence.

For reinstatement of a missed deadline under Section 233 ZPO, the deadline must have been missed through no fault of the party. The lawyer’s fault is generally attributed to the client under Section 85(2) ZPO.

However, the BGH stressed that professional duties must remain reasonable under the circumstances.

That matters in a legal profession whose technical infrastructure has fundamentally changed.

Before mandatory active use of beA, the situation was largely the opposite. Fax was an established part of legal practice, and courts did not necessarily expect a lawyer to master an entirely new electronic system in the middle of a deadline emergency.

The BGH now applies the same logic to today’s digital environment.

A firm that has fully transitioned to beA, no longer maintains an operational fax machine and whose lawyer has no practical experience with computer faxing may not be expected to learn and deploy an unfamiliar system within minutes of a critical deadline.

An Unsuccessful Rescue Attempt Should Not Automatically Count Against the Lawyer

Another important aspect of the ruling is the Court’s treatment of voluntary emergency measures.

Suppose a lawyer was not actually required to switch to fax because doing so was unreasonable under the circumstances. If the lawyer nevertheless tries to use fax as an additional rescue measure, the failure of that voluntary attempt should not automatically create the fault that prevents reinstatement.

The BGH therefore distinguishes between two questions:

Was the lawyer required to use the substitute method?

and

Did the substitute method itself comply with the formal rules?

A failed attempt does not necessarily answer the first question.

In other words, the BGH did not validate the defective fax. Instead, it indicated that an error committed during a potentially unnecessary emergency measure should not automatically defeat reinstatement.

This Is Not a Free Pass for Law Firms

The ruling should not be interpreted as saying that lawyers can simply stop preparing for technical failures.

The BGH did not establish a universal rule that faxing is unreasonable whenever beA fails. The answer depends on the actual circumstances of the individual firm.

If a functioning fax machine is still available and the lawyer is familiar with it, using that fax may well be reasonable. The same can apply to other alternative communication methods that are genuinely available and familiar to the firm.

The lower court must therefore determine whether using fax was actually unreasonable in this particular case. The BGH has not yet granted reinstatement itself.

What Law Firms Should Take From the Decision

The most useful lesson is organizational rather than technological.

Every firm should have a clear procedure for handling a beA outage. That procedure should identify who records technical problems, which alternative filing methods are actually available, who knows how to use them, and how evidence of the outage will be preserved.

These details can later become decisive in a reinstatement application.

A digitally focused firm also does not necessarily need to keep every legacy technology permanently operational simply because it might theoretically become useful during an emergency. The BGH’s reasoning recognizes that modern electronic systems can genuinely replace older working methods.

The decisive issue is not which technical options exist in theory, but which alternative was realistically possible and reasonable for the lawyer in the specific situation.

Conclusion

The BGH’s decision is an important clarification for the increasingly digital German legal profession.

On the one hand, the Court maintains strict standards: substitute filings must comply with formal requirements, and technical outages must be documented and substantiated promptly.

On the other hand, the Court recognizes that professional diligence has to reflect modern working realities. A lawyer working in a fully digital firm cannot necessarily be expected, late at night and under severe time pressure, to revive obsolete equipment or master an unfamiliar online fax service within minutes.

For law firms, the message is therefore balanced: do not assume that every legacy technology must remain immediately available, but do build a reliable process for technical emergencies and document failures carefully.

The best reinstatement application remains the one that good organization makes unnecessary.

Author: Oliver Otto, Genese.de

Prepared for: Timespin.net and Genese.de

The AI Productivity Paradox: Why Higher Productivity Does Not Mean Less Work

Thomas Delfing — Mon, 05 Oct 2026 03:38:22 +0000

Artificial intelligence (AI) promises one major benefit above all: saving time. Documents can be analyzed within minutes, software code can be generated faster, and information can be processed at a speed that was difficult to imagine only a few years ago.

So, in theory, AI should make the working day shorter. If employees can complete the same tasks more efficiently, they should need fewer hours to achieve the same results.

Yet the reality is often very different.

AI Increases Productivity — But Not Necessarily Free Time

Research and workplace experience increasingly suggest that employees whose jobs benefit most from AI do not automatically work fewer hours. In some cases, they may work longer or take on significantly more tasks.

The reason is straightforward: when technology makes a task faster, companies often use the newly available capacity to increase output rather than reduce working hours.

An employee who can complete eight hours of work in six hours does not necessarily go home two hours early. Instead, those two hours may be filled with additional analysis, customer work, meetings, projects, or administrative tasks.

The result is a fundamental AI productivity paradox: technology can make individual tasks more efficient while simultaneously increasing the amount of work employees are expected to complete.

The Rebound Effect in Knowledge Work

This pattern is particularly visible in knowledge-intensive professions.

Developers can use generative AI to write code, identify errors, and create documentation faster. Lawyers can analyze contracts more efficiently. Consultants can process information and prepare reports in less time. Managers can summarize large volumes of data almost instantly.

But the time saved rarely disappears.

Instead, employees may handle more projects, analyze additional information, serve more clients, or take on responsibilities that would previously have required additional staff or time.

This resembles the economic rebound effect: when a resource becomes more efficient to use, demand for that resource can increase rather than decrease.

Applied to work, a more productive hour becomes economically more valuable. That can create an incentive to use the hour more intensively instead of eliminating it.

AI Changes How Companies Should Measure Productivity

This development also challenges the traditional debate about working hours.

Discussions about the four-day week, 35-hour versus 40-hour workweeks, and labor shortages often focus primarily on how long people work. But AI makes another question increasingly important:

What is actually being accomplished during those working hours?

Two employees may each record eight hours of work while producing very different levels of value.

One may spend much of the day on repetitive administration. Another may use AI tools to automate routine tasks and spend the recovered time on customer service, product development, strategic planning, or innovation.

Traditional time tracking records both days as eight-hour working days. From a business perspective, however, their contribution may be completely different.

This means companies increasingly need to look beyond hours worked and analyze how working time is used.

AI Cannot Fix Inefficient Processes on Its Own

Another challenge is that companies often introduce AI into existing workflows without changing the underlying processes.

An AI assistant may produce a document within minutes, but the document can still spend days waiting for approval. An AI system may generate an analysis instantly, but the final decision may still require several meetings.

Similarly, writing an email may take only seconds with AI assistance. If easier communication simply results in more emails, the technology has increased speed without necessarily creating meaningful productivity gains.

In these situations, technological efficiency improves while organizational efficiency remains largely unchanged.

For businesses, the key question is therefore not simply whether AI makes individual tasks faster. It is whether the entire workflow becomes more efficient.

What Happens to the Time AI Saves?

For managers, one question should become central:

Where does the time saved by AI actually go?

If a process genuinely eliminates two hours of work, the company may achieve lower costs, shorter working hours, or additional capacity for higher-value activities.

But if those two hours are immediately replaced by more meetings, emails, reports, and projects, the company may simply be producing more work at a faster pace.

That is not necessarily bad. More output can create significant business value. The problem arises when higher work intensity is mistaken for genuine productivity improvement.

AI can increase an employee's ability to complete tasks. It does not automatically determine whether those tasks are valuable or necessary.

From Time Tracking to Activity Analysis

This is where modern approaches to time and activity tracking become increasingly important.

Instead of asking only “How many hours did an employee work?”, companies need to ask:

Which activities consumed those hours?
Which tasks became faster through AI?
Which tasks disappeared completely?
Where did the recovered time go?
Was it used for higher-value work?
Did AI reduce workload or simply increase output expectations?

Solutions such as TimeSpin focus on understanding how working time is actually allocated, rather than looking only at the total number of hours recorded. This can help companies identify changes in workflows and understand whether technology-driven productivity improvements are translating into meaningful business outcomes.

The goal is not to eliminate time tracking. Instead, companies can make it more useful by connecting working hours with the activities performed during those hours.

The Real AI Revolution Is Happening Inside the Workday

The public debate around AI often focuses on increasingly powerful models, automation, and computing capabilities. For businesses, however, one of the most important changes may be much less spectacular: how employees use their working time every day.

AI creates a new economic resource — available time.

But that time does not automatically become free time.

Companies must decide how to use it.

Organizations that simply expect employees to complete more work with AI may increase their output. But organizations that redesign workflows, eliminate unnecessary tasks, and deliberately redirect saved time toward innovation, customer service, strategic work, or employee development may achieve much more meaningful productivity gains.

The central management challenge of the AI era is therefore not simply introducing more AI tools.

It is deciding what work should still be done, what can be automated, and what employees should do with the time that AI creates.

The most important question may not be how many working hours AI can save.

It may be:

What will companies do with the time AI was supposed to give them?

Based on the original article by Oliver Otto, Bremen, September 15, 2026.