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An analysis of commercial register data shows that start-up activity in Germany has plummeted this year after the corona pandemic ended in 2022.
In recent years, Germany has experienced an unprecedented economic roller coaster ride, ranging from the corona pandemic to inflation. But while the pandemic has put many businesses to the test, and even forced some to close, inflation has managed to affect startup activity in the country in a very different way. A detailed analysis of commercial register data over the past five years sheds light on this remarkable trend.
A look at the data
The commercial register data show a significant decrease in the number of company start-ups in Germany since 2022. In particular in the years 2019, 2020 and 2021, the number of start-ups remained relatively stable, with fluctuations being recorded in the various calendar weeks. In 2019, the year started with 2,880 foundations in the 20th calendar week, but reached a low point of 2,354 foundations in the 25th calendar week before it rose again.
The post-pandemic tipping point
However, times changed after the end of the Corona pandemic in 2022. While the economic outlook was initially optimistic, analysis of the data for this year shows a striking void in start-up activity. Only 1,878 and 2,414 start-ups were recorded in calendar weeks 24 and 23, which represents a drastic decline compared to previous years, even if these figures do not include the start-up of associations. Post-pandemic uncertainty, coupled with economic uncertainties and rising inflation, seem to deter potential entrepreneurs.
Inflation as the new stumbling block
While the Corona pandemic has undoubtedly had a significant impact on business activity, it is worth noting that inflation has emerged as a new factor negatively affecting start-up activity in Germany. Inflation can increase the cost of starting a business as commodity, rent and labor prices rise. This could make budding entrepreneurs reluctant to start new businesses as economic uncertainty and rising costs pose a significant risk.
Outlook and challenges
Current data suggests that start-up activities in Germany are facing serious challenges. As the economic landscape continues to be characterized by uncertainty, it will be crucial for governments, business associations and companies alike to devise strategies to encourage entrepreneurship and support budding founders. The effects of inflation on start-up activity illustrate the need for a holistic approach to ensure economic stability and growth in Germany.
Overall, the analysis of the commercial register data makes it clear that start-up activity in Germany is influenced by a variety of factors, from the pandemic to inflation. The coming months and years will show whether and how Germany can overcome these challenges in order to stimulate start-up activities in the country again.
| Year | KW 20 | KW 21 | KW 22 | KW 23 | KW 24 | KW 25 | KW 26 | KW 27 | KW 28 | KW 29 | KW 30 | KW 31 | KW 32 | KW 33 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019 | 2880 | 2746 | 2148 | 2708 | 2157 | 2354 | 2793 | 2785 | 2801 | 2770 | 2714 | 2770 | 2596 | 2692 |
| 2020 | 2697 | 2069 | 2625 | 2121 | 2237 | 2807 | 2840 | 3048 | 3034 | 2735 | 2954 | 2861 | 2682 | 2809 |
| 2021 | 3458 | 2744 | 2857 | 3467 | 3286 | 3266 | 3334 | 3181 | 3278 | 3068 | 3219 | 3046 | 2939 | 2992 |
| 2022 | 2344 | 2299 | 2708 | 2414 | 1878 | 2345 | 2372 | 1993 | 2138 | 2111 | 2431 | - | - | - |
| 2023 | 1692 | 1821 | 1327 | 1861 | 1604 | 1791 | 2235 | 1749 | 1703 | 1888 | 1755 | 1128 | 2294 | 819 |
Data sources: Commercial Register 2019-2021, StartupDetector Newsletter 2022-2023 (excluding associations).
Note: Data missing for week 31-33/2022
The GEM country report Germany 2021 presents pleasing results regarding start-up activities in 2021 and their connection to the COVID-19 pandemic. The start-up rate, measured by the total early-stage entrepreneurial activity (TEA), has increased significantly compared to the previous year. This could be due to a positive response from business and the adaptability of those looking to start a business during the pandemic.
Start-up rate at the second highest level since 1999
The TEA rate, which represents the proportion of 18-64 year olds in Germany who have founded a company or are in the process of founding one, reached the second highest value in 2021 since the survey began in 1999 – 6.9%. This represents an increase of 2.1 percentage points compared to the previous year (4.8%). This increase suggests that, despite the ongoing uncertainties due to the pandemic, the willingness to start a business has increased in Germany.
Pandemic as driver for new business opportunities
Interestingly, more than a third of the TEA founders surveyed appear to indicate that the COVID-19 pandemic has opened up new business opportunities. This makes it clear that in the midst of the crisis, entrepreneurial opportunities can also arise that lead to new start-ups. In 2020, that proportion was even lower (a quarter of TEA startups were based on pandemic-related opportunities).
More focus on digital sales channels
Although around 76% of TEA founders in Germany have set up their sales channels digitally, the report shows that there is still room for further progress in the field of digitalization. In particular, cooperation between established companies and young, up-and-coming start-ups could lead to a win-win situation. Digital sales platforms and the customers of established companies could offer young companies faster market access.
Gender differences in start-up activity
An interesting aspect highlighted in the report concerns gender disparities in start-up activity. This shows that the gender gap, i.e. the difference between the start-up activities of men and women, was reduced during the COVID-19 pandemic. This applies above all to the prospective founders (nascent entrepreneurs), whose proportion is equalizing. The results indicate that women are more likely to intend to start a business, but are less likely to put them into practice than men.
Measures to promote start-ups by women
The report proposes various measures to further reduce the gender gap and to promote the start-up activities of women. This includes the expansion of childcare options, the promotion of women in business and STEM subjects and the presence of successful female founders as role models. Access to venture capital for female founders could also be improved, especially in the technology-oriented area.
Conclusion: increase in start-up activities despite the pandemic
The GEM country report Germany 2021 shows that the start-up rate in Germany increased in 2021 despite the ongoing COVID-19 pandemic. This could be due to an increased adaptability of the entrepreneurs, the identification of new entrepreneurial opportunities and the positive reaction of the economic policy. Gender differences in start-up activity have also narrowed during the pandemic, indicating increased support for start-ups by women. In order to further support this trend, targeted measures could be taken to strengthen the framework conditions for women in the start-up world.
In a groundbreaking announcement, Microsoft Excel has unveiled a new chapter in data analytics by introducing Python integration to its platform. This momentous stride brings together the power of Python's analytical capabilities and the versatility of Excel's data organization and visualization tools. With the launch of Python in Excel, users can seamlessly merge Python and Excel analytics within the same workbook, ushering in a new era of efficiency and sophistication in data analysis.
A Fusion of Python and Excel: The Next Evolution in Data Analytics
From its inception, Microsoft Excel has been at the forefront of transforming data handling, analysis, and visualization. Now, with Python in Excel, Microsoft takes another leap forward, offering a Public Preview of this groundbreaking integration. The synergy between these two stalwarts in the data world allows users to directly input Python code into Excel cells, with the calculations executed in the Microsoft Cloud. The results, including plots and visualizations, are then seamlessly integrated into the Excel worksheet, all without requiring any intricate setup.
The initial roll-out of Python in Excel is available for those participating in the Microsoft 365 Insiders program, accessed through the Beta Channel in Excel for Windows.
Unveiling the Distinctive Features of Python in Excel
Catering to Analysts' Needs: Excel's familiar tools like formulas, charts, and PivotTables are utilized by millions for data analysis. Now, Python in Excel takes this a step further by natively integrating Python directly into the Excel grid. The new PY function enables users to input Python code directly into Excel cells, offering access to potent Python analytics alongside Excel's trusted features.
Unleashing Python's Power via Anaconda: Python in Excel leverages Anaconda Distribution for Python, a repository embraced by countless data practitioners globally. This integration facilitates access to popular Python libraries like pandas, Matplotlib, and scikit-learn, amplifying the analytical prowess available within Excel.
Security and Cloud Compatibility: Python in Excel operates securely in the Microsoft Cloud environment, utilizing Azure Container Instances for isolated execution. The integration ensures data privacy, restricting Python code's knowledge of users' identities and keeping workbook data isolated and secure.
Team Collaboration Made Effortless: Collaboration takes center stage with Python in Excel. Teams can interact with and refresh Python-powered analytics without grappling with complex installations or management of libraries. Collaboration tools like Microsoft Teams and Outlook seamlessly enable shared workbooks and foster a cohesive working environment.
Microsoft's Commitment to Python: The partnership across various Microsoft teams underscores the company's dedication to enhancing Python's accessibility and integration. Guido van Rossum, Python's creator and Microsoft Distinguished Engineer, lauds this milestone, highlighting the collaborative spirit.
Unlocking New Avenues in Data Analysis
Python in Excel opens up a realm of possibilities, transforming Excel from a traditional spreadsheet tool into an advanced analytical powerhouse. Advanced visualizations utilizing Python's renowned charting libraries, machine learning, predictive analytics, and even data cleaning are now within Excel users' grasp. This integration enhances the workflow of diverse sectors, from education and corporate analytics to financial analysis.
The Road Ahead
With Python in Excel making its debut through the Public Preview for the Microsoft 365 Insiders program, the future holds promise. Expectations are high as Microsoft works on refining the integration, expanding editing experiences, error management, documentation, and more. The integration's potential to revolutionize data analysis and collaboration ensures a keen eye on its evolution.
In this era of data-driven decision-making, Microsoft's Python in Excel heralds a transformative era where two juggernauts, Python and Excel, coalesce to empower analysts and organizations worldwide. The fusion of these platforms unlocks a future of unparalleled data exploration, analysis, and insight generation.
Artificial intelligence (AI) was recently predicted as a possible trigger for a wave of mass unemployment, as various occupations would be threatened by automation. However, the anticipated employment crisis has not materialized, even as AI technologies such as ChatGPT have gained traction.
Despite AI's growth, the job market remains stable, and unemployment rates have not soared as projected. The perceived threat of widespread AI-driven job loss is more complex than initially thought. AI's capabilities are impressive but limited, still unable to handle the majority of tasks that humans perform. Instead of replacing human workers, companies have adopted a strategy of enhancing human performance with AI assistance. This has led to an unexpected outcome: businesses are realizing the challenges of transitioning to an AI-driven workforce.
Industries that were considered ripe for AI disruption, such as law and medicine, are not seeing the mass layoffs initially predicted. For instance, a generative AI tool used by a global law firm aids lawyers in tasks but has not replaced them. In medicine, AI complements radiologists by expediting certain tasks, but it's not equipped to make complex medical decisions.
The reason for AI's limited impact on jobs lies in its inability to replicate the diverse tasks and adaptability that humans bring to the table. While AI can excel at specific tasks, its shortcomings prevent it from fully replacing human workers across various roles.
Reports of companies replacing employees with AI should be taken with caution. Often, these announcements are linked to broader downsizing efforts rather than a seamless transition to AI-driven operations.
While AI's influence on jobs is undeniable, the narrative of massive unemployment is far from accurate. As AI technology advances, certain roles may be displaced, but the value of human skills, adaptability, and nuanced decision-making remains indispensable. In the ongoing AI evolution, the clear lesson is that human potential remains underrated, and the true impact of AI on employment is more nuanced than the initial hype suggested.