Areas of Interest
Content Type
Industries
- Aerospace and defense
- Banking, Financial Services, and Insurance
- Energy and Resources
- Federal Government
- Healthcare and life sciences
- High-tech and telecommunications
- Higher Education
- Media and entertainment
- Private equity
- Public Sector
- Retail and manufacturing
- Social Impact Institutions
- Travel and transportation
Technologies
- Artificial Intelligence
- Automation
- Blockchain
- Business and data analytics
- Cloud
- Customer relationship management (CRM)
- Cybersecurity
- Digital Services
- Enterprise resource planning (ERP)
- Human capital management (HCM)
- Internet Of Things
- Machine Learning
- Networking
- Supply chain management (SCM)
- Virtual reality/Augmented reality
Areas of Interest
Latest Reports
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 6: Banking and Financial Services Sector Benchmarks
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 5: Discrete Manufacturing Sector Benchmarks
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 4: Process Manufacturing Sector Benchmarks
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 3D: Benchmarks by Organization Size
In these chapters, we provide a complete set of benchmarks for organizations within the specified size classification. Small organizations benchmarks are in Chapter 3A, midsize organizations in Chapter 3B, large organizations in Chapter 3C, and very large organizations in Chapter 3D. These chapters use a three-year sample. There are 98 respondents in the small organization sample, 102 in the midsize sample, 65 in the large sample, and 40 in the very large sample.
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 3C: Benchmarks by Organization Size
In these chapters, we provide a complete set of benchmarks for organizations within the specified size classification. Small organizations benchmarks are in Chapter 3A, midsize organizations in Chapter 3B, large organizations in Chapter 3C, and very large organizations in Chapter 3D. These chapters use a three-year sample. There are 98 respondents in the small organization sample, 102 in the midsize sample, 65 in the large sample, and 40 in the very large sample.
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 3B: Benchmarks by Organization Size
In these chapters, we provide a complete set of benchmarks for organizations within the specified size classification. Small organizations benchmarks are in Chapter 3A, midsize organizations in Chapter 3B, large organizations in Chapter 3C, and very large organizations in Chapter 3D. These chapters use a three-year sample. There are 98 respondents in the small organization sample, 102 in the midsize sample, 65 in the large sample, and 40 in the very large sample.
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 3A: Benchmarks by Organization Size
In these chapters, we provide a complete set of benchmarks for organizations within the specified size classification. Small organizations benchmarks are in Chapter 3A, midsize organizations in Chapter 3B, large organizations in Chapter 3C, and very large organizations in Chapter 3D. These chapters use a three-year sample. There are 98 respondents in the small organization sample, 102 in the midsize sample, 65 in the large sample, and 40 in the very large sample.
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 2: Composite Benchmarks
This chapter provides composite metrics for all survey respondents across all sectors and organization sizes. The sample includes 154 organizations and is stratified by size and sector as described in the survey methodology section. Respondents must have at least €50 million in annual revenue or IT spending greater than €1 million and maintain at least some operations in Europe. There is no upper limit on the size of survey respondents.
European IT Spending and Staffing Benchmarks 2024/2025: Chapter 1: Executive Summary
Chapter 1 provides an overview of the key findings from the full study and describes the contents of the subsequent chapters. It also includes information on the study participants and the survey methodology.
Optimizing Power Consumption in Data Centers in the age of AI
As companies increasingly repatriate their data centers, optimizing power consumption has become a crucial priority for enterprise buyers. This shift offers opportunities for improved operational efficiency while also presenting challenges related to energy management, sustainability, and resource utilization. The demand for power in data centers, is further augmented by the rising energy needs of high-performance chips. This exponential data growth and increased compute power requirements are further stressing the existing power infrastructure. As the use of large data becomes more widespread, optimizing power within datacenters will become crucial to the enterprise spend and operational efficiency.
