HRIT Salary Guide 2024






Our Latest Report

Inform Your Hiring Strategy

Benchmark salaries, benefits and industry trends across the HRIT hiring market. Inform your hiring strategy and beat the competition. The guide shares insights on HRIT professionals' pay, benefits, experience and market specialisation in Germany, Austria and Switzerland.

Unrivalled talent insights

  • Fixed salary benchmarks for permanent positions across various HRIT modules
  • Fixed salary data by region
  • Bonus and equity information offered to professionals 
  • Diversity data, strategy and the gender pay gap
  • Schools producing HRIT talent
  • Learning and Development programmes
  • Most important benefits to HRIT professionals
  • Employer value propositions to attract HRIT talent






 

2024's HRIT Hiring Market

In 2024, the shift to cloud-based HRIT systems is widespread, particularly as SAP announces the extension of maintenance for core applications of SAP Business Suite 7 software until the end of 2027. This means organisations using this ERP system are actively seeking skilled professionals to manage the transition to the cloud. 

Change management and the individuals leading transformation projects remain crucial for many businesses, as they determine the success of the transition. The implementation of HRIT systems is seen as a key factor in attracting and retaining talent, while also offering an appealing employee experience to the broader business.

The adoption of Artificial Intelligence tools has gained momentum in recent years, with 2024 witnessing increasing popularity. From applicant tracking to identifying attrition, many users of HRIT systems are looking to incorporate AI into their human capital processes.

These current trends significantly impact today’s hiring market, with both consultancies and end users seeking specialised skills and experience to navigate HRIT transformation and adoption successfully. However, the talent shortage remains a challenge, as there are few skilled professionals compared to the increasing number of opportunities. This intense competition to attract and retain top talent underscores the importance of our Salary Guide. It aims to provide professionals with valuable insights into current salary trends, skill requirements, and job opportunities, while also helping employers understand professionals’ needs and shape their hiring strategies accordingly. We hope you find it informative.

Our Research

Methodology

The purpose of this methodology is to provide a clear understanding of the approach utilised in conducting a survey aimed at SAP and HRIT professionals. This survey aimed to gather insights into various aspects of the SAP hiring industry, including compensation data (Fixed salaries, bonuses and equity), working environments, trends, challenges, and best practices.

Survey Design:

  • Objective: The primary objective of the survey was to understand the perspectives and experiences of SAP professionals as well as gather data that could provide industry wide salary benchmarks.

  • Questionnaire Development: A comprehensive questionnaire was designed to cover key areas such as compensation, industry trends for 2024, important benefits, learning and development programmes, and challenges faced by SAP professionals when seeking a new job.

  • Pilot Testing: Prior to the official launch, the questionnaire underwent pilot testing to ensure clarity, relevance, and effectiveness in eliciting the desired information.

  • Question Types: The questionnaire included a mix of multiple-choice questions, Likert scale items, and open-ended questions to capture a broad spectrum of responses.

Sampling Method:

  • Target Population: The target population comprised professionals actively involved in and working with SAP across various industries in Germany, Austria and Switzerland.

  • Sampling Technique: A combination of convenience sampling and purposive sampling techniques was employed to reach out to a diverse pool of professionals.

  • Sample Size: The survey aimed to collect responses from over 500 SAP professionals to ensure adequate representation and statistical reliability.

Data Collection:

  • Online Survey Platform: The survey was administered using a reputable online survey platform, ensuring ease of access and data security.

  • Distribution Channels: The survey link was distributed via professional networks, industry forums, and targeted email invitations to reach the intended audience.

  • Data Collection Period: The survey was conducted over 3 weeks in February 2024 to allow sufficient time for respondents to participate and provide thoughtful responses.

Data Analysis:

  • Quantitative Analysis: Responses to multiple-choice and Likert scale questions were subjected to quantitative analysis using statistical tools to identify trends, patterns, and correlations.

  • Qualitative Analysis: Open-ended responses were analyzed thematically to extract insights, opinions, and anecdotes shared by respondents.

Ethical Considerations:

  • Informed Consent: Participants were provided with clear information about the purpose of the survey and their voluntary participation. Consent was obtained before proceeding with the survey.

  • Anonymity and Confidentiality: Respondents were assured of the confidentiality of their responses, and measures were implemented to anonymize data to protect the privacy of participants.

Limitations:

  • While efforts were made to ensure the representativeness of the sample, the findings may be subject to biases inherent in survey research, such as self-selection bias.

  • The generalizability of findings may be limited to the population of Executive Search professionals who participated in the survey.

Conclusion:

The methodology employed in this survey aimed to uphold standards of rigor and validity in data collection and analysis, thereby providing meaningful insights into the perspectives and practices of Executive Search professionals.

This methodology outlines the systematic approach adopted in conducting the survey, ensuring reliability and credibility in the generation of findings and conclusions.