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  • Writer's pictureDavid Santos Hernández

How to boost the ability to recognise the Salary Gender Gap through Data Discovery


On October 13, the Government of Spain introduced two new Royal Decrees regarding gender equality of salaries. On the one hand, the obligation to present an equality plan has been extended to companies with more than 50 employees (previously set at 250 employees). On the other hand, the contents to be included in the equality plans and the need to prepare a remuneration record are now clearly indicated in order to have a common baseline of information to analyze the salary differences by gender amongst the most relevant aspects of the new regulations stated in the Royal Decrees RD 901/2020 and RD 902/2020.


The deadlines established for the entry of the new regulations vary depending on the number of employees as follows:

  • Companies with more than 250 employees that were previously required to issue an equality plan have one year to introduce the new requirements.

  • Companies that have to implant an equality plan for the first time will also have one year from the establishment of the negotiating committee that will internally regulate the equality plan.

The publication and monitoring of equality plans will be done in a yearly basis and their duration may not exceed four years.


From The Future of Finance Function we recommend the use of Data Discovery technologies for the generation, monitoring and control of equality plans. The use of these platforms can not only facilitate the preparation of the self-diagnosis stage required by the new law, but can also facilitate the Human Resources areas to go beyond the new approved regulations in term of data analysis.


How can Data Discovery platforms contribute to the process of preparing and monitoring Equality Plans?


Platforms such as Qlik Sense, Power BI or Tableau, have developed a set of agile visual reporting tools that allow a high level of interaction when searching for patterns, relationships or trends through multivariate analysis of multiple interconnected data sets..


The main benefits are a greater capacity to analyze data and the simplicity to manage some processes such as the control and monitoring of the evolution of equality measures adopted in the anual equality plans on a monthly basis. This makes possible to identify deviations in the gender gap ratio and indirect inequalities in a more agile and efficient way, eliminating the efforts associated with the manual preparation of spreadsheet reports.




Data Discovery tools make a difference when it comes to graphically representing the gender breakdown of wages from different point of views such as professional category, geographic dispersion, hours of training, absences, etc.


The implementation of this type of platforms has a rapid return on investment since they eliminate the time that the teams involved in generating the Equality Plan use in manual data processing and reporting. This frees up time that allow HR or external auditors to focus on the identification of possible salary differences or discrimination based on gender across the different areas of the organization.



En The Future of Finance Function ponemos a nuestro equipo a disposición de las empresas que quieran hacer una valoración y despliegue de nuestra solución RDS (Rapid Deployment Solution) en Qlik Sense para la elaboración y seguimiento de autodiagnóstico necesario para los Planes de Igualdad.


In The Future of Finance Function we have developed a pre-built solution in Qlik Sense for the preparation and follow-up of the the Equality Plans. Our team provide guidance to companies to perform an assessment and deployment of our Gender Gap rapid deployment solution.

Nuestra metodología para la implantación de modelos de Data Discovery se basa en la premisa “Start small, then escalate”. Esto permite ir evolucionando nuestro modelo predefinido para cubrir la normativa incluida en los RD 901/2020 y RD 902/2020 e ir ampliando o adaptando el modelo gradualmente a necesidades especificas de cada empresa.


Our methodology to deploy of Data Discovery models is based on the premise "Start small, then escalate". This allows our "Plug & Play" model to evolve and cover local regulations to gradually expand or adapt the model to the specific needs of each company.



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