HR has a proliferation of data from numerous sources, using this data to offer information to the business to support people interventions is where we aim to help you. We contend HR is not short of data, but rather the skills and experience to know which is more valuable than the other and to use that data intelligently to influence business decisions and outcomes.
The following programme shows how we can begin to address that.
We have worked with HR people from all sectors, nationalities and size of organisations.
If you need to make better use of people data in your role; if you have an interest in learning more about how to use data or if you are an HR Leader who needs this skill in their team – then this is for you.
If you could use some help answering the 4 basic questions below then this is for you.
Join 8-10 like minded peers for this 1 day foundation workshop on data basics, introduction to data modeling, statistical methods and reporting.
We will help you understand the real basics and take you through the four steps to creating credible and reliable insights based on data.
- What question am I answering – what do I need to measure (need)
- How best to measure it – survey, existing data sets or outputs from HR systems (source)
- How best to use what I have measured (modeling)
- How best to present the findings (data visualisation)
This workshop can be run internally for whole team or partial team and can be revised to reflect the particular business context of your organisation at the time of the programme
There is no pre-work except being ready to learn!
There will an additional option to undertake real projects back at work with remote coaching
To explore both the opportunities and challenges of using data
To develop a collective and shared view of the opportunities to improve HR’s reputation by understanding and making greater use of data
To improve participants confidence in applying data in real situations
To identify some ‘next steps’ for the participants in applying data
To share practical examples of how data should and should not be used