How to Prepare Your Data Sources for HR Analytics

5 Tips to Prepare Your Data and get the Most out of People Analytics

Data and analytics historically didn’t play a large role in HR. Organisations made workforce decisions primarily based on instincts or intuition. Today data and analytics are an essential part of the HR strategy. With large amounts of data and analytical tools available, organizations can dramatically improve the way they identify, attract, develop, and retain talent using quality data. Moreover, the successful use of data in HR is an important driver of the cultural change needed for an entire organisation to become more data driven.

HR analytics, also referred to as people analytics, workforce analytics, or talent analytics, is a method to analyse workforce data to get to know employees better and use the insights for managers to take better decisions about the workforce. The point here is that HR analytics is taking place in HR but it is a strategic support function for the business as a whole.

The journey to build a successful HR analytics function starts with building skills in analytical thinking and data analysis and applying them for workforce planning. But for the whole HR analytics function to succeed, it is necessary to build the first steps upon high quality workforce data.

Only quality data can deliver value and the responsibility for it lies within HR. Once low quality or outdated workforce data finds its way into HR analytics, it’s next to impossible to generate valuable insights. Later stage activities such as Human Centred Design or EX implementation would look good on paper but will hardly produce any results. And it will be difficult to find out why.

If you plan to invest in HR analytics or have already done so, you can make sure that you can deliver valuable insights and results with these five steps.



Your job architecture holds the most basic information about the structure of and the roles in your company. If your job landscape is not consolidated then there cannot be a consistent approach to handle the job data. You need to know your existing workforce – which tasks are being done in which place, by whom and their contribution to the business – to deduce any conclusion. If you find one or more of these typical signs for an unconsolidated job architecture in your company, clean it up.

  • There exist different job titles for similar roles.
  • The job descriptions are detailed but fail to capture the real essence of a job.
  • The job descriptions are outdated or even obsolete, they don’t correctly describe the role today.
  • There are different job evaluation practices throughout the company, leading to different careers and compensations for people who should be treated similarly.
  • There is no or no effective approach to capture and store the skills and competencies of your people (see below).
  • The value being generated by a job for the company is not mentioned in the job description.



Typically, companies use different systems for different HR tasks. Some use Excel sheets, some are creating a core HR backbone out of complex legacy systems, others use a variety of applications to manage the different HR processes such as talent acquisition, performance management or succession planning. A fragmented landscape of data sources will prove to be problematic for achieving a reliable overview. There will remain doubts about the accuracy of the data and this means elevated risk when taking strategic decisions.  Build an integrated data infrastructure or at least one source of truth for the most basic workforce data.



Once your job architecture and accuracy of employee data are taken care of, the challenge remains to deduce conclusions in a meaningful way. Any tool that visualizes your data will be of great help to understand it better. It should offer you at least the following:

  • Compare values between different groups. I.e. being able to compare the employee engagement scores by geography will help to decide in which location you need to dig deeper.
  • Show relationships between variables. I.e. figuring out if there is correlation between the employees’ level and their turnover to focus your retention measures.
  • Display evolutions and make predictions. E.g., completion of trainings by course over time to design learning paths and adapt offerings.
  • Highlight data patterns across locations and demography. E.g., visualizing the potential impact of new technologies on the different parts of your workforce.



HR deals with personal data and data privacy rules can get easily in the way of accessing the data needed. For each report required by HR the data needs to be reconciled and the relevant security rights need to be configured accordingly. This requires effort and time from specialists and can often result in delays in receiving data, making it obsolete upon obtaining or even worse, no access to the needed data at all. But this issue can easily be solved by creating one single data source and pre-defining the access rights accordingly. This will be of great help to support the top-level management with meaningful short-term responses.



Skill management is becoming increasingly important for strategic workforce planning. But skills and competencies need first to be captured before being able to answer relevant questions.

  • How do we split and classify skills in a way that accurately captures the essence of what people can do?
  • Should competencies, attributes or interests also be considered for career paths?
  • How do we capture the evolution of skills, i.e. when employees gain a new skill?
  • What is the best way to plan for skills that are yet to emerge?

The process of capturing skills is tightly connected to the first two requirements mentioned: a well-designed job architecture and using appropriate, consolidated data-sources. For example, you can involve employees by asking them about their skills, ask their project peers, managers or extract data from documents (CVs, Degrees…). The important thing is to store the answers in the one single HR data back bone where you can update them easily. Then you will not only be able to access and analyse the data but also to verify its accuracy by comparing them and keep track of changes.


HR analytics offers immense value and no larger company will be able to get around creating a respective function. But don’t rush creating it. Get you basics right with the above-mentioned preparation to make sure that you deliver on the promises of HR analytics. Have a look at our Ultimate Guide to Job Architecture and get a step closer.