HRLTT – HR Analytics: Utilising Big Data in a HR Business Partnering Role

Data analyticsThese are the thoughts and takeaways from the latest HR Leadership Think Tank (HRLTT) held on Thursday 26th March 2015 hosted by HCL’s Jaya Satish (Europe Sales HR Lead and Sales HRBP) titled ‘HR Analytics: Utilising Big Data in a HR Business Partnering Role’.

The following summary has been prepared to reflect a segment of the discussion held amongst senior HR professionals from leading national and international businesses. Specific company details, experiences and examples have been omitted from this summary as all discussions are held under ‘Chatham House Rules’.

Within our daily working lives we consistently contribute to the vast amount of data that’s being gathered and circulated by many corporates and research institutions. However, only recently have businesses begun to take advantage of utilising employee data to its full extent. We now live in an age powered by technology where the business landscape is constantly being transformed by the volume, pace and access to ‘Big Data’. Businesses who fail to embrace this change will inevitably begin to lose their competitive edge and will adversely impact their operational performance and productivity. In this executive summary we will be discussing the concept of ‘big data’ and how it can be used effectively in a business partnering role.

Firstly, it is key to mention that gathering data (sometimes known as MI) is not enough – this then needs to be analysed for trends in order to be utilised fully and give the ability to make informed decisions. Before gathering data businesses should always think about what questions they are trying to answer with it and then decide what should be collected. Answers from data should always be aligned to the business goals and what it is trying to achieve. Does the business know what it is asking HR? Sometimes not, so instead HR should look at the business drivers and see how they can answer these with data. HR Business Partners should also guide business leaders to find the questions they should be asking to deliver on their goals.

Business Drivers for HR Analytics

  • Becoming predictive rather than reactive
  • Making informed decisions
  • Making sure decisions are based on fact rather than gut-feeling of line managers (eg. performance reviews)
  • Helping HR make informed recommendations to the business
  • Helping to form a business case for certain initiatives
  • Be more informed when setting KPIs  – for example: staff turnover – business reacts when it is too high but could analytics show that this level is good for certain departments?


Currently many companies just collect quantitative data such as KPIs and use this to make decisions. However, this is not enough. To truly understand employees and trends qualitative data (or softer data) also needs to be included. Businesses should be focusing on the analytics and reasoning for figures and softer data in order to gain a deeper understanding and make truly informed decisions.

It is very important to have a clear understanding of the skillset needed to be able to successfully analyse data. What skills are needed to draw meaningful insights from data? Curiosity, a strong sense of business savvy, understanding of business needs, strategic thinking and financial acumen.  Do HR teams currently possess these skills and if not should they be trained or should an analyst be brought in to assist? It was suggested that the best method is to have an employee who can “crunch the numbers” and has skills to do this but also has the communication skills to be able to translate the meaning of these numbers to an HR Business Partner to help them tell the ‘story’. This HRBP should then have the business acumen to be able to decide on what this data means for the business and what should be done about the findings. If companies decide to train current HR employees on data analytic skills it is essential they have some of these traits, such as curiosity to really want to understand and analyse the data. Does the company already have people in the organisation who have these skills and just don’t know it – tools such as ProFinda can help companies understand and find these people within their organisation. One suggestion is that finance already have the “number crunching” skills and ability to translate these to the business so should they partner with HR in data analysis?

Another thing that companies need to bear in mind before implementing data analytic strategies are the systems that the company has in place. Are these able to gather live data points on a regular basis and have the architecture to help with benchmarking and delving into this data? An excel spread sheet is not live and therefore is it an efficient way to track data? Internal investment in tools is essential to have the place to input and collect data for designated individuals to analyse. Some recommendations for systems to use are Workday connected to Salesforce or Visa. There are currently a lot of new start ups focusing on this sort of analytics.

Businesses also have to realise that data analytics is not a quick fix and something that should just be jumped into without careful consideration just because everyone else is doing it. Depending on the size of an organisation it can take between three to seven years to get data analytics to the sophisticated level that is desired. As mentioned before the business needs to carefully consider what answers they are trying to find with analytics before setting any processes up.

For a company to be sophisticated in data analytics the culture of the organisation needs to support this and employees need to have the mindset that they want to make educated decisions with data. Training also needs to be provided so that teams use data in the right way and feel like they are utilising it to its full potential rather than wasting time.

Another thing to bear in mind is that predictive data may not be exactly right. But does this matter? As long as it is predicting the right type of trends which are leading to the right decisions or ways of thinking then is it ok if actual outcomes are slightly different to predictions?

How should HR communicate insights to the business?

It is essential to understand the business leaders – where, when and how they would most like to be communicated to? Face to face and having a real conversation to answer questions seems to be the most effective method. Communication of a story and meaning rather than just being sent data and facts and figures helps senior managers understand the full impact data analysis can have.  Also sending a simple summary to leaders so they can refer to this after meetings is a good way to make sure they do more with the data than just listen to it and forget it rather than implement decisions based on it.

Data Capture / Measurement

Rather than waiting for lots of accurate data companies should start with pilot projects. This will help enable them to understand what information data analysis can provide and therefore understand further what data they should be collecting. Demonstrating the value that analysis of data can add on a small scale is also more likely to increase business buy in for a larger scale project.

As discussed qualitative information is very important in understanding employees but how can this be gathered and used? Sentiment analysis tools can be used to capture exit interviews and other qualitative information.  Are businesses gathering stories rather than just tick boxes which don’t lead to informed decisions? For example why is this person leaving? Was this really understood rather than just one tick box which can not be read into properly? Quantitative and qualitative data needs to be balanced. E.g. with retention numbers don’t just look at figures look at why people left and who left and whether this was actually a good thing for the business. When using big data for understanding employees businesses should not forget they are talking about people with personalities and aspirations and this needs to be considered.

When gathering data HR needs to take it from all areas of the organisation to support business goals. Business Partners need to sit in on senior management decisions to let them know the goals and pressures of the business and then understand how they can use data to aid decisions or help reach these goals.

Using the data the business already has but analysing it within HR is a good way to get businesses to listen and start to realise the value of data analytics. It is important to show them different meanings and insights on their own data. However, HR also need to make sure they only show the relevant information so discussions are focused.

Just a few of the things that data analytics can help with are:

  • Succession planning
  • Productivity and talent segmentation – determining where investment should go
  • Performance management
  • Capacity planning.


HR are dealing with people – they are not necessarily completely predictive but data analytics can discover trends that lead to informed decisions. One of the most important questions to ask before using data analytics is “can the company demonstrate clear ROI on using data analytics?”

“The most effective HR Business Partners can boost employee performance by 22%, employee retention by 24%, revenue growth by 7% and profit growth by 9%”. However, business leaders only rated 1 in 5 (20%) of their current HRBPs as ‘highly effective’ (CEB 2015 report). Is data analytics the answer to becoming a truly effective HR Business Partner?

Oasis HR

Written by , Network Driven HR Recruitment

Oasis HR is a multi-award winning HR Recruitment Agency based in London that delivers Contingency and Search services within the Human Resource and Business Change Markets. Our client base encompasses all industry sectors and we have a proven track record of delivering permanent, interim and temporary professionals at all levels across all HR disciplines. From a £20k HR Administrator to a £200k HR Director, Oasis HR is well placed to identify, approach and secure the best available talent in the market

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