HR Analytics has been a hot topic for the past few years however many businesses and HR practitioners still have little or no knowledge and experience in applying statistical data that associates HR and business strategy. But it isn’t so hard to get started once you know a few hot tips for where to begin.
As A-HA’s resident Data Scientist I’ve had the opportunity to work with a number of awesome companies to help design, develop and build HR Analytical Dashboards. Dashboards, that tell a compelling story, based on facts and evidence to assist HR practitioners influence business decisions. Reflecting on my learnings and experience to date, my top 5 tips for designing and building powerful HR Analytics are:
First things first! Identify the particular challenge or strategic issue that is important to the business. Then define the people outcomes that will drive results. Knowing the answers to these questions will go a long way to help define and design HR metrics that are most relevant to influence business decision making.
This sounds simple, but too often I see data for data’s sake without a clear connection to the business risk or issue in question.
The data collection and analysis process will usually be rigorous and time consuming. Rather than spend months and months creating or looking for data that you don’t readily have access to, just get started with what you have, ensuring the data is of high quality and is relevant to the business.
Once you feel confident, increase this knowledge, and start designing measures that enable you to report on simple metrics such as retention, attrition, performance and engagement.
Once the foundations are in place you can then take the next leap and embed predictive actions and deliver recommendations to those metrics.
For example, you might start with identifying levels of turnover using simple current data and then evolve this to identify the factors that predict whether an employee will leave and to be aware of what would make an employee leave or stay.
Never just show raw data. The numbers are much more impactful if you tell a story with them. As the saying goes, a picture can tell a thousand words. For maximum impact present data visually by using graphs and charts that are simple and easy to interpret – Let it be the hero! Here’s a good example:
Present data with context. For example, don’t just show a trend for this month, but overlay how this compares to previous months or what last year looked like, to visually see what this means compared to earlier timeframes.
When you try and tell a story, from time to time you may need to show the complexity that lays just below the surface. Deducing not just the ‘what happened?’ but ‘why?’ and ‘what does it mean? In our example above, the big question will obviously be what happened in December 2014? Why the big drop in headcount? Did the change impact proportionately across genders? If not, why not?
It is not always easy to translate data into action; however, only actionable insights will influence decision-making.
The insights need to support recommendations for changes in behaviour, strategy, policy or future interventions.
Knowing the results is not enough; your business must be influenced to want to act on them. I’ve helped design an innovative HR X-Ray and Diversity Dashboard for A-HA’s clients. Both tools are designed to quickly and simply extract existing data and present it in a crisp visual format that provides clear direction on priorities for action and areas of strength to leverage off. Let me know if you’d like to see a quick demo.
Once your HR Analytics report is available, start sharing and talking to it!
Make it simple, by speaking the language of the business. Create short punchy power point packs to explain HR analytics in an easy and non-technical way. Illustrate your message using charts so the business can visualise the results to tell the story.
And finally, it is vitally important that the communication process involves identifying recommended actions based on the analytical results. For example, if a company is concerned about reducing the turnover of high performers, one action might be to better understand employee engagement. A great example for gender equality analytics is the Workplace Gender Equality Agency (WGEA) Gender Equality Benchmark Insight Guide which A-HA is proud to have co-created and co-designed with WGEA. The Benchmark Insights Guide provides great templates and examples on how to communicate gender equality data to influence organisational change.
I hope the 5 tips I’ve shared with you in this article were insightful and useful to you. I’d love to hear from people who have implemented or who are currently using HR Analytics within their business. Do you have any insightful tips to share, particularly for others who are either thinking about it or at the initial stages of building HR Analytics? Drop us a line below to share your thoughts.
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