People Analytics: Data Says More Than Intuition
Nowadays, data is used to understand every part of a business operation and analytical tools are embedded into day-to-day decision making. Meanwhile, employees have always been the most critical asset of any organisation. It is time for organisations to combine these two factors to improve both hiring and business management.
What is people analytics?
People analytics applies statistics, technology and expertise to large sets of talent data, which results in making better management and business decisions for an organisation. In other words, it means using data to make smarter recruiting decisions, such as Who to hire? Who to promote? How much should we pay them? How to improve the retention rate?
According to Deloitte, 86% of the business leaders are deeply concerned about retention and engagement. 89% about leadership. And more than 84% about the current workforce skills. That’s why people analytics is so important. It can help organisations attract and retain the best people available, but also foresee potential problems with enough time to react.
Implementing people analytics
Research has found that even though 78% of business organisations rate people analytics as important, only 7% rate their organisations as having strong HR analytics capabilities. Organisations that want to implement people analytics into their business need internal due diligence. They have to ask themselves the following questions: Where are we? Where do we want to be? How much will it cost? Depending on these answers, the HR department will have to put together a business plan. They have to be up to speed and make sure that they are not losing opportunities. During this process, organisations have to take the following things into account:
1. Clean the house before dreaming big
Analytics in HR today are often inconsistent and not always up to date. There are a lot of big companies that still don’t know how many employees/contracts they have. The HR teams will have to clean a bit first. This is called datafication of HR.
2. The lack of trust in the HR department
A significant minority of CEO’s/CFO’s believe that the HR department does not understand the people needs of their business. Therefore, they will probably not support an investment in people analytics conducted by the HR. HR departments should seek small wins first and get internal support afterwards.
3. Finding the right tools
There are many tools (software) available depending on the size of the industry, the type of industry, etc. Each company needs to find the right tool for them.
4. The skills gap
A lot of HR employees don’t know how to read and analyse data. They’ve never been taught to do so. This is something they will have to work on in the following years.
5. Ethical or legal challenges
How much information about an employee should/can an organisation track, without going beyond what seems acceptable or even legal.
Problems organisations can resolve with data
People analytics can become a very strategic competitive advantage for companies. Companies can address countless problems with data. The first problem is recruitment. The benefits of data-driven recruitment include increased quality of hire, predicting the speed of hire, improving candidate experience, diversity embedded into the recruitment process and delivering on recruitment capacity. Companies can identify the highest performers and introduce promotions based on data-driven conclusions, avoiding political and sometimes unfair promotions. They can also identify the reasons why employees leave, evaluate skills gaps a build better offers.
What does this mean for recruiters?
Data and analytics literacy has become an imperative for HR professionals. The scope of the traditional recruitment function will not disappear but evolve. Recruiters will need to learn all practices, but afterwards, they will become fluent in understanding data. This way, they will get closer to the business and become real trusted internal advisors. The recruitment function will evolve, while the traditional screening process will get automated with sophisticated algorithms. However, data is not able to substitute relationships recruiters create and nurture with both candidates and clients.
Examples of successful people analytics implementation
Google’s focus on people analytics began way back in 2006 when Laszlo Bock was hired as SVP of People Operations. Bock, who believed that data could unlock ways to improve the workplace created a team of PhDs and ex-consultants to analyse workforce data and support the People Operations mission: ‘find them, grow them, keep them’.
Microsoft is a very data-driven organisation. They had a project that was led by the General Manager for HR Business Insights (a mathematician by background) to define what early attrition means at Microsoft. The conclusion was that Microsoft’s early attrition is less than two years due to the high relative investment of a new hire (recruitment cost, signing bonus, relocation, onboarding assistant from teammates, interview time, the opportunity cost of another good hire that may have stayed, etc.). The estimate was that the cost of attrition is at 150% of the salary. If a candidate leaves before the two years are completed, the cost of this candidate is 150% of the salary that Microsoft paid because they lost an opportunity.
Then there is the ISS A/S, a Facility Services company. They wanted to find the link between employees that are engaged and how this has an impact on the customer experience that they offer to their customers. They worked with a well-known consulting firm to do this analysis. They wanted to show a link between the two engagement measures in the process.
Elpida Ormanidou, who was Walmart’s Global People Analytics Vice President built up the retailer’s workforce analytics resource into a global team of more than 60 data analytics specialists. She described four segments that make the ‘analytics engine’ of her team: modelling and data mining; research; prototype and visualisation; and test and learn.
In the end, HR analytics is just one part of big data. In a few years, a specific department within an organisation will be running data for all of the departments.