If someone has told you that data analytics is something relatively new in Human Relations, do not believe them. The truth is that a big part of the HR work is to plan. You cannot have proper planning without accurate forecasting, something we have already discussed at this analytics blog. Well, it turns out that HR people and their industry as a whole are still far of maturity in terms of utilizing its data (trust us, they have a lot) into predictive analytics. Recent Deloitte survey of business and HR leaders shows that companies exploiting HR analytics are extremely small fraction of the market – 4% in 2015 vs 8% in 2016. The study highlights that this number is going to increase due to a shift of HR professionals expectations.
Data analytics in all of its forms can be extremely useful in the fields of identifying, recruiting and retaining talent. Smart and efficient workforce scheduling is yet another field where data predictive analytics can be extremely helpful.
Retention and Turnover
Talent retention is crucial since the company has invested a lot in every employee. In some business domains like IT, for instance, the learning curve hit its peak at least after a couple of years. So any resignation in advance is a complete loss of resources.
We have to keep in mind that there is a healthy amount of turnover. This means that the organization is not blocked and some fresh talent is infused within. It is widely accepted among HR professionals that a turnover as of 5% a year is OK and this number might be tweaked depending on the market or the business domain. Anything above or below should raise questions within HR departments and COOs.
Predictive analytics is capable of giving unbiased answers of the questions that such business problem might arise. It can identify its genesis in order to make the solution fast and efficient. Because such turnover issues might be because of the salary levels, corporate culture, management, learning opportunities, benefits, workloads, etc. Experimenting and split testing with all of them is time-consuming and sometimes expensive.
Actionable metrics to be analyzed
In a recent blog post, Visier – HR SaaS platform with integrated forecasting, shared an interesting view on what you can do with the HR data, backed by their professional experience. Just take a look at this particular graphic to see which metrics you might keep an eye on in order to get actionable insights through predictive data analytics:
Payment and Performance
Raising payments to fight increasing turnover is a common misconception among managers. Professional HR experts know how important the benchmarking is so they are pretty cautious when it comes to a salary increase. Despite doing this, their key task is to identify stellar performers or soon to be such and keep them within the organization. It is widely accepted that over performers must be financially compensated.
Predictive analytics is capable of modeling the most efficient level of performance based compensation differential which states the salary difference between average and over performance. Turning this critical question into a single number allows for powerful insight across the organization; it means that different locations, business units, and groups of employees can be easily compared using simple visual analyses, says Ian Cook from Visier in a publication issued by HRZone.
Predicting Analytics and HR
Predictive analytics can be a powerful tool for business as a whole, just like the sales forecasting apps provided by A4E. While different analytics solutions are capable of giving insights into employee benefits, promotions, and talent management, predictive analytics are starting to be used for deeper forecasting. For example, they can help measure the efficacy of training courses or to identify which employees are more likely to reach their targets and why. It might point which of the performed CSR initiatives is most efficient in terms of contribution to corporate culture and employee involvement. Such insights can easily have a big impact and are boosting the efficiency in HR policies.