In today’s service oriented world, data is used extensively to understand customer behaviour and improve customer experience, but this type of analysis is seldom applied to an organisation’s own workforce.
Considering an organisation’s staff is responsible for executing the business plan, it should be regarded as an extremely valuable asset. So, wouldn’t it make sense for a company to get a better understanding of the characteristics that determine a high performing employee?
There are numerous ways predictive analytics can be used to devise strategies for employee retention and compensation. It can help understand employee behaviour, increase employee productivity and even be used to calculate when an employee is likely to leave and join the competition.
Customer-facing businesses always grapple with employee churn. High attrition rates are undesirable as they negatively impact company productivity and reduce business agility. Therefore, knowing when an employee is at risk of leaving and putting in place protections to mitigate that effect – particularly during the first year of service when organisations invest heavily in training and development – can be an effective cost-saving insight.
An organisation’s hiring strategy can also be informed by developing models that ensure the right job candidates are shortlisted and interviewed based on their retention probabilities and skills suitability. Using text analytic techniques, organisations can efficiently draw up a shortlist based on keyword selections – saving recruiters time and effort sorting through unwanted resumes.
Employee compensation packages can be structured more effectively when an organisation knows all the information that is likely to determine an employee’s performance – and knows what the exact cost of employing the person really is. Rather than pegging compensation to traditional KPIs, using prescriptive analytics a business can consider a wider number of factors, such as the likelihood of an employee remaining with the company over a period of time, as a way of optimising compensation and bonus packages.
Workforce analytics provides the ability not just to predict employee satisfaction but also find the root cause behind any particular problems. By analysing all the data points available about an employee, management can take more informed HR decisions. Unstructured data text analytic techniques give HR departments the ability to tap into a goldmine of information, such as free form text surveys, interviews, performance reviews, customer feedback forms and even social media data. This unstructured data can be merged with traditional data and used in workforce analytics projects to add a new dimension and understanding to human capital management.
The HR problems faced by a retail bank may differ significantly from those of a telecoms company, or a manufacturing giant, but the analytic principles remain constant across industries. To uncover the challenges your organisation faces in retaining staff and remunerating employees appropriately, just follow the data, because the data never lies.