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How to Solve Problems in the Workplace Using Predictive Analytics

Solving recurring problems in the workplace – and preventing them from happening again – can be made easier using predictive analytics. 

From analyzing employee data to predict future patterns of behavior, including staff turnover rates and the potential for attrition, to using people analytics to gauge how new hires will benefit the business, the advantages of using predictive analytics in the workplace are abundant. 

There are plenty of resources on predictive analytics that you can access online. You could even consider completing an online business analytics masters. Otherwise, this brief overview will also provide you with some insight. 

Common Workplace Problems: How Predictive Analytics Can Help Solve Them

Some of the most common workplace problems include:

Hiring and Staffing: It Can Help Human Resources with Recruitment

When it comes to hiring staff, HR departments can benefit greatly from using predictive analytics to understand their recruits. 

Using predictive recruitment tools can help recruiters select potentially high performers for their teams. Of course, there is no real way of knowing if a new hire will remain consistent with the gleaming potential they display in their interview. But, by analyzing a job candidate’s past achievements, actions, and behaviors, their future performance can be somewhat premeditated.

For example, if an applicant has been a high achiever throughout their schooling and higher education, and has achieved top study scores, their future behavior in the workplace will likely be similarly studious and diligent. In addition to this, if they have taken on professional work experience from a young age, this can demonstrate characteristics such as initiative, drive, and determination. Analyzing this type of historical data can help to gauge the future value of certain individuals to the business.

Staff Turnover, Resignation, and Attrition

Using predictive analytics can also help employers reduce the risk of staff attrition and high rates of resignation. By analyzing historical data to ascertain the reasons for which past staff have resigned, employers can better predict the likelihood of this happening again. This in turn can help them to make organizational changes to prevent high staff turnover from occurring again in the future. 

But what are the predictive analytics metrics employers should consider to help solve these common workplace issues? Just keep reading as we uncover these strategies. 

Problem Solving and Predictive Analytics: How To Do It

So, how can you use predictive analytics for problem-solving in the workplace? Here are some of the top techniques: 

Reviewing Internal Staff Engagement Surveys

Staff engagement surveys – and the job satisfaction scores they elicit – are excellent examples of valuable data that can help drive and inform predictive analytics. If staff engagement is high, employees are, logically, more likely to stay in their jobs. Conversely, if job satisfaction scores are worryingly low, it can be predicted that staff turnover rates could be a future cause for concern.  

Armed with this feedback, employers can take survey comments on board to make necessary improvements for their staff. Employers may find that more needs to be done to foster a positive and productive work culture – such as introducing a social events committee, for example. Alternatively, they may find that their staff feel stretched and overworked – in which case, additional human resources may need to be acquired. 

Assessing the Results of Performance Reviews

Analyzing performance review results can also help predict future outcomes. Job satisfaction surveys can only go so far – it is only by looking at performance data that we can truly understand employee engagement and productivity. 

Naturally, an employee who scores well in their performance review is more likely to be happy in their job. If a typically high performer is starting to show signs of lower productivity, this could be demonstrative of a deeper issue. They could be experiencing burnout, or may even be looking for employment elsewhere.

Ultimately, understanding the past actions and behaviors of employees can help predict, preempt, and prevent similar future problems from arising again. Issues such as staff burnout,  attrition, and high turnover rates of resignation, can all be avoided if employers take the time to look at the data. Similarly, companies can also make better decisions in terms of the new employees they hire, by looking at how well they have performed in the past.

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