Predictive analytics is a technology that makes use of existing data to predict future trends and outcomes. The technology makes use of predictive algorithms to analyze future trends. With the evolving technology and increasing competition in the business world, hiring and retaining the top talent remains the biggest concern for most companies.
Why predictive analytics is important
Any successful business in today’s times will have a productive and satisfied workforce. When the employee attrition rate is high, it can bring many problems for companies in the form of hiring and training costs. Also, as the positions remain vacant for extended durations, the existing staff will have to bear the burden which could lead to decreased productivity. This can be very taxing for any company as high attrition rate not only leads to financial and productivity losses but also brings a bad name to the company. Prospective employees will shy away from joining a company that has a high attrition rate.
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Predictive analytics offers a lot of value as it predicts individual behavior on predefined terms. As the job market has become more competitive than ever, attracting and retaining top talent has become more important than ever. This not only helps companies achieve their targets but also helps them expand their business and become leaders in their domain. Another important factor when it comes to hiring is millennials. Businesses that successfully manage to recognize the needs of the millennial workforce are more likely to succeed. Millennials expect more from their employers, including rewards and recognition to keep them motivated. True productivity can only be achieved when the workforce is engaged and aligned with the objectives of the business. However, if HR departments do guesswork that is not backed by data-driven insights, they cannot meet the needs of the employees. Fortunately, predictive analytics can help them study the behavior of individuals and teams, and take corrective measures wherever necessary.
Predictive analytics reduces human emotions and biases from decision-making
Businesses can make bad decisions if they rely too much on human emotions and do not have data-based insights. To improve their decision-making process, companies can make use of data analytics that eliminates human emotions and biases. The employee surveys can be made more number-centric as ratings can always be quantified to arrive at a conclusion. Companies already have most of the data related to their employees and it doesn’t require any special effort to get any additional data. There can be many factors on which an analysis can be done to determine what leads to attrition. These could be pay scales, past performances, benefits, promotions, leaves, commute time, etc. These are some of the common factors that lead to employee attrition. For example, if employees spend around 2-4 hours on commute each day, it is highly unlikely that they might continue with the job for too long. Similarly, if some employees, who were due to promotion or salary raise, were ignored, it could to them quit their jobs for better prospects elsewhere. HR departments can use this information to build on their plans for the future.
Data analytics always enjoy a benefit over employee surveys because businesses already have all the employee-related information with them. Surveys, if based on opinion, can be very tough to quantify and arrive at a conclusion as human emotions will always play a major role in the decision-making. For example, data like salary, leaves or commuting time are fact-based and there can’t be two opinions about them. Predictive analytics can be integrated with the company culture and employees can be sensitized on how it can affect their productivity and success. Taking into account predictive analytics, businesses can think objectively when it comes to decision-making and avoid emotional reactions. For this to happen, of course, it will need a wide sensitization about how data analytics work and customization according to the style of operations.
How predictive analytics can foresee employee attrition
Businesses that can predict employee attrition trends can do themselves a great favor. Once they manage to identify the alarming trends, they can work towards solving the problems faced by employees. The overall attrition rate can be reduced by working specifically on those employees who are facing particular problems. Quite often it can happen, especially at lower hierarchical levels, that the exit of one employee could lead to the exit of many others in the team. The situation in the company could really be worse but it could also be due to the fact that the employee who was living had managed to successfully influence others. To avoid this, if the HR department can identify such problematic employees, they can easily control the overall attrition rate.
If employees have been leaving due to poor pay scales, businesses can work on this aspect to prevent employee turnover. Maybe they can identify solutions without necessarily increasing salaries. High employee turnover is always taxing for any business, both in terms of productivity and finances.
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Tools for predictive analysis are plenty and businesses that focus on predictive HR analytics for the welfare of their employees will be perceived as futuristic employers. It will also help them showcase their humanitarian side and win the trust of both current and prospective employees. Predictive analytics tools have great potential to improve the productivity of teams and the overall work culture. If a company wishes to increase the salary or offer benefits like remote working for employees who have to travel a lot, they will manage to have a much more productive workforce. A business with a productive workforce will not only achieve its goals in the shortest time but will also see profit rising quickly.
Reference:
Using predictive analytics in employee retention, FM-Magazine, 01 Dec 2018
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