Predictive analytics and forecasting in one of the branches of advanced analytics that make assumptions regarding the incoming trends, patterns and predict the future. The future performance and trends are forecasted using statistical algorithms. This technique uses the input signaling and historical data as a primary source of information along with the statistical techniques, modern software and algorithms, image, videos, and other forms of data. The basic principle on which predictive analytics operate is “machine learning”(ML).
It I a multi-approach methodology that many companies employ. Predictive analysis and forecasting along with its constituent techniques are being implemented in organizations to find out the future trends and measure the chances of risks or opportunities.
The domains that are being benefitted from predictive analytics are:
- Banking and financial services.
- Retail services.
- Manufacturing.
- Health Insurance.
- Oil, gas, and other utilities.
- Human resources.
Predictive analysis and data analytics has been around for decades, but in past, the industries were not eager to invest that much into this emerging technology. But times have changed now, the time has finally come when this technology is rapidly being adopted by more and more enterprises. It is important to know why predictive analytics is catching many eyes. What is the impulse to inculcate predictive analytics and forecasting in the corporate world? There are many answers to these questions that give us various reasons for employing this revolutionary robotic technique. The bottom line idea that drives the increased use of this technology in organizations nowadays is the competitive advantage that it confers to industries. Apart from this, some other advantages are also adding up to its increased usage, some of which are discussed here:
- Companies nowadays are flooded with tons and tons of data and numbers. These data reside in form of various images, videos, transcriptional log files, and other forms of data. Scientists have successfully employed the use of this data to gain access to the future and make successful predictions using deep learning and machine learning. Machine learning (ML) is the basic platform on which AI-powered predictive analytics and forecasting work. This technique enables the machines to operate automatically using the installed data and helps in finding out the predictive patterns and making assumptions about future trends. Predictive analytics and forecasting are combined with prescriptive analytics to drive the actions needed, based on the assumed trends.
- The computers and machines seem to be a nice calculated long term investment to gain outweighed profit in future. They are faster and cheaper than traditional technology. Moreover, the installed software is constructed in such a way as to make it more user-friendly. This gives a competitive advantage to the companies, outstanding them in the rest of the corporate world. So, it is to say that it is no longer a domain of just mathematicians and statisticians. Business analysts and experts are striving to ingrain these technologies in their sector as well.
- Marketing campaigns can also be optimized by enterprises using predictive analysis and forecasting.
The business sector uses historical data to predict the organization’s economic stability in the future. A picture of future sales, revenues, and profits can be crafted just by using predictive analysis
Predictive HR Analytics
Predictive HR analytics is just a domain of predictive analysis and forecasting that uses human resources (HR) to collect data from the past and present and make future predictions regarding the outcomes. It digs into the informational data to extract, analyze and construct statistics, leading to the identification of patterns, trends, and correlations shortly.
Predictive analysis in human resources helps the confounding runners to make calculated decisions that add to the enthusiasm and working capacity of the workforce.
What Predictive HR Analytics Has To Offer?
Predictive analytics offers assistance to organizations that makes it more appealing in modern times. In the past, the organizations worked with conventional technologies and techniques. But now, the times have changed and many companies are now introducing predictive HR analytics to attain their desired goals. Predictive models for HR enable the companies to gain access to the factors that might influence their output results.
According to Deloitte’s 2018 People Analytics Maturity Model, only 17 percent of the total worldwide organizations had accessible and utilized HR data. This percentage is significantly higher than 8 percent in 2015, and 4 percent in 2014. That means the companies can now collect, integrate and analyze data. These companies seek help to:
- To reduce the chances of risk.
- To reduce the chances of human error.
- To enhance the working capacity and performance of workers.
- To enhance the overall productivity of the working environment.
- To analyze worker’s profile.
- In making decisions that benefit the organizations in the longer run.
How Predictive Analytics In Human Resources Works:
Predictive analytics and forecasting use historical data to forecast potential scenarios and outcomes that can assist in planning and making strategic decisions. Large quantities of human-based data are managed by Human Resources Information System. After applying predictive analysis and forecasting algorithms to this data, science-based proven data help us in establishing predictive models, instead of relying on conventional ways.
HR predictive analytics enable HR to predict the effect of different policies on the well-being and working capacity of the workers. Here are some of the ways predictive HR analytics are helping organizations:
Predicting employee turnover:
Every organization and company experiences a certain level of employee turnover. And there could be many possible etiological factors behind this. A higher level of employee turnover poses a threat to the running organization because:
A higher level of turnover leads to high recruitment costs and increased lost revenue. The productivity and output percentages of the company are reduced considerably as they are directly influenced by this turnover ratio.
The employees that leave the organization, apart from affecting the economic stability of the company, also take away the knowledge, experience, and skills with them. And many times, the customers that rely on them also go away with them. This further adds up to the lost revenue of the company. It is estimated that the total cost of the replacement of mid-level employees is about 150% of their total annual salary. This gives a direct idea about the significance of predictive analysis in human resources. By applying, predictive analytics and forecasting, the company can save many millions.
Predictive HR analytics help organizations in predicting which employee is likely to leave the job.
By implying predictive analysis, they can also evaluate the possible causes that what factors are contributing to the employee turnover rates, and why employees would leave the company.
The evaluation of risk factors helps the company in modifying its policies and developing strategies to retain its working staff, thus reducing the cost of lost revenues.
Job security, reasonable wages, promotions, bonus, and a healthy working environment secures the workers and they are less likely to leave.
Aid In The Hiring Process
Predictive analytics can aid companies in the hiring process. Google’s hiring process is now computer-generated and fully automated, requiring no human intervention. The installed software automates the entire process and is well adapted to find out the best candidate. In this way, we can also find out the possible risk and probability of people leaving the company.
It is estimated that the newly hired sales workers, who do not get a promotion within the next four years, are much more likely to leave the company.
There are many other standard criteria set by predictive analytics tools that help in the recruitment of the best candidate. This way, companies can attain the maximum productivity levels by imposing predictive analysis in human resources.
Identification Of Disengaging Employees
Employee retention is a growing challenge faced by many companies. The workers tend to leave the company if they do not get the desired wages or growth opportunities. The factors that might lead to increased turnover and dissatisfaction of employees are very well assessed by predictive analysis and forecasting algorithms.
The workers who are disinterested and demotivated are more likely to quit the job. Working environment, relationship with colleagues, and managing team attitudes also help in predicting if an employee is likely to quit or not. Predictive analysis in human resources is employed by HR managers to recognize the disengaging and uninterested workers. Suitable replacements can be found beforehand, this way.
This helps the HR manager to keep a balance in the workplace. Furthermore, this step ensures maximum productivity of the company and financial outputs. The predictive models and trends help HR managers to devise strategies to retain employees and reduce employee turnover.
Implement Artificial Intelligence at work to meet the changing expectations of teams around the world
To Bridge Skill Jobs
It happens often that HR managers might end up hiring candidates that fit the qualification criteria but lack the necessary skills required for the job. Thus, a lot of time and money is spent in training such employees to get them accustomed to the right set of skills. This creates, what we call a “skills gap” that is highly unfavorable for the organization.
Implementation of HR predictive analytics tools can help in closing the skills gap. Historical data is analyzed and interpreted, and a predictive analytics algorithm can help in bridging the skill gap. Predictive analysis in human resources can help the HR managers in deciding which employees to recruit and which existing employees should be upskilled. In this way, time and resources are channeled in the right direction. Predictive HR analytics also determine the right set of skills for the right employees and identify all those shortcoming areas that need improvement. This is a crucial step as the employee’s education, working experience, and skills are analyzed to get a better understanding of the skills and shortcomings of the candidate. Apart from leveraging predictive HR analytics, organizations can also implement blockchain to bridge this skill gap.
Forecasting Talent
Just like bridging skill gaps, predictive HR analytics help in forecasting which employee and particular skill set can be a success for the organization. The organizations can predict which new hires are more likely to be a success after evaluating their background experiences, past projects, and skills. HR managers tend to focus on retaining these types of new hires and talents.
Managing Absenteeism:
Predictive analysis in human resources may be employed to predict employee absenteeism and the ways to reduce it. The predictive analysis algorithms generate multiple theories and validate them to find out the possible reasons for absenteeism and increased leaves. These hypotheses generated based on historical data are shared with the HR managers, to improvise various strategies and modify existing policies to reduce the increasing absenteeism in the organization. This step saves resources, time, and unnecessary expenditure and also ensures maximum working capacity and productivity of workers.
Forecasting Talent
Just like bridging skill gaps, predictive HR analytics help in forecasting which employee and particular skill set can be a success for the organization. The organizations can predict which new hires are more likely to be a success after evaluating their background experiences, past projects, and skills. HR managers tend to focus on retaining these types of new hires and talents.
Managing Absenteeism:
Predictive analysis in human resources may be employed to predict employee absenteeism and the ways to reduce it. The predictive analysis algorithms generate multiple theories and validate them to find out the possible reasons for absenteeism and increased leaves. These hypotheses generated based on historical data are shared with the HR managers, to improvise various strategies and modify existing policies to reduce the increasing absenteeism in the organization. This step saves resources, time, and unnecessary expenditure and also ensures maximum working capacity and productivity of workers.
Managing HR Budgeting
HR budgeting is a crucial part of HR operations. The budget needs to be optimized for the proper allocation of funds for hiring, training, resources, and salaries. Predictive analysis in human resources works on the principle of machine learning (ML) and deep learning, which helps in forecasting the budget requirement according to the number of employees and the expansion of a business organization.
Predictive HR analytics aid in continuous and regular monitoring of whether the budget is over-utilized or under-utilized. Funds can be reallocated if any issue arises. What-if scenarios are run before making future budget strategies using predictive analysis in human resources.
HR Metrics Dashboard
HR metrics dashboard is an essential core of human resources planning and strategies. It is used as a tool that provides a basic platform for forming informed decisions within an organization, such as for the Human resources department. The three topmost functions of the HR dashboard are:
- To keep track: Regular monitoring enables HR to keep a track of all the ongoing activities going on within an organization and amongst employees. This regular tracking is done by the predictive analytics workforce metrics. Using predictive analysis and forecasting, new patterns can be predicted. This buys some time to address the incoming future problems before they influence the business market.
- To aid the HR manager in performing better: An HR metric dashboard helps the managing teams and managers of organizations to perform better. The report can give an idea about the necessary changes or significant developments within the teams. For example, an undue strain is exerted on the accounting department when there is a higher employee turnover. Managers, in such scenarios, are more likely to put their whole emphasis on employee retention and keep a track of all the future outcomes if they continue to lose their workers. Predictive analysis in human resources, thus forms the essential core of modern enterprises.
- To handle problems efficiently: The HR predictive analytics metrics dashboard also gives a chance to handle the problems more efficiently and with greater transparency. This transparency within an organization is well maintained by predictive analysis and forecasting tools.
How To Successfully Implement Predictive HR Analytics?
Predictive analysis and forecasting are the new faces of technology. Companies are striving for the successful implementation of predictive HR analytics. Here are some of the ways they can inculcate this into their organizations:
- Definite business objective: HR leaders and managers should have definite company goals. Priorities should be set keeping in mind the long-term desired goals. Moreover, the company members should determine all the metrics that will help in the achievement of the desired goals.
- Familiarity with HR analytics: Predictive HR analytics needs to be fully understood by the companies and their managing teams to be benefitted to the maximum. HR professionals can increase their understanding level through diverse learning options. They should fully grasp the fundamental background algorithms to ensure the successful implementation of strategies in favor of the company as well as in the favor of employees.
- Harnessing the power of predictive analytics and forecasting: HR predictive analytics can be applied to specific objectives and hence maximizes the outcome percentage. An example in this regard is the incorporation of HR predictive analytics in designing an effective career development program. This step addresses the gaps in the company’s working efficiency and future competency needs. This allows the managing teams to train their employees in the desired way.
Predictive Analytics Is The Ultimate Game-Changer:
After going through all the possible aspects of predictive HR analytics, it is safe to say by applying predictive analysis and forecasting tools, astonishing results can be attained. This list of applications is just a start of the possibilities that predictive analysis and forecasting help us with.
Predictive analysis in human resources is one of the key trends to follow in the emerging technology era and there is a pretty good reason behind it- your business needs it more than ever before, especially to survive in this competing environment. Although we are never too sure what is going to happen in the future, predictive analysis and forecasting help us in identifying the trends and patterns that may fall in the upcoming days.
These patterns assist in calculating the probabilities and possibilities, which help the HR leaders to run their organizations in a much better way. Our environments are being restructured by predictive analytics algorithms. All hail to the emerging technologies that are making our lives easier!