Human capital forms the foundation of any organization, and employee performance has a significant impact on the bottom line. In fact, research indicates that a five per cent increase in employee engagement is linked to a three percent growth in revenues in the subsequent year. Yet, most HR departments struggle in the management of employee performance.
Employees often perceive performance reviews as a process that inclines heavily towards traditional practices (Bell Curve Method), is subjective and consumes time. If they are not satisfied with outcomes, their morale, productivity and performance may plunge. Consequently, it may lead to high turnover. However, it is an important exercise given that it creates a high-performing culture and motivates top-performing employees. It enables the organization to identify skill gaps, develop learning and development programs, retain employees and do succession planning.
Most organizations have realized that conventional performance review systems are outdated, do not capture real-time performance, and fail to provide timely feedback and improvement opportunities to employees.
Predictive analytics can be applied to the workforce to identify traits/patterns that account for bad or good performance on an individual and team basis. Since analytics is an amalgamation of powerful mathematical algorithms, it also gives objective insight into their work preferences and the factors that drive their performance. An article published in The Times of India talks about a case study on how analytics helped a manufacturing firm predict what was wrong with employee performance. Using analytics, this company discovered that morale of ten employees was down due to their issues with manager. The management quickly stepped in to resolve the situation and take preventive measures before the employee performance deteriorated further.
Adani Group has hired an analytics startup firm Vahanalytics, which uses machine learning for driver profiling, behavior and performance. The startup will track the vehicles deployed at Adani Group’s Mundra Port and capture information on whether drivers have been speeding, taking sharp turns or not following driving norms. These reports will help Adani Group to predict the performance factors of drivers and make timely innervations in regards to their training.
With the help of analytics, HR can also identify engagement activities which have the maximum and minimum impact on employee performance. This exercise has two-fold advantages. One, an organization can direct their investment towards initiatives that generate the highest interest in the engagement levels. Two, an organization can define measurable metrics that co-relate engagement and performance.
Since organizations usually review employee performance annually, it leaves little time for HR to act on possible flight risks. However, performance analytics gives real-time information to take timely decisions. HR can recognize red flags of performance and predict which employees fall in the highest flight risk category. It can then either discuss the matter directly with the employees or implement tailor-made retention programs to re-engage them. When HR can gauge employee performance from analytics, succession planning also becomes easier. It can anticipate promotions, transfers and firing in advance. Accordingly, it can forecast workforce requirements and work towards filling the open positions.
HR is also discovering advantages of analytics in predicting employee performance and improving quality of hiring during recruitment. Analytics can mine data on candidate’s personality, behavioral traits and skills to throw useful insights into whether he or she would be the right fit for the organization.
Gathering data about your recruiting sources is the first step to honing your strategies in on what works. Once you have enough recruiting data, you will be able to predict which sources your best candidates come from, and invest your time, energy, and money into those sources that yield the best return.
A good screening system will not only help you remove unfit candidates from the get-go, but it will provide data on the value of your various recruiting sources.
In today’s hiring environment, it can be difficult to tell from a resume, a cover letter, or someone’s social media profile whether they’re a good match for the job –particularly if you don’t know the right factors to focus on.
Now that you have recruited from the best pools and screened out the least qualified candidates based on predictive analytics, you must choose a specific candidate to hire.
Use psychometric profiles to collect data and help with selection. When you have enough data to become predictive, you will understand which types of people are attracted, well-suited, and well-matched to your corporate culture and the roles you’re looking to fill. You will find a certain type of person, with certain characteristics, who thrives in your organization.
Predicting the employees who will thrive at your company brings a multitude of benefits. Those employees will perform better, respond well to your distinct methods of training and coaching, and will likely stay at your organization longer.