“The continuous process of improving performance by setting individual and team goals which are aligned to the strategic goals of the organization, planning performance to achieve the goals, reviewing and assessing progress, and developing the knowledge, skills, and abilities of people.”
Introduction
Does your organization have a focussed employee evaluation system in place? You must be thinking that, a focused employee evaluation is related to the subjective opinion of the reporting manager and hence the process remains utterly flexible. But, certain HR aspects remain to be far from what we think! In fact, software process interventions have evolved largely to transform the business outcomes associated with HR. Let’s see how AI-based software frameworks have changed the perspective of performance management in any business.
But, what is employee performance management all about? Taking a quick look at some of the basic concepts, it is understood to be a strategic goal setting process, while addressing critical function areas related to employee performance. But, what does a performance system critically review? Is it an information exchange process on a structured note? Deciding on individual productivity is the first step while aligning the business goals with individual career goals remains to be the last one.
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Role of AI in Employee Performance Management
A survey done on the majority of organizations reveal that, although performance driven data drives the technology of appraisals, data feeds are often incorrect as it gives inaccurate results. Surveys conducted by reputed HR schools like SHRM prove that a majority of the performance review mechanisms remain to be inaccurate. Going through valid research surveys it is reported that approximately 2,44,000 employees had undergone performance reviews for 2 million hours so to say! But, does the huge time engagement really improve the efficiency of the process?
What Are the Major Benefits of Using AI Driven Software?
Many of the industry based HR experts, reveal that AI driven software primarily rely on data, and hence reduces human error to a large extent. A data oriented result remains to be less biased besides improving the scale of individual performances. Automation of the data collection process remains to be advantageous, as it helps with managing the value of data. Therefore, does the automated process produce data driven projections? Conventional performance reviews are executed on the basis of the availability of limited data and certain fixed performance indicators.
AI-based performance management software reviews, on the contrary, gather data from various authentic sources, analyze them and strategically forecast the performance not only based on the current period but how the individual employee has improved his performance over a period of time. This gives a more accurate picture of the employee’s potentiality and how it can be improvised in relation to organizational development. It is interesting to note that traditional performance management reviews have been mostly periodic reviews within a majority of organizations. AI-based performance management reviews, however, remains to be an on-going process which helps the managers to provide a continuous collection of data from various sources. This helps the managers to analyze on the basis of accurate data available and in turn, give quick and concise feedback on the individual performance. Research suggests that up to 60% of employees prefer continuous feedback mechanisms.
Can Automated Performance Reviews Bring Out the Best Advantage?
Is it that, software driven performance process manages to give good feedback for any employee concerned? Previously, managers had to rely on employees’ version of their performance and to some extent their own subjective opinion on a particular review process. However, automation initiated through AI based tools, can make the process quite interactive as well as transparent.
Going forward, it is explained that AI-based performance management software has helped the managers to establish a performance oriented work culture within the organization. Creating user engagement on a large scale, behavioral assessment tools are deployed to ensure employee competence. Nevertheless, an employee needs improvement and accordingly managers can arrange for training, learning and development programs in accordance to the criteria being measured through automated performance reviews.
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AI in Measuring KPIs
Do you know that stalwart US brands like Microsoft have recently started to implement different technologies for measuring employee performance working in their organization?
In a drive to enhance efficiency, technology driven key performance indicators (KPI) parameters are being put in place while, Microsoft’s Workplace Analytics lets employers monitor individual’s data. Automated time-sheets on the other hand, drive a clear reflection on employee engagements. Before, we take a holistic view on trends pertaining to the US for instance, let’s take a look at another retail behemoth like Walmart. How has Walmart been doing it? In fact, Walmart has patented its technology platform to generate automated reports on employee performance. Innovative sensor oriented sound mechanisms are put in place to capture employee interactions within the work environment.
Best AI-based Employee Performance Management Software
Some of the best AI-based employee performance management software available in the market are:
- BambooHR
- Lattice
- 15Five
- Paylocity
- Leapsome
- Employment Hero
- PerformYard
- ADP Workforce Now
- HiBob
- FlowyTeam
Conclusion
Post-pandemic, AI-based performance management software has gained momentum significantly. Employee Performance Management has become one of the most crucial parts of Human Capital Management (HCM) which broadly includes the process of planning, monitoring, developing, rating, and rewarding an individual employee’s abilities. AI interventions have transformed similar processes across business verticals while ensuring continuity of performance-driven through consistency as well.
[To share your insights with us, please write to sghosh@martechseries.com]