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The Definitive Guide to AI in Performance Management: 2021 Edition

AI can transform performance evaluation and the experience for everyone involved.

The Definitive Guide to AI in Performance Management: 2021 Edition

AI can transform performance evaluation and the experience for everyone involved. We discuss seven benefits of AI in performance management.

The Covid-19 pandemic witnessed most businesses adopting new ways of working. Many employers went remote, impacting how employees communicate and interact with customers and their co- workers. While most organizations have reopened, employees continue to perform their jobs very differently.

So, how productive have organizations actually been through the pandemic? The economy is much stronger and almost at par with pre-pandemic levels – a critical indicator of productivity. That said, many businesses have struggled to cope or in some cases, even shuttered.

The key difference between organizations that thrived and organizations that wound up operations is their approach to managing talent, more specifically, workforce performance.

As we head into a new era of work, employee performance is at the forefront of organizational success. In the book, Time, Talent, Energy: Overcome Organizational Drag and Unleash Your Team’s Productive Power, Eric Garton and Michael Mankins explain that the companies in the top quartile of performance are 40% more productive than the rest. They are the very best when it comes to managing scarce time, talent, and energy. In fact, it is this chasm that determines the competitive advantage of businesses.

Decoding Performance Management in 2021

As businesses evolve, performance management practices should too. Unfortunately, many HR departments still rely on traditional approaches to measure employee contribution. Apart from being tedious and stressful, annual performance reviews have no effect on how employees do their jobs.

So, why do we still have annual reviews? Well, the easy answer is that most organisations have always conducted employee evaluations this way and change is never easy. Annual performance reviews are a relic of the industrial era where organisations attempted to take a more employee- centric approach to human resource management. But the events of this past year have created new challenges and opportunities for organizations that traditional performance processes simply cannot cope with.

Let’s look at a few factors that are driving the demand for better performance management practices:

  1. The Growing Skills Divide
    While the employment numbers might suggest that unemployment is higher than pre- pandemic levels, industries are still reporting difficulties in finding skilled employees. A recent study by Deloitte reveals that this might be a $1 trillion problem for the manufacturing industry.
    Similarly, the technology industry has also reported a massive shortage of skilled workers. 50% of CIOs believe that the lack of skills is making it difficult for their companies to adapt to changing business needs. 60% say that their skills shortage is making it harder for their companies to remain competitive.
  2. Employee Experience Takes Center Stage
    The pandemic exposed gaps in organizations’ strategies and one area that stood out was the employee experience. A recent survey that polled 500 HR leaders found that 92% believed employee experience will continue to be a top priority in 2021 and beyond. The way organizations shape their employees experiences in both physical and virtual settings has become paramount.
    Employee expectations from their employers are now different. Despite the relaitively high unemployment rates, employees have become more selective about their prospective employers.
    Countless studies have demonstrated that individual moments or micro-experiences in employees’ interactions with their work and workplace play a major role in how they feel about their employer’s purpose, brand, and culture. Performance management is a big part of this experience. Objective, data-driven performance management builds employee trust and motivates them to bring their best selves to work everyday.
  3. Industry 4.0
    The business landscape has evolved dramatically over the past year and half. There is a sea change in the way organizations approach technology, digitization, and new working models. During the pandemic, digitization has been one area that witnessed massive growth – everything from customer service to supply-chain to healthcare have been transformed. The adoption of artificial intelligence (AI), machine learning (ML), and robotic-process automation (RPA) to improve operations is at an all-time high.

The disruption has also opened the floodgates to innovation. Consider this, in the third quarter of 2020 alone, there were over 1.5 million new business applications in the U.S. – almost double the figure for the same period in 2019. A McKinsey study found that businesses moved 20 to 25 times faster than they thought possible on things like building supply-chain redundancies, improving data security, and increasing the use of advanced technologies in operations.

Changing business priorities have created an imperative for organizations to reconfigure their operations – and an opportunity to transform them. To the extent that they do so, greater productivity will follow.

It’s become clear that traditional performance management practices and tools are quickly becoming redundant as organizations grapple with these changes. As organizations look to bring transparency into their performance processes and design structures to support long-term business goals, AI can prove to be a potent enabler.

The Role of AI in Performance Management

HR is no stranger to artificial intelligence (AI). Recruitment, learning, and the employee experience is already being shaped by AI. Performance management is the next best area for AI integration. As a process, performance management lends itself well to the application of technologies like AI and ML because it’s largely intended to be data-driven.

The limitations of traditional approaches to performance management are centered around bias, inaccuracy of performance data, and the long turn-around time. Most employees are rated on the basis of recent achievements that their managers or supervisors remember instead of their year- round performance. Further, the entire process of annual reviews or traditional performance management is focused around measuring rather than improving. So, it naturally fails to capture employee potential.

Organization’s Goals and Values  

Figure 1: The traditional approach to performance management

With AI, organizations can address all of these challenges and more. They can use their technology to design better performance management processes.

Let’s take a look at some of the benefits of using AI in performance management.

7 Benefits of Integrating AI into Performance Management

As a process that thrives on accurate data collection, performance management is ripe for disruption. With the average number of tools and solutions in the workplace increasing drastically since the pandemic, AI and ML-based performance management software can tap into a variety of data sources and virtually countless data points to help HR professionals design better performance processes.

Here’s a look at the top seven advantages of using AI in performance management:

Predict Employee Performance

Thanks to AI, organizations can begin to predict employee potential even before they are hired. AI-based hiring assessments can provide employers with comprehensive data around future employee performance and role-fit. AI-based competency assessments and psychometric evaluations (like the ones we offer!) help employers gain a better perspective of a potential employee’s capabilities and strengths.

In the workplace, AI-enabled performance monitoring tools can help talent professionals and line managers predict how an employee will perform with a specific task. For instance, an AI performance solution can tell Joe’s manager that he makes X number of mistakes on a project with a complexity of level 2. This equips Joe’s manager with better context around his performance. He can then use these insights to deliver relevant learning or coaching interventions.

The ability to predict employee performance with AI holds tremendous promise for talent management. Armed with objective data around an employees’ capabilities, productivity, and skills, talent professionals can transform organizational performance.

Eliminate Bias or the Halo Effect
Performance management processes have long been fraught with bias and prejudice. These biases are well-documented, conscious or unconscious behaviors that unfairly influence the assessment of an employee’s contribution. While biases like race and gender are easy to spot, others are more ephemeral and may be harder to identify.
Humans’ logical fallibility is detrimental to objective performance assessment. AI can seamlessly tap into all employee productivity touchpoints and analyze their performance in a more objective and meaningful context. These assessments can take place in real-time and flag behavioral or performance changes well before they become a business challenge, allowing line managers and talent professionals to address underlying causes of performance drops and design relevant interventions.

Real-Time Performance Management
Real-time performance management or 360-degree performance management is the process of monitoring employee performance on an on-going basis throughout their tenure with the organisation. Performance tools that leverage AI and automation for data collection and analysis and provide real-time information around employee performance.
Netflix transformed its talent potential by instituting a 360-degree performance management process.
AI brings more flexibility in the way employers approach performance management. It allows organizations to continuously capture insights from both structured (think calendars, time logs, and collaboration tools) and unstructured data (text in emails, messages, and video calls) to shed light on productivity levels, employee sentiment, and engagement in real-time.

Improve Feedback Loops
Manager or supervisor feedback is perhaps the most critical element in performance management. In the context of workforce composition, feedback becomes even more important as younger generations of workers expect regular feedback with shorter turnaround times.

Research indicates that employees would like 65% more feedback than they currently get. One of the main reasons why employees don’t receive enough feedback is because managers are typically strapped for time. Providing personalized, candid, and objective feedback on a regular basis can become overwhelming for most managers.

This is where AI can help. AI-based performance tools collect productivity and performance data in real-time, enabling continuous feedback loops. This helps managers have more constructive conversations with their reportees and drive long-term behavioral change.

Improve the Employee Experience
AI-based performance systems are critical to the employee experience. Regular feedback, unbiased decision-making, and more personalized coaching opportunities are perhaps the most important influencers of employee experience in performance management.
AI-based performance tools can help organizations perform pulse surveys and analyze responses to determine overall employee sentiment. They can identify factors that improve or impair the employee experience in the context of performance management.
They also add the much-needed level of transparency that allows employees to understand how they are progressing in their careers. This again feeds into more productive feedback conversations that enable employees to align with organizational objectives. Ultimately, these factors lead to a better employee experience.

Deliver Better Learning Outcomes
As the collective thinking around employee performance evolves, AI solutions offer organizations the opportunity to apply performance insights to improve business outcomes. AI-based solutions can identify skills and knowledge gaps that hinder optimal employee performance.
By providing accurate performance data, AI solutions enable talent teams to design more relevant learning interventions to address key skills and knowledge gaps. In the long run, this translates to better profitability, higher employee satisfaction, and improved organizational capabilities.

Leverage I/O Psychology to Drive Continued High-Performance
AI-powered performance management solutions can do more than just measure and analyze performance. Solutions backed with sound behavior science can help organizations integrate gentle “nudges” to drive continued behavioral change. For instance, AI-solutions can nudge managers at the right time to provide feedback.

These solutions integrate easily with other workplace software to determine the best opportunity to send a “nudge” that inspires action.

While the points we’ve mentioned above are in no way exhaustive, they capture some of the most important benefits that organizations can expect from their AI-powered performance management system.

That said, we’d like to conclude by stating that technology is not your silver bullet. The best technologies can fail when there are cultural problems embedded within an organization. Technology can help design better performance management processes and practices but it is no substitute for human-led training and coaching.

As you embark on your journey towards better performance management, remember to communicate frequently and freely – after all it is what will help you engage your employees with your performance management process and make the most out of AI.