This article was published on Forbes.
In today’s fast-paced corporate world, performance metrics have taken center stage in evaluating an employee’s worth and contribution. Dashboards are illuminated with real-time data, charts meticulously track the trajectory of sales figures, and key performance indicators (KPIs) calculate productivity down to the last decimal. It’s a data-driven era, and metrics are seen as the ultimate measure of an employee’s performance. But is this the whole story? No. Not even close.
As we dive deeper into the intricate landscape of organizational success, a compelling argument begins to emerge: Behaviors matter more than metrics.
Measuring What Truly Matters
Since the 1990s, organizations have eagerly adopted corporate performance management frameworks, including balanced scorecards, KPIs and objectives and key results (OKRs), as the bedrock for aligning strategy with execution. These frameworks have become the stars of board meetings and management discussions, providing the compass for achieving organizational goals. In recent years, a noble attempt was made to extend these frameworks to frontline employees. Unfortunately, this strategy often fell short of expectations. Why? The missing piece of the puzzle was employee engagement.
The Engagement Dilemma
Frontline employees often found it challenging to relate to the metrics presented to them. While senior leadership may have found KPIs and OKRs motivating and insightful, frontline employees frequently regarded them as abstract figures with little relevance to their day-to-day responsibilities. The result? Disengagement.
To tackle this engagement dilemma, organizations explored advanced gamification solutions. They aimed to make KPIs more engaging by gamifying them. However, gamification alone didn’t address the root cause of performance issues—employee behaviors. A mere layer of gamification wasn’t enough to drive meaningful behavioral change.
Connecting Metrics To Behaviors
The key to unlocking true performance improvement is in connecting metrics to the behaviors that underpin them. Consider this scenario: a sales representative’s performance metric of conversion rate (lead to opportunity) dropped. That metric on its own is not enough to drive an action for improvement. However, if you identify the reason, or root cause behavior, such as not asking enough clarifying questions at the beginning of the call—you can impact this behavior through targeted actions. These actions can range from training using a role-play simulation, creating a challenge focused on asking more questions or coaching with a shadow call to help improve.
AI’s Transformational Role
This is where artificial intelligence (AI) emerges as a game-changer. AI has revolutionized the way we analyze employee performance. Instead of solely focusing on end results, AI delves deeper into employee interactions and behaviors. It deciphers patterns and nuances, shedding light on why certain metrics may be underperforming. For instance, AI might reveal that an employee struggles with handling escalated customer calls, leading to extended call durations and decreased customer satisfaction.
By harnessing technologies like natural language processing (NLP), generative AI (GenAI) and conversation intelligence, AI efficiently, organizations can efficiently identify behaviors that require improvement at scale.
Engagement And Self-Reflection
Once these behavioral insights are at hand, the next crucial step is cultivating engagement and self-reflection among employees. While managers providing feedback is valuable, authentic growth takes place when employees themselves recognize and comprehend their performance gaps. AI plays a pivotal role in this regard by offering personalized feedback. It empowers employees to acknowledge their strengths and identify areas in need of improvement.
Moreover, envision micro-surveys, in which employees provide their opinions on their circumstances. This not only elevates engagement but also instills a sense of control, granting employees the agency to steer their own development.
Coaching And Alignment
With a crystal-clear understanding of behavioral gaps, managers can provide more targeted and impactful coaching. Instead of generic training sessions, coaching can zero in on specific behaviors, ensuring that employees receive tailored support. Furthermore, by aligning coaching sessions with AI-driven insights, organizations stand a better chance of effectively bridging performance gaps.
Importantly, the human element remains indispensable. It helps prevent AI alienation and brings human empathy and creative problem-solving into the equation, surpassing the confines of standardized playbooks.
Adaptive Micro-Learning
In a diverse working environment like a contact center, the one-size-fits-all approach falls short. Enter adaptive training driven by AI. This approach guarantees that employees receive training tailored to their unique needs. For example, if an employee excels in technical knowledge but struggles with soft skills like communication or empathy, adaptive training modules can be designed to enhance these specific areas. This personalized approach ensures that employees are not just trained but are trained effectively.
Conclusion
In the ever-evolving landscape of contact centers and contemporary organizations, it’s critical to look beyond traditional metrics. By harnessing the power of AI, we can attain deeper insights into the behaviors that drive these metrics. With the right tools and strategies in place—encompassing engagement, self-reflection, targeted coaching and adaptive micro-learning—we can empower our employees to not merely meet but exceed their potential.
Metrics, while informative, no longer stand alone as the ultimate measure of employee performance. Instead, behaviors take center stage, guiding organizations toward a brighter future where employee engagement and growth drive success.
The goal is to create a performance experience, one that is guided, personalized and engaging.