Three data-driven ways to create positive feedback loops within your workforce

CTO and Founder at CallMiner. Responsible for the strategic direction of business development, research and artificial intelligence.

If you step back to observe the reasons for the great resignation, one thing is clear: employees do not feel involved or valued in their work. In fact, according to Gallup, disengagement can cost a company of 10,000 people $60.3 million a year. This may stem from a lack of development opportunities or a sense of disconnect from personal relationships in the workplace, but without action from business leaders, employee attrition rates will only continue to rise. increase.

However, this action must also be accompanied by a change of mentality. So many organizations focus on fixing what employees are doing wrong. What if we instead focused on identifying what people do to the right? Could we use positive actions to validate behaviors and train others?

Technologies like AI can help organizations (and their managers) access the data and insights they need to not only keep pace with unique employee needs, but also to provide positive, personalized feedback and feedback. opportunities that keep employees engaged and happy.

Here are three ways AI, automation, and data-driven techniques can provide more effective personal feedback loops with employees who build authentic connections and stronger relationships.

1. Model success stories with Analytics

Many organizations rely on AI to understand the conversations taking place with customers, prospects, and other key stakeholders, but traditionally organizations have focused on using this information to improve CX ( in other words, for the benefit of customers). And while this is important, there are also opportunities to understand employee performance. By analyzing these customer/employee conversations across all channels and at scale, managers can explore the most effective employee behaviors. Using these success stories can lead to more effective and personalized coaching and training for the rest of their workforce.

For example, by analyzing their conversations with customers, one of our clients discovered that empathy and understanding were the core characteristics of his top performing sales reps. Had they relied on a manual review of these interactions, they probably wouldn’t have been able to identify these soft skills as having a positive impact on the customer experience.

This information empowered the company’s management team to take action and make better decisions about how to onboard, train and reward their employees. Not only were employees motivated to learn from what their peers were doing right versus what they were doing poorly, but after training an entire field on these best practices, customers were seeing better results at scale.

2. Creating two-way feedback loops to prevent burnout

Once a new training program is introduced, technology can help determine its effectiveness and gather important field data on what can be improved. Much like the voice of the customer (VoC), collecting data about the voice of the employee (VoE) can lead to better retention and job satisfaction.

At this same company, their training programs weren’t just for employees. A feedback loop has been established so that employees can also give their opinion on the effectiveness of the training programs for them. By capturing this information, the company could understand where programs could continue to be improved and, additionally, how supervisors could improve their delivery or execution of training.

By empowering supervisors and giving employees a voice in the training process, the company has established a culture of trust, accountability and continuous improvement.

3. Use the data to find stars flying below the radar

With larger teams, it can be easy for managers to focus on overall KPIs, compliance initiatives, or quality assurance (QA) goals. As a result, they can only analyze a handful of interactions from their direct reports and only speak to them when something is wrong. This approach lets a large majority of interactions slip through the cracks.

Automation technology and AI can help managers and supervisors scale up these efforts not only to seek out potential areas for performance improvement, but also to find star employees who might otherwise be overlooked. For example, a member of the customer support team may score high on Net Promoter Scores (NPS), but further investigation may reveal an approach or technique that continually keeps customers from turning and merits further consideration. additional recognition. This particular employee might be ready to onboard new employees so that their behaviors are shared with the larger team or to manage a team themselves.

KPIs are a great performance indicator, but they can’t go any further. Identifying unexpected areas where your top performers excel can create a clearer picture of their place in the organization’s future and can uplift people who might otherwise struggle to progress.

Data-driven information scaling capabilities

It can be easy for organizations and leadership teams to get overwhelmed when onboarding new team members and managing their existing workforce, while considering how to give employees the training and culture they need to stay engaged and happy.

Automation and AI can help scale certain management capabilities by providing insights into employee performance, discovering how and why certain employees excel, and using it. to the right behaviors to train others. By acknowledging big moments, creating personalized coaching, and enabling two-way feedback loops, companies can avoid common disengagement pitfalls that led to the Great Quit in the first place.

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