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

CTO and Founder of call miner. Responsible for strategic direction through business development, research and artificial intelligence.

If you take a step back to look at the motives behind the Great Resignation, one thing is clear: Employees don’t feel engaged or valued in their jobs. In fact, according to Gallup, disconnection can cost a company of 10,000 people $60.3 million a year. This can stem from a lack of development opportunities or feeling disconnected from personal relationships in your workplace, but without action from business leaders, employee attrition rates will continue to rise.

However, this action must also be accompanied by a change in mentality. Many organizations focus on correcting what employees are doing wrong. What if we focused instead on identifying what people are doing straight? Could we use positive actions to validate behaviors and empower others?

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

Here are three ways AI, automation, and data-driven techniques can deliver more effective personal feedback loops with employees building genuine connections and stronger relationships.

1. Success story modeling 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 those insights to improve CX (in other words, to benefit customers) . And while that’s important, there are also opportunities to understand how employees are performing. By analyzing these customer/employee conversations across channels and at scale, managers can gain insight into the behaviors of the most successful employees. Using those success stories can lead to more effective, personalized coaching and training for the rest of your workforce.

For example, when analyzing conversations with their customers, one of our clients found that empathy and understanding were key traits of their most successful sales reps. If they had relied on a manual review of these interactions, they likely would not have been able to identify these soft skills as having a positive impact on CX.

These insights enabled the company’s management team to take action and make better decisions about how to recruit, train, and reward their employees. Employees were not only motivated to learn from what their peers were doing right versus what they were doing wrong, but having trained an entire field on these best practices, customers were experiencing 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 collect important data on the job about what can be improved. Like voice of the customer (VoC), collecting data on voice of employee (VoE) can lead to better retention and job satisfaction.

At that same company, their training programs weren’t just for employees. A feedback loop was established so that employees could also give feedback on how effective they thought the training programs were for them. By capturing this information, the company was able to understand where programs could be further improved and, furthermore, how supervisors could get better at delivering or executing training.

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

3. Using data to find stars that fly under the radar

With larger teams, it can be easy for managers to focus on general KPIs, compliance initiatives, or quality assurance (QA) goals. As a result, they may only analyze a handful of their direct reports’ interactions and only talk to them when something goes wrong. That approach lets the vast majority of interactions fall by the wayside.

Automation technology and AI can help managers and supervisors scale these efforts to not only look for potential areas for performance improvement, but also find star employees who might otherwise go unnoticed. For example, a member of the customer support team may get high marks when it comes to Net Promoter Scores (NPS), but digging deeper may reveal an approach or technique that continually keeps customers from churning and deserves additional recognition. This particular employee might be ready to onboard new hires to have their behaviors shared with the larger team or manage a team themselves.

KPIs are a great performance indicator, but they can only go so far. Identifying the unexpected areas where your best people excel can create a clearer picture of where they fit in the future of the organization and can lift people who might otherwise struggle to move forward.

Data-driven information scale management capabilities

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

Automation and AI can help scale some management capabilities by providing insights into how employees are performing, discovering how and why some employees excel, and using those straight behaviors to train others. By acknowledging the big moments, creating personalized coaching, and enabling two-way feedback loops, companies can avoid the common disconnect traps that led to the Great Quit in the first place.

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