Mastering acquisition and talent management do not guarantee retention. No tech company is immune to turnover. Dropbox reports that their workers leave after 2.1 years. For Uber, employees stay in the company for an average of 1.8 years, despite the office’s generous package, benefits, and amenities. For Tesla, the average tenure does not cross 2.1 years.

On the flip side, companies with the shortest typical employee tenure have the most aggressive talent acquisition.

Not addressing employee turnover will adversely impact productivity, bog down coworkers and their morale, create bottlenecks for talent management, wasting hours and dollars.

From our research, three factors cause attrition. The lack of internal growth opportunities, low employee satisfaction, and a fundamental disconnect due to a lack of respect.

Talent Management Tech: Making Attrition Strategy Predictable and Preventable

Using the right strategies and tools will ensure that the talent management team has candidates with the right skills and fit for your organizational culture.

Tracking individual employee journey at scale

Talent management tech tracks micro and macro-level trends within the workforce. It can help identify key individuals you can invest in learning and development, skill-building programs and check their response for feedback.

If insights show improvement, then you are on the right track. If they do not respond, it is an opportunity to return to the drawing board and find strategies to turn them around.

Sourcing actionable data and addressing problems before they emerge

User-sourced salary information and company deep dives provide talent management insight into market conditions, allowing talent acquisition to make more competitive offers, understand hiring trends, and create a brand for the company.

It further allows them to assess potential risks for departure by empirically evaluating its pay structures and reading internal reviews. Aggregating data can assist in making changes.

Artificial intelligence-driven real-time predictive analytics data can help talent management identify sentiment patterns of employees at risk of leaving. After understanding the areas of concern, talent management can proactively resolve issues to prevent early departure.

Additionally, integrated HR chatbots can nudge satisfied and happy employees to share reviews on external platforms to correlate your internal employee happiness index with the aggregated scores on such platforms.

Personalizing experiences for employee satisfaction and success

HR chatbot can practice empathy using customized questions to make employees feel like their voice is being heard. An outlet can mitigate burnout, give talent management a chance to solve issues before your top talent leaves and provide them with insights requiring their bandwidth.

While AI technology is significant in helping talent management improve the company’s productivity, talent intelligence can assist in acquiring a motivated and skilled fit to join the company.

How Are Companies Using AI to Arrest Attrition?

Here are a few companies using AI-driven technology to improve their talent management practices.

Case study 1 – Automating employee feedback collection

Research shows that at least 50% of HR partners collect, track, and analyze employee feedback, which does not add value to HR partners’ and employees’ growth. The data aggregation could be done effectively in real-time. Surprisingly, employees are as receptive to chatbots as HR partners.

AXA Affin HR team interacts with almost 1,000 employees in real-time with chatbots. They achieved an 87% response rate with their AI chatbot, saving thousands of work hours for HR partners who are now applying themselves in solving their workforce’s problems.

Case study 2 – Facilitating upskilling of employees with job roles at risk

Talent intelligent platforms can assist talent management in identifying job roles at risk of disruption. Its dashboard shows job roles that may be useful for your company’s business strategies and the possible career pathing with new programs and certifications. Talent management can upskill/reskill existing talent instead of acquiring new talent, saving capital.

A global enterprise introduced two digital initiatives to facilitate employee skilling. The first initiative allows its employees to assess their digital knowledge and create customized learning plans on an app. The app sends employees learning assets to help them unlock their innovative creativity at scale.

The second initiative allows employees to collaborate and share innovative solutions on an internal platform. It uses gamification to incentivize the building and sharing of assets with wide applicability. Employees can learn from one another and apply their new skills.

Companies of any size can use this collaborative approach to give employees access to more resources and help them build the skills they need to succeed.

Case study 3 – Monitoring at-risk employees

Altimetrik’s employee to HR partner ratio is 400:1, which presents near-impossibility in tracking at-risk employees. Using a chatbot as a proactive reach-out engine, integrated into the company’s intranet collects data on employees’ concerns.

Though the data may not help the talent management team prevent high-risk talent from leaving, they will at least get a headstart on taking preventive measures before they are approached with a resignation letter.

Additionally, corporate intranets are using AI to process data and learn from it. A prominent technology outsourcing company operates an in-house built interactive AI entity to answer employees’ questions. The AI gathers insights into employees’ concerns, and it sends them more information that may interest them, like vacation policies, shifts, pay stubs, etc.

The possibilities for AI systems are undeniable. Large companies are implementing these tools to automate many processes. A talent intelligence platform like Draup allows you to look at the employee base and compare it against peers.

Additionally, the Hiring Opportunity Index deep dives into their skill sets and ranks them in new-age skills sets. By leveraging AI, talent stakeholders can empower themselves with real-time talent data and gain the upper hand in the talent war.