The ability to swiftly adapt to new technologies and emerging industry trends is paramount. However, many organizations face a persistent challenge: skills gaps. These gaps can block an organization’s achievements for their vision and mission.

This widening gap between in-demand skills and current workforce skills slows down productivity and innovation compared to competitors who advance and improve their operations and processes to promote sustainability and growth. And when employees lack essential skills, tasks can take longer to complete and the quality of work may suffer. This inefficiency can lead to missed deadlines and reduced output, ultimately affecting the company’s bottom line.

Through experience we’ve seen how data-driven tools can provide a formulaic approach to assessing and analyzing skills gaps. With advanced analytics and big data, learning leaders can determine what skills to train their employees on and how to plan accordingly to develop a skilled workforce. In this article, we’ll evaluate how to effectively use data-driven methods to close skills gaps, enabling organizations to be agile and resilient.

Understanding Skills Gaps

Research from McKinsey & Company shows that 87% of companies globally do not have the skills they need soon. For instance, a high-tech company may discover that their workforce’s skills are obsolete, and that their customer service team may need upskilling on how to apply artificial intelligence (AI)-based tools in their role.

Here are some of the reasons for skills gaps:

• New and emerging technologies like generative AI and augmented reality (AR) have increased the pace of change, necessitating ongoing employee training to upskill and reskill their workforce. However upskilling the entire workforce on how to apply these advanced technologies can be expensive.
• Colleges/universities often fail to ready graduates for the workplace, and do not match their curricula with in-demand industry skills — hence a group of fresh graduates who are not workforce ready.
• Stressed and frustrated employees, who may feel underqualified for, can be more likely to leave an organization, increasing attrition rates and decreasing talent.

Identifying skills gaps with assessment tools.

Data analytics aim to identify a workforce’s current skills and any weaknesses or areas of improvement. Learning leaders can use assessment tools like performance metrics, employee feedback and project outcomes to identify learning needs.

Here are some of the assessment tools learning leaders can use to gain insight for closing employee skills gaps:

• Data for employee performance: This might involve past areas for improvement, project completion rates and productivity measures. This data analysis helps to provide insight into overall employee performance trends where delinquencies and/or lagging skills are most common.
• Self-assessments tools: can help assess employee skills and competencies regularly. A natural complement to this subjective data is objective performance data, all of which give a full picture of the skills landscape.
• Learning management systems (LMS): can monitor how much an employee is actively engaging with delivered training programs and courses. They can refer to data from those systems to determine which skills are being developed or still need improvement.

Skills data collection and analysis tools and technologies.

These tools are designed to help you collect skills data:

• Data analytics software: this can include tools like Tableau, Power BI or Google Data Studio, which can allow businesses to see and analyze their results. These platforms are useful for trend identification and data-driven decisions.
• Human resource information systems (HRIS): HRIS solutions with more comprehensive data can be integrated from other sources with that of skills management, such as Workday or SAP SuccessFactors to get a 360-degree view of the skills and performance of many employees through their HRIS platforms.
• AI and machine learning: The use of AI and ML can help to predict the needs of future skills based on the data available to us. These innovations can crunch mountains of data to predict the future course of the industry and advise what should be included in training programs.

If used well, these measurement tools can improve the accuracy and effectivity of addressing current skills gaps in organizations. This ensures the best to nurture employee development and therefore achieve organizational success in totality.

Data-Driven Best Practices for Closing Skills Gaps

Closing skills gaps is essential for maintaining competitiveness and fostering employee growth. Here are three data-driven techniques to consider when closing company skills gaps:

Personalized L&D programs based on data insights.

• Individual skill assessment: Collect data on employee performance and skills through assessments and surveys.
• Customized learning plans: Use the data to create tailored training programs that address specific skill deficiencies.
• Continuous feedback: Implement regular feedback loops to adjust training programs based on employee progress and changing needs.

Predictive analytics for future skills requirements.

• Trend analysis: Analyze industry trends and organizational data to predict future skills needs.
• Skills gaps forecasting: Use predictive models to identify potential skills gaps before they become critical.
• Proactive training initiatives: Develop training programs that prepare employees for future demands, ensuring the organization stays ahead of industry changes.

Predictive analytics can help organizations be proactive, rather than reactive, in addressing skills gaps, ensuring long-term success and adaptability.

Leveraging an LMS to track progress and effectiveness.

• Centralized learning platform: Use an LMS to manage all training activities and materials in one place.
• Progress tracking: Monitor employee progress through detailed reports and dashboards.
• Effectiveness measurement: Assess the impact of training programs using data analytics to refine and improve them continually.

An LMS provides a comprehensive solution for managing training and development, making it easier to identify areas of improvement and ensure training effectiveness.

The Importance of Data-Driven Approaches

Addressing specific gaps, such as cybersecurity skills gaps, is also crucial for ensuring the security and resilience of organizations in an increasingly digital world. Using data-driven techniques to close skills gaps can offer a powerful solution for organizations striving to stay competitive in a rapidly evolving market. By leveraging data, companies can accurately identify skills deficiencies, tailor training programs and measure the effectiveness of their interventions.

This approach can not only enhance individual employee performance but also boost overall organizational productivity. Embracing data-driven methods can ensure a more agile and adaptable workforce, ready to meet the challenges of tomorrow. As we move forward, continuous learning and data-informed decision-making can be key to closing skills gaps and driving sustainable growth.