The Business Case for Measuring, Monitoring, and Improving Employment Impact: Attrition & Job Quality

October 28, 2024

Overview 

High employee turnover is a critical issue, especially in knowledge-based industries. Lunum’s analysis of 3,000 companies shows a strong link between lower attrition and improved job quality. Metrics such as Living Wage, Demographic Representation, and Opportunity by Seniority were key, with seniority showing the greatest impact. This highlights the importance of integrating employment impact metrics into human capital & resource management strategies to reduce turnover and improve performance. 

Background 

Employee attrition poses a significant challenge for many organizations, particularly in sectors where turnover rates can exceed 15% (Pallathadka et al., 2022) (Figure 1). This is especially critical for companies with high-skill, knowledge-based workforces—like those in IT, software, and telecommunications—that rely heavily on their employees. While various knowledge management tools have emerged to facilitate the creation, sharing, and utilization of knowledge within organizations, employees continue to be the primary custodians of this invaluable resource. The insights gained through hands-on experience are often difficult to institutionalize, store, or retrieve effectively. Consequently, the workforce emerges as the most vital asset for knowledge-based companies, with financial performance closely tied to workforce productivity (Sainju et al., 2021). 

Figure 1: Average attrition levels by sector (2024) 

As a result, the human resource practices of recruiting, training, and ensuring job satisfaction are critical concerns for many companies (Bezdrob and Sunje, 2021). Losing valuable employees can have significant repercussions, forcing firms to compete for talent against their primary competitors. The costs associated with employee replacement are estimated to be approximately 2.5 times an individual’s salary (Kaur, 2017). Moreover, the consequences of employee turnover can extend beyond simply finding a replacement. For instance, attrition can hinder a company’s ability to meet commitments and fulfill contracts.  Attrition can also contribute to fatigue and safety issues for the rest of the workforce. This may lead to the loss of customers, reduced market share, and damage to morale and reputation. Therefore, understanding the factors contributing to employee attrition can expedite the identification of factors that enhance employee satisfaction. 

A New Type of Analysis 

Recent advancements in data collection have introduced innovative sources of workforce information. Companies like Revelio now mine and process raw data from platforms such as Indeed and Glassdoor, generating estimates of key workforce metrics, including employee counts, job types, wages, and attrition levels. Lunum utilized this data from 3,000 companies to develop a statistical model that analyzed the relationships between attrition and eight employment impact metrics, which are part of the Impact Accounting framework and designed to measure job quality (Figure 2). 

Figure 2: Lunum’s Engine & IFVI’s Employment Impact Methodology  

This Impact Accounting Framework was a joint initiative between the Global Steering Group for Impact Investment and the Impact Management Project (initially incubated at Harvard Business School and later becoming IFVI) and aims to create financial metrics that measure a company’s financial, social, and environmental performance. In our analysis, we found statistically significant effects between attrition and Living Wage, Demographic Representation, and Opportunity by Seniority (Figure 2). The latter effect had the largest magnitude (Figure 3) and is visibly supported in the raw data, before modeling (Figure 4). 

Figure 3: Model Results – Coefficients/Slope 

Figure 4: Pre-modeling – Attrition vs Opportunity by Seniority 

Furthermore, when drilling down to sectors we can see specific patterns between Attrition and Opportunity by Seniority in the raw data which lead us to expand our model design to test for more granular relationships (Figure 5).  

Figure 5: Pre-modeling – Attrition vs Opportunity by Seniority (by Sector) 

The expanded model was able to capture several sector-specific effects for the three aforementioned impact metrics, most of which are statistically significant at the 0.05 level. (Figure 6).  

Figure 6: Model Results – Statistically Significant Sector Effects 

Summary 

Employees are the most critical asset for many companies and serve as important knowledge sources that directly affect operational efficiency. The cost of replacing employees is estimated to be approximately 2.5 times their base salary. Lunum’s analysis of 3,000 companies revealed a statistically significant effect between higher performance in key Employment Impact metrics and lower attrition rates. These effects differ by sector in both magnitude and significance level. Understanding these relationships and their governing dynamics can serve as a powerful tool for senior leaders, to help shape human capital management strategies.  

Looking Ahead.  

Measuring impact is a tool for transformation, driving better decision-making that creates tangible business value while benefiting workers, communities, and other stakeholders. Partner with Lunum to illuminate opportunity within your organization and value chain.  

About Lunum  

Lunum helps companies put a value on their values by understanding how complex value chains impact individuals, economies, and communities. We use data to help companies realize a return on investment in people and communities and recognize how their practices can have a positive impact on the world.  

For more information, please reach out to us: www.lunum.io or follow us on LinkedIn. 

REFERENCES 

H. Pallathadka, V.H. Leela, S. Patil, B.H. Rashmi, V. Jain, S. Ray, Attrition in software companies: Reason and measures, Materials Today: Proceedings 51 (1) (2022) 528-531 

Sainju, C. Hartwell, J. Edwards, Job satisfaction and employee turnover determinants in Fortune 50 companies: Insights from employee reviews from Indeed.com, Decision Support Systems 148 (2021) 113582 

M. Bezdrob, A. Sunje, Transient nature of the employees’ job satisfaction: The case of the IT industry in Bosnia and Herzegovina, European Research on Management and Business Economics 27 (2021) 100141. 

R. Kaur, Employee Retention Models and Factors Affecting Employees Retention in IT Companies, International Journal of Business Administration and Management 7 (1) (2017) 2278-3660. 

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