Faced with this reality, the default response for many has been reactive—inflating salary offers, offering sign-on bonuses, and fighting a costly war for talent. Here at Telos Brothers, our analysis suggests this approach treats the symptom, not the underlying condition. The current economic and labor environment is not a temporary storm to be weathered, but a fundamental paradigm shift. It is an accelerant exposing the brittleness of legacy operational models.
The challenge is not simply a people shortage; it's a systemic process bottleneck. The solution lies not in hiring faster, but in rethinking the very nature of work itself through intelligent automation.
Beyond the Resignation Label
To effectively solve the problem, we must first correctly diagnose it. While compensation is a factor, a growing body of research indicates that the reasons for the mass exodus are far more nuanced. A comprehensive analysis by Gallup found that the top drivers for resignations included a lack of opportunities for development, a disconnect from the company's purpose, and a lack of well-being—often stemming from burnout (Gallup, 2022).
This burnout is frequently a direct consequence of how work is designed. Organizational psychology provides a powerful framework for this: the Job Demands-Resources (JD-R) model. This model posits that employee strain occurs when job demands (e.g., workload, cognitive load) are high and job resources (e.g., autonomy, feedback, skill variety) are low (Bakker & Demerouti, 2007).
Many roles within modern enterprises are disproportionately skewed towards high-demand, low-resource tasks: manual data entry, cross-platform information reconciliation, report generation, and other repetitive, rule-based activities. These tasks are not just inefficient; they are actively detrimental to employee engagement, stifling the creativity and critical thinking that organizations desperately need. By forcing highly capable human minds to function like biological processors, we are engineering the very disengagement that leads to resignations.
The Flawed Orthodoxy of Linear Scaling
For decades, the unchallenged orthodoxy of business growth was linear: increased output required a proportional increase in human capital. This model, a holdover from the industrial age, creates inherently fragile and expensive systems. The costs of employee turnover are significant, with research suggesting that replacing a single employee can cost between one-half to two times their annual salary when accounting for recruitment, onboarding, training, and lost productivity (SHRM, 2019).
In the current environment, this linear model is untenable. The strategic imperative must shift from scaling the workforce to scaling operational capacity independent of headcount. This is the core principle of the automation mandate.
The New Equation for a Resilient Enterprise
We propose a new key metric: Operational Alpha, or the ability to generate efficiency and output that outpaces market and competitor norms through superior process design. Intelligent Automation, particularly Robotic Process Automation (RPA), is the primary engine for achieving this.
The objective is to systematically deconstruct workflows, isolate high-volume, rule-based tasks, and delegate them to a digital workforce. This is not about replacing people; it's about a strategic reallocation of human capital to higher-value functions. The efficiency gain is not merely theoretical. A 2021 study on RPA implementation in the banking sector showed potential cost reductions of 20-25% and significant improvements in data quality and compliance (Lhuer, et al., 2021).
The core calculation remains elegantly simple. If a manual process takes T_manual hours of an employee's time and its automated equivalent requires T_automated hours (often negligible for pure execution), the human capacity unlocked for strategic work is:
When this equation is applied systematically across an organization, it creates a powerful flywheel effect. The initial ROI from automating a single process funds the next, creating compounding gains in productivity and freeing your team to focus on what humans excel at: complex problem-solving, strategic innovation, and building nuanced customer relationships.
From Task Execution to Strategic Augmentation
This transformation redefines the role of the employee from a task executor to a strategic operator. The World Economic Forum's "Future of Jobs" report has consistently highlighted a growing demand for skills like analytical thinking, creativity, and complex problem-solving, while the demand for manual data entry and administrative skills declines (WEF, 2020). Automation is the mechanism that facilitates this shift.
Consider the practical implications:
Finance: An Accounts Payable clerk, freed from manually keying in invoice data and performing three-way matching, is elevated to a role of cash flow analyst and vendor relationship manager. They now use the perfectly structured data provided by the automation to negotiate better payment terms and identify savings opportunities.
Human Resources: An HR coordinator, no longer bogged down by the repetitive paperwork, system access requests, and scheduling of new-hire onboarding, can now focus on creating a world-class onboarding experience, developing career pathways, and strengthening corporate culture—the very "job resources" that the JD-R model identifies as critical for retention.
The businesses that thrive in this new era will be those that view automation not as a cost-cutting tool, but as a human capital empowerment strategy. They are building a symbiotic relationship between their human and digital workforces to create a more resilient, scalable, and innovative enterprise. The challenges of 2022 are not a signal to retreat; they are a clear mandate to evolve.
References
Bakker, A. B., & Demerouti, E. (2007). The Job Demands-Resources model: State of the art. Journal of Managerial Psychology, 22(3), 309-328.
Gallup. (2022). The Great Resignation Is Not Over. Gallup Workplace. Retrieved from https://www.gallup.com/workplace/391922/great-resignation-not-over.aspx
Lhuer, X., Sayin, A., & Wiedenmann, A. (2021). The new scaling imperative for robotics process automation. McKinsey & Company.
SHRM. (2019). 2019 Retention Report: A Look at the Costs of Employee Turnover. Society for Human Resource Management.
U.S. Bureau of Labor Statistics. (2022). Job Openings and Labor Turnover Survey. JOLTS. Retrieved from https://www.bls.gov/jlt/
World Economic Forum. (2020). The Future of Jobs Report 2020. WEF.