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This case study aims to explore the efforts of a small start-up company, whose unique solutions are being deployed in the fight against COVID-19, with encouraging results. Using innovative technology and local volunteer networks, they have set out to identify the medical needs of local care providers, while reducing the effects of fraud, corruption and mis-management.

This case study involved the interrogation of data made available by the company and an interview with the chief executive officer.

The research suggests that small enterprises can have a positive impact, far beyond what either the state or the market might assume. By properly equipping and empowering people at the grassroots level, they can identify and solve local resourcing issues and root-out fraud, corruption and mismanagement before they happen.

This is a unique approach to the problem of resource management in the non-profit sector, with implications for grant projects beyond the COVID-19 pandemic.

The aim of this research is to determine the extent to which the human resource (HR) function can screen and potentially predict suicidal employees and offer preventative mental health assistance.

Drawing from the 2019 National Survey of Drug Use and Health (N = 56,136), this paper employs multivariate binary logistic regression to model the work-related predictors of suicidal ideation, planning and attempts.

The results indicate that known periods of joblessness, the total number of sick days and absenteeism over the last 12 months are significantly associated with various suicidal outcomes while controlling for key psychosocial correlates. The results also indicate that employee assistance programs are associated with a significantly reduced likelihood of suicidal ideation. These findings are consistent with conservation of resources theory.

This research demonstrates preliminarily that the HR function can unobtrusively detect employee mental health crises by collecting data on key predictors.

In the era of COVID-19, employers have a duty of care to safeguard employee mental health. To this end, the authors offer an innovative way through which the HR function can employ predictive analytics to address mental health crises before they result in tragedy.