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How to retain talent with AI signals that forewarn signs of trouble

Marc Gingras, WorkForce Software

In 2019, the World Health Organization declared burnout—a state of physical or emotional exhaustion caused by prolonged stress—an occupational phenomenon affecting workers’ health.

A term once used to describe an affliction commonly associated with attorneys, military personnel and medical practitioners (among other high-achieving, high-powered professions), the number of employees reporting a feeling of burnout has recently increased so significantly that it’s become practically a common side effect for anyone employed during the COVID-19 pandemic.

Recent polls suggest that as many as three out of four workers are experiencing burnout on the job1, and Gallup recently reported that 62% of women and 52% of men feel stressed on a typical day2—numbers that are well up from before the pandemic. Additionally, a recent survey found that employers and employees are misaligned on key issues like job training, scheduling flexibility and pay rates, which negatively impacts the employee experience and further exacerbates employee’s perceptions of their workplace.

High levels of stress not only affect an individual’s health and personal well-being—they also affect how an organisation operates, leading to lower levels of productivity, increased injuries on the job and lower job satisfaction.

As a result, workers are changing or quitting jobs—many in traditionally inflexible industries and workplaces — in search of higher wages, a better work-life balance, increased flexibility of work locations and schedules, more job opportunities and less stress in what’s been dubbed “the great resignation.” A recent survey by Microsoft suggests that 41% of employees are expected to change roles this year3, mirroring similar UK studies.

With the average cost of turnover per employee costing organisations upwards of £25,0004 (due to hiring and recruitment, onboarding and training and the loss of workplace productivity), retaining staff has become an increasing priority for HR professionals in the UK and around the globe, who are often already spread thin with increased workloads resulting from the pandemic, budget constraints and the constant pursuit of efficiency.

AI to the Rescue
Ongoing advancements in data availability, natural language processing, optimisation and machine learning are alleviating the burden placed on budget and time-constrained HR departments and frontline managers. Technology is helping them proactively identify signs of employee burnout, distress and lower job satisfaction by surfacing insights on attendance, scheduling preferences and employee sentiment so HR teams can make data-informed decisions that improve the employee experience.

Here are some of the ways HR practitioners can harness the power of workforce management software — now and in the future — and AI to assess whether an employee is dissatisfied at work and accelerate emotionally intelligent decision making in their organisation to better the employee experience and work lives of employees.

Data-Driven and Data-Informed
What we do at work and when we do it plays an important role not only in how an organisation operates, but also in a person’s sense of self and emotional well-being. But due to our always-on culture and workplace expectations, staff can be hesitant about raising concerns related to their schedules, workload, personal and professional priorities, and the overall experience they’re having at work—and opt for leaving their job entirely.

Instead, scheduling, time and attendance data, employee sentiment and other information that’s difficult to parse through can be surfaced by data tracked in workforce management software. This way, changes in behaviour or workplace dissatisfaction can be identified and dealt with early on before employees decide to leave an organisation.

Data on paid leave can paint a picture of whether an employee is getting enough time away from a job. If a staff member hasn’t requested or been approved for vacation over the past few months or has only taken a day off here or there, they may be prone to burnout. AI could alert a manager to find space in the employee’s schedule to take time off and recharge.

Time and attendance and scheduling data can indicate that an employee is possibly dissatisfied at work—say, if the data shows they’re repeatedly showing up to work late with no previous pattern of tardiness, or if their schedule is frequently changed by management less than two days before a shift, or they’re being asked to work more weekends than the company policy states. Conversely, for commission-based employees, weekends may be the more desirable shifts.  But depending on an individual’s circumstances or financial needs, getting or not getting weekend shifts could negatively impact an employee’s earning potential, making them more likely to seek other, more consistent work.

Leveraging detailed sales data can help organisations ensure the proper resource levels to prevent employees from working too many busy shifts without adequate support or too many employees being scheduled during a slower time that could lead to them feeling underworked. Both could be surfaced by AI for proactive outreach to assess whether an employee is more likely to be stressed out on the job or feeling unengaged.

By surfacing this data, along with additional info from HR systems — like when an employee last received a pay raise or completed a peer review — AI can provide HR practitioners with insights on the current state of an employee’s experience with an organisation and whether changes need to be made or a shift in company mindset is needed to better support and engage them.

The Future of AI and Workforce Management
Advancements in AI are making it easier for organisations to increase efficiency — whether it’s automating actions that don’t require human intervention, improving day-to-day operations or dynamically triggering assessments on how their employees are feeling at work — and finding new ways to streamline human resource management with greater focus surfaced through data and proactive interventions from managers or HR.

AI can also be used to identify undesirable shifts and incentives that might make them more desirable to workers. Based on how often shifts are swapped, employees call in sick or employee sentiment on workloads during certain shifts, organisations could optimise scheduling to fairly distribute hours, identify more desirable pay rates or other offers to ensure shifts are covered and employee sentiment remains high.

Similarly, AI will identify negative changes or trends in individual employee productivity or attendance patterns—such as an unusual spike in lateness, either organisation-wide or with individual employees. Software can automatically send a pulse survey to assess the reasons why (maybe peak traffic periods are affecting employees’ commutes or personal obligations, like school drop-offs and pick-ups, are making it harder to report for work on time) and share the insights with the manager or human resources team so they can make scheduling and staffing changes accordingly.

Advancements in natural language processing could allow HR practitioners to utilise chatbots and assistants to solve scheduling problems, process time-off requests and assess employee sentiment about their workload, safety issues on the job site, feelings on repetitive or low-value tasks or the effectiveness of shift managers and leaders, and surface insights if a follow-up or change needs to be made at an organisational or operational level.

Using AI to Accelerate Emotionally Intelligent Decision Making
Improper workforce management practices affect job satisfaction and often contribute to an employee leaving an organisation. Those who don’t consider employees’ needs and invest in technology that enhances the employee experience risk losing more staff in the future. Although AI was once feared for its ability to make certain jobs redundant, if anything, it’s enabled HR professionals to make more human decisions, according to HR Tech Influencer Tyrone Smith Jr.5, who says analytic tools designed to promote active listening and predictive responses can highlight potential trouble and help organisations better support employees.

As with any technological advancements, there are specific data and privacy laws, rules and regulations, employment rights and ethical quandaries to consider, especially when it comes to AI. But, when executed properly, AI can free up the human workforce needed to perform manual, time-consuming tasks and leverage insights into employee’s day-to-day experiences that would otherwise be difficult to glean, giving HR teams and managers more opportunities to connect with and support employees in meaningful ways.

As the adage goes: “You can’t manage what you don’t measure.” Recent advancements to AI and modern workforce management software solutions — like the WorkForce Suite and WorkForce Experience — make it possible for organisations to do both.

In addition to labour forecasting, scheduling, capturing time and attendance, and ensuring compliance, among other workforce management processes, employers and HR leaders can harness the data captured by workforce management software to make data-informed, more emotionally-intelligent decisions.

By surfacing insights on attendance, scheduling preferences and employee sentiment to assess whether an employee is dissatisfied, overworked, or ready to quit, AI can help HR professionals engage talent and improve job satisfaction while future-proofing their organisation against further employee churn. With millions across the globe considering a career move, every employee (and experience they receive at work) counts.

References

  1. “Burnout: Modern Affliction or Human Condition?” Lepore, Jill. The New Yorker. May 17, 2021. https://www.newyorker.com/magazine/2021/05/24/burnout-modern-affliction-or-human-condition
  2. ‘State of the Global Workplace: 2021 Report.’ Gallup. https://www.gallup.com/workplace/349484/state-of-the-global-workplace.aspx
  3. ‘2021 Work Trend Index.’ Microsoft. https://www.microsoft.com/en-us/worklab/work-trend-index/hybrid-work
  4. ” The Cost of Brain Drain: Understanding the financial impact of staff turnover.” Oxford Economics. February 2014. https://www.oxfordeconomics.com/my-oxford/projects/264283
  5. “How AI tech and virtual reality can help boost employee experience.” Smith Jr., Tyrone. HR Executive. February 2, 2021. https://hrexecutive.com/how-ai-tech-and-virtual-reality-can-help-boost-employee-experience/

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