We’ve seen from time to time how new technologies have impacted and changed different industries across the globe. From mechanizing tasks in factories previously done by people to being able to work remotely anywhere in the world; we’ve seen all kinds of drastic changes to how work can be done.
Most recently, we’ve all been hearing about Artificial Intelligence (AI) and its transformative impact on the workplace across nearly every industry. It’s changing how work is being done and how decisions are being made. In industries that employ frontline workers, AI and other technologies, such as machine learning, could significantly improve how organizations schedule employees, making the process more efficient, fair, and adaptive to changing organizational needs.
Organizations that are in the social and community services industry are the kind of environments where balancing fairness, predictability, and the human touch is crucial. Staff in this sector are often balancing complex emotional work, crisis situations, vulnerable clients’ needs, and personal commitments.
How AI can improve scheduling efficiency and fairness
There are many ways AI can support that balance while also improving operational flow and logistics planning for organizations. From the organizational standpoint, AI can handle many of the routine administrative tasks that used to consume managers’ time. It can automatically create schedules based based on: employee availability, labour laws, union rules, job type, and forecasts. If employees are able to set their availability preferences, then AI could use this information to match their availability preferences with the organization’s scheduling needs, reducing administrative work and time.
AI doesn’t just eliminate these routine tasks for managers, it’s transforming leadership itself, altering how managers make decisions, lead teams, and plan strategically. Machine learning technology and AI systems can analyze massive amounts of data to recommend actions and predict demand and staffing needs based on patterns, historical data, and seasonal trends. When the decision-making process is data driven, decisions are made faster, are more objective, and more accurate. Managers should be the final decision makers so that they can review and adjust the recommendations made by AI, but when managers spend less time on logistics planning and reviewing schedules or timesheets, they can spend more time on the human side of leadership that involve coaching, mentoring, and long-term goals.
Supporting compliance and reducing risk
Not only can AI assist organizations with reducing administrative work and making better informed decisions, it can also assist organizations with compliance. HR and payroll teams could stay ahead of errors or legal violations by preventing them with AI’s ability to monitor overtime limits, break or rest requirements, and other obligations. It is much more costly for organizations when they have discovered these errors or violations after the fact.
Enhancing employee well-being without losing the human touch
AI-driven scheduling doesn’t just aid an organization to operate better; it can aid in the well-being of their employees and reshape frontline work. Its ability to analyze scheduling patterns can help managers ensure equitable distribution of shifts amongst employees, balanced workloads across team members, and flagging inequitable scheduling or distribution of shifts if certain employees are consistently receiving fewer or less desirable shifts than other employees.
With time tracking, schedule patterns, and workload data, AI could also predict risks of burnout. Managers can use this information to prevent burnout risks, proactively support the well-being of their teams, and finalize schedules sooner, giving employees more stability and reducing their stress. AI can provide predictions based on patterns found in data, but it cannot “see” when a worker is emotionally drained or affected by a tough case or a crisis situation they’ve had to handle; only humans can.
This is when managers can accommodate the personal needs or health concerns of their team members where AI cannot. When AI is used as a decision support tool rather than a decision maker tool, it can support fairness and predictability without losing the human touch. It removes the noise and repetition so leaders can do what only humans can do: inspire, connect, and make judgment calls that require empathy and vision.
Author Credit:
Today’s Simply Shift feature comes from guest contributor Sujany Kajanthrarajah, who brings a grounded HR perspective from the social and community services sector.
Connect with Sujany on LinkedIn: linkedin.com/in/sujany-k/
