Remember when video killed the radio star? Now it seems algorithms have it out for the human experience, or at least that’s what some people fear.
Algorithms and machine learning are embedded into seemingly everything these days. Social media feeds? Of course.
Retailers can use algorithms to determine the optimal price of a product to maximize profits.
Staff scheduling? Yep, there’s even an algorithm for that.
Algorithms are good for business. Organizations utilize machine learning to reduce redundancies and improve workforce operations. They are designed to control labor costs by calculating exactly how many employees are needed at any given time of day. Accurate schedules created well in advance of a shift can have a tremendous impact on the lives of employees.
Unpredictable and overburdened schedules take a toll on employees. So what can organizations do? Facing a time when customer experience is paramount and organizations are trying to increase efficiencies and cut costs, many companies are turning to vendor partners who have solutions that incorporate algorithms and machine learning technology.
Improving Lives
On the whole, humans crave consistency in their lives. Routine and knowing what to expect is comforting. So when it comes to work, employees like to have a consistent schedule they can rely on. Consistent and fair. This can be challenging for those working in service industries like food, retail, and healthcare.
A lot goes into scheduling staff in these industries, given their extended hours and holidays. It can be very frustrating for managers and schedulers to schedule staff to the expected need, and make sure employees are treated fairly in terms of weekends and holidays. Without the proper tools, there’s a lot to keep track of when creating staff schedules.
This is where machine learning and automation come in handy. The maybe harsh reality is that if there is a task that can be automated, AI can deliver, and it can typically deliver more accurately and efficiently than a human. This means good news for an employer. But what about the employees? Are they faring better because of technology?
Let’s look at the healthcare industry.
The healthcare field has higher rates of staff burnout and it’s easy to see why. Working in such a volatile environment as patient care, the emotional toll and physical demands can be taxing. On top of that, throw in the stressors of schedule issues, perceived inability to take a vacation, problems with managers and other co-workers, etc., and all of this can leave nurses and other providers burned out, often within a few years of beginning their career.
Healthcare provider organizations that have used predictive analytics for nurse scheduling and staffing have achieved outcomes that include increased staff satisfaction scores, improved nurse retention, and decreased the amount of time managers spend on schedule creation and staffing tasks.
Automation not only means increased efficiencies for an organization, but it can also ease a lot of strain on employees. Building accurate schedules that optimizes the available workforce allows employees to live their lives by creating a healthy and consistent schedule that isn’t going to burn them out.
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Hurting Employee Satisfaction
Sometimes, what is intended to improve efficiencies and improve the lives of all involved backfires. For example, if a robot controlled employee schedules, it could lead to less consistent schedules as AI is looking for efficiencies. Additionally, there could be a toll on employees trying to respond to the AI recommendations.
We don’t have to look much further in the robotics race than Amazon. This warehouse industry giant employs more than 1.1 million Americans today, but the rise in its AI investments likely means there’s a day coming when warehouse robots will be able to replace just about every human task and worker.
In addition to the drive to automate more warehouse tasks, there are much higher expectations for workers. This increased strain on employees has resulted in the rise of the number of work-related injuries. The working conditions of Amazon warehouses has been a cause for recent employee strikes, which calls into question the use of automation.
We don’t have the solutions to Amazon’s workforce challenges. We will leave that up to Jeff Bezos.
Remediating Automated Staffing Issues
An algorithm that predicts census is a long way from artificial intelligence that uses data to make decisions and complete tasks. But we are still talking about advanced technology that is utilizing data to influence human decisions.
Along with accurate forecasting, good schedule oversight is necessary for appropriate staffing and to mitigate any potential problems. Ensuring staff commitments are met, submitting schedules on time, making sure there is a competency mix of resources (charge nurses, experienced RNs, etc.), and utilizing contingency resources such as float pools are steps to take to ensure a properly balanced schedule. And these are tasks to be done by the person in charge of scheduling.
Predictive analytics technology is not magic. You can’t plug it in, press a button and expect perfection. Nurse scheduling software that is fueled by predictive analytics is only as good as the data it is fed and the people who use it. Building accurate predictive models relies on reliable data from each organization. The more accurate data that is fed into the software, the better the prediction will be.
With any new technology, there always comes potential risks and opportunities. Careful oversight on the part of the people implementing new technologies and making tweaks as issues arise is key positive outcomes.
