AI-Driven Demand Forecasting: How Does It Work?by Lindsay Rose
For some, the thought of artificial intelligence (AI) conjures up some rather Doomsday-like imagery…robots taking over the world or the banishment of humankind altogether. But that’s just Hollywood. In reality, we interact with forms of AI every day. Do you rely on auto-correct when drafting emails or sending texts? That’s AI. Ever binge a show Netflix recommended for you? That’s AI. Do you use Waze or Google Maps to get around town? That’s AI, too.
AI technology is often used to perform tasks that humans are inherently bad at—such as remembering and applying large and complex rule sets.
Let’s see shift schedulers, can we think of a common task that requires you to remember lots of rules, data and requests? That’s right, those frustrating, but oh-so-critical weekly or monthly employee schedules! Who is eligible to work? Who has requested time off? Who is already pushing overtime? Am I at risk for labor law non-compliance?
It’s this kind of complexity that makes demand forecasting with employee schedules the perfect job for AI.
What Is Demand Forecasting?
Demand forecasting is the process of estimating or predicting the demand for goods or services based on historical data. It’s a process that’s essential to ensuring your schedules include the optimal number of employees to serve customers and keep business running smoothly, but it only adds to the complexity of building employee schedules. Demand can be different things in different industries. In retail and restaurants, it is largely driven by foot traffic and seasonal events, in hospitality it may be bookings, and in other commercial businesses, it may be driven by production targets or project due dates.
Shift schedulers know that employee scheduling is anything but simple. And when employees’ schedules aren’t right, it impacts customer and employee experiences alike. Many schedulers must rely on guesswork as they try to schedule the right mix of staff to match demand, which is especially complex during any seasonal fluctuations. Without proper coverage, employees can wind up either overworked or bored. Customers may not get the attention or service they need. And the business suffers with dissatisfied employees, frustrated managers, and unnecessary labor costs (link to labor budget blog). How can you make sure you have just-right coverage without under or over staffing?
Enter AI-powered demand forecasting from TCP’s Humanity Scheduling.
What Is AI-Driven Demand Forecasting & Who Needs It?
TCP’s Humanity AI-powered scheduling experience uses 2 key features— Demand-Driven Scheduling and Auto-Scheduling—to build out schedules optimized for both demand forecasts and compliance while providing flexibility for their employees. And it saves managers countless hours in the process.
When it comes to managing and forecasting demand, some industries have it harder than others. Retail, restaurants, hospitality, and higher education have definite ebbs and flows, and not being prepared is bad for business; however, these areas have a certain level of predictability. Healthcare, on the other hand, can be very unpredictable and the stakes are about as high as they come when lives are on the line.
How Does AI-Powered Employee Scheduling Work?
Generally speaking, artificial intelligence and machine learning are not linear processes, but cyclical processes that continuously learn and evolve to offer an optimal output. In this case, a conflict-free schedule that ensures you have the right people in the right place at the right time. Here’s how it works:
Step 1: Set Up Metrics and Staffing Rules
Identify key drivers for your organization and set up staffing rules for Humanity to translate them into labor demand forecasts.
Step 2: Demand Forecasting for Labor
Schedulers can use Humanity Forecast to project demand forecasts in the coming weeks with both Humanity’s AI engine and through their own metrics.
Step 3: Build Out Schedule
Create schedules that are based on forecast demand, and compliant to preset conflicts by using Auto Scheduling and the conflict management engine.
Step 4: Assign Shifts to Employees
Use Auto Scheduling to publish schedules that match demand as well as roles, employee availability and compliance requirements.
Rinse and repeat! Demand forecasting with Humanity’s AI-Powered Schedules continuously improves over time. The more historical data it has, the more ideal your employee schedules will become.
If haphazard shift scheduling practices have you tearing your hair out, opt for a data-driven, demand-based approach with AI-powered scheduling. You’ll get optimal schedules that will leave both managers and employees smiling. Learn more about TCP’s Humanity AI-powered employee scheduling.