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How to Use Algorithms to Comply to Predictive Scheduling Laws

By Ethan Loo – WFM Sales Development Representative at Widget Brain

 

While shift-workers will see benefits to their schedules and their lives, managers are challenged with how to create schedules that adhere to these new laws. What does this mean for the way your workforce is managed and how can you comply?

What are Predictive Scheduling Laws?

In cities like San Francisco, New York, and Seattle, predictive scheduling laws aka fair workweek laws are being enacted across North America. Increasingly, states like Oregon and Massachusetts are getting more involved with predictive scheduling laws.

 

Clauses in these laws include compensation for changes to posted schedules, prioritising current employees before hiring more staff, and minimum rest requirements between shifts, which limits “clopenings”. These laws also require companies to post schedules at least two weeks in advance, and failure to adhere to the new regulations can result in significant fines.

 

How does this affect your stores?

These new changes in scheduling rules challenge managers to commit more time towards creating shifts for their stores while reducing their responsiveness to demand fluctuations. Over time, this creates inefficiencies in coverage. Stores may miss sales opportunities and traffic peaks or become overstaffed because shifts were created in advance and can’t easily be modified. Demand forecasts give managers an idea of what to expect in terms of volume and staffing requirements, but these projections are only as helpful as they are accurate.

 

Most managers have spreadsheets or legacy systems that make demand projections based on experience, intuition, and simple forecasting methods (e.g., historical averaging). However, they may not be able to account for specific demand trends or special occasions such as holidays, conventions, or sports events which consequently could lead to inaccurate demand forecasts. Furthermore, managers are challenged to make good schedules farther in advance than they might typically be used to. When assigning shifts, the new predictive scheduling laws come into play again: managers have to account for labour laws such as minimum rest times as well as specific communication rules around changes.

 

So what’s the best way to handle these new requirements while still efficiently scheduling your locations? More and more companies are leveraging the power of intelligent forecasting, scheduling, and staffing algorithms.

 

How can advanced algorithms help?

Algorithms can alleviate the challenges of predictive scheduling through three functionalities: Labour Demand Forecasting, Shift Creation, and Shift Filling.

 

Labour Demand Forecasting Algorithms give your business the ability to staff well in advance and minimize inefficiencies. AI-driven forecasting accounts for fluctuations in volume that simple algorithms may not be able to anticipate. For instance, machine learning techniques can pick up on trends and features in historical data that simple forecasting methods often miss, leading to improved accuracy versus the benchmark. All in all, these algorithms give more accurate insights on future labour demand needed, allowing managers to better anticipate their workload in the coming weeks.

 

But don’t be fooled: a great demand forecast can only take your scheduling so far. Even with an accurate forecast, creating the best shifts to cover your demand can be time-consuming and error-prone. Shift Creation algorithms help by automatically finding the best combination of shifts based on demand, labor laws, and business goals such as minimizing overtime and other penalties. By optimizing shift creation, you can effectively balance the competing goals of cost savings and customer service. All together, adding intelligence to the shift creation process better matches your coverage to the forecast demand. This makes it easier to build schedules further in advance and avoid the headaches of manually planning against uncertainty.

 

The last step in the process is to assign employees to the shifts. These algorithms can take insights generated by demand forecasting and shift creation and combine them with roster information to assign shifts that work for your employees and your managers. The best Shift Filling algorithms can reduce employee overtime, adjust for employee preferences, and – most importantly – handle tricky scheduling laws. They can avoid “clopenings” and reduce over-assignment of shifts. These algorithms are most valuable when they are adjustable at any time to keep up with the changing needs of your company and individual locations.

 

When utilized in concert, demand forecasting, shift creation, and shift filling algorithms orchestrate a fine-tuned schedule that can help reduce the scheduling challenges of predictive scheduling laws.

We believe in the future of smarter workforce management

At Widget Brain, we’re helping companies get ahead of tomorrow’s workforce management challenges. Not only do we provide best-in-class algorithms for labour demand forecasting, workforce optimization, capacity planning, and more, Widget Brain creates mass-customized solutions that scale to meet your company’s needs. If you have questions or want more information, please feel free to email me.

 

By Ethan Loo – WFM Sales Development Representative at Widget Brain