What's your workforce demand forecasting accuracy?

1 Why accuracy matters

The accuracy of your workforce demand forecasts affects your workforce scheduling, which is the method you use to assign shifts, tasks, and roles to your employees based on your demand predictions. If your forecasts are inaccurate, you may end up with overstaffing or understaffing, which can have negative consequences for your business. For example, overstaffing can lead to wasted labor costs, lower productivity, and lower employee engagement. Understaffing can lead to poor service quality, customer dissatisfaction, lost sales, and higher employee turnover. Therefore, it's important to monitor and evaluate the accuracy of your forecasts regularly, and adjust them as needed.

2 How to measure accuracy

One way to measure the accuracy of your workforce demand forecasts is to compare them with the actual demand that occurred. This can be done by using metrics such as the mean absolute percentage error (MAPE), which calculates the average percentage difference between the forecasted and actual demand. The lower the MAPE, the higher the accuracy. For example, if your forecasted demand for a week was 1000 hours and your actual demand was 950 hours, your MAPE would be (|1000 - 950| / 950) x 100 = 5.26%. Another metric you can use is the mean absolute deviation (MAD), which calculates the average absolute difference between the forecasted and actual demand. The lower the MAD, the higher the accuracy. For example, if your forecasted demand for a week was 1000 hours and your actual demand was 950 hours, your MAD would be |1000 - 950| = 50 hours.

3 How to improve accuracy

Accuracy in workforce demand forecasts can be affected by a variety of factors such as the quality of data, the complexity of demand patterns, the frequency of forecasts, and the methods and tools used to generate them. To enhance accuracy, you should use historical data that is relevant, reliable, and updated regularly. Analyzing your demand patterns can help identify any trends, seasonality, or outliers that may influence your forecasts. Choosing a forecasting method that suits your business needs and objectives is also important; possible options include time series, regression, or machine learning. Utilizing a workforce management software to automate and optimize your forecasting process can provide you with real-time data and insights. Additionally, it is recommended to review and revise your forecasts periodically and incorporate any feedback or changes that may affect your demand.

4 How to benchmark accuracy

Another way to assess the accuracy of your workforce demand forecasts is to benchmark them against industry standards or best practices. This can help you identify your strengths and weaknesses, and set realistic and achievable goals for improvement. However, benchmarking can be challenging, as different industries and businesses may have different definitions and expectations of accuracy, and different sources and methods of data collection and analysis. Therefore, it's important to use relevant and comparable benchmarks, and adjust them according to your specific context and needs.

5 How to communicate accuracy

Finally, it's important to communicate the accuracy of your workforce demand forecasts to your stakeholders, such as your managers, employees, and customers. This can help build trust and credibility, as well as foster collaboration and alignment. To communicate your accuracy effectively, use clear and consistent metrics and terminology, and explain how they are calculated and interpreted. Additionally, provide context and rationale for your forecasts, and highlight any assumptions or limitations that may affect them. Share your results and insights, and show how they relate to business goals and performance indicators. It's also beneficial to solicit feedback and input, acknowledge any errors or gaps that may occur, celebrate successes, and recognize team efforts. Measuring, improving, benchmarking, and communicating accuracy is essential for workforce scheduling quality and ultimately business outcomes.