A labor management system is a software solution designed to manage human labor within a warehouse or distribution center. By compiling employee data throughout the day, a labor management system is able to report productivity levels on a group of employees or individuals, allowing managers and executives to see where their labor dollars are spent and optimize their human assets.
The demand for labor management systems has skyrocketed from the increasing costs of hiring, training and retaining top-level employees. In addition, labor is amongst the highest expenses incurred by most warehouse or DC operations.
Labor management systems provide warehouses and DC managers with labor planning and forecasting tools, real-time performance visibility, analytics and labor standards which aid improvements in management decisions, coaching, productivity and keep costs to a minimum.
What Are the Benefits of a Labor Management System?
- Critical data collection & reporting – A labor management system collects and reports performance data to monitor progress on set goals and objectives.
- Increasing employee satisfaction – Employee satisfaction improvements stem from fair performance targets, coaching and incentive programs.
- Productivity improvements and labor savings – Managers are enabled to identify and adjust inefficient work processes. Thus allowing them to optimize their workers and reduce overall labor costs.
- Improved management decisions – A labor management system provides real-time insights that enables management to reallocate work, transfer resources and manage costs in a timely manner.
- Improved customer satisfaction – By collecting and making sense of data, labor management systems are able to better forecast and predict assignment completion so that customers receive their orders on time.
Next Generation Labor Management Systems Use Machine Learning for Predictive Performance Standards
In order to provide better labor insights, labor management systems are equipped with labor standards. Traditionally, a few industrial engineers armed with stopwatches and clipboards conduct time studies to determine labor standards. These pre-defined models are static, use only a limited number of variables and require heavy maintenance.
More advanced labor management solutions utilize machine learning to provide more dynamic and predictive performance standards. Machine learning solutions analyze warehouse data to develop predictive models for workforce planning. This data can come from multiple sources, including warehouse optimization systems, mobile devices and warehouse control systems.
Machine learning will free time for managers and engineers to focus on process improvements, optimization strategies and constantly adapt to market demands. To learn more about machine learning vs. engineered standards, check out our blog post, Machine Learning Will Make Warehouse Managers More Productive.