Workforce management (WFM) is an institutional process that aims to optimize productivity, competency, and engagement of an organization's workforce. Generally this process relies on software to plan business needs more effectively than through a spreadsheet. WFM typically includes all activities needed to maintain a productive workforce: human resource management, performance and training management, budgeting, forecasting, and scheduling.
While WFM has traditionally focused on operational efficiency and cost reduction, its focus has expanded to include enhancing the employee experience (EX), particularly for frontline or hourly workers. Modern WFM systems are used as tools to improve employee engagement, provide flexible work arrangements, and reduce attrition.
Core components
Workforce management software helps users follow relevant legislation, local agreements and the contracts of individual employees including work-life balance guidelines. WFM software also helps organizations comply with labour standards and union agreements, since non-compliance can expose employers to fines and litigation. The starting point is a clear definition of the work required through engineered standards and optimal methods for performing each task as efficiently and safely as possible.
It is seen as a complete approach to make an organization's workforce as productive as possible, reduce labor costs, and improve customer service. Core processes often incorporate:
Forecasting and budgeting: Creating demand-based forecasts to determine the required workload and number of staff. This is often based on analyzing historical data (such as sales figures or customer contacts) to establish engineered standards.
Scheduling or rostering: Creating and deploying schedules or rosters to workers. This includes integrating staffing requirements, peak loads, skills, labor laws, and contractual terms.
Employee involvement: Providing tools for employees to be involved in the scheduling process, such as managing availability or bidding for shifts.
Performance management: Measuring performance, providing feedback and coaching, and managing incentives and online training.
Time and attendance: Capturing time-worked data for payroll and managing working time accounts.
Process analysis: Monitoring and analyzing the entire WFM process to find efficiencies.
Employee experience
A primary driver for modern WFM adoption is the improvement of the employee experience, especially for deskless or hourly workers who may not have corporate email. This includes capabilities such as:
Flexible scheduling or rostering: Empowering employees with tools for shift-swapping, shift-bidding, and self-scheduling or auto rostering based on their preferences.
Employee communications: Delivering targeted corporate communications (such as updates or training modules) directly within the WFM application.
Sentiment capture: Using pulse surveys to measure employee sentiment at key moments (e.g., after onboarding or a promotion) to improve the work environment.
Schedule stability and predictability
Studies have shown that the stability which comes from scheduling shifts through WFM apps leads to benefits for workers and their employers. In the Stable Scheduling Study, a randomized controlled field experiment carried out at 28 Gap stores and published in 2018 by researchers associated with the Center for WorkLife Law and the University of Chicago, stores that gave hourly retail workers more consistent and predictable schedules recorded a 7% increase in median sales and a 5% rise in labor productivity compared with control stores. Subsequent analysis of the same experiment reported that more predictable schedules were also associated with improved sleep quality among the workers studied.
Role of artificial intelligence
The WFM market has been impacted by the integration of artificial intelligence (AI), shifting the software from a simple system of record to a "system of intelligence." Uses of AI in WFM could include demand forecasting with predictive analytics, optimizing employee schedules, and assigning workers to tasks based on their skill set.
Algorithmic management, a process of using software and algorithms to schedule, assign, and monitor workers, has also drawn criticism. Researchers and labour organizations have warned that using automated scheduling to accommodate short-term demand can produce unpredictable hours and introduce income volatility for frontline employees. It also raises concerns about employer surveillance and the transparency of those scheduling decisions. Reporting on erratic, software-generated schedules in retail and food service, including a 2014 New York Times investigation, contributed to public and regulatory attention to scheduling practices and to the adoption of "fair workweek" or predictive scheduling laws in several United States jurisdictions.
Field service management
Workforce management also uses the process of field service management in order to have oversight of company's resources not used on company property. Examples include:
Demand management – to help forecast work orders to plan the number and expertise of staff that will be needed
Workforce scheduler – using predefined rules to automatically optimise the schedule and use of resources (people, parts, vehicles)
Workforce dispatcher – automatically assigning work orders within predefined zones to particular technicians
Mobile applications for technicians – allowing dispatchers and technicians to communicate in real time.
Market growth
In the 1980s and 1990s, enterprise software investment focused on topics like: supply chain management, production planning, and enterprise resource planning. As labour costs and workforce complexity grew, organizations gave increasing attention to personnel, and workforce management became an established category of business software in industries such as healthcare, retail, and manufacturing.
Adoption has been driven in part by labour pressures in sectors that rely on large hourly or shift-based workforces, also known as frontline employees. In retail, sizable hourly workforces, high rates of employee turnover, and demand-driven scheduling have made labour management a persistent operational challenge.
In manufacturing, labour shortages and skills gaps have intensified interest in workforce planning; a study by Deloitte and the Manufacturing Institute projected that as many as 2.1million manufacturing jobs in the United States could go unfilled by 2030. Market-research firms estimate the global market for workforce management software in the single-digit billions of US dollars; one 2026 estimate placed it at approximately US$9.8billion, with continued growth forecast through the end of the decade.
Delivery models
WFM systems are typically delivered in three ways: as an on-premises system (where software is installed on a business's own servers), a hosted system (managed by an outside provider), or as a cloud-based computing service (Software as a Service, or SaaS). While many large enterprises historically used on-premises systems, cloud-based solutions have become the standard for modern WFM.
As society continues to adopt new technologies such as smartphones and enterprise mobility tools, more companies are allowing employees to become mobile. Mobile workforce management refers to software and services used to manage employees who work outside company premises, such as field teams, and can include device management, tracking, dispatch, and communications.
The need for social distancing imposed by the COVID-19 pandemic has brought about major changes in both employer's and employee's vision of remote work, which will likely have a long-lasting impact on workforce organization and management in the coming years.
↑Copulsky, Gerald C. Kane, Rich Nanda, Anh Phillips, and Jonathan (10 February 2021). "Redesigning the Post-Pandemic Workplace". MIT Sloan Management Review. Retrieved 2021-08-07.{{cite web}}: CS1 maint: multiple names: authors list (link)
Workforce Asset Management Book of Knowledge (John Wiley & Sons Publishing, 2013): Disselkamp, Lisa, ed. (2013). Workforce Asset Management Book of Knowledge. doi:10.1002/9781118636442. ISBN9781118636442.
