Using Data to Forecast and Meet Hiring Demands in Tight Labor Markets

Chief among them: how do I know the right number of people to hire to find the right balance between meeting production requirements and controlling budget? Equally important, how can I make the right decisions to maximize my budget and productivity?

Ramp-up planning--responding to an anticipated significant increase in production or service requirements--requires determining the number of workers needed, where to find them, wage analysis, how flexible schedules could be used to manage costs, and how short-term benefits could be used to attract and engage staff.

Data can help.

Historical Data

Analyzing past company data can provide insights into hiring needs. For instance, if you know that you had X number of loading dock employees on staff who efficiently handled X volume of loads during the 2021 holiday season, and you predict that volume to increase by a certain amount, you can calculate an estimate of how many additional employees you might need this season.

Your own data also provides a benchmark that can be used to evaluate effectiveness and productivity on an ongoing basis.

Local Data

Local data on available staff/talent is also an important indicator to help in new hire ramp -up planning. For instance, if the unemployment rate in your local geography (the area that staff would normally come from) is 4%, you’re facing a tighter hiring market than if unemployment was at 8%.

Local data that may be available through Chambers of Commerce, economic development groups, and others can help you stay attuned to labor availability and shortages in your recruiting area.

Government Agency Data

Data is available from a wide range of governmental agencies like the U.S. Census Bureau, the Bureau of Labor Statistics (BLS), the Department of Labor’s Wage and Hour Division, and others.

This data may be broader than what you need to make decisions locally, but can give insights into potential trends that may impact your area now or in the future.

Trade Association Data

There is a trade association to represent virtually every industry and every type of job. For instance, in the manufacturing industry, trade associations like the National Association of Manufacturers or The Association for Manufacturing Excellence.

These organizations study their industries and collect and report data to members.

Predictive Data

Advanced analytics like the kind now available through artificial intelligence (AI) and machine learning can offer extremely reliable insights and direction when considering the type and number of workers to bring on board to handle any kind of special need. Powered by data gathered from a variety of sources, AI can help you make future decisions based on what has happened in the past, and the current labor market trends.

While, as we’ve seen, there are a number of sources of data that can be used as an aid in ramp-up planning, accessing, evaluating, and appropriately using this data to make sound recruitment and hiring decisions takes time.

Another challenge that companies face when needing to ramp up staffing is that this need may not exist in the future. Hiring full-time staff now to address peak demand will only result in overstaffing--and overspending--in the future.

And, face it. As you’re focused on meeting customer demand, while maintaining production capacity within your budget, you don’t have the time to crunch numbers or engage in strategic recruitment activities, especially  in a tight and very competitive labor market.

We can help.

Companies like GoJob have access to data, advanced analytics capabilities, and the capacity to help companies determine their hiring needs and staffing volumes--and the resources to help fill that volume with staff on a temporary basis. In most cases, we can get you the staff you need within 24 hours on average. You realize significant short-term gains while avoiding long-term liabilities.

Learn more.