By Gustav Anderson
Jul. 12, 2022
In light of a persistent labor shortage, high employee turnover, and inflation rates likely to cause a spike in operating costs, many businesses across the nation find themselves searching for better ways to improve scheduling flexibility and control unpredictable wage costs.
Data from a recent study suggests businesses with more variable hours that provide schedules less than ten days in advance suffer the most from employee turnover. Retaining workers is more important than ever in today’s economy, and many are turning to labor forecasting techniques for help.
Indeed, labor forecasting has arrived – and it is here to stay for hourly workforces. But, what exactly is labor forecasting?
In short, labor forecasting is a function of workforce management that helps businesses determine where, when, what kind, and how many employees are needed to successfully meet projected customer demand.
Okay, so that is a basic definition. But what does labor forecasting really involve? Perhaps an easier way to understand labor forecasting is to break it down into a simple equation.
Don’t worry, this math is about as easy as it gets. Labor forecasting can be broken down into the following equation:
Demand forecasting + labor modeling = labor forecasting
Without a proper demand forecast, a business is simply left with a labor model blind to the external habits of the market. This is not a complete labor forecast.
Without a labor model, a business merely has a mess of forecasted demand data with no real plan to quickly and efficiently deploy staff to meet that demand. Again, this is not a complete labor forecast.
To properly forecast labor, a business first needs to predict future demand, and then it needs to build out a model to distribute employees and shifts according to that demand.
Now that we understand labor forecasting in a broader sense of the term, let’s take a closer look at its individual parts.
The more widely known of the two labor forecasting components is called demand forecasting. It helps organizations project things like sales and foot traffic for upcoming weeks, giving them a better understanding of their staff and scheduling requirements.
Here are a few different demand forecasting methods:
The most basic of demand forecasts, qualitative forecasting is for when a business doesn’t have enough historical sales data to use as a reference. It primarily involves conducting market research on industry trends, seasonality, and targeted customers to generate extremely broad predictions in demand.
Average of Past Dates
One of the most common forms of demand forecasting, the average of past dates method creates basic demand predictions in the hospitality, food and beverage, and retail industries. Its accuracy is quite limited, however, as it only uses sales data from your POS system, omitting many variables that come into play when forecasting customer demand.
It works by averaging historical sales data across a specified date range, using these averages as rough predictions for demand going forward.
For instance, a user might choose to average out their sales from last year’s Black Friday weekend to use as a forecast for this year’s upcoming Black Friday. Or, they can simply take sales averages from the past three weeks and project them forward on a continual basis.
Recent developments in AI and machine learning offer the most accurate options for demand forecasting currently available.
AI forecasting works by feeding customer data (sales, foot traffic, orders), external data (weather, holidays, events, etc.), and demand patterns (seasonality, trends, weekdays) into a machine learning algorithm. This algorithm then learns the relationships between all the different data sources to create demand predictions up to four weeks out.
This technology makes it possible to incorporate a wide range of demand-influencing factors in your forecasts – something more basic demand forecasting software cannot do.
Once you have your demand forecast, it’s time to put together an effective labor model. Doing this gives you insight into your current labor supply and the supply of labor you’ll need going forward. It also helps you determine the best way to distribute staff across your business.
This form of modeling simply looks at your staff availability and business operating hours. Its purpose is to keep just enough staff on hand to operate the business during operating hours, nothing more.
Since it heavily focuses on internal requirements and excludes external demand variables, simple internal modeling often results in problems with understaffing and overtime.
A step above internal modeling, the Delphi method anonymously surveys many different team leaders and decision makers in different locations to get an aggregate understanding of an organization’s labor needs.
While the Delphi method takes into account much more than just employee availability and operating hours, it is still quite inefficient due to its qualitative and anonymous nature.
With this advanced model, AI creates ratios of required labor to meet forecasted demand down to specific teams, locations, and roles. These ratios guide scheduling managers away from potential over/understaffing issues and reduce overall labor costs.
For instance, for every 20 pizza delivery orders a business receives on a Thursday, this model might suggest a ratio of 3 delivery drivers and 2 cooks to properly meet that demand. These ratios take the guesswork out of labor models, helping managers plan their staffing around customer demand and not just internal requirements.
As labor forecasting becomes increasingly more intertwined with employee scheduling and workforce planning, businesses everywhere are beginning to reap the benefits of optimized forecasts.
Here are some of the ways proper labor forecasting directly improves your bottom line:
Understanding labor forecasting is one thing; effectively utilizing it is another.
The best way to implement a labor forecasting strategy is to use labor forecasting software. It automates the entire process for you, running predictive demand calculations and generating labor ratios in minutes.
This kind of technology is rapidly evolving the way businesses manage their labor – and Workforce.com is at the forefront of this evolution. Here’s why:
Workforce.com’s industry-leading AI uses historical sales, economic patterns, and external variables to generate intricate demand predictions that fuel your labor forecasts. This method is significantly more accurate than the typical labor forecasting platform which only uses historical sales averages.
With Workforce.com’s labor forecasting, managers can see the number of staff per role needed to meet expected demand for every location, team, and shift – detail that far surpasses most other labor forecasts that just give general staff count recommendations.
Managers can automatically create schedules in a single click based on their labor forecasts, eliminating hours of admin time previously spent manually plugging staff into weekly spreadsheets.
To find out more about how labor forecasting works, check out the webinar below featuring Jack Light, a Labor Economics PhD Candidate at the University of Chicago.
To get started on implementing a labor forecasting strategy, contact us today. We’d be happy to chat.
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