Labor budgeting is a method of forecasting annual, quarterly, and weekly labor costs based on expected workload. Budgets usually include historical sales, a growth factor, and some labor projections. By multiplying the number of hours worked by the cost of each employee, labor costs can be easily calculated. However, there is a common misconception about how easy it is to determine work hours while also strategically staffing for the future. This presents a challenge for businesses considering multiple organizational changes that may have an impact on their current workforce structure and, as a result, their overall labor budget. Frequently asked questions include: What if I open a new location? What if the minimum wage rises, and I want to avoid having to hire more people? Retailers require timely insight into the optimal staffing mix and recruitment efforts necessary to accommodate these realistic business changes in order to determine the optimal staffing mix and associated costs in all possible future scenarios.
While managing all possible future scenarios may appear daunting, strategic planning technology can resolve them all in a matter of seconds. It is critical to simplify the process of comprehending and strategically planning staffing levels for organizations to operate efficiently. Using optimization, also known as strategic planning algorithms, retailers can easily maintain the appropriate recruitment efforts and staffing levels as an accurate and necessary input into their labor budget. With this technology, I (as a retailer) can confidently plan for the future, knowing that the recommended staffing levels are appropriate for my costs and organizational structure.
As a result, how does one plan strategically to ensure that the right mix of employees is available throughout the year to meet changing demand? You can simplify workforce planning in a matter of seconds with strategic planning algorithms.
Simple iterations of variable inputs can reduce the inefficiency of manual calculations and allow for the creation of "what-if" scenarios. The dynamic and required staffing levels for each week of the budgeted time period are determined using a variety of user-specific factors such as optimal staffing ratios, recruitment costs, and penalties for over- or understaffing in relation to demand.
You can build your ideal workforce with accurate insight into your future labor pool, one that is optimized to reduce excess labor costs, minimize sales opportunities lost due to fluctuating staffing levels, and boost productivity. The algorithms provide a more realistic and timely input to the labor budgeting process as a whole, in addition to assisting in the development of the ideal workforce.
The strategic algorithm's goal is to keep the gap between required and current headcount as small as possible for each budgeted time period. The algorithm compares expected demand hours to current supply hours (including attrition) and suggests when employees should be hired, reallocated, or retrained to meet demand. Employees at all levels are adequately prepared to cover forecasted demand peaks and valleys, according to weekly recommendations.
OnShift assists you in maintaining the appropriate level of staffing at all times. We recommend realistic staffing levels for each time period based on your current staffing levels, turnover, and anticipated demand. Using OnShift's recommendations, you can forecast your future labor costs. When determining the optimal staffing ratio, OnShift considers a number of factors, including the cost of hiring or retraining employees as well as the efficiency rate of each type of employee.
If seasonal demand for services increases, OnShift will recommend which types of employees to hire or retrain and when. We'll figure out the best staffing mix for cutting costs while maintaining service levels.
Additionally, the algorithm takes into account a number of business constraints, such as the cost of hiring or retraining specific employee types, the desired/optimal full-time to part-time ratio, the efficiency rate of each employee type, and weighted penalties for exceeding or falling short of demand curve coverage (see graph above). If seasonal demand increases, for example, the algorithm will recommend which type of staff to hire or retrain and when to hire them based on efficiency factors, desired service level, and cost of covering the curve. The ultimate goal is to provide the most coverage for the least amount of additional staffing and revenue loss.
Not only does strategic staffing planning help to reduce additional labor costs and improve service levels, but it also helps to align the labor budgeting process. Increased visibility into staffing levels and associated costs enables the development of a holistic labor budget – one that takes into account each week's staffing requirements and is backed up by optimization.
Are you thinking about reducing the size of your company's workforce? Do you want a better idea of how much staffing you'll need for your annual, quarterly, or monthly periods? Consider using optimization to strategically plan your next staffing move, whether that means solving your annual projected staffing outlook with the strategic algorithm or feeding optimized rosters into the strategic algorithm to generate your ideal staff mix. Our workforce optimization algorithms are built to take into account the intricacies of staffing.
