3 minute read

Digging Deep: Understanding the Cost of Staffing Adjustments in Retail Scheduling Requirements

In the retail industry, labor is the single largest controllable expense that retailers face. However, controlling that labor expense comes with a price. Retailers need to understand what makes up that cost; it is not as simple as just cutting labor to be profitable. There is a fine line between the cost of labor and the cost of doing business.

Regardless of the size of your labor team, think about the questions that they are often tasked to answer. Those questions often begin with “how much does it cost to…?” You need quick analysis. You need accurate analysis. It can be a lot of manual work to analyze the cost of all work content but even more work to dissect the cost of doing business. When trying to meet the demands of customer service, it is often necessary to add allowances for service standards. Some examples of these service allowances are:

This is where understanding the cost of staffing hours adjustments is essential. If you have recently audited your engineered labor standards, there is probably little wiggle room for reducing the cost of these raw hours. Raw engineered time is the work content. That along with an accurate forecast provide the baseline for labor hours demand. Staffing hours contain allowances or adjustments to raw hours to meet other business and service requirements. Once staffing adjustments are added to the engineered hours, the results are often referred to as scheduling requirements.

To get the best results, it’s important that staffing parameters are considered in total schedule hours requirements. This is tricky because some solutions on the market ineffectively attempt to allow for these within the labor standards that should model and quantify the work. That approach may get the total time right, but it does not properly position scheduling requirements.

Managing staffing parameters and staffing hours

Managing staffing parameters is a dynamic process that inherently must allow you to apply flexibility as situations warrant. Examples of common staffing parameter adjustments include:

Do you have the resources available to analyze the cost of optimizing staffing hours? This can be a very manual and time-consuming process. With many systems, the only way to do this is to set up a separate sandbox environment to test changes and variations of staffing parameter settings by simulating alternatives for a full week’s requirements for each store.

Imagine if you had a staffing analyzer that could do this analysis quickly, accurately, and at a granular level by staffing parameter. Such a tool could make the management and optimization of staffing parameter settings much easier, especially if it could model changes across a large enterprise.

Benefits of analysis and informed adjustments

Deeper insight translates into better performance. Some of the benefits of staffing analysis and fine-tuning staffing hours include the ability to:

Besides having transparency into the placement of hours as a result of each staffing parameter, another major benefit of a staffing analyzer toolset is the ability to run what-if scenario analysis. Such analysis must enable you to do a comparison analysis to cost operational changes. Your analysis might be two distinct scenario sets to compare, or you may want to make a series of layered changes to view the effect of each change layer. Of course, your review should not only be on the total weekly or daily hours changed, but how each change impacts the placement of hours by time of day.

Next-generation tools to more precisely place scheduling requirements and to quantify the impact of staffing requirements over and above raw engineered demand hours are available. These tools are particularly valuable for retailers using task-based scheduling to more specifically define and direct the placement of hours to perform expected task work. The best of these tools allows modeling across a large organization in a matter of minutes; a task that previously would have taken days for a skilled analyst to model and run even for a small set of stores. Using these tools for a prior week of actual data, a forecast week, or even a budget allows for better allocation of labor—your stores’ most important resource to drive sales and customer satisfaction. And as previously mentioned, it’s also your largest controllable expense; a fact that provides compelling motivation indeed!

With significant changes coming faster every day, aren’t these the tools you want to optimize your labor for competitive advantage?

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