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Next-Generation Workforce Management: An Inventory of Fresh Opportunities for Retail Stores

In a previous post, I discussed the impacts of higher labor costs in retail. This post will explore how retailers can address this significant challenge with the latest generation of workforce management (WFM) tools that leverage expanded use of artificial intelligence (AI), real-time data exchange and more robust enterprise computing platforms. These enhancements offer retailers an inventory of new opportunities for early adopters.

Forecasting has taken significant leaps forward

Everyone knows that forecast accuracy is critical, but understanding the nuances can be tricky. For example, what’s the value of making your store just $1,000 more accurate each week in the forecasting process? Simple math would indicate that for an average store, the quantifiable value means getting 5-8 hours closer to the “right” number of hours based on work content and engineered standards. But in reality, the value is almost always two or three times greater since accuracy at the daily department level can lead to misplacing many more hours through changes in product mix at the department level. I’ve never seen a case where an overspent hour in the meat department justifies an hour short of cashier labor on the front end. Getting closer to the “right” number saves hours and delivers better service with less waste. But how can you get there?

Machine-based learning algorithms have enabled significant improvements in forecast accuracy. With more businesses forecasting earlier to support worker-friendly scheduling timelines further in advance, these enhancements make an incredible difference. This is especially the case when a whole array of algorithms can compete to create the most accurate forecast possible.

The best systems also enable dynamic reforecasting once your forecast and schedule are published. Especially for those retailers scheduling further in advance, this means that you can consider vital inputs on promotional activities and weather for additional fine-tuning and adjustment. Coupled with task-based scheduling, this can give retailers an option to flexibly reallocate task assignments even after the schedule is published in order to best utilize the skills of the team scheduled. The older tools are mostly still wrapped around job-based scheduling and very basic formula-driven forecasting algorithms. Ultimately, the message is clear: stick with outdated functionality at your peril.

Staffing parameters can be better understood and managed

After your labor model calculates raw engineered time (standards applied to volume drivers), a number of processes place/spread hours or modify calculated time to create 15-minute staffing requirements to schedule. Typically, staffing parameters include open and close times, rounding, rounding links, min and max coverage, performance factors, queueing (for service areas), smoothing, etc. Too often, these have remained a mystery corner when creating staffing requirements. New analysis tools make these parameters far easier to understand and manage, with full visibility of the additional hours created over and above that engineered work content.

With the right tools, retailers can expose and manage numerous hours for best-practice task placement and to eliminate waste. Visual mapping of fixed and variable tasks along with the layered impacts of staffing parameters make the analysis quicker and easier. It also exposes new layers of optimization.

Automated scheduling is not just for the front end anymore

Years ago, scheduling systems were adopted mostly to automate the process of writing schedules for front end employees. Front end workload demands correlate directly with interval forecast volumes. This means that once standards are applied (along with rounding, smoothing and a few other staffing parameters), it becomes fairly easy to define scheduling requirements and match those requirements to the employee job and availability pool in order to write a schedule. More complex union or business rules tend to be handled by most systems, and even second- or third-tier systems can usually generate an automated schedule. Some may require more editing than others, but they all offer some convenience over trying to manually build schedules by hand.

For years, the promise has been to carry that functionality over to all departments across the store, or from “wall to wall.” It’s a promise that few systems have the functionality to fulfill. Why? Developing the requirements is far more complex, and placing those requirements is nothing close to the almost-perfect correlation between activity time and scheduling time like it is for front end. Some vendors will say the correct selection of associates is all store-level preference, and not a matter of getting the requirements right. Some will make it easy to copy prior weeks’ schedules and argue that’s all that is needed. Some just prefer to put their efforts into functionality that drives sales in other vertical markets but will say it’s “in their future roadmap.” Good luck waiting to get there.

But the fact is that automated, near edit-free schedules can be created across all store departments. Doing so can free managers’ time for higher-value activities, producing schedules that better reflect the week-specific forecasting needs while adhering to company policies, best practices and regulatory mandates. And when combined with task-based scheduling, most retailers find new opportunities to minimize waste through sensible cross-utilization of associates to address service peaks.

The tools don’t end with schedule publication

Most WFM systems’ functionality ends with schedule publication and associated reports. Thankfully, this is not true of the latest systems. The timing could not be better, because while retailers have always needed to respond to late-breaking changes in weather, promotions and competitive offerings, dealing with these changes is now compounded by further-in-advance schedule writing to support predictive scheduling requirements. Some of these predictive scheduling requirements make it difficult to adjust schedules without penalties, so the ability to manage further out and late-breaking changes with sophistication and precision is more important than ever.

Here’s where task-based scheduling offers the ability to reassign work to the crew as scheduled to make smart adjustments as they become needed. It’s a given that some variation to plans will sometimes have to occur. However, knowing where your performance stands during the week in progress and having tools to modify those workplans to make smart adjustments allows your store team to react sooner and in a best-practice manner. Your best managers are likely already making at least some of these changes, but do all of your managers? And do they make strategic adjustments to preserve your brand and service priorities? The right week-in-progress tools can make all the difference.

Continuous improvement without the costly analyst overhead

“Measure what you manage” and “learn from your experience” are key mantras to any WFM implementation. With that in mind, isn’t it remarkable that few systems capture and save system-generated forecasts and schedules to compare with the final edited and published versions? If you don’t have a strategy or toolset that measures forecast accuracy and scheduling effectiveness along with labor performance, how can you make meaningful progress by leveraging your experience? Here again, AI automation can perform much of this analysis work without the tedious dedication of labor analysts to sift through the details and draw meaningful conclusions. The new tools are based on regular, system-based analytics. Spend less time working on analysis and more time coaching based on system analysis.

Concluding thoughts

While higher labor costs and new employee-friendly policies and restrictions have created new challenges and pressures for both retail companies and for WFM tools, the best of the new systems offer retailers significant opportunities to overcome these challenges. These powerful solutions enable retailers to redeploy managers’ time to sales floor activities, and they create new sources of optimization and competitive advantage for those who are best equipped. In the wake of these exciting technological advancements, retailers are advised to take inventory of their needs and capitalize on opportunities. Start by considering upgrades to the weakest tools in your WFM toolbox, and then let the benefits fund appropriate reinvestments.

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