Preparing for Data-Driven Labor Management

8/21/2017

No matter how many robots, kiosks and shiny technology are readily available to improve the in-store experience, retail stores still need human power to operate and provide personalized customer service through store associates. After all, the human touch still gives brick-and-mortar retailers a key advantage over e-commerce merchants.



Labor management is key to ensuring each store has the right associates in place at the right time to provide this experience, without spending excessively on labor. If retailers can better predict the number and skill set of employees that each store needs every hour of every day each week, then customers receive prompt sales assistance, shelves are replenished in a timely manner, employees are neither idle nor overworked, and labor costs go down.



In fact, a data-driven approach to labor scheduling and labor budgeting often leads to significant cost savings AND improved customer service.



Understand Labor Management

Labor management is a set of integrated processes which affects the retail organization from the top down. It goes beyond managing employee schedules and allocating talent. It encompasses the entire process of aligning corporate financial plans with store labor budgets, and finally labor schedules.



Traditionally, at the highest level, corporate allocates a monthly budget towards labor. Often, the allocation is based on a percentage of sales which does not take into consideration the unique aspects of the individual stores, promotional calendars, etc. In many cases, this approach simply perpetuates past performance. A more data driven approach would base the allocation on unique key metrics such as traffic, tasks, promotional calendars, and store demographic attributes. Analysis of “time and motion” studies of key tasks are used to identify opportunities to improve the timing and productivity of “non-selling” tasks, with the goal of improving productivity around certain tasks to save or reallocate the labor hours into better customer service.



After answering the question “How do we allocate our constrained payroll dollars most effectively to minimize payroll costs and maximize sales?”, our labor budgets are generated on a weekly basis by store and/or department. Finally, hourly employees are scheduled based on their availability to meet those labor budget needs. “If I have x number of budget hours available for this store for this week, how should I schedule Mary Sue and Bobby Joe to cover those hours each day?” A data driven approach would look at historical patterns to optimize the scheduling.



Incorporate Best Practices

With a large number of complicated factors to consider in a data-driven approach, planners need to set and incorporate best practices across all areas of labor management. Best practices include:



Forecasting

o Adjust trended averages for seasonality and events including: sales promotions, customer traffic patterns, external data such as weather forecasts, etc.



Scheduling, Time and Attendance

o Optimize employee schedules to comply with key performance indices and labor percent targets.

o Create quarter-hour based schedules to support both department service levels and employee availability.

o Optimize non-selling activities and employee skills.

o Interface time and attendance with scheduling to monitor actual spend versus budgeted payroll expense.

o Automate downloads of schedules to the time and attendance system for shift compliance check.



Standards

o Set store specific task level target standards with seasonal variances.

o Establish minimum staffing requirements.



System Integration

o Interface point-of-sale data, receipt data, human resource data, scheduling software, time and attendance, and payroll.

o Account for budget constraints.



Budgeting

o Comply with Sales-Per-Labor-Hour (SPLH) standards and labor percent goals at both department and job levels adjusted for volume and seasonal variances.

o Recognize store specific layouts and specific store requirements.



Allocation

o Interface quarter-hour point-of-sale data at the department level.

o Establish seasonal and holiday patterns.



Reporting and Analysis

o Report at store and department level for daily labor management utilizing numerical and graphical representation of data.

o Use store and corporate level dashboards for daily and weekly performance versus plan, analysis of variances and trends.



See Cost Savings and Improve Customer Service

In today’s planning environment, too many retailers continue to rely on time-consuming, manually intensive practices and systems that stunt effective labor allocation. Understanding critical drivers and tasks to maximize employee effectiveness for “non-selling” activities and allocating resources to drive sales efficiently is key. Monitoring and benchmarking store level performance provides the opportunity to capture trends, continue to look for areas to improve and adjust to changing market conditions.



Even with a robust labor management software solution, retailers can’t simply flip a switch and expect magic. Retailers need to clearly understand all of the tasks and components that factor into the labor process and incorporate data from each of those areas into their data-driven labor management system. With the right data inputs and best practices in place, retailers will see cost savings and improved customer service through data-driven labor management. For example, if you have 1,000 stores with 15,000 hourly team members, saving two hours per store per week at $12 per hour will result in saving of $1.25M per year. That’s significant!






Tom Phelps is a partner at Columbus Consulting International.




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