Over the past few weeks, we introduced a series of blog posts (see part one and part two) looking at similarities between the 2011 baseball movie Moneyball and the analytics seen in today’s retail world. In the movie, the main characters Billy Beane (portrayed by Brad Pitt) and Peter Brand (portrayed by Jonah Hill) implement a statistical approach called sabermetrics, which helped Beane and Brand better understand baseball player and team performances. In the first post of the series, we outlined how sabermetrics can help put the right baseball players in the right positions to create team success. In retail, there is a parallel benefit to slotting employees in the right role when customers need them. In the second post, we described how sabermetrics uses past data to forecast future team performance. The same goes for retail; accurate forecasting is paramount to retail success!

In today’s final post of this series, we will describe how similar approaches exist between sabermetrics and retail around how retail leaders utilize what-if technology to examine labor changes. Let’s illustrate with an example. In sabermetrics, one helpful approach is to provide a useful function of the player’s donations to his team. When analyzing player data, coaches and analysts are able to understand the player’s contributions and how they add to or detract from the team’s goals. Given that correlation, general managers can sign or release players with certain characteristics that add or detract from the team’s overall mission. There is a scene in Moneyball where Beane is talking with his scouts about potential players. Beane suggests to the scouts that many average players contribute more to the entire team, making the overall team more valuable. This approach to understanding a given player’s characteristics allowed Beane to understand how that impacted the team as a whole.

How it plays out in retail

In retail, a similar approach is often used to understand how certain tasks contribute to an entire labor model. Using engineered standards, workforce management teams build labor models from the ground up. This means that the smallest levels of detail (i.e., specific motions within subprocesses of an overall process) are leveraged to build up the larger picture of required labor (i.e., all labor required within a certain department by day.) Having this level of detail allows retailers to make and model changes and see how that impacts the entire model. These modeling environments are often called what-if environments and offer analysts the capacity to determine how one small change would impact the greater whole. In the past, retailers would use their best non-scientific judgement (and previous trial-and-error) to determine these impacts; today, we estimate them with a low degree of error in real time.

As a recent example, we were part of an analysis where the retailer wanted to understand how much labor would be added to their stores if the requirement to spot-sweep the produce floors was increased from four times to eight times a day. Having engineered standards built at a granular level that included a frequency for sweeping floors allowed us to perform this analysis within the same day and report back to the retailer how much labor that would add to the entire labor model. Without a what-if standards analysis tool, this type of analysis would have taken much longer and likely would have been less accurate. This real-time type of analysis allowed the leadership team to make the decision much faster with a higher level of accuracy, while also allowing the workforce management team to quickly move on to further similar analysis on other labor studies.

In summary, having a labor model that is built on the smallest levels of detail provides retailers the ability to understand and model how certain characteristics contribute to the entire labor model. But, like Beane’s approach with the scouts, it’s also important to have a tool that can perform the analytics to provide such analysis. The tool saves time and ultimately money, making technological solutions with what-if capabilities very handy for retailers who want to increase their profits!

One of the largest retail expenses is labor efficiency. Companies employ various strategies to improve their labor rate for this reason. To perform at an optimum labor efficiency rate, retailers place equipment and tools within the work environment to maximize their workforce output. In my experience, some organizations do not have the right tools in place, while other organizations have what they need, but their organizational or maintenance tactics are so loose that they burn money on stalled production. Today’s blog post will review the effects of great equipment maintenance and organization, as well as how this affects workforce labor efficiency, through a topic called lean.

For those of you unfamiliar with this arena, lean comes from six sigma terminology and is focused on reducing waste in the workplace to ultimately reduce variation within production. For the most part, six sigma (which is the reduced variation piece) has been most effective in the manufacturing industry. The good news for those not in manufacturing is that lean (the reduced waste piece) can apply to any industry including retail. Within this blog post, going lean will refer to storing and managing tools effectively so employees know where to find what they need for every step of each process, even if the employee is new. More than that, going lean includes reducing unnecessary steps within the process that cost retailers money. Let us begin.

Get the right equipment in place first

No matter how skilled associates may be, they cannot execute at maximum output if the retailer lacks essential equipment or tools to do the work required. This is especially true when overall resources are compared to the number of employees who need to use them within each task. By providing associates with enough resources to get their jobs done, the retailer’s bottom line is positively affected, and the additional tools eventually pay for themselves. How does a retailer know if they have the right tools in place? First and foremost, a retailer must understand their processes, or standards. What does every step of every task require? To find out, many companies use engineers skilled in time and measure studies to lay out these standards across departments.

Store the tools in the same place every time

Inadequate storage of work materials is another factor that can impact labor efficiency. With poor equipment organization, retailers risk damaging tools or, at minimum, increasing wear and tear. Sure, some items are larger and therefore harder to lose, but if there are no preferred methods for storing smaller equipment, they often get lost. In some industries, like aviation, losing small parts in dangerous spaces (called Foreign Object Debris) can cost billions. In retail, keeping equipment in the same, well-defined, properly labeled space every time saves money in part replacements and labor efficiency. How does a retailer do that? Consultants and engineers often utilize a system called 5-S for this endeavor. Adapted from the Toyota company, the 5-S system stands for: sort, set in order, shine, standardize, and sustain.

Maintain the tools to increase safety and reduce costs

Regular maintenance of equipment is another factor that can have a positive impact on labor efficiency in the workforce. Maintenance often covers activities including inspection, testing, replacement and adjustment of tools necessary for the workforce. Maintenance plays a vital role in reducing the risk associated with workplace hazards and providing safer and healthier working conditions. Additionally, systems like visual method sheets show associates how to use tools properly, lessening the wear-and-tear on equipment and reducing maintenance. Those same visual aids can alert the right people when maintenance is due because they function as tracking mechanisms.

The indirect effect of going lean

Beyond the direct impact that proper equipment, maintenance and storage have on productivity and efficiency, there is an impact on associates’ morale which must be considered. When associates’ tools are organized and maintained effectively, it shows that leadership cares about them. Their morale increases, propelling them forward to do their jobs most effectively. This can cause a retail culture to unify around the vision and mission of the organization. Employees showcase passion for their work, and the result is more corporate energy to get jobs done, thus driving costs down.

What to do next

For these reasons, we encourage retailers to consider going lean through proper equipment maintenance and storage. The first step is to understand all the tasks that are expected from associates day to day. Many companies offer services to help in this standards development process. Next, with an understanding of the work, retailers can determine what tools are needed to perform to standard. Maybe existing tools will do the trick, but maybe updated equipment is needed to effectively compete with other retailers or to adequately meet customer demands. Once tools are procured, figuring out how to store and maintain those tools in a way that makes sense to employees who use them, keeping them safe and effective, will boost a retailer’s labor efficiency.

For retailers beyond these points, continue going lean. Consider storing only what is needed, organizing and upgrading equipment in an intuitive way, and creating guides for others that explain how and why standards are set like they are. Often, retailers do not have to spend significant capital to get more organized, but can do so in a piecemeal fashion over time. Regardless of the approach, going lean will reap dividends for any organization willing to take it on.

I’ve often heard the questions, “Why is there a difference between the output of my labor model and the sum of the scheduling requirements that I send to my automated scheduler? Should there be a difference, and why?” These are great questions that merit exploration. There is much to be gained from a solid understanding about the difference between the output of engineered labor standards in a labor model and the staffing requirements needed to drive an organization’s staffing and scheduling strategies.

Understanding engineered labor standards and the function of most labor models

Let’s start by reestablishing some basics. Most labor models are built to quantify workload. All work tasks/operations are identified. Some of these are fixed, and some are variable based on workload drivers (e.g., items, customers, packages, cases, types of cases, etc.) For the variable activities, the workload drivers are identified and mapped to the appropriate time standards. All activities have engineered labor standards, and some of these may have embedded store characteristics for equipment, distances or other points of variation as needed to create accurate, store-specific standards. Labor models will also typically support allowance management for personal fatigue, delay or other ongoing allowances you wish to define. But, in most cases at least, the final output of the labor model is engineered work content time, not necessarily the time needed to schedule that workload.

What’s the difference between engineered time and staffing requirements?

In addition to satisfying the raw engineered time it takes to perform the work, retailers have a variety of rules and conditions that must also be met as the workload is transformed into specific 15-minute scheduling requirements. The most basic of these is minimum (or maximum) coverage requirements. For example, a retailer might stipulate that regardless of how much work needs to be done, a specific job or department—or aggregation of departments—must have a minimum staffing coverage of one associate for a specified time range, such as 8:00 a.m. to 8:00 p.m. If we use a customer service counter as an example, this minimum staffing requirement can be responsible for more hours than the actual standard-based workload of the various operations performed at the service counter. 

Along with “min and max” staffing rules, other parameters may be defined in the staffing requirements process. For areas with service queueing, the defined queue parameters can also add time to the engineered workload. While the standards and volume drivers quantify the raw labor, managing the queue experience is often a vital part of customer satisfaction and repeat business. Ignoring this imperative in an effort to push optimization to only the engineered work content can have dire consequences that result in frustrated customers waiting in long lines.

Likewise, certain allowances for new-store learning curves and the introductory ramp-up for new technology or processes, etc. are sometimes best managed as staffing allowances instead of within the labor standards themselves. First, doing so provides greater visibility and easier management of temporary allowances which should be revised as the need goes away. Second, it does not misrepresent the clear work content of what should be expected by employees performing at the standard rate as defined by the organization. It allows the standard to be the standard, not to be morphed by temporary allowances.

I’ve seen retailers that have completely lost the integrity and faith in their standards by trying to meld staffing rules and considerations back into the standards. It is far more manageable to understand the difference and validity of engineered time versus staffing requirements time. 

But is staffing time easy to quantify and manage?

The reality is that solutions vary immensely from system to system regarding how easy it is to understand and manage staffing time. It is easy to see these summarily in the difference in weekly engineered hours and weekly schedule requirements. But to see which staffing decisions are causing more hours to be added—and where those hours are getting added across each day in the requirements—is something few systems do well. 

What must a better system do?

Ideally, you want to know how much each staffing parameter is contributing to extra hours. You should see this not only in aggregate, but in the individual layers by parameter or by special allowance. The visibility not only must be weekly or daily, but by time of day. Only then can you analyze whether that spend makes sense for your business and assess options. Perhaps the spread of the volume work could be different such that it creates fewer add-on hours due to minimum coverage. Or perhaps that minimum coverage should be challenged for some jobs, or maybe move from job-specific minimums to higher levels that still provide service but reduce a low-value spend. 

Whether the insights from such analysis allow you to remove hours for optimization or move hours to higher-value interactions that boost sales and customer retention, these decisions should be well informed and subject to ongoing scrutiny. 

With almost every retailer today looking to accomplish more with less, it is imperative to strategically invest and deploy labor resources where they will best drive sales, differentiation and customer loyalty. The elegance of these analysis tools presents a tremendous opportunity. In short, they enable a very small labor team to do far more than what larger labor teams without such tools could ever do to drive better staffing strategies.

Subscribe to Logile’s Blog

The use of detailed, store-specific engineered labor standards has been a significant advancement to support labor modeling and planning for retail stores. Techniques vary, but the approach is based on quantifying work content to both plan and assess performance rather than reliance on more basic key performance indicators (KPIs) such as sales per hour (SPH) or wage percent. Standards are defined for each operation or task performed and may include store-specific customization to account for special equipment, travel distances and other store characteristics. Modeling can be rather complex, with some departments having hundreds of standards or variations across a large-scale enterprise. These tools have brought great precision to the techniques available to model labor. However, with this approach comes the challenge to create organization and store-specific standards to get started, plus the ongoing resource commitment to keep the standards accurate as the business evolves over time.

With so much at stake in managing labor both for the
delivery of customer service and to manage retail’s #1 expense, labor standards
and systems to leverage them in forecasting, staffing and scheduling are back
on the priority list for most organizations. Those who successfully automated front
end scheduling are moving to wall-to-wall scheduling (all departments), and
others are working refinements to address weak links in their WFM ecosystem.
Often that involves a full refresh of the labor standards and the opportunity
to get more detailed and precise about how much time each operation and task
takes.

But is this the only path forward?

What if your organization can’t afford the engineering
studies required to build the standards? What if your organization is unwilling
or unable to provide resources to keep your standards current? What if you
barely have the talent on board necessary to oversee this ecosystem, identify
and resolve outliers, and counsel stores when managers consider the hours
inadequate to do the job? Or what if you are a 10-store independent that cannot
even staff a dedicated labor specialist, let alone a labor team?

Do any of these factors mean that you are stuck doing
planning and scheduling on pencil and paper or with the same tools you used
15-20 years ago? Is that good enough even when you face the same challenges as
larger organizations in executing your format with less experienced managers
and employees?

The answer is no. There is no reason that organizations with
these constraints cannot benefit from the latest advancements in forecast
accuracy, scheduling effectiveness, mobility, and real-time data flows to
facilitate better store management. But it may take different approaches to the
way you build and manage labor standards to make a better WFM ecosystem
practical for your situation.

Empirical vs. incremental standards

The most advanced tools and features for standard
development are designed to create empirical standards that quantify exactly
how much time it should take to perform an operation, a task and—collectively—a
department. It can take hundreds of operations in a single department to model
all of the work. Some tasks are fixed, and others vary by work volume (items,
customers, pounds, packages, cases, etc.) Empirical standards set out to
quantify how many hours it takes, in a well-organized environment, for an
average trained person working at an all-day pace to do the work. 

Incremental standards take a different approach. The best
incremental standards also look at work in both a fixed and variable approach.
A fully variable approach like SPH or a financial measure like wage percent is
far less effective. Incremental standards recognize that we don’t necessarily
know or need to know the endgame answer for how much time it really takes. Instead,
it understands how much time we are currently taking and sets a reasonable goal
to improve upon that. This approach accepts imperfection but is also built with
the key change management consideration that you can’t move directly from your
current state to the endgame all in one step anyway. Steady, incremental
progress is not only more achievable, but it is almost always more sustainable.

Do the best forecasting, staffing and scheduling tools still work with incremental standards?

Taking the incremental approach to standards, whether you do
that in certain departments or across most of your departments, does not negate
the benefits of better forecasting and scheduling. In fact, it can often
significantly reduce the time to implement a solution and get benefits flowing.
And you always have the option of dialing up the details where you see the
benefits in doing so. 

While resources are still required to deploy, train and
manage the solution set, it can be done without huge engineering services or a
staff of dedicated engineers to maintain your standards. Of course, the same
underlying conditions for success must be present whether your standards are
built for incremental steps forward or for a clear picture of quantified
optimal performance. Management must be involved and engaged, and workplace
conditions must be orderly. High-volume and highly repeated work processes
should utilize the best, store-specific method to do the work safely and
efficiently, and good management must be present and active in shaping
expectations and facilitating training and performance. All of those conditions
for success still apply, regardless of which approach you take for
standards. 

The bottom line

The cost of creating and maintaining detailed engineered
standards need not be a barrier for game-changing labor improvements in
forecasting, staffing, scheduling and store execution. You have other options.
The right system and configuration will allow you to leverage less detailed
incremental standards to make improvements that help you serve your customers
better than ever, while managing your largest controllable expense. 

And the best part of that news is that the latest systems
and approaches can offer significant benefit potential not just for industry-leading
companies, but also for smaller chains or independents—including those with 10
or fewer stores!