– Supply Chain Insight –
Last-minute holiday wish list from your Distribution Center Directors
Supply Chain Operations & Finance
When the holiday season rolls around, for most, holiday wish lists include items like the most recent gaming system, winter clothing, household items, sporting goods, and gift cards to popular online retailers.
For Distribution Center Directors, the list is a little more simple and straight forward.
Let’s get right into what’s hot this year in the world of order distribution.
Higher Direct Labor Efficiency
Regardless of what channel you are servicing, seasonal increases in inbound orders from customers naturally mean more throughput demand on the operation.
This increase in demand could be coming from a specific assortment of holiday items or, as in most cases, it could be an increase across the board. Either way, especially this time of year, orders typically from with a promise. Retail stores need to be stocked for holiday shopping and online orders need to be fulfilled and shipped out in time for those Secret Santa giveaways. It’s a stressful time of year. It’s more stressful, however, if you don’t know how to scale your order throughput in a profitable way.
To some, scaling up throughput means adding additional labor to the operation floor. But, as many experienced operators know, this doesn’t always help increase order throughput. Moreover, it can significantly increase shipping costs if the operation is running sub-optimally to begin with.
Related: Scaling up your direct labor force? Read this first.
The good news is, there are ways to profitably scale order throughput, and they might just be hiding in plain sight.
Give your HR Director a much-needed day off and continue reading.
According to a recent warehouse labor productivity study done through ROFDA and FMI, order selection accounts for a little over 50% of the average fulfillment operation’s direct labor spend, and selection travel is a big part of that. This means that, if the goal is to increase efficiency, you should start with an evaluation of your slotting requirements and your pick path.
Most common cause of unnecessary selection travel?
Before implementing SKUStream, our fulfillment optimization system, into an operation, we oftentimes conduct what we call a Strategic Opportunity Assessment to uncover area of expected improvement. Out of the various assessments we do, one of the more common is what percentage of items are located in an optimal pick slot vs. sub-optimal. When it comes to sub-optimal, we’re referring to items located in slot types that are either too big or too small. In can confidently say that in the majority of our SOA’s, the most common cause of unnecessary selection travel within an operation is an overabundance / misuse of large profiles. Slotting your item in the most productive slot types not can not only reduce replenishments, case handling, letdowns and putaways, but it can also help you tighten up your selection path and minimize unnecessary travel.
Proper item sequencing can go along way to not only minimize product damage, increase ergonomics, and adhere to food safety concerns, but it can also boost the productivity of your order selectors. Consider the fact that each time an order selector picks a case from the rack, they have to decide where that case fits on the pallet. If they are picking crushable cases, topless cases, or heavy cases – to name just a few examples – out of sequence, the order selector is forced to shuffle cases, or worst, reconfigure the pallet. In addition, if your WMS has a built-in case weight restriction for certain heights, improper sequencing can lead to the creation of additional order assignments.
Most common cause of improper sequencing?
In my experience, there are two common causes of improper sequencing. First and foremost, it begins and ends with source data and proper item classification. The second is a lack of proper slotting tools. Having the data doesn’t help if you don’t have the means to easily use it while making slotting decisions. Experience and gut-feeling may work for a percentage of your variety – the more common items to the operation – but relying on that alone to optimize your sequencing for your full variety is a recipe for disaster over time as it’s a near impossible task to do manually.
In more complex operations (pick and pack e-commerce, for example) where there are multiple direct labor functions working concurrently, process flow is critical to not only your labor productivity levels but also to avoiding bottlenecks. Even if you do use an LMS and have access to detailed labor data, consider walking the floor to closely observe and time your different labor functions and even build out a process flow map to really understand what tasks and functions are involved in every aspect of a specific process.
Most common cause of process bottlenecks / inefficiencies?
Now, while I’d usually put the blame on an overly complex process (or one that has not been fully thought through), the most common culprit is usually the evaluation of efficiency in the first place. When it comes to most labor management systems, the most common labor KPIs are units/hour productivity and efficiency to labor standard, if they exist. What’s not often tracked consistently is shift utilization, which is on-task percentage against shift (paid) hours. This should be your baseline for tracking process efficiency as it considers all variables / potential bottlenecks regardless of how productive a specific process is. Consider a situation where you have a highly productive employee, exceeding all productivity goals but after every order, the employee has to reset their RF scanner to reestablish a system connection. The time it takes to reset the scanner will not show up in the productivity assessment, but it will show up when evaluating on-task %.
Whether it’s the segregation of slow-moving items, the introduction of different slot profiles, or slotting items by order commonality, the evaluation of different slotting strategies can be one of the most impacting decisions an operator can make. Although, these are all more tactical decisions that require some deeper thought and analysis, some can be implemented relatively quickly and without much or any CapEx.
Most common cause of an ineffective slotting strategy?
There can be many causes, of course, going back to things that drain productivity in general, like unnecessary selection travel and sub-optimal slotting causing excess labor tasks; however, when it comes to slotting strategies, something that sticks out like a sore thumb in most operations is how the slowest and fastest moving items are being handled. Handled improperly, your slower moving items can be a major drain on pick front and overall capacity if not situated in the proper rack type. Your faster moving items on the other hand, if slotted improperly, are likely to cause a noticeable increase in replenishments, shorts, putaways, and letdowns. Essentially, when planning a slotting strategy, your cornerstones should be your hyper-fast and hyper-slow items.
More operating capacity
Now, in most cases, unless we’re talking about a facility that’s been around well beyond its design year, what’s typically needed before anyone discusses an expansion is an assessment of operating capacity utilization, both in terms of pick fronts and overall cube operating capacity, as there’s typically more space available than what meets the eye. Let’s review some best practices for the proper assessment of operating capacity.
Pick front utilization
Typically, the first thing to look at when assessing pick front capacity is active SKU assortment vs. currently available pick fronts. One thing to remember, however, is within a season operation, if your SKU variety is increasing, and you’re not doing anything to adjust available pick fronts, capacity constraints are inevitable. A lack of pick front capacity can mean limited slotting optimization options, or even limited slotting options in general, depending on how full the operation is. A general rule is that if there’s less than 10% margin between your available pick fronts and your active SKU assortment, it’s going to negatively affect efficiency and, potentially, operating capacity. In this case, the quickest way to free up extra space is re-slotting slower moving items to smaller slot types.
As mentioned earlier in this post, in our experience, a thorough assessment of an operation’s current slotting usually uncovers a large number of items slotted in profiles that are too large. If you have a high pick front utilization. This assessment is a good place to start. From an operator’s perspective, this naturally may increase replenishments, letdowns and fingerprinting – and it’s true – but if you’re moving the right items, the increase should be negligible.
Operating capacity utilization
Now, I’m not going to sugar coat things here. If you’re operation is near its operating capacity – typically 80-85% of total available cube capacity – you may need to begin looking at more strategic options such as reducing weeks of supply for some slower moving items, SKU allocation across the distribution network (operations dedicated to specific customers or a specific profile of item, for example) or, in some cases, an expansion to the site. Once you pass that 80-85% threshold, you’re going to begin noticing space constraints (lack of pick fronts, for example), productivity lulls, safety issues, bottlenecks and, of course, your ability to deal with seasonal peaks will be hindered.
For those looking for potential alternatives, an interesting finding that came out of the warehouse productivity study that I referenced earlier, was the potential benefits of adding a very narrow aisle (VNA) concept for an operation’s slowest moving items.
What the findings revealed was while VNA provides 21% less productivity, the average operator using it is able to ship 57% more volume in 2/3 of the space of those who don’t have it. This means that, for most, cap-ex avoidance can off-set productivity losses.
They key, however, in ensuring this area does not turn into a bottleneck, is the consistent management of items within the VNA area.
Better Tool Kit
Finally, what Distribution Center Director doesn’t want a better tool kit?
For the most part, if your operation is struggling with scaling order throughput, increasing labor efficiency, and maximizing its operating capacity, it might just be a product of an outdated or incomplete tool kit. Don’t get me wrong, I’ve seen a lot of creative solutions built using spreadsheets and different kinds of databases, but the fact is, to really optimize an operation and stay ahead of the curve, you need to leverage data and proven analytics. Fulfillment optimization systems, up until a few years ago, have been the secret weapon of the best-in-class. Now, with all the cost-pressures and external variables (including ever changing consumer buying habits) these advanced systems are not just for the best-in-class, they’re essential.
Why is a fulfillment optimization system so important?
Leverages important operational data, on a daily basis
Data is king. You’ve likely heard that before. There is a reason why literally every decision elsewhere in your organization is driven by data. Why should that be any different in a fulfillment operation? The fact is that, as creative as your existing spreadsheets are, there’s simply no way to leverage all the data you need. Spreadsheets and simple databases were not created as fulfillment optimization tools. In the absence of readily available and accurate data, operators are left to rely solely on experience and assumptions. No operator or analyst really wants to be on the hook for designing and activating a complex 1,000,000 sq. ft. distribution center using a spreadsheet and basic modeling. Modern problems require modern solutions, as they say.
Considers important and complex trade-offs
One of the reasons data is so important when it comes to optimizing processes is that it allows you to consider costs / benefits all potential outcomes. A fulfillment optimization system can be used to create and implement facility design, layout and slotting scenarios based on desired cost, complexity, and order throughput, among many other things.
Provides actionable intelligence connecting concept to execution
Conceptual planning is all well and good (and, of course, necessary) but when it’s not directly connected to the eventual implementation – whether you’re activating a new greenfield operation, or just looking to execute on a new slotting strategy – the chance of what’s implemented being close to what was initially conceptualized is very slim. This is a problem. Fulfillment optimization systems contain functionality that can not only be used to conceptualize multiple design, layout and slotting scenarios but also take these scenarios through to the eventual zoning and mass-slotting of the items, ensuring the data and logic that was used for conceptual planning is the same data and logic that’s used for implementation.
Consistently challenges the status quo
The status quo is the adversary of continuous improvement. One of the reasons why some operations consistently struggle with capacity constraints and low labor efficiency, despite having the most advanced management systems on the market is because, by definition, management systems uphold and manage the status quo, therefore upholding any and all inconsistencies that may exist within the operation. To be fair, management systems were not created to challenge the status quo. That’s where fulfillment optimization systems come in. Leveraging data and advanced analytics, fulfillment optimization systems and there to not only help the operation improve within its current state but also challenge the current state altogether. You would be surprised at the improvement opportunities hiding just outside of the status quo.
To find out how a fulfillment optimization system can help mitigate waste and increase profit in your operation, we recommend starting with a no-obligation Strategic Opportunity Assessment.
Categories: Distribution Center Design, Engineered Slotting, Logistics & Resource Planning, Warehouse Optimization,