What does the sun have to do with your distribution operation?

Even those with rudimentary knowledge of our solar system probably know that our planet Earth is one of 8 planets (sorry, Pluto) that are constantly revolving around the near-perfect (and massive) ball of hot plasma that we call our sun. The Sun’s immense gravitational force is what keeps all 8 planets in orbit, each circumnavigating the radioactive yellow dwarf star at their own distance and speed.

For the past 4.5 billion years, Earth has consistently remained a shade (no pun intended) over 91 million miles away as it continuously circles the sun – although, during those summer heatwaves, it feels like it’s a lot closer than that.

Throughout those hot summer heatwaves or grueling cold fronts in the dead of winter, we may fill our small talk with complaints about the weather but, the reality is that Earth exists within what’s known as a circumstellar habitable zone – more affectionately referred to as the Goldilocks zone.

If you’re familiar with the fairytale Goldilocks and the Three Bears, you probably know why this relatively small habitable area is referred to as the Goldilocks zone. Essentially, within this zone, Earth exists close enough to the Sun that liquid water (essential for life as we know it) can exist without freezing in the cold or vaporizing in the heat.

In other words, it’s not too hot and it’s not too cold. It’s the right temperature for us all to exist and thrive.

So, what in the world does this have to do with your distribution operation? Well, when it comes to fine-tuning your fulfillment operation, it turns out the same is true. The universal principle “not too much, not too little…just the right amount” is just as true in managing logistics resources as it is in the creation of life on earth, though the stakes are, of course, a little higher in the latter.

Simply put, for logistics resources such as distribution center space, capacity, equipment, and direct labor, having too much may be just as detrimental to performance (and your bottom line) as is having too little. The most optimal operations have to find a sort of Goldilocks zone of their own.

While our solar system’s Goldilocks zone is measured in complex astronomical units (with the average distance between Earth and the sun representing 1 astronomical unit), you don’t have to be an astrophysicist to figure out your operation’s sweet spot – though having the right tools on hand to keep your operation fine-tuned throughout the year does help.

Let’s unpack using a couple of examples…

The first example illustrates labor cost as a function of staffing.

Now, like any model, there must be some constants. In this case, we’re assuming a daily average shipping volume of 50,000 cases and an average productivity rate of 150 cases / hour per employee. You, of course, know that there is no such thing as constants in a distribution operation but they do help us illustrate the point, and it does also serve as a reminder that, to truly fine-tune an operation, you’re dealing with potentially hundreds of parameters and moving variables.

Within the model above, you can see that, based on a productivity level of 150 cases picked per hour, per employee, the sweet spot for order selection staff is 42, or 336 hours. Any more or less and you’d be incurring additional costs, either through OT expenditure or through a build-up of unnecessary labor. The costs of short-staffing might be obvious but over-staffing is also expensive. You may assume that, if productivity remains constant, over-staffing will result in less shift hours being spent but, as Parkinson’s law states, work tends to expand to fill the time allotted for its completion. You will probably agree that this is true in most operations. It’s actually why many executives prefer to have some percentage of OT (typically around 5%) on the books, as it shows a more optimal utilization of labor hours.

The trick for shift supervisors is to manage this model on a daily basis while ensuring the operation is set up to allow for optimum productivity as, within this model, task efficiency is the most impactful lever for cost control. The more productive your selectors are, the fewer hours you need on the floor.

Now let’s review the same principle, this time looking at labor cost as a function of DC size.

While the first model is most optimally overlayed on top of a finely tuned operation where peak productivity can be achieved, using labor cost as a function of DC size allows us to get into the details of how to achieve that optimum productivity rate in the first place – before labor requirements are evaluated.

Now, DC size is certainly not the only consideration when optimizing an operation but it is one of the more impactful ones. As you can see in the model above, footprint (sq. ft.) is often the determining factor of the operation’s order selection travel path. We’ve mentioned it multiple times before but order selection is typically responsible for 50% of the average operation’s direct labor cost. With that in mind, the longer the pick path, the more expensive the order selection labor will be – especially if the throughput is the same.

Now, in a perfect world, orders processed would be the only consideration here but that’s just not the case in the real world. You have to adhere to constraints such as available equipment, product storage requirements, unit dimensions, temperature zones, mobile equipment, etc. However, the model does effectively illustrate the clear trade-off between travel and forklift labor. It’s one of the primary trade-offs that our fulfillment optimization system, SKUStream, makes on a daily basis when providing slotting and other more tactical recommendations, but you can see it clearly – in a more rudimentary way – above. Simply put, the more product on the floor, the more distance your selectors will have to cover for each order but the fewer replenishment, letdowns and putaway tasks your operation is likely to incur.

Though the potential for travel savings are often quite a bit higher, operators tend to lean towards capturing the forklift savings for a few different reasons. The first is that forklift tasks are more visible and can potentially cause dangerous aisle congestion. The next is that, in order to attain travel savings, the layout – or pick path – must be adjusted, and sometimes that’s not a feasible proposition. Finally, without the right tools, it’s very difficult to evaluate the saving opportunity, especially when it comes to more tactical improvements to a layout.

Often, through our Strategic Opportunity Assessments, we find over 500k in operational savings hiding in plain sight. You discover how quickly adjustments are made when that kind of money is at stake.

Finally, when it comes to DC sizing, while we show a linear relationship between footprint and travel path in our model, it doesn’t have to be the case. This is most important during the first few years after activation where the operation is growing into the full available capacity of the building. While a new operation is designed typically for 5-7 years of growth, your layout should be designed for your current requirements.

There you have it. Take a lesson from our Solar system and make sure you discover and adhere to your own operational sweet spots, whether you’re planning labor requirements, designing your pick path, or optimizing any number of other areas within your operation. Life as we know it is not at stake but you will find a direct and significant impact to your bottom line.

If you’d like more information on how a fulfillment optimization system can help you find your operation’s Goldilocks zone, check out SKUStream.