It’s pretty simple: If you want to improve your warehouse operations and increase efficiency, you need to know where you’re starting from. Fortunately, there is one metric that we’ve found is the perfect introduction to data-driven improvements.
Every time a client asks us to help them diagnose their warehouse operations, we start the only way we know how: analyzing the data. Unfortunately, in many cases, the “right” data isn’t easily accessible and there can be conflicting interpretations that make it difficult to make sense of it. All too often, the discussion disintegrates when the following statement is uttered: “(Insert unusual event here) happened around that time, so the results would have been better had it not been for that.” Sound familiar?
You can’t manage what you don’t measure
When clients are looking to start assessing their warehouse operations, I always advocate for using a metric that is simple to understand, translates easily between disparate facilities, and is nearly indisputable. I recommend this because the more you attempt to make your metric global or all-encompassing in nature, you’ll find that the effort to obtain the data rises exponentially. You also find that the more granular the metric is, the more people become sensitive to it, leading to inevitable disputes. This is true even if you have a labor-management system in place. Like any tool, they can be misapplied and end up producing low-quality data leading to misconstrued metrics if not used properly.
The most useful warehouse metric of all
So, if you’re looking to start tracking meaningful data and make immediate improvements, I would begin with throughput. In the simplest terms, throughput is the Total Items Shipped (X) divided by Total Direct Labor Hours to arrive at Items Shipped per Hour. For the X value, I suggest identifying the most meaningful, relevant unit of measure that can be easily obtained for your business. For instance, if you routinely process a combination of cases and pallets, I would settle on using total cases as the relevant unit, converting any pallets to cases, and using the aggregate result as the input.
Once you’ve decided on a metric, you’ll need to standardize how and when the data will be captured. This is best done on a daily, weekly, and monthly basis. Then you can evaluate the results with the goal of driving variability to within ±5%.
The point of all of this is to get really good at managing your daily throughput by either shifting demand or labor to maintain a level of consistency. This makes it possible to generate savings for line items such as rush freight charges and overtime. Becoming adept at measuring and applying the throughput metric will give your company the capability to consider adding additional metrics to gain further visibility and increased operational control. It’s just another milestone on the never-ending journey toward efficient and predictable supply chains.
Taking your organization to the next level requires quantifiable and reliable measures of performance. Reach out to us. We’ll show you how Chainalytics can help you harness the power of data to build a more consistently efficient supply chain. Our one-of-a-kind approaches like digital assets and managed analytics services combined with top supply chain operations talent consistently deliver actionable insights and measurable outcomes for our clients.
Stephen Bartolotta is a principal in Chainalytics’ Supply Chain Operations consulting practice. He has more than 30 years’ experience leading transformative supply chain strategy engagements in warehouse design and operations, inventory management, transportation, and business strategy.
