Detailed Image has had a really busy Spring season. Everyone has had to chip in a bit extra at the warehouse to ensure that we get all of the orders out the door in a timely manner. This past week was so busy that Mike, Greg, and I went in Sunday to pack boxes for about five hours, something we’ve never done before outside of the Black Friday to Cyber Monday rush. We’ve also each had many days where we’ve had to go into the warehouse unplanned to help out.
One of the more difficult things has always been figuring out at what threshold we need extra people in the warehouse beyond the scheduled team. What we’re really trying to quantify is: how much physical work needs to be done to get all of the orders out? For years we always relied on the total dollar amount of orders in our shipping queue. This is a good metric, but it has some noticeable flaws, especially on busy days. For instance, if we’re running a 20% off sale, that number will appear to be lower than the actual amount of work that needs to be done (an order that usually costs $100 will only be factored in at $80). Or, if we have a buffer on sale (as we do this month) and we’re selling a lot of them, it could make it appear as if there’s more work than there actually is because there’s a big difference in how long it takes to package a single $130 item than $130 in $10 – $20 products.
Given this, we asked ourselves, what numbers do we have that will help normalize this data a bit and give us a simple number that we can work off of on a daily basis? We decided that we could get a much better idea of how busy we were if we factored in total dollar amount being shipped, total number of packages being shipped, total number of items being shipped, and total weight being shipped. We then came up with a maximum threshold for each, the absolute most we think we can do in one business day given our current team, which we guessed to be roughly 20% higher than our previous maximums. These maximums will likely change any time we add staff or introduce a new efficiency.
We weighted each of these factors equally to come up with a simple single percentage that gives us a better approximation of how busy we are. We can view it in “real-time” for what is currently in our shipping queue, and also have a report so that we can compare it to the past. Our maximum is roughly five times larger than our average day, meaning that on average we’re around 20% capacity but that we’ve fluctuated up to about 80% on our busiest day. I’m not sure if this is normal for e-commerce companies or not. I certainly think the seasonal nature of our business, combined with how often we run sales, factors in to the variation quite a bit.
Here’s a shot of the variation from before, during, and after a recent sale (read from bottom up, so the 15% day is the first day in the example):
I’m really excited about this. It’s a very simple metric, which is why I think it works. It’s hard to try to think in terms of packages and revenue relative to our staffing capabilities, but it’s easy to think in terms of percentages. In both the short term and long term this should help us out quite a bit with our warehouse staffing decisions.