Those of us who have made a living from Logistics for a few years will probably admit that the principles to which we work haven’t changed much since the time the Romans had to figure out where to put their grain stores.
We hold stocks of things to smooth out the ripples in our supply chains, whether caused by forecast inaccuracy or mis-matches between production and consumption cycles. The challenge is where to store things and, once we’ve decided, how many of each to put in one spot. In this simplified view of our profession, it could be argued that transport is merely an extension of the same concept, because transport is about relocating things from where they are now to where they will be of sufficiently higher value to justify the bother of moving them.
As usual, entropy is out to get us. Even if we could conceive of having everything in exactly the right place today, we can be sure that tomorrow we will wish things were slightly different.
In virtually every supply chain worthy of the name, countless variables conspire to push chaos back into our ordered world. We try to put in place systems to identify the agents of chaos and combat them, using the structure of our logic to direct labour as if they were troops on the battlefield. Like any Commanders, we must always be mindful of the cost/benefit of the instructions we issue.
But let’s not stretch the military metaphor too far. In modern battles it’s very difficult to determine whether we’re better off today than we were yesterday. Happily, in warehousing we need not concern ourselves with the court of public opinion because we can instead rely on the objectivity of mathematics.
Here’s a representation of a sizeable warehouse, with convenient cross-isles delineating three principal pick zones. The colour coding illustrates fast-moving items in red (they’re “hot”) with slower moving items in shades of green and blue.
Stocks may once have been in the best place to meet a demand profile, but the ravages of forecast variability, seasonality and new product introductions (amongst many other things) have somewhat diminished our efficiency.
Notice, for example, the green item occupying a primary location just below and to the left of the shipping dock. Perhaps this item has come off promotion, or is no longer in season. It’s probably covered in a layer of dust.
With the fast-moving items spread through the warehouse, we’re spending time unnecessarily travelling. We should be spending that time picking. We’re wasting money.
Feeding the same order profiles into the world’s best mathematical optimisation engine might offer the following alternative storage plan.
Notice that the red fast movers are now located in the zone nearest to the shipping dock and they are spaced out in a manner that ensures that the picking operations do not run into difficulties of congestion.
That’s a whole lot better.
So now the real challenge is to move from what you have to what you should have, gaining in each move more than what it costs to carry it out. This is exactly why I have said before that you just gotta love maths!
Maths will tell you which moves are of the highest benefit, and exactly what they will cost in the real world of having to conduct your day-to-day operations at the same time. You can carry them out, a section at a time, using end-of-shift fork-lift drivers that might otherwise be underemployed.
Whether you count your cost savings and efficiency improvements in dollars, pounds, bitcoin, pieces of silver or pretzels, you’ll be a whole lot better off when you keep entropy at bay.
How much better off?
Let’s put it this way: our solutions pay for themselves in months, not years.
