Many distributors assume they can handle one more warehouse order for free. Aren’t all warehouse operational-costs fixed in the moment? And isn’t keeping people busier good? Alas, no!

Let’s look at the cold statistics for a contractor-supply distributor’s monster, Central Distribution Center (CDC).

The facts

This $200MM+ distributor’s CDC ships to: local customers; branch replenishments; and branch cross-docked orders. Here are the CDC’s 2020 annual stats:

  • Outbound sales shipments: $100MM;
  • Total cost of running the DC: $10.2MM (not including purchasing costs for replenishment stock);
  • Annual picks of 672,602 that go into 136,000 orders;
  • Average cost per pick: $15.11; per order $74+;
  • 11, 700 active SKUs averaging 57 picks per SKU;
  • SKUs ranked by picks reveals that the top 45 range from 3,500 annual picks down to 1,900.;
  • 25 of these 45 were small-margin-dollars/pick SKUs averaging (as a group) $7.62 in margin-dollars/pick. That’s $7.49 below the average cost/pick of $15.11.;
  • The 25 – as a group – had total picks of 43,854. (.2% of SKUs total 6.5% of picks).; and
  • Theoretical picking loss? $15.11 – 7.62 = a loss per pick of ($7.49) x 43,854 picks = ($328,466.)

But, the picking-loss damage goes further down the ranking report!

The top 150 most-losing SKUs have a margin-dollar total that is $1MM below the $15.11 margin-dollar break-even.

Management was shocked and immediately defensive. They nitpicked the cost model and raised other data-free, wishful, counter points. But, the analytics patiently refuted every plea for keeping the status quo.

What to do?

The analytics revealed a blend of solutions that would reduce losses and/or consolidate picks to allow more throughput growth without adding more manpower. The easiest, initial solution would be to automate the existing picking costs by inserting collaborative robots (cobots).

How exactly? Relocate the 150+ biggest-losing SKUs from their respective, supplier-line aisles to one tight area. There: a no-traveling, person would do 300+ picks per hour feeding request from five-to-seven cobots per full-time picker. With the bots doing all of the travelling, total costs (and errors) are projected to drop by 50-to-80%.

For value-added consulting and the cobots — as a monthly service — check out the niche-creator and leader

Moral of the story

Effective analytics reveal big, surprising insights that require big changes for big gains. Does your company have the curiosity and big courage to put breakthrough insights from to work?