Page 19 - UnderstandingJanSanRedistribution_flipbook

1. Achieve 95% cycle count accuracy on 20 A+ items everyday as a measure for how good physical
stock housekeeping was to reduce the need for stock checks and the inability to find stock which
was supposed to exist.
2. Accurate and timely processing of all orders for the other location was given top priority on both
sides of the fence.
3. Receive all incoming stock the same day or no later than 7AM the next morning. This avoided stock
outs of popular items that had landed, but had not yet been received.
4. All new and expiring sales contracts – typically won and lost on annual bid cycles – were documented
and scheduled on a calendar shared by both the sales and the purchasing department, so that
both inventory and future demand numbers could be manually adjusted on a timely basis. This
avoided sudden waves of poor fill-rates, because a new, volume contract would deplete key items
quickly.

Stage Four: Eureka Moment! New Formula:

Turn/Earn factor + fill-rate boost + virtual selling of 8k + more cross-docked items = WOW

Deuce and a task team started to do a formal review of how demand forecasting could be done better for
the biggest suppliers and stumbled over an odd story. ABC had decided to push one big commodity supplier
(Line One) over another (Line Two). For over a year, ABC bought Line Two through a Master Distributor (MD/
Wholesaler) to take care of residual customer demand that would presumably be switched to Line One as
quickly as possible while ordering about 40 truckloads direct from Line One’s factory. After one year, sales
on Line Two had grown by 15% versus only 5% for Line One. Why the big growth difference when ABC was
trying to do the opposite? Could it have been to dramatically better fill-rates on all of the items in Line Two?

Thinking deeper, the team reasoned that ABC was buying about 30 different items in both lines, but in
each line only about 4 items generated 80% of the sales, while the others had turns of 2 to 8 times per
year. It is very difficult to forecast demand for items that sell in smaller quantities over longer periods of
time. The longer the time inbetween re-ordering, the greater the degrees of both stock outs and excess
stock problems. Because the master distributor delivered all items within two days, the fill-rates for the
bottom 25 items went way up, while the average investment in those items went down. The MD was not
only providing ABC with a better turn-earn on these items, but much higher fill-rate benefits! Perhaps the
customers that buy smaller quantities of specialty items are more fill-rate sensitive in contrast to those
customers that buy big volumes of the commodity items on a bid basis. (?) Retaining the specialty buyers
with better fill-rates could explain the 15% growth rate which may have come from a competitor that was
buying Line Two direct and trying to cover “shorts” with other, double-transaction cost heroics.

The logical extrapolation of this discovery was to propose a new type of partnership with the right MD in
which:
■ ABC buys as much as they can from MD on a vendor managed inventory (VMI) basis.
■ MD delivers in the middle of every night, 5 days a week so that, in theory, whatever is sold out of
ABC’s warehouse today or is ordered for next day delivery can get to the customer the next day
after being cross-docked first thing in the morning.

■ ABC could then experiment with new ways to sell the next day availability of the MD’s additional
8500 items that they stocked above and beyond ABC’s 1500 stocked items.
■ ABC leverages the MD’s web catalog for all 10,000 items in their cash-n-carry, “wholetail” store
just as Grainger and REI have done.

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