GO DEEP ON FILL-RATE ECONOMICS; CHANGE
STRATEGY
In most
distribution channels, a distributor’s inventory, fill-rate score is
foundational to its basic service value proposition. Fill-rates aside, a
company can tune many basic service metrics to the specific needs of a target
niche of customers such as:
·
Late cut-off
time(s) for placing orders.
·
Faster
turn-around times for orders picked up and/or delivered.
·
Knowledgeable,
helpful service personnel.
·
Zero errors on
filled orders, delivered on time – both guaranteed!
·
Heroic
recoveries routines (etc.).
But, if we
don’t have the full amount of a line item in local stock that a customer needs “now”,
all of the other service elements seem, at least in the moment, a bit lacking.
“Fill-rates
just have to be good enough” many service-minded distributors might reply.
“No other
competitors can afford to have a 100% guaranteed in-stock, fill-rate level on a
broad, slow-turning array of items. With “good” fill-rates, our hustle to get
the balance of what the customer needs, we’ll win the satisfaction, retention/defection
war.”
How many
distributors actually measure these claims and look at the cost trade-offs
between higher fill-rates and hustle-for-the-balance-of-the-order costs? Read
on about how one MRO supply distributor did some deeper thinking about fill-rate
economics to gain insights that are transforming their profitability with next-level
partnerships with a master distributor.
“Deuce”
Lawson, a Reluctant Pinch Hitter for An Ailing Relative’s Distribution Business
Deuce Lawson,
the hero of this story, sold his own manufacturing business in mid-career and
was in a relaxing, family-centric, transition stage when his brother-in-law had
a serious heart attack. Deuce was then drafted, by his sister, into running a
45-employee, two-location, distribution business (call it ABC Supply) that was
losing money for a number of reasons about which Deuce had no initial clue.
The
veteran managers at ABC assured Deuce that the key to solving ABC’s problems
was to hire more sales reps in order to grow sales to spread “fixed costs” until
it became profitable. Deuce knew “fixed costs” better than most from his years
in manufacturing. He saw ABC as a mostly variable cost business and was not
satisfied with the vets’ advice to “try-harder” at “more of the same”. Looking
outside the business, he found and partnered with a veteran wholesale industry
consultant for fresh advice on how to turn the company around.
This new
team immediately solved some structural problems like: too many mediocre sales
reps calling on too many small accounts generating too many profit losing
orders. At the same time, they also re-invented “basic service brilliance” by measuring
8 different metrics. While many employees were panicked about the counter-intuitive
wisdom of downsizing the sales force and solving the small order problem – both
which, by the way, worked sensationally – they all embraced the ideas of
better, measurable, service value. But, it was the specific challenge of
achieving a breakthrough improvement for fill-rates that led to new discoveries
and a new business model.
Stage
One: How to measure fill-rates better to have a base from which to improve?
Initially fill-rates
were not being measured at all. The first solution was a simple, software and
inside-sales-routine fix that allowed every item that a customer wanted to order
be entered against what was in stock to then generate a statistical report on fill-rates
(and “the shorts”) by item categories from most picked to dead. Actual fill-rates
for all levels of items were surprisingly lower (by over 10 percentage
points) than what everyone had imagined. And, the weak fill-rates were, in
turn, one of the causes for creating too many unprofitable small orders as well
as unmeasured, customer dis-satisfaction and potential defection rates.
Stage
Two: What were the hard and soft costs of solving “short” line items?
ABC’s vets
minimized the impact of the lower, actual fill-rate scores, because ABC was “so
good at solving the shorts” a number of ways. With deeper analysis, each way had
its economically dysfunctional aspects. For example:
1)
A customer
would call and ask if ABC had an odd item. If ABC didn’t have it, the customer
would call other distributors to find it. A quick survey by Deuce discovered
that if ABC could have had the odd item, the customer would have also ordered
other commodity items on the same order. Demand for both the odd and the
common items were not being captured in the computer which would then, overtime,
raise suggested inventory investment and fill-rates on those items. So, if the
customer was a top 20% most profitable account, inside sales people were coached
to ask what the rest of the order was and input that demand into the computer
even though the entire order was still lost. And, the inside sales reps would mention
that this extra step was aimed at “improving the (important customer’s) future
service quality”. Deuce’s assumption was that: if ABC was going to invest
more in inventory it might as well be in the specific items that best customers
wanted.
2)
If a customer
wanted 5 widgets, but ABC had 3, the inside reps were trained to encourage the
customer to back-order the balance and not let “the other two get away”. But,
this created two sets of small order transaction costs for both ABC and the
customer.
The new routine is to ask if the item is for internal
supplies, if so, may the line be shipped complete for 3. Then, the next order
can be for the normal 5, assuming stock has been refreshed. By not backordering
a small order, if possible, a set of extra transaction costs are saved for both
parties. This policy is working!
3)
Except…what if the
customer needed all 5 right away? There were several options. ABCs first reflex
was often to ship the balance from its satellite branch, if possible. But, Deuce
reasoned that this solution also created two sets of order transaction costs
for both ABC and the customer, and the costs were even higher for shipping from
the other location. There was extra freight and some inter-branch bickering
costs over doing stock checks and timely shipment for “someone else’s
customers”. And, the demand history for such shipments was incorrectly staying
with the shipping branch, so that the originating branch’s demand history would
be chronically under-counted and the shipping branch over-counted. How can a
computer help buyers forecast item demand better if we don’t feed the right
demand data into the right location?
4)
Option two for
solving “shorts” was to offer customers substitute items for the 2 short or
even all 5 on a superior quality solution, but at the inferior product price. Many
customers liked this option, but again the demand for what the customer
wanted to buy was left with the substituted item, so the computer forecasting would
recommend buying more of the substituted item and less of what customers really
wanted – a “vicious feedback cycle”.
Stage
Three: How to improve fill-rates immediately for the least incremental, net
cost?
Deuce taught
everyone the importance of and the how-to’s for making sure that demand for
what the customer originally wanted was captured at the location from which
they wanted to buy it. He also implemented the following service programs
– all with measurable tracking records:
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 suppose 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:
TurnEarn
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) 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 in between 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, what ever 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 leverage’s
the MD’s web catalog for all 10,000 items in their cash-n-carry, “wholetail”
store just as Grainger and REI have done.
Stage
Five: Making the grand partnership actually work.
ABC
pitched 3 different MDs on the partnership plan, but only one really “got it”
and had the organizational capacity and track record of progressiveness to
potentially make this VMI and virtual-selling scenario happen. Lots of
questions and concerns were raised by both parties, but the answers were
already in existence in other channels that have followed in Wal-Mart’s
footsteps. Implementation of this grand plan is now under way (12/06), and
scenarios for opening up a totally new type of location that would be designed
around receiving 10K items in the middle of every workday night are being
planned.
CONCLUSIONS
Twenty
years ago Wal-Mart first proved to the world that by buying straight truckloads
into master distribution centers on a VMI basis, they could get the following benefits
at its stores.
·
Cut inventory
in the stores in half.
·
Improve true fill-rates
by over 10%.
·
Double the
number of items offered in the same size store.
·
Attract more
customers from even further away due to more items with higher fill-rates and
of course, every day low prices. And,
·
See average
purchases per customer visit climb 78%.
Now, with
third party VMI implementation firms, web service networks between channel
partners, and web order entry systems that can be private labeled for any
number of distributor/dealers, these benefits can be achieved between MDs and
distributors. And, this new platform offers great new benefits to
manufacturers, but that is another story. For more on: this story; fill-rate
economics; VMI; virtual selling of MD items through small footprint stores with
next, early AM delivery; and “the next story” about manufacturers benefits, hit
the “discussions” button at www.merrifield.com
to enter a “collaborative space” adventure with blogs and wiki content provided
by distribution channel experts.
© Merrifield
Consulting Group, Inc.
Article
1.15
December,
2006
D. Bruce
Merrifield, Jr.
www.merrifield.com