July 3, 2022





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.




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.



[1] This entire article is published in a “collaborative space” in which an editorial staff is creating a “wiki” about fill- rate economics. All readers are welcome to join to learn more and contribute questions, opinions, etc. Look under the “discussions” button at www.merrifield.com for how to get there.