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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, over time, 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.
                     3. 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!

                     4. 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?
                     5. 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:

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