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KEL019

SUNIL CHOPRA

Excel Logistics Services “The quality of our performance has improved significantly, but stores continue to complain

about our deliveries,” said John Margolis, general manager of the Springfield Warehousing and Distribution Center (WDC) run by Excel Logistics Services. Margolis looked at the customer satisfaction survey for the fourth quarter of the previous year. “At this point, it is becoming increasingly difficult for us to make further improvements. We need a detailed plan of action regarding what to do next. Robin, I would like to see an initial plan from you in the next couple of months. Why don’t you begin by looking at the receiving function?” Robin Stalk, quality manager at the WDC, nodded her head.

Background Founded in 1989, Excel Logistics Services (ELS) was a wholly owned subsidiary of Excel and

Co., a large national retail chain. Prior to 1989, Excel handled its own logistics functions, including warehousing and transportation. In 1989, ELS was spun off as a separate company with the sole objective of providing logistics services. Initially, all of ELS’s business came from Excel. At present, only 85 percent of ELS’s business came from the parent company, and ELS was actively seeking business outside of Excel. Although ELS had plans for growth, it wanted to stay in the business of providing logistics services to retail chains.

ELS operated a network of seven warehousing and distribution centers for Excel and Co. Each WDC was assigned a region in which it served all Excel stores. Each WDC typically stocked all items needed by stores in the region it served. Company buyers at Excel placed orders for merchandise with suppliers. These orders were based on forecasted demand at retail stores and were delivered to the WDCs where they were received and held in storage. When stores ran out of a product, store managers placed replenishment orders for merchandise at the WDC. If the product was available, the order was picked at the WDC and delivered to the stores. The stores primarily cared about orders being delivered in the right quantity at the right time.

The Springfield WDC The Springfield WDC served a total of 194 stores. The 194 stores were divided into three

categories (A, B, and C) by decreasing order of size. There were 57 A stores, 75 B stores, and 62 C stores. A total of 12,539 items were stocked at Springfield. The majority of these items were referred to as breakpack items (9,944 in total), with the rest being full-case items. For breakpack items, such as answering machines or telephones, ELS received cases of a certain size from its suppliers. Stores

©2004 by the Kellogg School of Management, Northwestern University. This case was prepared by Professor Sunil Chopra. Cases are developed solely as the basis for class discussion. Cases are not intended to serve as endorsements, sources of primary data, or illustrations of effective or ineffective management. To order copies or request permission to reproduce materials, call 800-545-7685 (or 617-783-7600 outside the United States or Canada) or e-mail [email protected]. No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Kellogg School of Management.

For the exclusive use of A. Bachan, 2018.

This document is authorized for use only by Ahmad Bachan in MNGT 404 POM Spring 18-1 taught by Jian Li, Northeastern Illinois University from January 2018 to May 2018.

EXCEL LOGISTICS SERVICES KEL019

were allowed to place orders for quantities less than a full case because ELS broke open the cases and shipped the items to the stores in smaller quantities. Thus, it was not unusual to have partial cases of breakpack items in storage. For full-case items, stores were required to order at least a case. For these items, ELS only needed to handle cases and did not break them into smaller units.

The WDC at Springfield had a total area of 1.1 million square feet and was divided into six modules (see Exhibit 1). Breakpack items were stored in Module 1, while full-case items were stored in Module 3. The other modules were used for sorting and the staging area. On average, Springfield had an inventory worth $46 million, which corresponded to about a one-month demand from stores in the region.

Margolis was hired as the general manager at the Springfield WDC in January of the previous year. A portion of his bonus was based on a quarterly survey of store managers taken by ELS management. The last survey prior to Margolis’s arrival indicated that store managers were very dissatisfied with the performance of the Springfield WDC. Springfield was a poor performer and ranked last within the ELS network. Customers (retail store managers) complained that orders were late and not delivered in the right quantity.

Upon arriving, Margolis focused his attention on service quality at the WDC. Margolis quickly realized that no performance data was available within the Springfield WDC. In fact, none of the processes were well defined. He had to put an entire quality program in place and appointed Robin Stalk as quality manager. Stalk had spent considerable time at Springfield and was knowledgeable about the processes and problems. As a first step, Stalk and Margolis identified receiving, inventory storage, order filling, and shipping as the four key processes at Springfield. Receiving referred to the process of receiving deliveries from suppliers and putting them into storage at the WDC. Inventory storage referred to the process of storing products at the WDC. Order filling referred to the process of receiving a store order, picking required items from storage, and loading the delivery truck. Shipping referred to the process of transporting the store order from the WDC and delivering it to the store. These four processes were identified as key because any error in these processes impacted Springfield’s ability to supply a store order on time and in the right quantity. An error in receiving or inventory storage could result in an improper quantity of a particular product showing up in the inventory system. As a result, the WDC could promise delivery to a store from stock, even though the item was out of stock. This error would be detected when the WDC tried to fill the order and found they could not. This would cause the delivery to the store to be late. Margolis’s objective was to manage the four processes in the warehouse in such a way that store orders could be delivered in the right quantity at the right time.

By June, detailed process flow maps were constructed for each of the four processes (see Exhibit 2 for receiving) and key objectives were identified for each process. To identify the objectives, Stalk and Margolis took into account store requirements in terms of delivery accuracy. The process mapping and objective identification was done in coordination with the personnel involved with each process. The operators were expected to follow procedures as described in the process flow maps. The hope was that with more clearly defined processes, performance would improve. To further motivate personnel, customer survey results for all WDCs were posted all over the warehouse. Margolis hoped that employees would be motivated to avoid being at the bottom of the list and encouraged to follow the process more carefully, resulting in better performance. These actions bore fruit, and Springfield moved up to third place by the fourth quarter. Unfortunately, on an absolute scale, performance was still quite bad with several dissatisfied store managers.

Margolis needed an approach to take quality to the next level. He had heard of Statistical Process Control (SPC), and wanted to use the methodology to improve process performance at Springfield.

2 KELLOGG SCHOOL OF MANAGEMENT



KEL019 EXCEL LOGISTICS SERVICES

SPC had traditionally been used in manufacturing settings for measurable variables such as the thickness of a plate. In a warehouse setting, it was hard to define how wrong a process had been but easy to classify the outcome as being defective or not. Therefore, Margolis and Stalk decided to measure whether different stages of a process had been defective or not. The initial focus was on the receiving process.

The Receiving Process The receiving flow chart (see Exhibit 2) is an overview of all the tasks necessary to receive a

vendor shipment into the WDC. The team members were:

• A guard who began the receiving process by checking trailer loads into the WDC yard

• A receiving officer who prepared the receiving packet and keyed received quantities into the inventory system

• A yard driver who positioned drop trailers in the proper dock door and removed released trailers to the carrier pickup area

• An unloader who removed the trailer and palletized the product

• A slotter who performed detailed receiving duties (to ensure proper PO, quantity count, etc.), assigned inbound pallets to stocking locations, and also performed vendor compliance audits

• A putaway driver who moved received palletized product from the receiving area to the assigned stocking location

Detailed Data Collection The Springfield warehouse performed about 8,000 transactions in receiving on a daily basis. To

prepare SPC charts, Stalk decided to analyze 800 transactions daily for the next 45 days. A sample size of 800 transactions was selected to ensure that most days had at least three or more transactions that were defective. It would be impossible to construct SPC charts if most samples had no defective transaction.

After talking to experienced people involved in the receiving process, Stalk used fishbone diagrams to identify the following five sources of error that were likely to occur:

Slotter: Errors in any of the slotter functions Keying: Errors in receiving officer keying quantities into the inventory system Letdown: Errors in any of the unloader functions ITR ADJ: Errors in receiving packet prepared by receiving officer Putaway: Errors in putting the pallet/stack in the wrong location

All errors that could not be assigned one of these five categories were grouped as “other.” Stalk also decided to separate the performance data for Modules 1 (breakpack) and 3 (full case).

After 45 days, Stalk had plenty of data to look at (see Exhibits 3, 4, and 5). She still was not sure how best to organize it and prepare a plan for action.

KELLOGG SCHOOL OF MANAGEMENT 3




Discussion Questions

1. Help Stalk organize the data by preparing a run chart.

2. Prepare appropriate process control charts to see if the process is in control. Is the receiving process in or out of control?

3. Customer service requirements determine that receiving process errors should never exceed 2 percent on any given day. What percentage of the days is likely to exceed 2 percent error, given the current performance at receiving? Assume a total of 8,000 transactions per day, 4,000 in each module.

4. Prioritize the set of actions you would take to ensure that more than 99 percent of the days have less than 2 percent receiving process error.

5. Can you think of a continuous improvement framework that Stalk can use as an engine to improve performance in the receiving process and other processes at Springfield?





Exhibit 1: Layout of Springfield WDC (1728’ × 576’)

GUARD RECEIVING OFF. YARD DRIVER UNLOADER SLOTTER PUTAWAY

Tr

Office Area

Module 1

Module 3

Receiving Area

Shipping Area

Exhibit 2: Process Flow Chart: Excel Logistics Services, Receiving

uck arrivesat gate

Check intrailer

Liveunload?

Assign trailer toreceiving locat.

Deliver papersto office

Prepare receivingpacket

Enter completedreceipt to system

Enter slottingreassignments tosystem

File receivingpacket

Position trailerto dock door Unload trailer

Sort cartons byitem

Floor stack?

Build Pallets by

Stage pallets inreceiving apron

Match itemsreceived to PO

Count quantityreceived

Compare quantityto deliverymanifest

Assign pallet tostocking location

Complete receivingpacket

allet/stackssignedion

Return unslottedpallets to manager

Return empty pallets to

unloading area

Y

N N

Pu pin alocat

Put pallet/stack in assigned location

item

Build pallets by item





Exhibit 3: Overall Performance of Receiving Process

Date Slotter Errors Keying Errors

Letdown Errors

ITR ADJ Errors

Putaway Errors

Other Errors

Total Errors

Total Slots Checked

06/01 4 1 1 1 0 3 10 800 06/02 11 2 1 2 2 7 25 800 06/03 11 2 0 2 4 4 23 800 06/04 6 6 0 0 2 11 25 800 06/05 6 0 0 1 3 4 14 800 06/06 19 0 0 0 1 5 25 800 06/07 11 0 0 0 2 2 15 800 06/08 3 1 2 0 1 16 23 800 06/09 3 0 3 0 1 3 10 800 06/10 3 0 3 0 0 5 11 800 06/11 5 0 3 0 0 7 15 800 06/12 0 1 1 0 1 22 25 800 06/13 4 1 3 0 4 5 17 800 06/14 2 0 2 0 0 19 23 800 06/15 0 2 2 0 0 1 5 800 06/16 2 2 0 0 1 0 5 800 06/17 4 0 1 0 2 0 7 800 06/18 3 1 4 2 0 0 10 800 06/19 4 0 3 0 2 1 10 800 06/20 7 2 2 0 3 3 17 800 06/21 13 0 2 0 1 9 25 800 06/22 7 0 2 0 2 5 16 800 06/23 4 0 4 0 1 6 15 800 06/24 7 0 0 0 2 7 16 800 06/25 2 0 1 0 4 2 9 800 06/26 2 0 1 0 4 1 8 800 06/27 2 0 2 0 0 8 12 800 06/28 8 1 1 0 0 6 16 800 06/29 7 1 1 0 0 7 16 800 06/30 1 1 1 0 1 4 8 800 07/01 10 0 2 0 1 8 21 800 07/02 7 0 2 0 2 4 15 800 07/03 4 0 1 0 6 1 12 800 07/04 6 0 2 0 1 1 10 800 07/05 3 0 1 0 0 2 6 800 07/06 0 2 2 0 0 1 5 800 07/07 1 0 5 0 0 19 25 800 07/08 5 0 2 0 0 3 10 800 07/09 5 2 2 0 1 6 16 800 07/10 6 0 0 0 1 2 9 800 07/11 9 0 3 0 0 8 20 800 07/12 9 0 3 0 0 8 20 800 07/13 4 0 2 0 5 0 11 800 07/14 0 0 3 0 8 1 12 800 07/15 0 0 2 0 0 5 7 800 Total 230 28 78 8 69 242 655 36,000





Exhibit 4: Module 1 Performance Date

Slotter Errors

Keying Errors

Letdown Errors

ITR ADJ Errors

Putaway Errors

Other Errors

Total Errors

Total Slots Checked

06/01 1 0 1 0 0 0 2 400 06/02 10 2 1 2 1 1 17 400 06/03 9 1 0 2 4 2 18 400 06/04 6 6 0 0 2 7 21 400 06/05 3 0 0 1 3 0 7 400 06/06 1 0 0 0 0 1 2 400 06/07 7 0 0 0 1 2 10 400 06/08 1 1 2 0 1 16 21 400 06/09 3 0 3 0 1 1 8 400 06/10 3 0 3 0 0 3 9 400 06/11 5 0 3 0 0 3 11 400 06/12 0 1 1 0 1 21 24 400 06/13 4 1 3 0 3 5 16 400 06/14 2 0 2 0 0 0 4 400 06/15 0 2 2 0 0 1 5 400 06/16 2 2 0 0 0 0 4 400 06/17 1 0 1 0 1 0 3 400 06/18 3 1 4 2 0 0 10 400 06/19 3 0 3 0 2 1 9 400 06/20 7 2 2 0 2 2 15 400 06/21 13 0 2 0 0 8 23 400 06/22 7 0 2 0 2 1 12 400 06/23 4 0 4 0 1 4 13 400 06/24 5 0 0 0 1 5 11 400 06/25 2 0 1 0 4 2 9 400 06/26 1 0 1 0 3 1 6 400 06/27 2 0 2 0 0 5 9 400 06/28 6 0 1 0 0 4 11 400 06/29 5 0 1 0 0 5 11 400 06/30 1 0 1 0 0 4 6 400 07/01 8 0 2 0 1 7 18 400 07/02 7 0 2 0 2 4 15 400 07/03 2 0 1 0 6 1 10 400 07/04 4 0 2 0 1 1 8 400 07/05 2 0 1 0 0 1 4 400 07/06 0 2 2 0 0 0 4 400 07/07 0 0 5 0 0 15 20 400 07/08 2 0 2 0 0 3 7 400 07/09 3 2 1 0 0 2 8 400 07/10 3 0 0 0 1 2 6 400 07/11 7 0 3 0 0 8 18 400 07/12 7 0 3 0 0 8 18 400 07/13 2 0 2 0 5 0 9 400 07/14 0 0 3 0 8 0 11 400 07/15 0 0 2 0 0 1 3 400 Total 164 23 77 7 57 158 486 18,000





Exhibit 5: Module 3 Performance Date

Slotter Errors

Keying Errors

Letdown Errors

ITR ADJ Errors

Putaway Errors

Other Errors

Total Errors

Total Slots Checked

06/01 3 1 0 1 0 3 8 400 06/02 1 0 0 0 1 6 8 400 06/03 2 1 0 0 0 2 5 400 06/04 0 0 0 0 0 4 4 400 06/05 3 0 0 0 0 4 7 400 06/06 18 0 0 0 1 4 23 400 06/07 4 0 0 0 1 0 5 400 06/08 2 0 0 0 0 0 2 400 06/09 0 0 0 0 0 2 2 400 06/10 0 0 0 0 0 2 2 400 06/11 0 0 0 0 0 4 4 400 06/12 0 0 0 0 0 1 1 400 06/13 0 0 0 0 1 0 1 400 06/14 0 0 0 0 0 19 19 400 06/15 0 0 0 0 0 0 0 400 06/16 0 0 0 0 1 0 1 400 06/17 3 0 0 0 1 0 4 400 06/18 0 0 0 0 0 0 0 400 06/19 1 0 0 0 0 0 1 400 06/20 0 0 0 0 1 1 2 400 06/21 0 0 0 0 1 1 2 400 06/22 0 0 0 0 0 4 4 400 06/23 0 0 0 0 0 2 2 400 06/24 2 0 0 0 1 2 5 400 06/25 0 0 0 0 0 0 0 400 06/26 1 0 0 0 1 0 2 400 06/27 0 0 0 0 0 3 3 400 06/28 2 1 0 0 0 2 5 400 06/29 2 1 0 0 0 2 5 400 06/30 0 1 0 0 1 0 2 400 07/01 2 0 0 0 0 1 3 400 07/02 0 0 0 0 0 0 0 400 07/03 2 0 0 0 0 0 2 400 07/04 2 0 0 0 0 0 2 400 07/05 1 0 0 0 0 1 2 400 07/06 0 0 0 0 0 1 1 400 07/07 1 0 0 0 0 4 5 400 07/08 3 0 0 0 0 0 3 400 07/09 2 0 1 0 1 4 8 400 07/10 3 0 0 0 0 0 3 400 07/11 2 0 0 0 0 0 2 400 07/12 2 0 0 0 0 0 2 400 07/13 2 0 0 0 0 0 2 400 07/14 0 0 0 0 0 1 1 400 07/15 0 0 0 0 0 4 4 400 Total 66 5 1 1 12 84 169 18,000




BackgroundThe Springfield WDCThe Receiving ProcessDetailed Data Collection

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