This document discusses improving on-time delivery for customers. It begins by classifying customers into A, B, and C categories based on revenue. It then discusses standard lead times and explores improving on-time delivery through setting SMART goals, analyzing current performance, and addressing issues like variable lead times and improper planning. Solutions proposed include formalizing order promising processes, focusing on bottlenecks, and implementing a systematic approach using tools like MRP and metrics. Actual results showing improved on-time delivery are presented.

1. Improving On-Time Delivery
Customer ABC Classifications
and Standard Lead Times
Presented to Western Mass. APICS Chapter #19
By Thomas G. Cantin, CPIM
Copyright 2010 All rights reserved

2. ABC Classifications
• Inventory ABC Classifications
A - 20% of items represent 80% of $
B - 30% of items represent 15% of $
C - 50% of items represent 5% of $
• Customer ABC Classification
Based upon total sales revenue
Use yearly totals to avoid seasonality
Rankings may be modified

3. ABC Customer Classification
QUANTITY RUNNING REVENUE RUNNING
Units Total Percentage Dollars Total Percentage
A WORLWIDE EMPORIUM 207,771 207,771 28.2% $548,530.92 $548,530.92 15.8%
A ROCK SOLID 73,921 281,692 38.2% $412,269.68 $960,800.60 27.6%
A BELLA VILLA 70,840 352,532 47.8% $456,253.76 $1,417,054.36 40.7%
A CAPITAL COMPANY 66,504 419,036 56.9% $189,368.40 $1,606,422.76 46.1%
A DANUBE INC. 54,209 473,245 64.2% $312,204.23 $1,918,626.99 55.1%
A RED ZINGER 52,756 526,001 71.4% $214,862.36 $2,133,489.35 61.3%
A WINE & BRINE 32,634 558,635 75.8% $249,767.78 $2,383,257.13 68.5%
A BROWN & COMPANY 31,884 590,519 80.1% $163,352.48 $2,546,609.61 73.1%
A FRENCH CONNECTION 24,057 614,576 83.4% $183,439.47 $2,730,049.08 78.4%
A CAMERA WEAR 20,299 634,875 86.1% $188,737.60 $2,918,786.68 83.8%
B CTS WEATHERPROOF 17,184 652,059 88.5% $73,240.45 $2,992,027.13 85.9%
B SNOW WHITE 16,386 668,445 90.7% $57,694.38 $3,049,721.51 87.6%

4. Lead Times
• Planning Horizons
• Demand Rates
• Manufacturing or Service Environment
– Mass Customization
– Flow
– Cellular
– Job Shop
– Engineer to Order
– Project Management

5. Lead Time Calendar
FEBRUARY
S M T W T F S
21 22 23 24 25 26 27
28 1 2 3 4 5 6
MARCH
S M T W T F S
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 31 1 2 3

6. Lead Time Calendar
FEBRUARY
S M T W T F S
21 22 23 24 25 26 27
28 1 2 3 4 5 6
MARCH
S M T W T F S
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 31 1 2 3

7. Lead Time Calendar
FEBRUARY
S M T W T F S
21 22 23 24 25 26 27
28 1 2 3 4 5 6
MARCH
S M T W T F S
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 31 1 2 3

8. Improving On-Time Delivery
• Where are you now?
• Where do you want to be?
• SMART Goal format
– Specific (by business segment or Customer)
– Measurable (is data readily available?)
– Attainable (do you have the resources?)
– Realistic (not just a hope or a dream)
– Tangible (time-based)

9. Starting Point
2006-2008 Actual
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
OEM
SS
OEM 90.0% 88.0% 87.9% 87.2% 74.5% 82.0%
SS 88.0% 84.0% 89.3% 87.8% 72.4% 76.8%
YE YE Q1 Q2 Q3 Q4
2006 2007 2008 2008 2008 2008

10. Using a Decision Map
• On-Time Delivery is one of the most
important high-level, strategic objectives.
• Must get key stakeholders involved.
• S&OP meeting is a good starting point
– Materials/Capacity
– Operations
– Sales & Customer Service
– Shipping/Logistics

11. Completed Decision Map
Assumptions:
A1: Material is available at each
operation as planned and scheduled.
A2: Associates are available at agreed
staffing levels with the correct skill sets.
A3: Actual customer orders and
forecasts are received far enough in
advance to allow for proper planning and
fulfillment.
A4: Product is automatically allocated by
the system.
Success Factors:
S1: Achieve On-Time delivery of:
OEM SS
January 89% 87%
February 90% 88%
March 91% 89%
Q1 90% 88%
S2: Achieve 95% (units) fill rate and
90% (item) fill rate against stocking
levels by the end of the first quarter.
Decision Objective:
What is the best way to
improve our on-time
delivery performance?
Other Objectives:
1. Institute a cycle-counting program.
2. Reduce overall inventory levels.
Option 1:
Re-allocate resources to match
production capabilities to actual
mix & volume demanded.
Option 3:
Perform value-stream mapping
in order to identify key product
families.
Option 4:
Utilize available capacity
within each product line to
support stocking levels.
Option 2:
Increase set-up reduction
efforts to provide greater
scheduling flexibility.
Constraint 4:
Provided that we can rely on
forecasts and stocking levels to
be relatively accurate.
Constraint 3:
Provided that we can minimize
the impact of non-conforming
materials.
Constraint 2:
Provided that we can avoid
overtime expenses in excess of
target (budgeted) amounts.
Constraint 1:
Provided that we understand
what the actual production rates
are for each department.
Relevant Concerns:
1. There may be (cultural) resistance
to change policies and procedures .
2. (Short) lead time expectations from
several customers.

12. Measuring On-Time Delivery
• Promise Dates given to Customers
• Customer Request Dates
• Customer Measurements
– By Entire Order
– By Line Item
– By Number of Units
• CAUTION: On-Time Delivery should not
be based upon revenue dollars shipped

13. The Seven Key Dates
• Order receipt date
• Order entry date
• Customer request date
• Promise date
• Completion date
• Allocation date
• Ship date

14. Backlog Profile in Trouble
Backlog Profile Thursday, 06/26/08
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
Week Ending Dates
Quantity
Capacity
Promised
Capacity 0 0 0 0 0 0 0 0 0 0 0 1,200 0 0 4,800 4,800 4,800
Promised 6 0 37 84 0 0 60 72 60 497 919 5,593 6,650 4,302 3,827 3,475 3,300
4/12/2008 4/19/2008 4/26/2008 5/3/2008 5/10/2008 5/17/2008 5/24/2008 5/31/2008 6/7/2008 6/14/2008 6/21/2008 6/28/2008 7/5/2008 7/12/2008 7/19/2008 7/26/2008 8/2/2008

15. Order Promising Mistakes
• Variable lead times given to Customers
– Earlier when slow; later when busy
– Erratic lead times from supply partners
• Improper planning parameters
– Throughput rates are not known
– Old data is being used
• Inconsistent processes
– Within planning and scheduling, customer
service, production, etc.

16. Stop Making Bad Promises
• Institute a formal order promising process.
• Communicate changes to Customers.
• Focus on the Detailed Scheduling and
Planning required to keep the promises
you are making.
• Ensure that there is feedback within a
closed-loop planning system.
• Improve the processes and systems.

17. Expedite with Extreme Caution
• Expediting impedes normal product flows
and gives rise to informal management
systems (hot sheets, special lists, etc.).
• Do we understand why there was a
request or need to expedite?
• When people are in a rush, they often get
the (important) details wrong.
• Remember that when everything is a
priority, then nothing is a priority.

18. Senior Management
• Outline problems identified from work that
has already been done.
• Use data and specific examples to relate
problems to resource allocation, as well as
internal results and impact on Customers.
• Prioritize proposed solutions and try to
provide multiple options instead of simple
“Yes” or “No” decisions.

19. OEM Data December 2008
Early On-Time 1 - 7 8 - 14 15 - 30 GT 30 Totals Early On Time Late
A Total 195,965 67,027 14,934 12,094 11,236 4,583 305,839 62.1% 24.3% 13.6%
B Total 61,656 44,672 8,398 8,748 4,342 2,090 129,906 47.5% 34.4% 18.2%
C Total 17,305 4,745 2,574 4,158 10,971 732 40,485 42.7% 11.7% 45.5%

20. Resource Allocation
• Focus on Real Bottlenecks.
• Dispel Myths of Artificial Bottlenecks or
Man-made constraints.
• Challenge or Confirm basic assumptions
inherent to the process.
• Be mindful of other objectives.
• Speak about what success will look like
and the benefits to be realized.

21. Scheduling & Loading
Two basic strategies:
1. Forward-scheduling, infinite capacity
• Earliest completion date
• Focus on material availability
• “Load-and-go” mentality
• Expedite incoming materials; chase orders
2. Backward-scheduling, finite capacity
• Latest start date
• Planned and scheduled around constraint

22. Order Policies & Lot Sizes
• Customer order minimums
– How do you incorporate your forecasts?
– What is your target service level?
• Production lot sizing (min./max.)
– Lot-for-lot
– Fixed order quantity
• Set-ups and change-overs
– Are they accounted for in planning?

23. Forecasts and Service Levels
Service Stocking Levels
60,000
70,000
80,000
90,000
100,000
110,000
120,000
Units
Net On-Hand Units 61,557 77,440 76,582 83,892 84,738 97,676 91,027 86,943 89,811 86,128 71,106 85,629 93,631
Target Stocking Level 117,497 117,497 117,497 110,607 110,607 110,607 110,607 110,607 110,607 110,607 110,607 110,607 110,607
Fill Rate 52.4% 65.9% 65.2% 75.8% 76.6% 88.3% 82.3% 78.6% 81.2% 77.9% 64.3% 77.4% 84.7%
2/24/2009 3/3/2009 3/10/2009 3/17/2009 3/24/2009 3/31/2009 4/7/2009 4/14/2009 4/21/2009 4/28/2009 5/5/2009 5/12/2009 5/19/2009

24. A Systematic Solution
1. Ability to review new orders against current
backlog profile and lead times
2. Formal order promising policies/guidelines
3. Visibility of orders within MRP/DSP tools
4. Controlled order release
5. Ability to monitor progress of order
6. Capability of in-process corrective action
7. Meaningful metrics tracked and published
8. Continuous improvement of processes

25. Actual Results
2009 On-Time Delivery
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
Month
On-TimeDelivery%
OEM
SS
OEM 89.1% 96.1% 96.3% 96.9% 97.1% 98.1% 98.3% 98.8% 94.5% 97.7% 98.6% 98.7%
SS 77.8% 92.7% 92.0% 99.8% 99.5% 99.7% 100.0% 99.6% 99.7% 99.8% 99.8% 99.9%
January February March April May June July August September October November December

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