i n t e g r i t y - s e r v i c e - e x c e l l e n c e af global logistics support center (afglsc)...
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I n t e g r i t y - S e r v i c e - E x c e l l e n c e
AF Global Logistics Support Center (AFGLSC)
1
Order Response Time
Mike McClure, 402 SCMS/GUSB
12 Mar 2013
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 2
Order Response TimeAgenda
Review AFGLSC monthly ORT chartsCurrently distributed to OSD, AFMC, Depot Mx, AFGLSC, DLA
Mainly at the working level, with some going up to leadership as requested
Presentation normally contains 16 slides of performance, today only 5 slides
Review some recent ORT analysisWhat we are doing with ORT and what is it telling us?
Back-up Slides - Improving the CWT MetricORT developed by AFGLSC to overcome measurement and analysis issues with average CWT
Uses both closed and open orders ….. combines two traditional measures, CWT with open BOs
Uses customer order date, not closed date ….. real time, not delayed
Uses percentile buckets ….. much more accurate than the average of a non-normal distribution
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
AF Global Logistics Support Center (AFGLSC)
3
Order Response Time
Mike McClure, 402 SCMS/GUSB
13 Feb 2012
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 4
Measuring Enterprise Performance
AFGLSC 402nd, LIMS-EV Pipeline Analysis
Responsiveness to all customer demands AFGLSC, DLA, and Other SOS provides spares to customers
Best option is to have the part locally for immediate issue
Not all parts available locally, so backorder response time is key to deliver part within customer expectations
Order Response Time (ORT) Measures immediate
issue rate (same day) and backorder response times
90%
91%
87%
86%
85%
84%
87%
87%
86%
86%
85%
86%
86%
84%
84%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
11
Apr
11
May
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Jun
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Jul 1
1
Aug
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Sep
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Oct
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Nov
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Mx
Ord
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Depot MXW
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % 0-2 days Mx Orders
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 5
Measuring Enterprise PerformanceOrder Response Time (ORT), an improved CWT look
Order Response Time (ORT) previously called Calculated Issue Effectiveness (CIE)
What’s the data source? LIMS-EV CWT data
What’s different than CWT? Open orders included Performance grouped by open date, not closed date
Why ORT? Real-time responsiveness measure Much more accurate indicator of current support Customer focused by measuring percentage of immediate
issues and how long backorders are taking True “Tier” measure can be applied at multiple
Organizational levels
How to read the chart? The date axis represents customer order date Black line represents total customer orders Solid colors represent % of orders closed within time
period White % numbers represents % immediate issues
What about the goal? TDD like standard (customer gets x% of parts in y days) Calculated cumulative wait time (by order)
What does this metric tell us?• How often does a mechanic get a part when they order it?• If not, how long does it take to fill an order?• How many orders are placed in a given month?
ORT shows the real time, direct impact of supply support to the customer
90%
91%
87%
86%
85%
84%
87%
87%
86%
86%
85%
86%
86%
84%
84%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
11
Apr
11
May
11
Jun
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Jul 1
1
Aug
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Sep
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Oct
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Nov
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Dec
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Jan
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Mx
Ord
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Depot MXW
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % 0-2 days Mx Orders
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 6
Depot Mx (available by MXW, MXG, Mx shops, workload & supply codes)
Order Response Time
AFGLSC 402nd, LIMS-EV Pipeline Analysis, DLA Emall
90%
91%
87%
86%
85%
84%
87%
87%
86%
86%
85%
86%
86%
84%
84%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
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Oct
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Nov
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Dec
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Jan
12
Mx
Ord
ers
Ord
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espo
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Tim
e
Depot MXW
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % 0-2 days Mx Orders
92%
93%
89%
88%
87%
88%
89%
89%
88%
88%
87%
88%
88%
87%
87%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
11
Apr
11
May
11
Jun
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Jul 1
1
Aug
11
Sep
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Oct
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Nov
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Dec
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Jan
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Mx
Ord
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Ord
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Tim
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Depot MXW - DLA SOS
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % 0-2 days Mx Orders
84%
83%
81%
76%
80%
79%
81%
81%
78%
79%
78%
80%
80%
78%
76%
-5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
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Apr
11
May
11
Jun
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Jul 1
1
Aug
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Mx
Ord
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Ord
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Tim
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Depot MXW - AF SOS
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % 0-2 days Mx Orders
84%
78%
73%
65% 69
%
54%
69%
65%
66%
66%
66%
63%
58%
49% 57
%
-5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
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Apr
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May
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Jun
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Jul 1
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Aug
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Sep
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Mx
Ord
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Tim
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Depot MXW - Other SOS
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % 0-2 days Mx Orders
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 7
Operational Bases (available by WS, location & supply codes)
Order Response Time
AFGLSC 402nd, LIMS-EV Pipeline Analysis, DLA Emall
61%
62%
62%
62%
63%
62%
62%
62%
62%
62%
60% 65
%
64%
65%
64%
-50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
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Apr
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May
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Jun
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Jul 1
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Aug
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Sep
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Oct
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Cust
omer
Ord
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Operational Bases
Base Issue 1-2 days 3-10 days 11-30 days31-90 days 90+ days % base issue Orders
57%
58%
59%
59%
59%
60%
59%
59%
59%
60%
57% 63
%
62%
62%
61%
-50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
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Apr
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May
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Jun
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Cust
omer
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Operational Bases - DLA SOS
Base Issue 1-2 days 3-10 days 11-30 days31-90 days 90+ days % base issue Orders
76%
76%
74%
75%
74%
72%
74%
74%
75%
74%
74%
75%
75%
74%
74%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
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Apr
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May
11
Jun
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Jul 1
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Aug
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Cust
omer
Ord
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Operational Bases - AF SOS
Base Issue 1-2 days 3-10 days 11-30 days31-90 days 90+ days % base issue Orders
57%
58%
59%
60%
62%
62%
61%
60%
59%
57%
57% 62
%
62%
63%
61%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Feb
11
Mar
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Apr
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May
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Jun
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Jul 1
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Aug
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omer
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Operational Bases - Other SOS
Base Issue 1-2 days 3-10 days 11-30 days31-90 days 90+ days % base issue Orders
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 8
89% 90%86% 86% 85% 84% 87% 87% 86% 86% 85% 86% 86% 84% 84%
0
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0%
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100%
FY08
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Jul 1
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Aug
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Jan
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Ord
ers
% o
f Ord
ers
Depot Mx
Pass -Same Day Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Standard Orders
2 day TDD std ORT measure the percent of customer orders meeting their TDD standards
ORT includes both open & closed orders in the month they were ordered
The dotted black line shows the ORT goal (read on the left axis)
The white diamonds & values show the percent of orders filled within their TDD standard (read on the left axis)
Solid black line shows the count of orders received (read on the right axis)
Colors show the percent of orders that either passed or failed during the month Dark Green/Pass – Base Issue = Immediately filled Light Green /Pass – Closed = Filled during the month within standard Light Red/Failed – Closed = Filled, but exceeded their TDD standard Dark Red/Failed – Open = Not filled and have already passed their TDD standard Yellow/Pass – Open = Not filled, but have not exceeded their TDD standard
TDD Standards: These standards are specific to the geographic location of the customer, the priority of the order, and the mode of transportation with one exception: AFGLSC uses a 2-day standard for all depot maintenance orders
Order Response TimeTDD goal applied
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 9
Depot MxOrder Response Time
AFGLSC 402nd, LIMS-EV Pipeline Analysis, DLA Emall
Depot TDD std set to 2 days
89% 90%86% 86% 85% 84% 87% 87% 86% 86% 85% 86% 86% 84% 84%
0
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0%
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100%
FY08
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Feb
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Mar
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Apr
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Jul 1
1
Aug
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Jan
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Ord
ers
% o
f Ord
ers
Depot Mx
Pass -Same Day Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Standard Orders
2 day TDD std
82% 82% 80% 76% 80% 79% 81% 81% 78% 79% 78% 80% 80% 78% 76%
0
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60,000
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0%
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100%
FY08
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Ord
ers
% o
f Ord
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Depot Mx - AF SOS
Pass -Same Day Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Standard Orders
2 day TDD std
83%77%
73%65%
69%
54%
69%65% 66% 66% 66% 63%
58%
49%
57%
0
20,000
40,000
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120,000
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0%
10%
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100%
FY08
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Feb
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Mar
11
Apr
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11
Jul 1
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Aug
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Oct
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Jan
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Ord
ers
% o
f Ord
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Depot Mx - Other SOS
Pass -Same Day Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Standard Orders
2 day TDD std
91% 92%88% 88% 87% 88% 89% 89% 88% 88% 87% 88% 88% 87% 87%
0
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0%
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100%
FY08
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Feb
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Ord
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% o
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Depot Mx - DLA SOS
Pass -Same Day Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Standard Orders
2 day TDD std
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 10
Operational BasesOrder Response Time – IPG 1
AFGLSC 402nd, LIMS-EV Pipeline Analysis, DLA Emall
DoD Operational TDD std
88% 89% 90% 89% 90% 90% 90% 90% 90% 89% 89% 90% 89% 89% 90%
0
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0%
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100%
FY08
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Ord
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% o
f Ord
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Operational Bases - IPG 1
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
89% 90% 91% 90% 91% 92% 91% 91% 91% 91% 90% 91% 91% 91% 91%
0
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FY08
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Ord
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% o
f Ord
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Operational Bases - IPG 1 - DLA SOS
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
92% 91% 91% 91% 91% 91% 91% 91% 92% 91% 92% 91% 90% 90% 90%
0
20,000
40,000
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0%
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100%
FY08
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Mar
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Ord
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% o
f Ord
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Operational Bases - IPG 1 - AF SOS
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
78% 81% 83% 83% 83% 83% 82% 82% 81% 79% 81% 83% 81% 83% 83%
0
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FY08
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Ord
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Operational Bases - IPG 1 - Other SOS
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 11
Operational Bases Order Response Time – IPG 2
AFGLSC 402nd, LIMS-EV Pipeline Analysis, DLA Emall
DoD Operational TDD std
75% 77% 78% 80% 80% 81% 79% 79% 79% 79%73%
80% 76% 75% 76%
0
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FY08
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Ord
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Operational Bases - IPG 2
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
77% 80% 81% 82% 83% 83% 82% 82% 82% 82%76%
82% 79% 78% 79%
0
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100%
FY08
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Ord
ers
% o
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Operational Bases - IPG 2 - DLA SOS
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
76% 74% 73% 76% 74% 72% 72% 72%78% 78%
67% 71% 70%64% 63%
0
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0%
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100%
FY08
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Ord
ers
% o
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ers
Operational Bases - IPG 2 - AF SOS
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
64%67% 67% 69% 70% 70% 69% 70% 67% 66%
62%
72%65% 66% 67%
0
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0%
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100%
FY08
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Ord
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% o
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Operational Bases - IPG 2 - Other SOS
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (tracking) Orders
DoD TDD std
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 12
Order Response Time
Additional AnalysisExamples
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 13
Additional Analysis ExamplesMICAPs
Analysis Source: SMART & LIMS-EV
81%
80%
80%
78% 83
%
81%
82%
81%
82%
83%
81%
81%
83%
79%
79%
05,00010,00015,00020,00025,00030,00035,00040,00045,00050,000
0%10%20%30%40%50%60%70%80%90%
100%FY
08
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Apr 1
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1
MIC
AP
Coun
t
MIC
AP
Resp
onse
Tim
e
Operational Bases
0-3 days 4-7 days 2 weeks 3 weeks4 weeks More % 0-7 days Total MICAPs
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 14
Additional Analysis ExamplesTier down to MD/MDS, Command, Base, SOS, etc.
Analysis Source: SMART & LIMS-EV
73%
60% 65
%
79% 86
%
83%
83%
83%
83%
80%
73%
74%
71% 75
%
74%
65%
61%
54%
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jun
10
Jul 1
0
Aug
10
Sep
10
Oct
10
Nov
10
Dec
10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
CV-22 SOC
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % Base Issue Customer Orders
78%
79% 85
%
87%
86%
83%
83%
84%
82%
82%
84%
79%
79%
80%
78% 86
%
87%
82%
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jun
10
Jul 1
0
Aug
10
Sep
10
Oct
10
Nov
10
Dec
10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
AC-130U Fleet
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % Base Issue Customer Orders
74%
57% 60
%
78%
100%
0% 0% 0% 0% 0% 0%
65% 68
%
70%
68%
52%
54%
47%
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jun
10
Jul 1
0
Aug
10
Sep
10
Oct
10
Nov
10
Dec
10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
CV-22 Operational - 5806
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
77%
77%
70% 77
% 80% 83
%
83% 90
%
84%
82%
80%
78%
77% 79
%
76%
72%
64%
64%
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jun
10
Jul 1
0
Aug
10
Sep
10
Oct
10
Nov
10
Dec
10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
CV-22 Operational - DLA
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
WS B, MAJCOM
WS B, Base WS B, SOS
WS A, Fleet
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 15
Additional Analysis ExamplesBad Actors (identify NIINs, analyze, work root causes, chart)
62%
61%
64%
63%
64%
64%
63%
63%
63%
63%
64%
64%
66%
65% 69
%69
%69
%67
%
-50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000
0%10%20%30%40%50%60%70%80%90%
100%
Aug
10
Sep
10O
ct 1
0N
ov 1
0D
ec 1
0Ja
n 11
Feb
11M
ar 1
1A
pr 1
1M
ay 1
1Ju
n 11
Jul 1
1A
ug 1
1Se
p 11
Oct
11
Nov
11
Dec
11
Jan
12
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
Operational Bases (Bad Actors removed)
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
60%
58%
61%
61%
62%
61%
59%
58%
58%
56%
54%
54%
46%
42% 46
%45
%45
%47
%
-50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000
0%10%20%30%40%50%60%70%80%90%
100%
Aug
10
Sep
10O
ct 1
0N
ov 1
0D
ec 1
0Ja
n 11
Feb
11M
ar 1
1A
pr 1
1M
ay 1
1Ju
n 11
Jul 1
1A
ug 1
1Se
p 11
Oct
11
Nov
11
Dec
11
Jan
12
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
Operational Bases (Bad Actors)
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
82%
83%
83%
82%
84%
84%
83%
84%
83% 86
%88
%89
%91
%90
%91
%91
%89
%88
%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
Aug
10
Sep
10O
ct 1
0N
ov 1
0D
ec 1
0Ja
n 11
Feb
11M
ar 1
1A
pr 1
1M
ay 1
1Ju
n 11
Jul 1
1A
ug 1
1Se
p 11
Oct
11
Nov
11
Dec
11
Jan
12
Mx
Ord
ers
Ord
er R
espo
nse
Tim
e
Depot MXW (Bad Actors removed)
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
73%
73%
69%
69%
69%
68%
70%
67%
62%
61%
55%
47%
40%
32%
31%
27%
24% 32
%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
Aug
10
Sep
10O
ct 1
0N
ov 1
0D
ec 1
0Ja
n 11
Feb
11M
ar 1
1A
pr 1
1M
ay 1
1Ju
n 11
Jul 1
1A
ug 1
1Se
p 11
Oct
11
Nov
11
Dec
11
Jan
12
Mx
Ord
ers
Ord
er R
espo
nse
Tim
e
Depot MXW (Bad Actors)
same day 1-2 days 3-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
I n t e g r i t y - S e r v i c e - E x c e l l e n c e 16
Questions?
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
Air ForceGlobal Logistics Support Center (AFGLSC)
17
Improving the CWT Metric
Mike McClureOperations Research Analyst
AFGLSC 402 SCMS/GUSB
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
BLUF
18
Customer Wait Time (CWT) is an established metric, but is sensitive to extreme-value effects, volume bias and is lagging in nature
Order Response Time (ORT) has been designed to be more illustrative and actionable of real-time customer support
ORT was designed to overcome the shortfalls of CWT
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
Customer Wait Time (CWT)
Customer Wait Time (CWT) Defined in DoD 4140.61.3.2…a measurement of the total elapsed time
between the issuance of a customer order and satisfaction of that order Data is restricted to closed orders Excludes open orders, cancellations, and partial fills – significant
INFORMATION loss! Presented in the month the order was closed, therefore reflects problems
after the fact Typically, top-driver issues have already been fixed
19
M1 M2
Order 1
Order 2
Order 3Order 4
M3When CWT is calculated in M2, both order 3 and 4 are omitted from CWT calculation
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
010
020
030
040
050
060
070
080
090
010
0011
0012
0013
0014
0015
0016
0017
0018
0019
0020
0021
0022
0023
0024
0025
0026
0027
00
Freq
uenc
y
CWT Days
Volume
0100200300400500600700800900
1,000
0 10 20 30 40 50 60 70 80 90 100
Customer Wait Time (CWT)
Customer Wait Time (CWT) Typically reported as an average
with a target Average is skewed by extremes –
Penalty for closing old orders! Missing a target could be a
function of a single bad actor out of 100,000+ orders
Average is skewed by volume change, immediate issues offset longstanding backorders
Significantly more meaningful in percentile buckets
20
Typical CWT distribution
Average is a poor representation of the CWT distribution
Volume
Extreme values
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
Contribution of Closed Orders to CWT
21
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
200,000
0
2
4
6
8
10
12
14
16
18
20
Oct
06
Nov
06
Dec
06
Jan
07Fe
b 07
Mar
07
Apr
07
May
07
Jun
07Ju
l 07
Aug
07
Sep
07O
ct 0
7N
ov 0
7D
ec 0
7Ja
n 08
Feb
08M
ar 0
8A
pr 0
8M
ay 0
8Ju
n 08
Jul 0
8A
ug 0
8Se
p 08
Oct
08
Nov
08
Dec
08
Jan
09Fe
b 09
Mar
09
Apr
09
May
09
Jun
09Ju
l 09
Aug
09
Sep
09O
ct 0
9N
ov 0
9D
ec 0
9Ja
n 10
Feb
10M
ar 1
0A
pr 1
0M
ay 1
0Ju
n 10
Jul 1
0A
ug 1
0Se
p 10
Oct
10
Nov
10
Dec
10
Jan
11Fe
b 11
Mar
11
Apr
11
May
11
Jun
11Ju
l 11
Aug
11
Sep
11
Ord
ers
CWT
CWT Contribution by Closed Orders
Base Issues 1-3 days 4-10 days 11-30 days 31-90 days 91-180 days 180+ days CWT Orders
Volume skew
Extreme value skew + Next to impossible to
interpret real trendsIssue date
aggregation +
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
Order Response Time (ORT)
Order Response Time The percent of orders falling within pre-designated wait time buckets, DoD’s real intent? LIMS-EV CWT data source Both open and closed orders Data attributed to the customer order date Open orders seen as they age, data will update until the 90+ day population establishes
itself Performance directly attributed to the period in which it happened, making trend
analysis valid Not skewed by extreme values or by large volume changes Goals established using a TDD like standard (customer gets x% of parts in y days) or
by calculating a cumulative wait time (by order)
22
Actionable, top-drivers can be restricted to aging open orders, the future drivers of CWT
True “Tier” measure can be applied at multiple Organizational levels
Customer-focused, real-time responsiveness measure
M1 M2
Order 1
Order 2
Order 3
Order 4M3
When ORT is calculated in M2, M3 is still unknown, but order 3 and 4 current is used
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
Order Response TimeExamples
23
89% 90%86% 85% 86% 85% 84% 87% 87% 86% 86% 84% 86% 84% 82%
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
200,000
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
FY08
FY09
FY10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Dec
11
Ord
ers
% o
f Ord
ers
Depot Mx
Pass -Same Day Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (proposed) Orders
2 day TDD std
85% 86% 87% 87% 87% 88% 88% 87% 87% 87% 87% 85% 88% 86% 85%
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
200,000
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
FY08
FY09
FY10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Dec
11
Ord
ers
% o
f Ord
ers
Operational Bases
Pass -Base Issue Pass -Closed Pass -Open Fail -ClosedFail -Open % pass Std (proposed) Orders
DoD TDD std
61%
62%
62%
63%
62%
62%
62%
62%
62%
62%
62%
60% 65
%
64%
64%
-50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Dec
11
Cust
omer
Ord
ers
Ord
er R
espo
nse
Tim
e
Operational Bases
Base Issue 1-3 days 4-10 days 11-30 days31-90 days 90+ days % base issue Orders
87%
87%
83%
82%
82%
82%
80%
83%
84%
83%
83%
82%
83%
82%
79%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
FY08
FY09
FY10
Jan
11
Feb
11
Mar
11
Apr
11
May
11
Jun
11
Jul 1
1
Aug
11
Sep
11
Oct
11
Nov
11
Dec
11
Mx
Ord
ers
Ord
er R
espo
nse
Tim
e
Depot MXW
same day 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
84%
82%
83%
83%
82%
84%
84%
83%
84%
83% 87
%88
%90
%91
%91
%91
%90
%88
%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
Jul 1
0A
ug 1
0Se
p 10
Oct
10
Nov
10
Dec
10
Jan
11Fe
b 11
Mar
11
Apr
11
May
11
Jun
11Ju
l 11
Aug
11
Sep
11O
ct 1
1N
ov 1
1D
ec 1
1
Mx
Ord
ers
Ord
er R
espo
nse
Tim
e
Depot MXW (Bad Actors removed)
same day 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
75%
73%
73%
70%
69%
70%
69%
70%
66%
59%
59%
53%
40%
35%
29%
27%
25%
24%
-20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000
0%10%20%30%40%50%60%70%80%90%
100%
Jul 1
0A
ug 1
0Se
p 10
Oct
10
Nov
10
Dec
10
Jan
11Fe
b 11
Mar
11
Apr
11
May
11
Jun
11Ju
l 11
Aug
11
Sep
11O
ct 1
1N
ov 1
1D
ec 1
1
Mx
Ord
ers
Ord
er R
espo
nse
Tim
e
Depot MXW (Bad Actors)
same day 1-3 days 4-10 days 11-30 days31-90 days 90+ days % same day Mx Orders
ORT Top DriversExample
ORT Analysis
Found the worst performers for last 18 months for AF SOS ORT
Upper left chart is looking at just the bad actors
Lower left chart are when bad actors are filtered out
AF SOS constraints analyzed from the bad actors are below
Bad actors
Best performers