Transcript AASA Pulse: Supplier KPI Benchmarks 2013

AASA Pulse:
Supplier KPI Benchmarks
2013
2013 AASA Pulse: Supplier KPI Benchmarks
1
Contents
Page
Executive Summary
3
How to Use this Study
8
Returns
11
Fill Rates
18
Financial
34
Operations
44
Marketing and Forecasting
51
Results Segmented by Company Size
61
Results Segmented by Product Category
71
Appendix A: Profile of Respondents and Full
Responses to Selected Question
81
Appendix B: Methodology
87
2013 AASA Pulse: Supplier KPI Benchmarks
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Executive Summary
2013 AASA Pulse: Supplier KPI Benchmarks
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Executive Summary (1/4)
Metric
Returns
Fill Rates
Key Findings
Page
85% of respondents indicate that 2.5% or less of
warranty returns are related to actual quality issues
14
Stock adjustment rose again to worrisome levels,
raising concern about this practice across the
industry
15
Differentiation through high fill rates is becoming
more difficult as 74% of respondents had 94% or
better fill rate by unit volume
19
75% had order turnaround of three days or less
25
Although on average only a small amount of
business is done through vendor direct programs,
this activity has been increasing steadily for the
past 3 years; in addition, 26% of respondents had
10% or more of their sales through vendor direction
26-27
2013 AASA Pulse: Supplier KPI Benchmarks
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Executive Summary (2/4)
Metric
Key Findings
Page
Financial
Price changes decreased, though gross margin
mean and median were able to hold steady
35, 41
31
e-Tailing
Respondents estimate that on average 3.4% of
their sales ultimately are sold by channel partners
through e-tailing
Payment terms with retailers averaged 177 days for
respondents in 2012, with 24% at average terms of
291 – 360 days
36
Payment terms with WDs/Distributors average was
much less than retailers, averaging 86 days with
2/3 of respondents reporting terms between 46 to
90 days
37
Payment
Terms
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Executive Summary (3/4)
Metric
Operations
Marketing
Forecasting
Key Findings
Page
The percent of sales manufactured in-house increased
slightly to an average of 63.6% in 2012, though there
are widely divergent models on this point
45
Manufacturing in low cost countries averaged 36% for
2012, up 10 percentage points from 2011
47
Average days on hand of inventory reported by
respondents was 63 days
48
Overall marketing spend as a percent of revenue
averaged 3% for 2012
52
Customer specific marketing spend on average was
typically the highest area of marketing spend
53
90% of respondents reported access to POS and
forecasting data from channel partners; however only
34% use it “Always” or “Frequently”
57
For most of respondents POS data is very useful;
however, a subset finds limited value in the data
59-60
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Executive Summary (4/4)
Metric
Results
Segmented
by
Company
Size
Results
Segmented
by Product
Category
Key Findings
Page
For larger firms there is a more significant portion of
their business done via vendor direct
65
Smaller sized firms have played the largest part in
the e-tailing space
66
Larger firms experienced the greatest price increase
from 2011
67
Chemicals had the highest fill rates. The other
product segments were slightly below Chemicals,
but still all roughly achieved the target 95% fill rate.
74
Respondents estimate that e-tailing penetration is
the highest in the under car product
segment. Companies active in under car also
participate the most in the vendor direct programs.
76
Chemicals sell the most directly through e-tailing
76
Engine and General maintenance have the longest
payment terms
78
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How to Use this Study
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How to Use this Study
Results can be an invaluable resource in your business planning
What is the AASA Pulse?
•
•
•
•
•
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•
A benchmarking survey conducted on an
annual basis
Available exclusively to AASA members
Covers such key benchmarks as returns,
payment terms, order metrics and key
financial metrics
Developed with the assistance and input of
the AASA Marketing Executives Council
(MEC)
Analysis specifically targeted at aftermarket
manufacturers. It is the only research of its
kind available
The AASA Pulse is absolutely anonymous and
answers are kept strictly confidential
Detailed results are shared only with survey
participants
2013 AASA Pulse: Supplier KPI Benchmarks
What to use the data for:
•
Use the AASA Pulse as a vital tool to assist
you in your business and strategic planning
–
•
•
The data can help you determine what you
should target for improvement
And help identify where you are a
benchmark
–
•
Allows you to benchmark against industry
standards and best practices
And therefore allow you to focus your
improvement on other areas and metrics
Industry benchmarks to help in discussions
with your Board and investors
9
Understanding Box Plots
Box plots are used throughout the report; please use the following chart to reach a better
understanding of how to read and interpret a box plot
25%
Range of responses
4th Quartile
20%
3rd Quartile or
Upper Quartile
15%
Average or mean of
responses
The line between the
blue boxes is the
median or the
midpoint of all the
responses.
100% of
responses
10%
75%
2nd Quartile or
Lower Quartile
50%
25%
5%
1st Quartile
0%
Lower Quartile
Upper Quartile
Mean
Source: 2013 AASA Pulse: KPI Benchmarks Survey
2013 AASA Pulse: Supplier KPI Benchmarks
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Returns
2013 AASA Pulse: Supplier KPI Benchmarks
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Warranty Returns (1/2)
While warranty made up 1% or less of sales for 47% of respondents , 38% had 1-5% of
sales as warranty and 15% had greater than 5%
15%
38%
47%
2013 AASA Pulse: Supplier KPI Benchmarks
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Warranty Returns (2/2)
While warranty returns averaged 2.6% of sales, the range of responses was very large
Based on this
feedback, the
aftermarket has
roughly $3.5
billion dollars of
parts warranty
returns a year.
Note: at retail sales level
Source: AASA/AAIA Joint Channel Forecast Model
2013 AASA Pulse: Supplier KPI Benchmarks
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Warranty Returns and Quality Issues
85% of respondents indicate that 2.5% or less of returns are related to actual quality
issues
If the industry could reduce
warranty returns by half, the
industry could save ~$1.8 billion
which would go straight to the
bottom line of suppliers and
channel partners. If the industry
could reduce returns just to
quality issues the industry would
have $3.4 billion in addition profit.
Source: AASA/AAIA Joint Channel Forecast Model
2013 AASA Pulse: Supplier KPI Benchmarks
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Stock and Obsolescence Returns (1/2)
Stock and obsolescence returns clustered around 2-3%, with a wide range of results
2013 AASA Pulse: Supplier KPI Benchmarks
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Stock and Obsolescence Returns (2/2)
Stock adjustment rose in 2012, raising concern about this practice across the industry
Note: ~1 out of 10
respondents had >5%
returns in this category
In an era of “big data”,
advanced analytics
and supply chain
integration, should the
industry be
experiencing this level
of annual stock and
obsolescence returns?
2013 AASA Pulse: Supplier KPI Benchmarks
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Discrepancy Returns
Average discrepancy return continues to decrease, with 56% experiencing 0.05% or less
discrepancy returns
2013 AASA Pulse: Supplier KPI Benchmarks
Year
Average
Discrepancy
Return
2009
0.53%
2010
0.31%
2011
0.29%
2012
0.24%
17
Fill Rates
2013 AASA Pulse: Supplier KPI Benchmarks
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Fill Rates by Unit Volume (1/2)
Differentiation through high fill rates is becoming more difficult as 74% of respondents
had 94% or better fill rate by unit volume
2013 AASA Pulse: Supplier KPI Benchmarks
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Fill Rates by Unit Volume (2/2)
Fill rate by unit volume continues to increase with both the mean and median of
respondents falling above the desired target of 95%
2013 AASA Pulse: Supplier KPI Benchmarks
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Fill Rate by Dollar Value (1/2)
Fill rate by dollar value averaged 95.4% for respondents with 25% falling between 96.1%
- 98%
Mean = 95.4%
2013 AASA Pulse: Supplier KPI Benchmarks
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Fill Rate by Dollar Value (2/2)
Average fill rate by dollar value continue to increase from the low seen in 2010; the 95%
fill rate goal in the industry is increasingly becoming standard
2013 AASA Pulse: Supplier KPI Benchmarks
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Fill Rate by Line Item (1/2)
Fill rate by line item averaged 94.9%, slightly below the typical 95% goal in the
automotive aftermarket
Mean = 94.9%
2013 AASA Pulse: Supplier KPI Benchmarks
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Fill Rate by Line Item (2/2)
Fill rate by line item also increased in 2012 capping a three year upward trend
2013 AASA Pulse: Supplier KPI Benchmarks
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Order Turnaround
Average order turnaround for respondents averaged slightly above 3 days, though 75%
had order turnaround of three days or less
Year
Average
Order
Turnaround
(in days)
2009
5.7
2010
2.0
2011
2.8
2012
3.2
75%
2013 AASA Pulse: Supplier KPI Benchmarks
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Vendor Direct (1/2)
Business models diverge: while 26% sell more than 10% through vendor direct, 39%
report business through vendor direct programs is less than 1%
26%
39%
2013 AASA Pulse: Supplier KPI Benchmarks
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Vendor Direct (2/2)
Although on average only a small amount of business is done through vendor direct
programs, this involvement has been increasing steadily for the past 3 years
2013 AASA Pulse: Supplier KPI Benchmarks
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Overnight Shipping (1/2)
The majority of respondents (59%) indicate that less than 1% of their business was done
with overnight shipping, though the range of responses is wide
2013 AASA Pulse: Supplier KPI Benchmarks
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Overnight Shipping (2/2)
Surprisingly, median use of direct shipping has been declining though the average remains fairly
high (2.5% of business) due to outliers who utilize a lot of overnight shipping
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e-Tailing Through Direct Sale
Majority of respondents (76%) sell virtually nothing directly in the e-tailing channel, but
that means 26% are selling direct online 1% or more of sales
10% sell 3% or more through direct
e-tailing, indicating that the direct ecommerce sales model is being
explored by some suppliers
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e-Tailing by Channel Partners
Respondents estimate that on average 3.4% of their sales ultimately are sold through
e-tailing
Mean = 3.4%
2013 AASA Pulse: Supplier KPI Benchmarks
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Drop Shipments and Cross Docking (1/2)
Business requiring drop shipments/cross docking averaged 8.5% for 2012
Mean = 8.5%
2013 AASA Pulse: Supplier KPI Benchmarks
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Drop Shipments and Cross Docking (2/2)
In contrast to the previous three year decline, there was a significant spike in business
done by drop shipments or cross docking in 2012
While median
remains lower than
2009-2010, average
has increased as
drop ship/cross
docking increased
significantly among
a subset of suppliers
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Financial
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Price
Aftermarket price changes declined in 2012 versus 2011, averaging +1.8%; 56% of
respondents increased prices while 18% saw declines
56%
Year
Average
Aftermarket
Price Change
2011
+2.4%
2012
+1.8%
18%
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Terms with Retailers
Payment terms with retailers averaged 177 days for respondents in 2012; 24% had
average terms of 291 – 360 days
Mean = 177
2013 AASA Pulse: Supplier KPI Benchmarks
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Terms with WDs/Distributors
Payment terms with WDs/Distributors were much less than retailers, averaging 86 days
with 2/3 of respondents reporting terms between 46 to 90 days
Mean = 86
2013 AASA Pulse: Supplier KPI Benchmarks
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SG&A expenses in 2012
General selling and sales administration (SG&A) expenses as a percent of aftermarket
sales averaged 12% across respondents
Mean = 12.0%
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SG&A expenses over time
Average SG&A has crept up over the last 3 years, though the approximate quartile
range of 6% to 15% has remained steady
2013 AASA Pulse: Supplier KPI Benchmarks
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Gross Margin in 2012
Weighted average gross margin across all respondents was 32.6%; the range was large
with 26% at 25% or lower GM and 29% above 40% GM
29%
Mean = 32.6%
26%
2013 AASA Pulse: Supplier KPI Benchmarks
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Gross Margin over time
Weighted gross margin quartile range expanded and increased in 2012; mean increased
slightly (31.7% to 32.6%) although the median remained on par with 2011
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Aftermarket Research and Development Spending in 2012
Respondent’s companies’ estimated average spend on R&D was 3% for 2012, although
over a fifth spend less than 1%
Mean = 3%
2013 AASA Pulse: Supplier KPI Benchmarks
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Aftermarket Research and Development Spending over Time
R&D spend continues to increase for aftermarket suppliers
2013 AASA Pulse: Supplier KPI Benchmarks
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Operations
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In-House Manufacturing
The percent of sales manufactured in-house increased to an average of 63.6% in 2012;
nearly half of respondents manufacture more than 80% of their goods in-house
2013 AASA Pulse: Supplier KPI Benchmarks
Year
Average
Percent of InHouse Sales
2011
55.1%
2012
63.6%
45
Manufacturing in the U.S.
On average, respondents reported that 47% of aftermarket sales were manufactured in
the US, about the same level as the previous year
Year
Average Percent
of Sales
Manufactured in
US
2011
48%
2012
47%
Will the reshoring US “manufacturing renaissance” be seen in the future in the
aftermarket?
2013 AASA Pulse: Supplier KPI Benchmarks
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Manufacturing in Low Cost Countries
Manufacturing in low cost countries averaged 36% for 2012, up 10 percentage
points from 2011
2013 AASA Pulse: Supplier KPI Benchmarks
Year
Average Percent
of Sales
Manufactured in
Low Cost
Countries
2011
26%
2012
36%
47
Inventory Days on Hand
Average days on hand of inventory reported by respondents was 63 days, with nearly a
third reporting “Greater than 90 days”
Mean = 63 days
2013 AASA Pulse: Supplier KPI Benchmarks
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Outbound Freight Costs
3.1 – 5% was the most common range for freight costs as a percent of SG&A
2013 AASA Pulse: Supplier KPI Benchmarks
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Inventory Cost
Inventory costs averaged 19% of cost of goods sold; inventory was 20% or more of
COGS for 35% of respondents
35%
Mean = 19%
2013 AASA Pulse: Supplier KPI Benchmarks
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Marketing and Forecasting
2013 AASA Pulse: Supplier KPI Benchmarks
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Marketing Spend
Overall marketing spend as a percent of revenue averaged 3% for 2012, though 62%
spent 3% or less
Mean = 3%
62%
2013 AASA Pulse: Supplier KPI Benchmarks
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Marketing Spend – Customer Specific
Customer specific marketing spend on average was the highest area of marketing
spend, with nearly 30% of the overall marketing budget
Mean = 30%
2013 AASA Pulse: Supplier KPI Benchmarks
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Marketing Spend – Advertising
Over half of respondents reported marketing spend for advertising comprised less than
20% of their overall marketing budget; mean ad spending was 21%
Mean = 21%
57%
2013 AASA Pulse: Supplier KPI Benchmarks
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Marketing Spend – Trade Fairs
Marketing spend for trade fairs averaged 21% of the overall budget for respondents
Mean = 21%
2013 AASA Pulse: Supplier KPI Benchmarks
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Marketing Spend – Other
While the previous three categories comprise most marketing spend, 32% of
respondents spend 20% or greater of their marketing budget on other promotional tools
32%
Mean = 19%
Note: Means of the four categories do not add up to 100 percent as not all respondents added up to 100 percent.
2013 AASA Pulse: Supplier KPI Benchmarks
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POS and Forecasting Data
90% of respondents reported access to POS and forecasting data from channel
partners; however only 34% use it “Always” or “Frequently”
Are suppliers
fully leveraging
the data available
to them?
2013 AASA Pulse: Supplier KPI Benchmarks
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Value of POS data (1/3)
Nearly two thirds of respondents report that the POS data is “Useful” or “Very useful” in
improving their inventory levels and line fill
2013 AASA Pulse: Supplier KPI Benchmarks
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Use of POS data (2/3)
For most respondents, POS data is very useful; data is used as a benchmark for
performance and forecasts guide suppliers in projecting growth
Throughout your organization, how are you using POS/forecasting
data provided by customers?
“Guiding light in terms of true product performance in store…
We leverage this in combination of our outbound shipments to truly
understand demand so we can be responsive to customer
needs as well as proactive if we see issues with our key accounts
who provide this.”
“Helps determine potential demand activity for upcoming periods.
Provides a picture of the "health" of the market when consolidated
with other customers' performance. Allows collaboration with
customers on determining market strategies in given markets.”
“To understand trends and to understand forecasting. To help plan
for advertising budget.”
“Inventory modeling - we just started it, but it is very valuable.”
For full results, see Appendix
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Use of POS data (3/3)
However, a subset of respondents finds limited value in POS data
Throughout your organization, how are you using POS/forecasting
data provided by customers?
“Do not use.”
“The forecast error is approximately 50% and this applies to our
customers as well. (Therefore ½ of what was made does not sell through
for that period, simultaneously ½ of the actual demand is made in an
expedite mode or via the good fortune of having raw based on the
“minimum buy quantities” required by the supply-chain.”
“Rarely used”
“Unfortunately, we do not have a lot of additional information provided
to us at this time.”
“Limited use”
“We cannot as it is terribly inaccurate.”
For full results, see Appendix
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Results Segmented by Company
Size
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Methodology and How to Use
Methodology
•
•
•
To obtain further insight into the data, we
segmented results for select questions by the
aftermarket revenue size of the respondent.
We grouped respondents into three size
segments:
Annual US
Aftermarket Revenue
Number of
Respondents
<=$150 million
25
$151-$500 million
20
>$500 million
11
Note: Respondents who did not answer this
question were not included in the company
size segmentation
2013 AASA Pulse: Supplier KPI Benchmarks
How to Use
1. This analysis can provide insight on
advantages/disadvantages of size for
different metrics.
– In other words, are smaller or larger
companies more efficient or effective
on a given metric?
2. This analysis can also be used to
benchmark your company against your
closer peers in terms of relative size.
– The issues and performance of smaller
and larger companies can vary
considerably; this analysis helps you
understand better how your
performance benchmarks against
enterprises that are similar to you in
scale.
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Returns by Company Size
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
0%
0.5%
0.5%
Median
0.5%
1.8%
1.1%
Upper Quartile
3.5%
4.5%
3.1%
Mean (Avg.)
1.9%
3.4%
2.5%
Warranty Returns
Lower Quartile
Quality Issues as a percent of Warranty Returns
Lower Quartile
1.3%
1.3%
1.3%
Median
1.3%
1.3%
1.3%
Upper Quartile
1.3%
1.3%
1.3%
Mean (Avg.)
2.6%
3.1%
1.3%
Stock Adjustment and Obsolescence Returns
Lower Quartile
0.4%
1.5%
1.5%
Median
1.5%
2.5%
1.5%
Upper Quartile
4.5%
3.5%
2.5%
Mean (Avg.)
2.4%
2.5%
2.4%
2013 AASA Pulse: Supplier KPI Benchmarks
Mid-size firms had
the largest
warranty returns
Majority of
respondents,
despite the size of
the company,
indicated a small
amount of actual
quality issues
contributing to
warranty returns
Stock adjustments
were relatively the
same across
company size
63
Fill Rates by Company Size
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
Lower Quartile
95%
95%
95%
Median
95%
95%
95%
Upper Quartile
97%
97%
97%
95.4%
95.4%
95.3%
Lower Quartile
95%
93%
91%
Median
97%
96%
95%
98.5%
97%
98.5%
96%
95.4%
94.7%
Lower Quartile
94%
93%
93%
Median
95%
95%
93%
Upper Quartile
98.5%
97.4%
95%
Mean (Avg.)
95.6%
94.6%
93.8%
Fill rate as a % of unit volume
Mean (Avg.)
Fill rate as a % of
unit volume was
consistent across
firm size
Fill rate as a % of dollar value
Upper Quartile
Mean (Avg.)
Fill rate as a % of
dollar value was
highest for smaller
firms
Fill rate as a % of line items filled
2013 AASA Pulse: Supplier KPI Benchmarks
Fill rate as a % of
line items filled
was lowest with
larger firms
64
Shipping Metrics by Company Size
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
1.8
1.8
2
Median
2
2
2
Upper Quartile
4
4
3
2.7
2.7
2.5
Order turnaround (days)
Lower Quartile
Mean (Avg.)
Vendor direct (% of business)
Lower Quartile
0.1%
1.5%
0.1%
Median
1.5%
4%
8.8%
3%
11.3%
13.8%
8.1%
8.2%
10.3%
Upper Quartile
Mean (Avg.)
Order turnaround
for larger firms is
slightly lower
For larger firms
there is a more
significant
portion of their
business done
via vendor direct
Overnight shipping (% of business)
Lower Quartile
0.2%
0.2%
0.7%
Median
0.2%
1%
1%
Upper Quartile
1.7%
1.8%
1.3%
Mean (Avg.)
2.1%
3.6%
1%
2013 AASA Pulse: Supplier KPI Benchmarks
Medium sized
firms have the
most overnight
shipping as a
percent of their
business
65
e-Tailing by Company Size
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
Lower Quartile
0.2%
0.2%
0.2%
Median
0.2%
0.2%
0.5%
Upper Quartile
0.2%
0.2%
0.8%
Mean (Avg.)
2.8%
0.2%
0.7%
e-Tailing through Direct Sales
Smaller sized
firms have sold
the most directly
in the e-tailing
space
e-Tailing through Channel Partners
Lower Quartile
1.2%
1.1%
1.6%
Median
1.2%
2.2%
2.2%
Upper Quartile
5.3%
4%
3.5%
Mean (Avg.)
3.5%
3.8%
2.6%
2013 AASA Pulse: Supplier KPI Benchmarks
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Financial Metrics by Company Size (1/2)
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
31.5%
24%
24.3%
34%
33%
27.5%
Upper Quartile
32.5%
37.5%
37.4%
Mean (Avg.)
34.4%
32.2%
29.8%
No change
-0.4%
+0.5%
Median
+0.5%
+0.5%
+1.5%
Upper Quartile
+2.3%
+1.9%
+1.5%
Mean (Avg.)
+0.9%
+0.4%
+1.1%
Lower Quartile
1.8%
0.1%
1.3%
Median
2.5%
2.3%
1.8%
Upper Quartile
4.5%
2.8%
2.3%
4%
2.3%
1.7%
Gross Margin (Weight Average, Aftermarket)
Lower Quartile
Median
Smaller firms had
the highest gross
margins
Price Change Year-over-Year
Lower Quartile
Larger firms
experienced the
greatest price
increase from
2011
R&D (Aftermarket, % Sales)
Mean (Avg.)
2013 AASA Pulse: Supplier KPI Benchmarks
Smaller firms
spend the most on
R&D as percent of
sales
67
Financial Metrics by Company Size (2/2)
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
SG&A (percent of aftermarket sales)
Lower Quartile
4.5%
7%
8%
Median
5.5%
11%
10%
Upper Quartile
11.5%
15%
18%
Mean (Avg.)
9.8%
12.1%
12.7%
Payment Terms to Retailers (in days)
Lower Quartile
68
158
68
Median
113
258
258
Upper Quartile
158
326
258
133.7
231.3
183.6
Lower Quartile
3.5
3.7
3.5
Median
9.5
5.5
4
Upper Quartile
11
11
5.5
Mean (Avg.)
7.7
6.9
5.5
Mean (Avg.)
Smaller firms had
the lowest SG&A
Smaller firms had
the smallest
payment terms to
retailers with large
and medium firms
having a median
response of 258
days
Inventory Turns
2013 AASA Pulse: Supplier KPI Benchmarks
Smaller firms had
the largest amount
of inventory turns
68
Manufacturing Strategies by Company Size
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
% of Sales Manufactured In-House
Lower Quartile
22.5%
55%
55%
Median
65%
75%
85%
Upper Quartile
95%
90%
85%
57.6%
68.6%
66.7%
13.1%
15%
35%
Median
40%
45%
55%
Upper Quartile
95%
65%
85%
47.4%
43.2%
57.5%
Mean (Avg.)
Larger and
medium sized
firms manufacture
nearly 2/3 of sales
in-house on
average
% of Sales Manufactured in US
Lower Quartile
Mean (Avg.)
Larger firms
manufacture in the
US more than
small and medium
firms
% of Sales Manufactured in Low Cost Countries
Lower Quartile
2.5%
11.3%
15%
Median
25%
35%
25%
Upper Quartile
55%
55%
55%
34.6%
35%
34.4%
Mean (Avg.)
2013 AASA Pulse: Supplier KPI Benchmarks
Medium firms
manufacture in
low cost countries
slightly more than
others
69
Marketing Spend by Company Size
Respondent Revenue Size
Metric
<=$150 M
$151-500M
>$500M
Marketing Spend – Advertising (% of overall marketing spend)
Lower Quartile
5%
15%
5%
Median
15%
25%
25%
Upper Quartile
30%
35%
25%
18.5%
26.9%
21.7%
Mean (Avg.)
Medium firms
spend the most on
advertising as a
marketing tool
Marketing Spend – Trade Fairs (% of overall marketing spend)
Lower Quartile
12.5%
5%
5%
20%
15%
5%
Upper Quartile
27.5%
30%
25%
Mean (Avg.)
24.2%
19%
18.3%
Median
Smaller firms tend
to spend the most
of their marketing
budget on trade
fairs
Marketing Spend – Customer Specific (% of overall marketing spend)
Lower Quartile
10%
20%
15%
Median
25%
25%
25%
Upper Quartile
45%
35%
40%
28.5%
30.3%
28.8%
Mean (Avg.)
2013 AASA Pulse: Supplier KPI Benchmarks
Customer specific
spending is the
same regardless
of firm size
70
Results Segmented by Product
Category
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Methodology and How to Use
Methodology
•
•
•
To obtain further insight into the data, we segmented
results for select questions by company product
category.
Respondents provided the key product categories they
were active in:
Annual US Aftermarket
Revenue
Number of
Respondents
Engine
29
Under Car
21
General Maintenance Parts
20
Chemicals / Paint / Lubricant
8
How to Use
1. This analysis can provide insight on strength /
weakness of different product categories.
– In other words, are different product segments
more efficient or effective on a given metric?
2. This analysis can also be used to benchmark your
company against your closer peers in terms of
product segment.
– The issues and performance of companies in
different product segments can vary
considerably; this analysis helps you
understand better how your performance
benchmarks against enterprises that are
roughly similar to you in product category.
Respondents were able to choose multiple product
categories. Their responses were included in each
applicable category. Therefore the number of
responses in the sum of the categories noted above
will exceed the total number of survey responses.
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Returns by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
Lower Quartile
0.5%
0.5%
0.5%
-
Median
2.5%
1.8%
1.8%
0%
Upper Quartile
3.5%
3.8%
2.5%
-
Mean (Avg.)
2.7%
2.6%
2.9%
1%
Warranty Returns
Chemicals had the
lowest median of
warranty returns;
engine the highest
Quality Issues as Percent of Warranty Returns
Lower Quartile
1.3%
1.3%
1.3%
-
Median
1.3%
1.3%
1.3%
1.3%
Upper Quartile
1.3%
3.8%
1.3%
-
Mean (Avg.)
2.2%
4%
3.5%
1.8%
Stock Adjustment and Obsolescence Returns
Lower Quartile
1.8%
1.5%
1.5%
-
Median
2.5%
2.5%
2.5%
0.1%
Upper Quartile
4.5%
3.5%
4%
-
Mean (Avg.)
3.1%
2.7%
3%
1%
Amount of quality
issues was the
same regardless
of product
segment
Chemicals had the
lowest amount of
stock adjustments
for 2012; returns
were similar for
other categories
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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Fill Rates by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
93.5%
92.5%
93%
-
Median
95%
95%
95%
97%
Upper Quartile
97%
97.3%
97%
-
94.6%
94.7%
94.8%
96.5%
Fill rate as a % of unit volume
Lower Quartile
Mean (Avg.)
Fill rate as a % of dollar value
Lower Quartile
93%
91%
93%
-
Median
95%
95%
95%
98.2%
Upper Quartile
97%
97.3%
97%
-
94.7%
94.2%
94.4%
97.7%
Mean (Avg.)
Fill rate as a % of line items filled
Lower Quartile
93%
92.5%
93%
-
Median
95%
94%
95%
98.3%
Upper Quartile
97%
95.5%
97.9%
-
94.3%
93.8%
94.6%
95.9%
Mean (Avg.)
Chemicals had the
highest fill rate for
unit volume, dollar
and line items
filled. The other
product segments
were slightly
below Chemicals,
but still all roughly
achieved the
target 95% fill
rate.
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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Shipping Metrics by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
Order turnaround (days)
Lower Quartile
2
1.8
2
-
Median
2
2.5
2
3
Upper Quartile
3
3.3
3
-
2.6
3
2.4
3.1
Mean (Avg.)
Order turnaround
is lowest for
engine and
general
maintenance
parts; highest for
Chemicals
Vendor direct (% of business)
Lower Quartile
0.5%
1.5%
0.5%
-
Median
2.5%
5%
1%
3%
Upper Quartile
12.5%
12.5%
11.4%
-
8%
9.2%
6.3%
26.9%
Mean (Avg.)
Under car
participates the
most in vendor
direct programs
Overnight shipping (% of business)
Lower Quartile
0.7%
0.2%
0.3%
-
Median
1.2%
0.7%
1%
0.2%
Upper Quartile
2.8%
1.9%
2.5%
-
Mean (Avg.)
4.5%
2.3%
5%
0.3%
All product
segments have
very little business
done via overnight
shipping
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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e-Tailing by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
e-Tailing through Direct Sales
Lower Quartile
0.2%
0.2%
0.2%
-
Median
0.2%
0.2%
0.2%
1.2%
Upper Quartile
0.7%
1.7%
1.2%
-
Mean (Avg.)
1.6%
1.8%
2.2%
1.2%
e-Tailing through Channel Partners
Lower Quartile
1.2%
2.2%
1.2%
-
Median
2.2%
3.5%
2.5%
1.2%
Upper Quartile
3.5%
6%
4.3%
-
4%
4.6%
4.2%
2.1%
Mean (Avg.)
Chemicals sell the
most direct
through e-tailing
The under car
product segment
estimates e-tailing
has the highest
share of segment
sales.
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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Financial Metrics by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
R&D (Aftermarket, % Sales)
Lower Quartile
0.7%
1.3%
1.3%
-
2%
1.8%
2.3%
1.8%
Upper Quartile
3.1%
2.8%
3.1%
-
Mean (Avg.)
3.2%
2.4%
3%
2.6%
Median
General
Maintenance
spends the most
on aftermarket
R&D as a percent
of sales
SG&A (percent of aftermarket sales)
Lower Quartile
5.5%
7%
5.5%
-
Median
9.5%
10.8%
9.5%
9.5%
Upper Quartile
15%
23%
17.3%
-
11.8%
14%
12.9%
15.9%
Mean (Avg.)
Under Car has a
slightly higher
median SG&A
compared to other
segments
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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Payment Terms by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
Payment Terms to Retailers (in days)
Lower Quartile
158
68
113
-
Median
258
158
258
113
Upper Quartile
326
258
326
-
221.7
161.7
201.8
149.9
Mean (Avg.)
Engine and
General Service
have the longest
payment terms of
the product
segments to
retailers
Payment Terms to WDs/Distributors (in days)
Lower Quartile
68
68
68
-
Median
68
68
68
68
Upper Quartile
113
68
68
-
Mean (Avg.)
95.3
81.5
78.5
75.5
Payment terms to
WDs/Distributors
has the same
median across
segments, though
engine has some
outliers
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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Manufacturing Strategies by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
% of Sales Manufactured In-House
Lower Quartile
45%
22.5%
15%
-
Median
65%
65%
75%
75%
Upper Quartile
85%
85%
85%
-
62.3%
56.8%
52.6%
49.6%
Mean (Avg.)
% of Sales Manufactured in US
Lower Quartile
25%
20%
25%
-
Median
35%
25%
45%
95%
Upper Quartile
65%
60%
55%
-
44.2%
41.1%
43.4%
83.6%
Mean (Avg.)
% of Sales Manufactured in Low Cost Countries
Lower Quartile
15%
7.5%
15%
-
Median
35%
35%
35%
0.3%
Upper Quartile
55%
50%
55%
-
37.6%
33%
35%
11.9%
Mean (Avg.)
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
2013 AASA Pulse: Supplier KPI Benchmarks
General
Maintenance and
Chemicals
manufacture the
most in-house at
median, though
the story is the
opposite at the
mean; some
players in these
segments have
high levels of
outsourcing
Chemicals
manufacture
significantly more
in the US than
other segments
More than a third
of parts (nonChemicals)
manufacturing is
in low cost
countries
79
Marketing Spend by Product Segment
Respondent by Product Segment
Metric
Engine
Under Car
General Maintenance
Parts
Chemicals /
Paint / Lubricant
Marketing Spend – Advertising (% of overall marketing spend)
Lower Quartile
5%
5%
5%
-
Median
15%
15%
10%
45%
Upper Quartile
25%
35%
25%
-
20.2%
20.6%
15%
28.6%
Mean (Avg.)
Chemicals spend
the most of their
advertising budget
on advertising
(many players in
this segment have
branded products)
Marketing Spend – Trade Fairs (% of overall marketing spend)
Lower Quartile
5%
5%
5%
-
Median
15%
15%
15%
15%
Upper Quartile
25%
25%
25%
-
21.8%
17.9%
15.6%
16.4%
Mean (Avg.)
Marketing Spend – Customer Specific (% of overall marketing spend)
Lower Quartile
15%
15%
25%
-
Median
25%
25%
35%
45%
Upper Quartile
35%
45%
55%
-
26.4%
32.1%
37.5%
42.1%
Mean (Avg.)
Spend on trade
fairs is roughly the
same across
product segments
Chemicals and
maintenance parts
spend more of
their marketing
spend on
customer specific
initiatives
Note: Chemicals product category does not include the lower or upper quartile to ensure confidentiality of those respondents.
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Appendix A
Profile of Respondents
Full Responses to Selected Question
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Size of Respondents
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Number of Employees of Respondents
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Product Segments of Respondents
Note: Total does not add up to 100% due to respondents ability to select multiple categories
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Throughout your organization, how are you using POS/forecasting
data provided by customers? (1/2)
“Compare POS data to trends”
“Comparing customer generated forecasts to our own
internal forecasts”
“Component orders”
“Demand planning, assortment recommendations, SKU
sales and return trends”
“Do not use.”
“Forecasting. Inventory levels.”
“Guiding light in terms of true product performance in
store… We leverage this in combination of our outbound
shipments to truly understand demand so we can be
responsive to customer needs as well as proactive if we
see issues with our key accounts who provide this.”
“Helps determine potential demand activity for upcoming
periods. Provides a picture of the "health" of the market
when consolidated with other customers' performance.
Allows collaboration with customers on determining market
strategies in given markets.”
“Identify specific regional / customer trends for new
numbers.”
“In our sales and operational planning process.”
“Input into internal forecast systems”
“Inventory modeling - we just started it, but it is very
valuable.”
2013 AASA Pulse: Supplier KPI Benchmarks
“Limited to sales forecast. Not used consistently for supply
chain activities.”
“Limited use”
“Logistics team is using POS data for one major customer
to track new part sales at store level to adjust SKU level
forecast and planning to improve fill rates an reduce
inventory.”
“Mainly used for SKUs on the front end of the sales trend to
monitor the ramp up in sales, as well as large changes in
trend with mature or declining SKUs.”
“Our customers forecasts are vital to our production
scheduling and inventory planning to insure high order fill
and control inventory costs.”
“POS data very useful. Customer forecasts not very
accurate, used on exception basis. We review forecasts
with the customer when there are large discrepancies to
our internal forecast.”
“Purchasing / Forecasting; Product Management; Customer
Category Management”
“Rarely used”
“Sales & Operations budgets, PC&L, Supply chain”
“Sales forecasting”
85
Throughout your organization, how are you using POS/forecasting
data provided by customers? (2/2)
“The forecast error is approximately 50% and this applies to
our customers as well. (Therefore ½ of what was made
does not sell through for that period, simultaneously ½ of
the actual demand is made in an expedite mode or via the
good fortune of having raw based on the “minimum buy
quantities” required by the supply-chain.”
“To confirm internal information”
“To determine inventory levels”
“To improve our fill-rate”
“To optimize inventory and order fill”
“To order long lead time items and establish inventory
levels”
“To understand trends and to understand forecasting. To
help plan for advertising budget.”
“Unfortunately, we do not have a lot of additional
information provided to us at this time.”
“Use the data to bounce up against current forecast by
customer to look for flyers/numbers that are trending
significantly upward or downward.”
“Used in product rationalization and forecasting”
“Used in SIOP process.”
2013 AASA Pulse: Supplier KPI Benchmarks
“Using both historical POS with running POS provides
much more accurate forecasting capabilities. Comparing
both also helps to identify growing and declining trends of
specific parts or categories.”
“Using it to predict future sales trends; assessing individual
customers' share gains/losses.”
“We cannot as it is terribly inaccurate.”
“We have a dedicated analyst that uses the information to
coordinate inventory plans.”
“We try to understand customer forecast values and
compare to our historic and forecast data to optimize
materials management”
86
Appendix B
Methodology
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AASA Pulse methodology notes
•
The AASA Supplier Pulse report is an annual benchmarking survey covering
key automotive aftermarket supplier performance indicators (KPIs).
•
The purpose of the Pulse is to provide members with general information on
high-level benchmarking of sector performance. The information and
opinions contained in this report are for general information purposes only.
•
Participation is only available to AASA supplier members. Full reports are
provided only to survey participants and AASA Board members.
•
Surveys are sent to senior executives and member representatives at all
AASA members. There were 60 responses to this year’s survey.
•
The survey covers 2012 data (calendar or fiscal year, depending on
respondent). Answers were provided by respondents based on actual data if
available or best estimates. Most questions were multiple choice, so
numbers used in the report represent the midpoint of a selected multiple
choice answer.
•
The survey is anonymous and answers are kept strictly confidential.
Therefore, only aggregated results will be reported and individual responses
will not be released and will be destroyed after results are compiled.
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Contact Information
Paul McCarthy
Vice President
Industry Analysis, Planning and Member Services
Office: +1 919.406.8812 | Mobile: +1 248.914.2567
Email: [email protected]
Bailey L. W. Overman
Analyst/Coordinator
Industry Analysis and Member Services
Office: +1 919.406.8823
Email: [email protected]
AASA | Automotive Aftermarket Suppliers Association
10 Laboratory Drive | Research Triangle Park | NC | 27709 | USA
www.aftermarketsuppliers.org
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